introduction of the case study

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How to Write an Introduction for a Case Study Report

If you’re looking for examples of how to write an introduction for a case-study report, you’ve come to the right place. Here you’ll find a sample, guidelines for writing a case-study introduction, and tips on how to make it clear. In five minutes or less, recruiters will read your case study and decide whether you’re a good fit for the job.

Example of a case study introduction

An example of a case study introduction should be written to provide a roadmap for the reader. It should briefly summarize the topic, identify the problem, and discuss its significance. It should include previous case studies and summarize the literature review. In addition, it should include the purpose of the study, and the issues that it addresses. Using this example as a guideline, writers can make their case study introductions. Here are some tips:

The first paragraph of the introduction should summarize the entire article, and should include the following sections: the case presentation, the examinations performed, and the working diagnosis, the management of the case, and the outcome. The final section, the discussion, should summarize the previous subsections, explain any apparent inconsistencies, and describe the lessons learned. The body of the paper should also summarize the introduction and include any notes for the instructor.

The last section of a case study introduction should summarize the findings and limitations of the study, as well as suggestions for further research. The conclusion section should restate the thesis and main findings of the case study. The conclusion should summarize previous case studies, summarize the findings, and highlight the possibilities for future study. It is important to note that not all educational institutions require the case study analysis format, so it is important to check ahead of time.

The introductory paragraph should outline the overall strategy for the study. It should also describe the short-term and long-term goals of the case study. Using this method will ensure clarity and reduce misunderstandings. However, it is important to consider the end goal. After all, the objective is to communicate the benefits of the product. And, the solution should be measurable. This can be done by highlighting the benefits and minimizing the negatives.

Structure of a case study introduction

The structure of a case study introduction is different from the general introduction of a research paper. The main purpose of the introduction is to set the stage for the rest of the case study. The problem statement must be short and precise to convey the main point of the study. Then, the introduction should summarize the literature review and present the previous case studies that have dealt with the topic. The introduction should end with a thesis statement.

The thesis statement should contain facts and evidence related to the topic. Include the method used, the findings, and discussion. The solution section should describe specific strategies for solving the problem. It should conclude with a call to action for the reader. When using quotations, be sure to cite them properly. The thesis statement must include the problem statement, the methods used, and the expected outcome of the study. The conclusion section should state the case study’s importance.

In the discussion section, state the limitations of the study and explain why they are not significant. In addition, mention any questions unanswered and issues that the study was unable to address. For more information, check out the APA, Harvard, Chicago, and MLA citation styles. Once you know how to structure a case study introduction, you’ll be ready to write it! And remember, there’s always a right and wrong way to write a case study introduction.

During the writing process, you’ll need to make notes on the problems and issues of the case. Write down any ideas and directions that come to mind. Avoid writing neatly. It may impede your creative process, so write down a rough draft first, and then draw it up for your educational instructor. The introduction is an overview of the case study. Include the thesis statement. If you’re writing a case study for an assignment, you’ll also need to provide an overview of the assignment.

Guidelines for writing a case study introduction

A case study is not a formal scientific research report, but it is written for a lay audience. It should be readable and follow the general narrative that was determined in the first step. The introduction should provide background information about the case and its main topic. It should be short, but should introduce the topic and explain its context in just one or two paragraphs. An ideal case study introduction is between three and five sentences.

The case study must be well-designed and logical. It cannot contain opinions or assumptions. The research question must be a logical conclusion based on the findings. This can be done through a spreadsheet program or by consulting a linguistics expert. Once you have identified the major issues, you need to revise the paper. Once you have revised it twice, it should be well-written, concise, and logical.

The conclusion should state the findings, explain their significance, and summarize the main points. The conclusion should move from the detailed to the general level of consideration. The conclusion should also briefly state the limitations of the case study and point out the need for further research in order to fully address the problem. This should be done in a manner that will keep the reader interested in reading the paper. It should be clear about what the case study found and what it means for the research community.

The case study begins with a cover page and an executive summary, depending on your professor’s instructions. It’s important to remember that this is not a mandatory element of the case study. Instead, the executive summary should be brief and include the key points of the study’s analysis. It should be written as if an executive would read it on the run. Ultimately, the executive summary should include all the key points of the case study.

Clarity in a case study introduction

Clarity in a case study introduction should be at the heart of the paper. This section should explain why the case was chosen and how you decided to use it. The case study introduction varies according to the type of subject you are studying and the goals of the study. Here are some examples of clear and effective case study introductions. Read on to find out how to write a successful one. Clarity in a case study introduction begins with a strong thesis statement and ends with a compelling conclusion.

The conclusion of the case study should restate the research question and emphasize its importance. Identify and restate the key findings and describe how they address the research question. If the case study has limitations, discuss the potential for further research. In addition, document the limitations of the case study. Include any limitations of the case study in the conclusion. This will allow readers to make informed decisions about whether or not the findings are relevant to their own practices.

A case study introduction should include a brief discussion of the topic and selected case. It should explain how the study fits into current knowledge. A reader may question the validity of the analysis if it fails to consider all possible outcomes. For example, a case study on railroad crossings may fail to document the obvious outcome of improving the signage at these intersections. Another example would be a study that failed to document the impact of warning signs and speed limits on railroad crossings.

As a conclusion, the case study should also contain a discussion of how the research was conducted. While it may be a case study, the results are not necessarily applicable to other situations. In addition to describing how a solution has solved the problem, a case study should also discuss the causes of the problem. A case study should be based on real data and information. If the case study is not valid, it will not be a good fit for the audience.

Sample of a case study introduction

A good case study introduction serves as a map for the reader to follow. It should identify the research problem and discuss its significance. It should be based on extensive research and should incorporate relevant issues and facts. For example, it may include a short but precise problem statement. The next section of the introduction should include a description of the solution. The final part of the introduction should conclude with the recommended action. Once the reader has a sense of the direction the study will take, they will feel confident in pursuing the study further.

In the case of social sciences, case studies cannot be purely empirical. The results of a case study can be compared with those of other studies, so that the case study’s findings can be assessed against previous research. A case study’s results can help support general conclusions and build theories, while their practical value lies in generating hypotheses. Despite their utility, case studies often contain a bias toward verification and tend to confirm the researcher’s preconceived notions.

In the case of case studies, the conclusions section should state the significance of the findings, stating how the findings of the study differ from other previous studies. Likewise, the conclusion section should summarize the key findings, and make the reader understand how they address the research problem. In the case of a case study, it is crucial to document any limitations that have been identified. After all, a case study is not complete without further research.

After the introduction, the main body of the paper is the case presentation. It should provide information about the case, such as the history, examination results, working diagnosis, management, and outcome. It should conclude with a discussion, explaining the correlations, apparent inconsistencies, and lessons learned. Finally, the conclusion should state whether the case study presented the results in the desired way. The findings should not be overgeneralized, and the conclusions must be derived from this information.

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Knowledge Base

Methodology

What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

Provide new or unexpected insights into the subject
Challenge or complicate existing assumptions and theories
Propose practical courses of action to resolve a problem
Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

Exemplify a theory by showing how it explains the case under investigation
Expand on a theory by uncovering new concepts and ideas that need to be incorporated
Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Normal distribution
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Ecological validity

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

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Writing A Case Study

A Complete Case Study Writing Guide With Examples

What is a Case Study?

A case study is a detailed analysis and examination of a particular subject, situation, or phenomenon. It involves comprehensive research to gain a deep understanding of the context and variables involved.

Typically used in academic, business, and marketing settings, case studies aim to explore real-life scenarios, providing insights into challenges, solutions, and outcomes. They serve as valuable tools for learning, decision-making, and showcasing success stories.

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Types of Case Studies

Case studies come in various forms, each tailored to address specific objectives and areas of interest. Here are some of the main types of case studies :

Illustrative Case Studies: These focus on describing a particular situation or event, providing a detailed account to enhance understanding.
Exploratory Case Studies: Aimed at investigating an issue and generating initial insights, these studies are particularly useful when exploring new or complex topics.
Explanatory Case Studies: These delve into the cause-and-effect relationships within a given scenario, aiming to explain why certain outcomes occurred.
Intrinsic Case Studies: Concentrating on a specific case that holds intrinsic value, these studies explore the unique qualities of the subject itself.
Instrumental Case Studies: These are conducted to understand a broader issue and use the specific case as a means to gain insights into the larger context.
Collective Case Studies: Involving the study of multiple cases, this type allows for comparisons and contrasts, offering a more comprehensive view of a phenomenon or problem.

How To Write a Case Study - 9 Steps

Crafting an effective case study involves a structured approach to ensure clarity, engagement, and relevance.

Here's a step-by-step guide on how to write a compelling case study:

Step 1: Define Your Objective

Before diving into the writing process, clearly define the purpose of your case study. Identify the key questions you want to answer and the specific goals you aim to achieve.

Whether it's to showcase a successful project, analyze a problem, or demonstrate the effectiveness of a solution, a well-defined objective sets the foundation for a focused and impactful case study.

Step 2: Conduct Thorough Research

Gather all relevant information and data related to your chosen case. This may include interviews, surveys, documentation, and statistical data.

Ensure that your research is comprehensive, covering all aspects of the case to provide a well-rounded and accurate portrayal.

The more thorough your research, the stronger your case study's foundation will be.

Step 3: Introduction: Set the Stage

Begin your case study with a compelling introduction that grabs the reader's attention. Clearly state the subject and the primary issue or challenge faced.

Engage your audience by setting the stage for the narrative, creating intrigue, and highlighting the significance of the case.

Step 4: Present the Background Information

Provide context by presenting the background information of the case. Explore relevant history, industry trends, and any other factors that contribute to a deeper understanding of the situation.

This section sets the stage for readers, allowing them to comprehend the broader context before delving into the specifics of the case.

Step 5: Outline the Challenges Faced

Identify and articulate the challenges or problems encountered in the case. Clearly define the obstacles that needed to be overcome, emphasizing their significance.

This section sets the stakes for your audience and prepares them for the subsequent exploration of solutions.

Step 6: Detail the Solutions Implemented

Describe the strategies, actions, or solutions applied to address the challenges outlined. Be specific about the decision-making process, the rationale behind the chosen solutions, and any alternatives considered.

This part of the case study demonstrates problem-solving skills and showcases the effectiveness of the implemented measures.

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Step 7: Showcase Measurable Results

Present tangible outcomes and results achieved as a direct consequence of the implemented solutions. Use data, metrics, and success stories to quantify the impact.

Whether it's increased revenue, improved efficiency, or positive customer feedback, measurable results add credibility and validation to your case study.

Step 8: Include Engaging Visuals

Enhance the readability and visual appeal of your case study by incorporating relevant visuals such as charts, graphs, images, and infographics.

Visual elements not only break up the text but also provide a clearer representation of data and key points, making your case study more engaging and accessible.

Step 9: Provide a Compelling Conclusion

Wrap up your case study with a strong and conclusive summary. Revisit the initial objectives, recap key findings, and emphasize the overall success or significance of the case.

This section should leave a lasting impression on your readers, reinforcing the value of the presented information.

Case Study Methods

The methods employed in case study writing are diverse and flexible, catering to the unique characteristics of each case. Here are common methods used in case study writing:

Conducting one-on-one or group interviews with individuals involved in the case to gather firsthand information, perspectives, and insights.

Observation

Directly observing the subject or situation to collect data on behaviors, interactions, and contextual details.

Document Analysis

Examining existing documents, records, reports, and other written materials relevant to the case to gather information and insights.

Surveys and Questionnaires

Distributing structured surveys or questionnaires to relevant stakeholders to collect quantitative data on specific aspects of the case.

Participant Observation

Combining direct observation with active participation in the activities or events related to the case to gain an insider's perspective.

Triangulation

Using multiple methods (e.g., interviews, observation, and document analysis) to cross-verify and validate the findings, enhancing the study's reliability.

Ethnography

Immersing the researcher in the subject's environment over an extended period, focusing on understanding the cultural context and social dynamics.

Case Study Format

Effectively presenting your case study is as crucial as the content itself. Follow these formatting guidelines to ensure clarity and engagement:

Opt for fonts that are easy to read, such as Arial, Calibri, or Times New Roman.
Maintain a consistent font size, typically 12 points for the body text.
Aim for double-line spacing to maintain clarity and prevent overwhelming the reader with too much text.
Utilize bullet points to present information in a concise and easily scannable format.
Use numbered lists when presenting a sequence of steps or a chronological order of events.
Bold or italicize key phrases or important terms to draw attention to critical points.
Use underline sparingly, as it can sometimes be distracting in digital formats.
Choose the left alignment style.
Use hierarchy to distinguish between different levels of headings, making it easy for readers to navigate.

If you're still having trouble organizing your case study, check out this blog on case study format for helpful insights.

Case Study Examples

If you want to understand how to write a case study, examples are a fantastic way to learn. That's why we've gathered a collection of intriguing case study examples for you to review before you begin writing.

Case Study Research Example

Case Study Template

Case Study Introduction Example

Amazon Case Study Example

Business Case Study Example

APA Format Case Study Example

Psychology Case Study Example

Medical Case Study Example

UX Case Study Example

Looking for more examples? Check out our blog on case study examples for your inspiration!

Benefits and Limitations of Case Studies

Case studies are a versatile and in-depth research method, providing a nuanced understanding of complex phenomena.

However, like any research approach, case studies come with their set of benefits and limitations. Some of them are given below:

Tips for Writing an Effective Case Study

Here are some important tips for writing a good case study:

Clearly articulate specific, measurable research questions aligned with your objectives.
Identify whether your case study is exploratory, explanatory, intrinsic, or instrumental.
Choose a case that aligns with your research questions, whether it involves an individual case or a group of people through multiple case studies.
Explore the option of conducting multiple case studies to enhance the breadth and depth of your findings.
Present a structured format with clear sections, ensuring readability and alignment with the type of research.
Clearly define the significance of the problem or challenge addressed in your case study, tying it back to your research questions.
Collect and include quantitative and qualitative data to support your analysis and address the identified research questions.
Provide sufficient detail without overwhelming your audience, ensuring a comprehensive yet concise presentation.
Emphasize how your findings can be practically applied to real-world situations, linking back to your research objectives.
Acknowledge and transparently address any limitations in your study, ensuring a comprehensive and unbiased approach.

To sum it up, creating a good case study involves careful thinking to share valuable insights and keep your audience interested.

Stick to basics like having clear questions and understanding your research type. Choose the right case and keep things organized and balanced.

Remember, your case study should tackle a problem, use relevant data, and show how it can be applied in real life. Be honest about any limitations, and finish with a clear call-to-action to encourage further exploration.

However, if you are having issues understanding how to write a case study, it is best to hire the professionals. Hiring a paper writing service online will ensure that you will get best grades on your essay without any stress of a deadline.

So be sure to check out case study writing service online and stay up to the mark with your grades.

Frequently Asked Questions

What is the purpose of a case study.

The objective of a case study is to do intensive research on a specific matter, such as individuals or communities. It's often used for academic purposes where you want the reader to know all factors involved in your subject while also understanding the processes at play.

What are the sources of a case study?

Some common sources of a case study include:

Archival records
Direct observations and encounters
Participant observation
Facts and statistics
Physical artifacts

What is the sample size of a case study?

A normally acceptable size of a case study is 30-50. However, the final number depends on the scope of your study and the on-ground demographic realities.

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
Gives researchers the chance to collect information on why one strategy might be chosen over another
Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

It cannot necessarily be generalized to the larger population
Cannot demonstrate cause and effect
It may not be scientifically rigorous
It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
Explanatory case studies : These are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

Archival records : Census records, survey records, and name lists are examples of archival records.
Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research.

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
Read examples of case studies to gain an idea about the style and format.
Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal. The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

Provide new or unexpected insights into the subject
Challenge or complicate existing assumptions and theories
Propose practical courses of action to resolve a problem
Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible.

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

Exemplify a theory by showing how it explains the case under investigation
Expand on a theory by uncovering new concepts and ideas that need to be incorporated
Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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How to Write a Case Study: A Breakdown of Requirements

It can take months to develop a case study. First, a topic must be chosen. Then the researcher must state his hypothesis, and make certain it lines up with the chosen topic. Then all the research must be completed. The case study can require both quantitative and qualitative research, as well as interviews with subjects. Once that is all done, it is time to write the case study.

Not all case studies are written the same. Depending on the size and topic of the study, it could be hundreds of pages long. Regardless of the size, the case study should have four main sections. These sections are:

1. Introduction

2. Background

3. Presentation of Findings

4. Conclusion

The Introduction

The introduction should set the stage for the case study, and state the thesis for the report. The intro must clearly articulate what the study's intention is, as well as how you plan on explaining and answering the thesis.

Again, remember that a case study is not a formal scientific research report that will only be read by scientists. The case study must be able to be read and understood by the layperson, and should read almost as a story, with a clear narrative.

As the reader reads the introduction, they should fully understand what the study is about, and why it is important. They should have a strong foundation for the background they will learn about in the next section.

The introduction should not be long. You must be able to introduce your topic in one or two paragraphs. Ideally, the introduction is one paragraph of about 3-5 sentences.

The Background

The background should detail what information brought the researcher to pose his hypothesis. It should clearly explain the subject or subjects, as well as their background information. And lastly, the background must give the reader a full understanding of the issue at hand, and what process will be taken with the study. Photos and videos are always helpful when applicable.

When writing the background, the researcher must explain the research methods used, and why. The type of research used will be dependent on the type of case study. The reader should have a clear idea why a particular type of research is good for the field and type of case study.

For example, a case study that is trying to determine what causes PTSD in veterans will heavily use interviews as a research method. Directly interviewing subjects garners invaluable research for the researcher. If possible, reference studies that prove this.

Again, as with the introduction, you do not want to write an extremely long background. It is important you provide the right amount of information, as you do not want to bore your readers with too much information, and you don't want them under-informed.

How much background information should a case study provide? What would happen if the case study had too much background info?

What would happen if the case study had too little background info?

The Presentation of Findings

While a case study might use scientific facts and information, a case study should not read as a scientific research journal or report. It should be easy to read and understand, and should follow the narrative determined in the first step.

The presentation of findings should clearly explain how the topic was researched, and summarize what the results are. Data should be summarized as simply as possible so that it is understandable by people without a scientific background. The researcher should describe what was learned from the interviews, and how the results answered the questions asked in the introduction.

When writing up the report, it is important to set the scene. The writer must clearly lay out all relevant facts and detail the most important points. While this section may be lengthy, you do not want to overwhelm the reader with too much information.

The Conclusion

The final section of the study is the conclusion. The purpose of the study isn't necessarily to solve the problem, only to offer possible solutions. The final summary should be an end to the story.

Remember, the case study is about asking and answering questions. The conclusion should answer the question posed by the researcher, but also leave the reader with questions of his own. The researcher wants the reader to think about the questions posed in the study, and be free to come to their own conclusions as well.

When reading the conclusion, the reader should be able to have the following takeaways:

Was there a solution provided? If so, why was it chosen?

Was the solution supported with solid evidence?

Did the personal experiences and interviews support the solution?

The conclusion should also make any recommendations that are necessary. What needs to be done, and you exactly should do it? In the case of the vets with PTSD, once a cause is determined, who is responsible for making sure the needs of the veterans are met?

English Writing Standards For Case Studies

When writing the case study, it is important to follow standard academic and scientific rules when it comes to spelling and grammar.

Spelling and Grammar

It should go without saying that a thorough spell check should be done. Remember, many case studies will require words or terms that are not in standard online dictionaries, so it is imperative the correct spelling is used. If possible, the first draft of the case study should be reviewed and edited by someone other than yourself.

Case studies are normally written in the past tense, as the report is detailing an event or topic that has since passed. The report should be written using a very logical and clear tone. All case studies are scientific in nature and should be written as such.

The First Draft

You do not sit down and write the case study in one day. It is a long and detailed process, and it must be done carefully and with precision. When you sit down to first start writing, you will want to write in plain English, and detail the what, when and how.

When writing the first draft, note any relevant assumptions. Don't immediately jump to any conclusions; just take notes of any initial thoughts. You are not looking for solutions yet. In the first draft use direct quotes when needed, and be sure to identify and qualify all information used.

If there are any issues you do not understand, the first draft is where it should be identified. Make a note so you return to review later. Using a spreadsheet program like Excel or Google Sheets is very valuable during this stage of the writing process, and can help keep you and your information and data organized.

The Second Draft

To prepare the second draft, you will want to assemble everything you have written thus far. You want to reduce the amount of writing so that the writing is tightly written and cogent. Remember, you want your case study to be interesting to read.

When possible, you should consider adding images, tables, maps, or diagrams to the text to make it more interesting for the reader. If you use any of these, make sure you have permission to use them. You cannot take an image from the Internet and use it without permission.

Once you have completed the second draft, you are not finished! It is imperative you have someone review your work. This could be a coworker, friend, or trusted colleague. You want someone who will give you an honest review of your work, and is willing to give you feedback, whether positive or negative.

Remember, you cannot proofread enough! You do not want to risk all of your hard work and research, and end up with a final case study that has spelling or grammatical errors. One typo could greatly hurt your project and damage your reputation in your field.

All case studies should follow LIT – Logical – Inclusive – Thorough.

The case study obviously must be logical. There can be no guessing or estimating. This means that the report must state what was observed, but cannot include any opinion or assumptions that might come from such an observation.

For example, if a veteran subject arrives at an interview holding an empty liquor bottle and is slurring his words, that observation must be made. However, the researcher cannot make the inference that the subject was intoxicated. The report can only include the facts.

With the Genie case, researchers witnessed Genie hitting herself and practicing self-harm. It could be assumed that she did this when she was angry. However, this wasn't always the case. She would also hit herself when she was afraid, bored or apprehensive. It is essential that researchers not guess or infer.

In order for a report to be inclusive, it must contain ALL data and findings. The researcher cannot pick and choose which data or findings to use in the report.

Using the example above, if a veteran subject arrives for an interview holding an empty liquor bottle and is slurring his words; any and all additional information that can be garnered should be recorded. For instance, what the subject was wearing, what was his demeanor, was he able to speak and communicate, etc.

When observing a man who might be drunk, it can be easy to make assumptions. However, the researcher cannot allow personal biases or beliefs to sway the findings. Any and all relevant facts must be included, regardless of size or perceived importance. Remember, small details might not seem relevant at the time of the interview. But once it is time to catalog the findings, small details might become important.

The last tip is to be thorough. It is important to delve into every observation. The researcher shouldn't just write down what they see and move on. It is essential to detail as much as possible.

For example, when interviewing veteran subjects, there interview responses are not the only information that should be garnered from the interview. The interviewer should use all senses when detailing their subject.

How does the subject appear? Is he clean? How is he dressed?

How does his voice sound? Is he speaking clearly and making cohesive thoughts? Does his voice sound raspy? Does he speak with a whisper, or does he speak too loudly?

Does the subject smell? Is he wearing cologne, or can you smell that he hasn't bathed or washed his clothes? What do his clothes look like? Is he well dressed, or does he wear casual clothes?

What is the background of the subject? What are his current living arrangements? Does he have supportive family and friends? Is he a loner who doesn't have a solid support system? Is the subject working? If so, is he happy with the job? If he is not employed, why is that? What makes the subject unemployable?

Case Studies in Marketing

We have already determined that case studies are very valuable in the business world. This is particularly true in the marketing field, which includes advertising and public relations. While case studies are almost all the same, marketing case studies are usually more dependent on interviews and observations.

Well-Known Marketing Case Studies

DeBeers is a diamond company headquartered in Luxembourg, and based in South Africa. It is well known for its logo, "A diamond is forever", which has been voted the best advertising slogan of the 20 th century.

Many studies have been done about DeBeers, but none are as well known as their marketing case study, and how they positioned themselves to be the most successful and well-known diamond company in the world.

DeBeers developed the idea for a diamond engagement ring. They also invented the "eternity band", which is a ring that has diamonds going all around it, signifying that long is forever.

They also invented the three-stone ring, signifying the past, present and future. De Beers was the first company to attribute their products, diamonds to the idea of love and romance. They originated the idea that an engagement ring should cost two-months salary.

The two-month salary standard is particularly unique, in that it is totally subjective. A ring should mean the same whether the man makes $25,000 a year or $250,000. And yet, the standard sticks due to DeBeers incredible marketing skills.

The De Beers case study is one of the most famous studies when it comes to both advertising and marketing, and is used worldwide as the ultimate example of a successful ongoing marketing campaign.

Planning the Market Research

The most important parts of the marketing case study are:

1. The case study's questions

2. The study's propositions

3. How information and data will be analyzed

4. The logic behind what is being proposed

5. How the findings will be interpreted

The study's questions should be either "how" or "why" questions, and their definitions are the researchers first job. These questions will help determine the study's goals.

Not every case study has a proposition. If you are doing an exploratory study, you will not have propositions. Instead, you will have a stated purpose, which will determine whether your study is successful, or not.

How the information will be analyzed will depend on what the topic is. This would vary depending on whether it was a person, group, or organization. Event and place studies are done differently.

When setting up your research, you will want to follow case study protocol. The protocol should have the following sections:

1. An overview of the case study, including the objectives, topic and issues.

2. Procedures for gathering information and conducting interviews.

3. Questions that will be asked during interviews and data collection.

4. A guide for the final case study report.

When deciding upon which research methods to use, these are the most important:

1. Documents and archival records

2 . Interviews

3. Direct observations (and indirect when possible)

4. Indirect observations, or observations of subjects

5. Physical artifacts and tools

Documents could include almost anything, including letters, memos, newspaper articles, Internet articles, other case studies, or any other document germane to the study.

Developing the Case Study

Developing a marketing case study follows the same steps and procedures as most case studies. It begins with asking a question, "what is missing?"

1. What is the background of the case study? Who requested the study to be done and why? What industry is the study in, and where will the study take place? What marketing needs are you trying to address?

2. What is the problem that needs a solution? What is the situation, and what are the risks? What are you trying to prove?

3. What questions are required to analyze the problem? What questions might the reader of the study have?

4. What tools are required to analyze the problem? Is data analysis necessary? Can the study use just interviews and observations, or will it require additional information?

5. What is your current knowledge about the problem or situation? How much background information do you need to procure? How will you obtain this background info?

6. What other information do you need to know to successfully complete the study?

7. How do you plan to present the report? Will it be a simple written report, or will you add PowerPoint presentations or images or videos? When is the report due? Are you giving yourself enough time to complete the project?

Formulating the Marketing Case Study

1. What is the marketing problem? Most case studies begin with a problem that management or the marketing department is facing. You must fully understand the problem and what caused it. That is when you can start searching for a solution.

However, marketing case studies can be difficult to research. You must turn a marketing problem into a research problem. For example, if the problem is that sales are not growing, you must translate that to a research problem.

What could potential research problems be?

Research problems could be poor performance or poor expectations. You want a research problem because then you can find an answer. Management problems focus on actions, such as whether to advertise more, or change advertising strategies. Research problems focus on finding out how to solve the management problem.

Method of Inquiry

As with the research for most case studies, the scientific method is standard. It allows you to use existing knowledge as a starting point. The scientific method has the following steps:

1. Ask a question – formulate a problem

2. Do background research

3. Formulate a problem

4. Develop/construct a hypothesis

5. Make predictions based on the hypothesis

6. Do experiments to test the hypothesis

7 . Conduct the test/experiment

8 . Analyze and communicate the results

The above terminology is very similar to the research process. The main difference is that the scientific method is objective and the research process is subjective. Quantitative research is based on impartial analysis, and qualitative research is based on personal judgment.

Research Method

After selecting the method of inquiry, it is time to decide on a research method. There are two main research methodologies, experimental research and non-experimental research.

Experimental research allows you to control the variables and to manipulate any of the variables that influence the study.

Non-experimental research allows you to observe, but not intervene. You just observe and then report your findings.

Research Design

The design is the plan for how you will conduct the study, and how you will collect the data. The design is the scientific method you will use to obtain the information you are seeking.

Data Collection

There are many different ways to collect data, with the two most important being interviews and observation.

Interviews are when you ask people questions and get a response. These interviews can be done face-to-face, by telephone, the mail, email, or even the Internet. This category of research techniques is survey research. Interviews can be done in both experimental and non-experimental research.

Observation is watching a person or company's behavior. For example, by observing a persons buying behavior, you could predict how that person will make purchases in the future.

When using interviews or observation, it is required that you record your results. How you record the data will depend on which method you use. As with all case studies, using a research notebook is key, and will be the heart of the study.

Sample Design

When developing your case study, you won't usually examine an entire population; those are done by larger research projects. Your study will use a sample, which is a small representation of the population. When designing your sample, be prepared to answer the following questions:

1. From which type of population should the sample be chosen?

2. What is the process for the selection of the sample?

3. What will be the size of the sample?

There are two ways to select a sample from the general population; probability and non-probability sampling. Probability sampling uses random sampling of everyone in the population. Non-probability sampling uses the judgment of the researcher.

The last step of designing your sample is to determine the sample size. This can depend on cost and accuracy. Larger samples are better and more accurate, but they can also be costly.

Analysis of the Data

In order to use the data, it first must be analyzed. How you analyze the data should be decided upon as early in the process as possible, and will vary depending on the type of info you are collecting, and the form of measurement being used. As stated repeatedly, make sure you keep track of everything in the research notebook.

The Marketing Case Study Report

The final stage of the process is the marketing case study. The final study will include all of the information, as well as detail the process. It will also describe the results, conclusions, and any recommendations. It must have all the information needed so that the reader can understand the case study.

As with all case studies, it must be easy to read. You don't want to use info that is too technical; otherwise you could potentially overwhelm your reader. So make sure it is written in plain English, with scientific and technical terms kept to a minimum.

Using Your Case Study

Once you have your finished case study, you have many opportunities to get that case study in front of potential customers. Here is a list of the ways you can use your case study to help your company's marketing efforts.

1. Have a page on your website that is dedicated to case studies. The page should have a catchy name and list all of the company's case studies, beginning with the most recent. Next to each case study list its goals and results.

2. Put the case study on your home page. This will put your study front and center, and will be immediately visible when customers visit your web page. Make sure the link isn't hidden in an area rarely visited by guests. You can highlight the case study for a few weeks or months, or until you feel your study has received enough looks.

3. Write a blog post about your case study. Obviously you must have a blog for this to be successful. This is a great way to give your case study exposure, and it allows you to write the post directly addressing your audience's needs.

4 . Make a video from your case study. Videos are more popular than ever, and turning a lengthy case study into a brief video is a great way to get your case study in front of people who might not normally read a case study.

5. Use your case study on a landing page. You can pull quotes from the case study and use those on product pages. Again, this format works best when you use market segmentation.

6. Post about your case studies on social media. You can share links on Twitter, Facebook and LinkedIn. Write a little interesting tidbit, enough to capture your client's interest, and then place the link.

7 . Use your case study in your email marketing. This is most effective if your email list is segmented, and you can direct your case study to those most likely to be receptive to it.

8. Use your case studies in your newsletters. This can be especially effective if you use segmentation with your newsletters, so you can gear the case study to those most likely to read and value it.

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

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All You Wanted to Know About How to Write a Case Study

What do you study in your college? If you are a psychology, sociology, or anthropology student, we bet you might be familiar with what a case study is. This research method is used to study a certain person, group, or situation. In this guide from our dissertation writing service , you will learn how to write a case study professionally, from researching to citing sources properly. Also, we will explore different types of case studies and show you examples — so that you won’t have any other questions left.

What Is a Case Study?

A case study is a subcategory of research design which investigates problems and offers solutions. Case studies can range from academic research studies to corporate promotional tools trying to sell an idea—their scope is quite vast.

What Is the Difference Between a Research Paper and a Case Study?

While research papers turn the reader’s attention to a certain problem, case studies go even further. Case study guidelines require students to pay attention to details, examining issues closely and in-depth using different research methods. For example, case studies may be used to examine court cases if you study Law, or a patient's health history if you study Medicine. Case studies are also used in Marketing, which are thorough, empirically supported analysis of a good or service's performance. Well-designed case studies can be valuable for prospective customers as they can identify and solve the potential customers pain point.

Case studies involve a lot of storytelling – they usually examine particular cases for a person or a group of people. This method of research is very helpful, as it is very practical and can give a lot of hands-on information. Most commonly, the length of the case study is about 500-900 words, which is much less than the length of an average research paper.

The structure of a case study is very similar to storytelling. It has a protagonist or main character, which in your case is actually a problem you are trying to solve. You can use the system of 3 Acts to make it a compelling story. It should have an introduction, rising action, a climax where transformation occurs, falling action, and a solution.

Here is a rough formula for you to use in your case study:

Problem (Act I): > Solution (Act II) > Result (Act III) > Conclusion.

Types of Case Studies

The purpose of a case study is to provide detailed reports on an event, an institution, a place, future customers, or pretty much anything. There are a few common types of case study, but the type depends on the topic. The following are the most common domains where case studies are needed:

Historical case studies are great to learn from. Historical events have a multitude of source info offering different perspectives. There are always modern parallels where these perspectives can be applied, compared, and thoroughly analyzed.
Problem-oriented case studies are usually used for solving problems. These are often assigned as theoretical situations where you need to immerse yourself in the situation to examine it. Imagine you’re working for a startup and you’ve just noticed a significant flaw in your product’s design. Before taking it to the senior manager, you want to do a comprehensive study on the issue and provide solutions. On a greater scale, problem-oriented case studies are a vital part of relevant socio-economic discussions.
Cumulative case studies collect information and offer comparisons. In business, case studies are often used to tell people about the value of a product.
Critical case studies explore the causes and effects of a certain case.
Illustrative case studies describe certain events, investigating outcomes and lessons learned.

Need a compelling case study? EssayPro has got you covered. Our experts are ready to provide you with detailed, insightful case studies that capture the essence of real-world scenarios. Elevate your academic work with our professional assistance.

Case Study Format

The case study format is typically made up of eight parts:

Executive Summary. Explain what you will examine in the case study. Write an overview of the field you’re researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences.
Background. Provide background information and the most relevant facts. Isolate the issues.
Case Evaluation. Isolate the sections of the study you want to focus on. In it, explain why something is working or is not working.
Proposed Solutions. Offer realistic ways to solve what isn’t working or how to improve its current condition. Explain why these solutions work by offering testable evidence.
Conclusion. Summarize the main points from the case evaluations and proposed solutions. 6. Recommendations. Talk about the strategy that you should choose. Explain why this choice is the most appropriate.
Implementation. Explain how to put the specific strategies into action.
References. Provide all the citations.

How to Write a Case Study

Let's discover how to write a case study.

Setting Up the Research

When writing a case study, remember that research should always come first. Reading many different sources and analyzing other points of view will help you come up with more creative solutions. You can also conduct an actual interview to thoroughly investigate the customer story that you'll need for your case study. Including all of the necessary research, writing a case study may take some time. The research process involves doing the following:

Define your objective. Explain the reason why you’re presenting your subject. Figure out where you will feature your case study; whether it is written, on video, shown as an infographic, streamed as a podcast, etc.
Determine who will be the right candidate for your case study. Get permission, quotes, and other features that will make your case study effective. Get in touch with your candidate to see if they approve of being part of your work. Study that candidate’s situation and note down what caused it.
Identify which various consequences could result from the situation. Follow these guidelines on how to start a case study: surf the net to find some general information you might find useful.
Make a list of credible sources and examine them. Seek out important facts and highlight problems. Always write down your ideas and make sure to brainstorm.
Focus on several key issues – why they exist, and how they impact your research subject. Think of several unique solutions. Draw from class discussions, readings, and personal experience. When writing a case study, focus on the best solution and explore it in depth. After having all your research in place, writing a case study will be easy. You may first want to check the rubric and criteria of your assignment for the correct case study structure.

Read Also: 'CREDIBLE SOURCES: WHAT ARE THEY?'

Although your instructor might be looking at slightly different criteria, every case study rubric essentially has the same standards. Your professor will want you to exhibit 8 different outcomes:

Correctly identify the concepts, theories, and practices in the discipline.
Identify the relevant theories and principles associated with the particular study.
Evaluate legal and ethical principles and apply them to your decision-making.
Recognize the global importance and contribution of your case.
Construct a coherent summary and explanation of the study.
Demonstrate analytical and critical-thinking skills.
Explain the interrelationships between the environment and nature.
Integrate theory and practice of the discipline within the analysis.

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Case Study Outline

Let's look at the structure of an outline based on the issue of the alcoholic addiction of 30 people.

Introduction

Statement of the issue: Alcoholism is a disease rather than a weakness of character.
Presentation of the problem: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there.
Explanation of the terms: In the past, alcoholism was commonly referred to as alcohol dependence or alcohol addiction. Alcoholism is now the more severe stage of this addiction in the disorder spectrum.
Hypotheses: Drinking in excess can lead to the use of other drugs.
Importance of your story: How the information you present can help people with their addictions.
Background of the story: Include an explanation of why you chose this topic.
Presentation of analysis and data: Describe the criteria for choosing 30 candidates, the structure of the interview, and the outcomes.
Strong argument 1: ex. X% of candidates dealing with anxiety and depression...
Strong argument 2: ex. X amount of people started drinking by their mid-teens.
Strong argument 3: ex. X% of respondents’ parents had issues with alcohol.
Concluding statement: I have researched if alcoholism is a disease and found out that…
Recommendations: Ways and actions for preventing alcohol use.

Writing a Case Study Draft

After you’ve done your case study research and written the outline, it’s time to focus on the draft. In a draft, you have to develop and write your case study by using: the data which you collected throughout the research, interviews, and the analysis processes that were undertaken. Follow these rules for the draft:

Your draft should contain at least 4 sections: an introduction; a body where you should include background information, an explanation of why you decided to do this case study, and a presentation of your main findings; a conclusion where you present data; and references.
In the introduction, you should set the pace very clearly. You can even raise a question or quote someone you interviewed in the research phase. It must provide adequate background information on the topic. The background may include analyses of previous studies on your topic. Include the aim of your case here as well. Think of it as a thesis statement. The aim must describe the purpose of your work—presenting the issues that you want to tackle. Include background information, such as photos or videos you used when doing the research.
Describe your unique research process, whether it was through interviews, observations, academic journals, etc. The next point includes providing the results of your research. Tell the audience what you found out. Why is this important, and what could be learned from it? Discuss the real implications of the problem and its significance in the world.
Include quotes and data (such as findings, percentages, and awards). This will add a personal touch and better credibility to the case you present. Explain what results you find during your interviews in regards to the problem and how it developed. Also, write about solutions which have already been proposed by other people who have already written about this case.
At the end of your case study, you should offer possible solutions, but don’t worry about solving them yourself.

Use Data to Illustrate Key Points in Your Case Study

Even though your case study is a story, it should be based on evidence. Use as much data as possible to illustrate your point. Without the right data, your case study may appear weak and the readers may not be able to relate to your issue as much as they should. Let's see the examples from essay writing service :

‍ With data: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there. Without data: A lot of people suffer from alcoholism in the United States.

Try to include as many credible sources as possible. You may have terms or sources that could be hard for other cultures to understand. If this is the case, you should include them in the appendix or Notes for the Instructor or Professor.

Finalizing the Draft: Checklist

After you finish drafting your case study, polish it up by answering these ‘ask yourself’ questions and think about how to end your case study:

Check that you follow the correct case study format, also in regards to text formatting.
Check that your work is consistent with its referencing and citation style.
Micro-editing — check for grammar and spelling issues.
Macro-editing — does ‘the big picture’ come across to the reader? Is there enough raw data, such as real-life examples or personal experiences? Have you made your data collection process completely transparent? Does your analysis provide a clear conclusion, allowing for further research and practice?

Problems to avoid:

Overgeneralization – Do not go into further research that deviates from the main problem.
Failure to Document Limitations – Just as you have to clearly state the limitations of a general research study, you must describe the specific limitations inherent in the subject of analysis.
Failure to Extrapolate All Possible Implications – Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings.

How to Create a Title Page and Cite a Case Study

Let's see how to create an awesome title page.

Your title page depends on the prescribed citation format. The title page should include:

A title that attracts some attention and describes your study
The title should have the words “case study” in it
The title should range between 5-9 words in length
Your name and contact information
Your finished paper should be only 500 to 1,500 words in length.With this type of assignment, write effectively and avoid fluff

Here is a template for the APA and MLA format title page:

There are some cases when you need to cite someone else's study in your own one – therefore, you need to master how to cite a case study. A case study is like a research paper when it comes to citations. You can cite it like you cite a book, depending on what style you need.

Citation Example in MLA ‍ Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies. Boston: Harvard Business Publishing, 2008. Print.

Citation Example in APA ‍ Hill, L., Khanna, T., & Stecker, E. A. (2008). HCL Technologies. Boston: Harvard Business Publishing.

Citation Example in Chicago Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies.

Case Study Examples

To give you an idea of a professional case study example, we gathered and linked some below.

Eastman Kodak Case Study

Case Study Example: Audi Trains Mexican Autoworkers in Germany

To conclude, a case study is one of the best methods of getting an overview of what happened to a person, a group, or a situation in practice. It allows you to have an in-depth glance at the real-life problems that businesses, healthcare industry, criminal justice, etc. may face. This insight helps us look at such situations in a different light. This is because we see scenarios that we otherwise would not, without necessarily being there. If you need custom essays , try our research paper writing services .

Get Help Form Qualified Writers

Crafting a case study is not easy. You might want to write one of high quality, but you don’t have the time or expertise. If you’re having trouble with your case study, help with essay request - we'll help. EssayPro writers have read and written countless case studies and are experts in endless disciplines. Request essay writing, editing, or proofreading assistance from our custom case study writing service , and all of your worries will be gone.

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How to Write a Policy Analysis Paper Step-by-Step

Organizing Your Social Sciences Research Assignments

Annotated Bibliography
Analyzing a Scholarly Journal Article
Group Presentations
Dealing with Nervousness
Using Visual Aids
Grading Someone Else's Paper
Types of Structured Group Activities
Group Project Survival Skills
Leading a Class Discussion
Multiple Book Review Essay
Reviewing Collected Works
Writing a Case Analysis Paper
Writing a Case Study
About Informed Consent
Writing Field Notes
Writing a Policy Memo
Writing a Reflective Paper
Writing a Research Proposal
Generative AI and Writing
Acknowledgments

Definition and Introduction

Case analysis is a problem-based teaching and learning method that involves critically analyzing complex scenarios within an organizational setting for the purpose of placing the student in a “real world” situation and applying reflection and critical thinking skills to contemplate appropriate solutions, decisions, or recommended courses of action. It is considered a more effective teaching technique than in-class role playing or simulation activities. The analytical process is often guided by questions provided by the instructor that ask students to contemplate relationships between the facts and critical incidents described in the case.

Cases generally include both descriptive and statistical elements and rely on students applying abductive reasoning to develop and argue for preferred or best outcomes [i.e., case scenarios rarely have a single correct or perfect answer based on the evidence provided]. Rather than emphasizing theories or concepts, case analysis assignments emphasize building a bridge of relevancy between abstract thinking and practical application and, by so doing, teaches the value of both within a specific area of professional practice.

Given this, the purpose of a case analysis paper is to present a structured and logically organized format for analyzing the case situation. It can be assigned to students individually or as a small group assignment and it may include an in-class presentation component. Case analysis is predominately taught in economics and business-related courses, but it is also a method of teaching and learning found in other applied social sciences disciplines, such as, social work, public relations, education, journalism, and public administration.

Ellet, William. The Case Study Handbook: A Student's Guide . Revised Edition. Boston, MA: Harvard Business School Publishing, 2018; Christoph Rasche and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Analysis . Writing Center, Baruch College; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

How to Approach Writing a Case Analysis Paper

The organization and structure of a case analysis paper can vary depending on the organizational setting, the situation, and how your professor wants you to approach the assignment. Nevertheless, preparing to write a case analysis paper involves several important steps. As Hawes notes, a case analysis assignment “...is useful in developing the ability to get to the heart of a problem, analyze it thoroughly, and to indicate the appropriate solution as well as how it should be implemented” [p.48]. This statement encapsulates how you should approach preparing to write a case analysis paper.

Before you begin to write your paper, consider the following analytical procedures:

Review the case to get an overview of the situation . A case can be only a few pages in length, however, it is most often very lengthy and contains a significant amount of detailed background information and statistics, with multilayered descriptions of the scenario, the roles and behaviors of various stakeholder groups, and situational events. Therefore, a quick reading of the case will help you gain an overall sense of the situation and illuminate the types of issues and problems that you will need to address in your paper. If your professor has provided questions intended to help frame your analysis, use them to guide your initial reading of the case.
Read the case thoroughly . After gaining a general overview of the case, carefully read the content again with the purpose of understanding key circumstances, events, and behaviors among stakeholder groups. Look for information or data that appears contradictory, extraneous, or misleading. At this point, you should be taking notes as you read because this will help you develop a general outline of your paper. The aim is to obtain a complete understanding of the situation so that you can begin contemplating tentative answers to any questions your professor has provided or, if they have not provided, developing answers to your own questions about the case scenario and its connection to the course readings,lectures, and class discussions.
Determine key stakeholder groups, issues, and events and the relationships they all have to each other . As you analyze the content, pay particular attention to identifying individuals, groups, or organizations described in the case and identify evidence of any problems or issues of concern that impact the situation in a negative way. Other things to look for include identifying any assumptions being made by or about each stakeholder, potential biased explanations or actions, explicit demands or ultimatums , and the underlying concerns that motivate these behaviors among stakeholders. The goal at this stage is to develop a comprehensive understanding of the situational and behavioral dynamics of the case and the explicit and implicit consequences of each of these actions.
Identify the core problems . The next step in most case analysis assignments is to discern what the core [i.e., most damaging, detrimental, injurious] problems are within the organizational setting and to determine their implications. The purpose at this stage of preparing to write your analysis paper is to distinguish between the symptoms of core problems and the core problems themselves and to decide which of these must be addressed immediately and which problems do not appear critical but may escalate over time. Identify evidence from the case to support your decisions by determining what information or data is essential to addressing the core problems and what information is not relevant or is misleading.
Explore alternative solutions . As noted, case analysis scenarios rarely have only one correct answer. Therefore, it is important to keep in mind that the process of analyzing the case and diagnosing core problems, while based on evidence, is a subjective process open to various avenues of interpretation. This means that you must consider alternative solutions or courses of action by critically examining strengths and weaknesses, risk factors, and the differences between short and long-term solutions. For each possible solution or course of action, consider the consequences they may have related to their implementation and how these recommendations might lead to new problems. Also, consider thinking about your recommended solutions or courses of action in relation to issues of fairness, equity, and inclusion.
Decide on a final set of recommendations . The last stage in preparing to write a case analysis paper is to assert an opinion or viewpoint about the recommendations needed to help resolve the core problems as you see them and to make a persuasive argument for supporting this point of view. Prepare a clear rationale for your recommendations based on examining each element of your analysis. Anticipate possible obstacles that could derail their implementation. Consider any counter-arguments that could be made concerning the validity of your recommended actions. Finally, describe a set of criteria and measurable indicators that could be applied to evaluating the effectiveness of your implementation plan.

Use these steps as the framework for writing your paper. Remember that the more detailed you are in taking notes as you critically examine each element of the case, the more information you will have to draw from when you begin to write. This will save you time.

NOTE : If the process of preparing to write a case analysis paper is assigned as a student group project, consider having each member of the group analyze a specific element of the case, including drafting answers to the corresponding questions used by your professor to frame the analysis. This will help make the analytical process more efficient and ensure that the distribution of work is equitable. This can also facilitate who is responsible for drafting each part of the final case analysis paper and, if applicable, the in-class presentation.

Framework for Case Analysis . College of Management. University of Massachusetts; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Rasche, Christoph and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Study Analysis . University of Arizona Global Campus Writing Center; Van Ness, Raymond K. A Guide to Case Analysis . School of Business. State University of New York, Albany; Writing a Case Analysis . Business School, University of New South Wales.

Structure and Writing Style

A case analysis paper should be detailed, concise, persuasive, clearly written, and professional in tone and in the use of language . As with other forms of college-level academic writing, declarative statements that convey information, provide a fact, or offer an explanation or any recommended courses of action should be based on evidence. If allowed by your professor, any external sources used to support your analysis, such as course readings, should be properly cited under a list of references. The organization and structure of case analysis papers can vary depending on your professor’s preferred format, but its structure generally follows the steps used for analyzing the case.

Introduction

The introduction should provide a succinct but thorough descriptive overview of the main facts, issues, and core problems of the case . The introduction should also include a brief summary of the most relevant details about the situation and organizational setting. This includes defining the theoretical framework or conceptual model on which any questions were used to frame your analysis.

Following the rules of most college-level research papers, the introduction should then inform the reader how the paper will be organized. This includes describing the major sections of the paper and the order in which they will be presented. Unless you are told to do so by your professor, you do not need to preview your final recommendations in the introduction. U nlike most college-level research papers , the introduction does not include a statement about the significance of your findings because a case analysis assignment does not involve contributing new knowledge about a research problem.

Background Analysis

Background analysis can vary depending on any guiding questions provided by your professor and the underlying concept or theory that the case is based upon. In general, however, this section of your paper should focus on:

Providing an overarching analysis of problems identified from the case scenario, including identifying events that stakeholders find challenging or troublesome,
Identifying assumptions made by each stakeholder and any apparent biases they may exhibit,
Describing any demands or claims made by or forced upon key stakeholders, and
Highlighting any issues of concern or complaints expressed by stakeholders in response to those demands or claims.

These aspects of the case are often in the form of behavioral responses expressed by individuals or groups within the organizational setting. However, note that problems in a case situation can also be reflected in data [or the lack thereof] and in the decision-making, operational, cultural, or institutional structure of the organization. Additionally, demands or claims can be either internal and external to the organization [e.g., a case analysis involving a president considering arms sales to Saudi Arabia could include managing internal demands from White House advisors as well as demands from members of Congress].

Throughout this section, present all relevant evidence from the case that supports your analysis. Do not simply claim there is a problem, an assumption, a demand, or a concern; tell the reader what part of the case informed how you identified these background elements.

Identification of Problems

In most case analysis assignments, there are problems, and then there are problems . Each problem can reflect a multitude of underlying symptoms that are detrimental to the interests of the organization. The purpose of identifying problems is to teach students how to differentiate between problems that vary in severity, impact, and relative importance. Given this, problems can be described in three general forms: those that must be addressed immediately, those that should be addressed but the impact is not severe, and those that do not require immediate attention and can be set aside for the time being.

All of the problems you identify from the case should be identified in this section of your paper, with a description based on evidence explaining the problem variances. If the assignment asks you to conduct research to further support your assessment of the problems, include this in your explanation. Remember to cite those sources in a list of references. Use specific evidence from the case and apply appropriate concepts, theories, and models discussed in class or in relevant course readings to highlight and explain the key problems [or problem] that you believe must be solved immediately and describe the underlying symptoms and why they are so critical.

Alternative Solutions

This section is where you provide specific, realistic, and evidence-based solutions to the problems you have identified and make recommendations about how to alleviate the underlying symptomatic conditions impacting the organizational setting. For each solution, you must explain why it was chosen and provide clear evidence to support your reasoning. This can include, for example, course readings and class discussions as well as research resources, such as, books, journal articles, research reports, or government documents. In some cases, your professor may encourage you to include personal, anecdotal experiences as evidence to support why you chose a particular solution or set of solutions. Using anecdotal evidence helps promote reflective thinking about the process of determining what qualifies as a core problem and relevant solution .

Throughout this part of the paper, keep in mind the entire array of problems that must be addressed and describe in detail the solutions that might be implemented to resolve these problems.

Recommended Courses of Action

In some case analysis assignments, your professor may ask you to combine the alternative solutions section with your recommended courses of action. However, it is important to know the difference between the two. A solution refers to the answer to a problem. A course of action refers to a procedure or deliberate sequence of activities adopted to proactively confront a situation, often in the context of accomplishing a goal. In this context, proposed courses of action are based on your analysis of alternative solutions. Your description and justification for pursuing each course of action should represent the overall plan for implementing your recommendations.

For each course of action, you need to explain the rationale for your recommendation in a way that confronts challenges, explains risks, and anticipates any counter-arguments from stakeholders. Do this by considering the strengths and weaknesses of each course of action framed in relation to how the action is expected to resolve the core problems presented, the possible ways the action may affect remaining problems, and how the recommended action will be perceived by each stakeholder.

In addition, you should describe the criteria needed to measure how well the implementation of these actions is working and explain which individuals or groups are responsible for ensuring your recommendations are successful. In addition, always consider the law of unintended consequences. Outline difficulties that may arise in implementing each course of action and describe how implementing the proposed courses of action [either individually or collectively] may lead to new problems [both large and small].

Throughout this section, you must consider the costs and benefits of recommending your courses of action in relation to uncertainties or missing information and the negative consequences of success.

The conclusion should be brief and introspective. Unlike a research paper, the conclusion in a case analysis paper does not include a summary of key findings and their significance, a statement about how the study contributed to existing knowledge, or indicate opportunities for future research.

Begin by synthesizing the core problems presented in the case and the relevance of your recommended solutions. This can include an explanation of what you have learned about the case in the context of your answers to the questions provided by your professor. The conclusion is also where you link what you learned from analyzing the case with the course readings or class discussions. This can further demonstrate your understanding of the relationships between the practical case situation and the theoretical and abstract content of assigned readings and other course content.

Problems to Avoid

The literature on case analysis assignments often includes examples of difficulties students have with applying methods of critical analysis and effectively reporting the results of their assessment of the situation. A common reason cited by scholars is that the application of this type of teaching and learning method is limited to applied fields of social and behavioral sciences and, as a result, writing a case analysis paper can be unfamiliar to most students entering college.

After you have drafted your paper, proofread the narrative flow and revise any of these common errors:

Unnecessary detail in the background section . The background section should highlight the essential elements of the case based on your analysis. Focus on summarizing the facts and highlighting the key factors that become relevant in the other sections of the paper by eliminating any unnecessary information.
Analysis relies too much on opinion . Your analysis is interpretive, but the narrative must be connected clearly to evidence from the case and any models and theories discussed in class or in course readings. Any positions or arguments you make should be supported by evidence.
Analysis does not focus on the most important elements of the case . Your paper should provide a thorough overview of the case. However, the analysis should focus on providing evidence about what you identify are the key events, stakeholders, issues, and problems. Emphasize what you identify as the most critical aspects of the case to be developed throughout your analysis. Be thorough but succinct.
Writing is too descriptive . A paper with too much descriptive information detracts from your analysis of the complexities of the case situation. Questions about what happened, where, when, and by whom should only be included as essential information leading to your examination of questions related to why, how, and for what purpose.
Inadequate definition of a core problem and associated symptoms . A common error found in case analysis papers is recommending a solution or course of action without adequately defining or demonstrating that you understand the problem. Make sure you have clearly described the problem and its impact and scope within the organizational setting. Ensure that you have adequately described the root causes w hen describing the symptoms of the problem.
Recommendations lack specificity . Identify any use of vague statements and indeterminate terminology, such as, “A particular experience” or “a large increase to the budget.” These statements cannot be measured and, as a result, there is no way to evaluate their successful implementation. Provide specific data and use direct language in describing recommended actions.
Unrealistic, exaggerated, or unattainable recommendations . Review your recommendations to ensure that they are based on the situational facts of the case. Your recommended solutions and courses of action must be based on realistic assumptions and fit within the constraints of the situation. Also note that the case scenario has already happened, therefore, any speculation or arguments about what could have occurred if the circumstances were different should be revised or eliminated.

Bee, Lian Song et al. "Business Students' Perspectives on Case Method Coaching for Problem-Based Learning: Impacts on Student Engagement and Learning Performance in Higher Education." Education & Training 64 (2022): 416-432; The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Georgallis, Panikos and Kayleigh Bruijn. "Sustainability Teaching using Case-Based Debates." Journal of International Education in Business 15 (2022): 147-163; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Georgallis, Panikos, and Kayleigh Bruijn. "Sustainability Teaching Using Case-based Debates." Journal of International Education in Business 15 (2022): 147-163; .Dean, Kathy Lund and Charles J. Fornaciari. "How to Create and Use Experiential Case-Based Exercises in a Management Classroom." Journal of Management Education 26 (October 2002): 586-603; Klebba, Joanne M. and Janet G. Hamilton. "Structured Case Analysis: Developing Critical Thinking Skills in a Marketing Case Course." Journal of Marketing Education 29 (August 2007): 132-137, 139; Klein, Norman. "The Case Discussion Method Revisited: Some Questions about Student Skills." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 30-32; Mukherjee, Arup. "Effective Use of In-Class Mini Case Analysis for Discovery Learning in an Undergraduate MIS Course." The Journal of Computer Information Systems 40 (Spring 2000): 15-23; Pessoa, Silviaet al. "Scaffolding the Case Analysis in an Organizational Behavior Course: Making Analytical Language Explicit." Journal of Management Education 46 (2022): 226-251: Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Schweitzer, Karen. "How to Write and Format a Business Case Study." ThoughtCo. https://www.thoughtco.com/how-to-write-and-format-a-business-case-study-466324 (accessed December 5, 2022); Reddy, C. D. "Teaching Research Methodology: Everything's a Case." Electronic Journal of Business Research Methods 18 (December 2020): 178-188; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

Writing Tip

Ca se Study and Case Analysis Are Not the Same!

Confusion often exists between what it means to write a paper that uses a case study research design and writing a paper that analyzes a case; they are two different types of approaches to learning in the social and behavioral sciences. Professors as well as educational researchers contribute to this confusion because they often use the term "case study" when describing the subject of analysis for a case analysis paper. But you are not studying a case for the purpose of generating a comprehensive, multi-faceted understanding of a research problem. R ather, you are critically analyzing a specific scenario to argue logically for recommended solutions and courses of action that lead to optimal outcomes applicable to professional practice.

To avoid any confusion, here are twelve characteristics that delineate the differences between writing a paper using the case study research method and writing a case analysis paper:

Case study is a method of in-depth research and rigorous inquiry ; case analysis is a reliable method of teaching and learning . A case study is a modality of research that investigates a phenomenon for the purpose of creating new knowledge, solving a problem, or testing a hypothesis using empirical evidence derived from the case being studied. Often, the results are used to generalize about a larger population or within a wider context. The writing adheres to the traditional standards of a scholarly research study. A case analysis is a pedagogical tool used to teach students how to reflect and think critically about a practical, real-life problem in an organizational setting.
The researcher is responsible for identifying the case to study; a case analysis is assigned by your professor . As the researcher, you choose the case study to investigate in support of obtaining new knowledge and understanding about the research problem. The case in a case analysis assignment is almost always provided, and sometimes written, by your professor and either given to every student in class to analyze individually or to a small group of students, or students select a case to analyze from a predetermined list.
A case study is indeterminate and boundless; a case analysis is predetermined and confined . A case study can be almost anything [see item 9 below] as long as it relates directly to examining the research problem. This relationship is the only limit to what a researcher can choose as the subject of their case study. The content of a case analysis is determined by your professor and its parameters are well-defined and limited to elucidating insights of practical value applied to practice.
Case study is fact-based and describes actual events or situations; case analysis can be entirely fictional or adapted from an actual situation . The entire content of a case study must be grounded in reality to be a valid subject of investigation in an empirical research study. A case analysis only needs to set the stage for critically examining a situation in practice and, therefore, can be entirely fictional or adapted, all or in-part, from an actual situation.
Research using a case study method must adhere to principles of intellectual honesty and academic integrity; a case analysis scenario can include misleading or false information . A case study paper must report research objectively and factually to ensure that any findings are understood to be logically correct and trustworthy. A case analysis scenario may include misleading or false information intended to deliberately distract from the central issues of the case. The purpose is to teach students how to sort through conflicting or useless information in order to come up with the preferred solution. Any use of misleading or false information in academic research is considered unethical.
Case study is linked to a research problem; case analysis is linked to a practical situation or scenario . In the social sciences, the subject of an investigation is most often framed as a problem that must be researched in order to generate new knowledge leading to a solution. Case analysis narratives are grounded in real life scenarios for the purpose of examining the realities of decision-making behavior and processes within organizational settings. A case analysis assignments include a problem or set of problems to be analyzed. However, the goal is centered around the act of identifying and evaluating courses of action leading to best possible outcomes.
The purpose of a case study is to create new knowledge through research; the purpose of a case analysis is to teach new understanding . Case studies are a choice of methodological design intended to create new knowledge about resolving a research problem. A case analysis is a mode of teaching and learning intended to create new understanding and an awareness of uncertainty applied to practice through acts of critical thinking and reflection.
A case study seeks to identify the best possible solution to a research problem; case analysis can have an indeterminate set of solutions or outcomes . Your role in studying a case is to discover the most logical, evidence-based ways to address a research problem. A case analysis assignment rarely has a single correct answer because one of the goals is to force students to confront the real life dynamics of uncertainly, ambiguity, and missing or conflicting information within professional practice. Under these conditions, a perfect outcome or solution almost never exists.
Case study is unbounded and relies on gathering external information; case analysis is a self-contained subject of analysis . The scope of a case study chosen as a method of research is bounded. However, the researcher is free to gather whatever information and data is necessary to investigate its relevance to understanding the research problem. For a case analysis assignment, your professor will often ask you to examine solutions or recommended courses of action based solely on facts and information from the case.
Case study can be a person, place, object, issue, event, condition, or phenomenon; a case analysis is a carefully constructed synopsis of events, situations, and behaviors . The research problem dictates the type of case being studied and, therefore, the design can encompass almost anything tangible as long as it fulfills the objective of generating new knowledge and understanding. A case analysis is in the form of a narrative containing descriptions of facts, situations, processes, rules, and behaviors within a particular setting and under a specific set of circumstances.
Case study can represent an open-ended subject of inquiry; a case analysis is a narrative about something that has happened in the past . A case study is not restricted by time and can encompass an event or issue with no temporal limit or end. For example, the current war in Ukraine can be used as a case study of how medical personnel help civilians during a large military conflict, even though circumstances around this event are still evolving. A case analysis can be used to elicit critical thinking about current or future situations in practice, but the case itself is a narrative about something finite and that has taken place in the past.
Multiple case studies can be used in a research study; case analysis involves examining a single scenario . Case study research can use two or more cases to examine a problem, often for the purpose of conducting a comparative investigation intended to discover hidden relationships, document emerging trends, or determine variations among different examples. A case analysis assignment typically describes a stand-alone, self-contained situation and any comparisons among cases are conducted during in-class discussions and/or student presentations.

The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Yin, Robert K. Case Study Research and Applications: Design and Methods . 6th edition. Thousand Oaks, CA: Sage, 2017; Crowe, Sarah et al. “The Case Study Approach.” BMC Medical Research Methodology 11 (2011): doi: 10.1186/1471-2288-11-100; Yin, Robert K. Case Study Research: Design and Methods . 4th edition. Thousand Oaks, CA: Sage Publishing; 1994.

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BMC Med Res Methodol

The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

2 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Ann Robertson

3 School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

Anthony Avery

Aziz sheikh.

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables Tables1, 1 , ,2, 2 , ,3 3 and and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables Tables2, 2 , ,3 3 and and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables Tables2 2 and and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table (Table2 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table (Table4 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 8 ]

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Assessing the reliability of a physical-based model and a convolutional neural network in an ungauged watershed for daily streamflow calculation: a case study in southern Portugal

Original Article
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Published: 25 March 2024
Volume 83 , article number 215 , ( 2024 )

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Ana R. Oliveira 1 ,
Tiago B. Ramos 1 ,
Lucian Simionesei 1 &
Ramiro Neves 1

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The main goal of this study was to estimate inflows to the Maranhão reservoir, southern Portugal, using two distinct modeling approaches: a one-dimensional convolutional neural network (1D-CNN) model and a physically based model. The 1D-CNN was previously trained, validated, and tested in a sub-basin of the study area where observed streamflow values were available. The trained model was here subject to an improvement and applied to the entire watershed by replacing the forcing variables (accumulated and delayed precipitation) to make them correspond to the values of the entire watershed. The same way, the physically based MOHID-Land model was calibrated and validated for the same sub-basin, and the calibrated parameters were then applied to the entire watershed. Inflow values estimated by both models were validated considering a mass balance at the reservoir. The 1D-CNN model demonstrated a better performance in simulating daily values, peak flows, and the wet period. The MOHID-Land model showed a better performance in estimating streamflow values during dry periods and for a monthly analysis. Hence, results show the adequateness of both modeling solutions for integrating a decision support system aimed at supporting decision-makers in the management of water availability in an area subjected to increasing scarcity.

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Introduction

The IPCC 2022 report (Pörtner et al. 2022 ) projects an increase in the frequency and severity of low flows in Southern Europe, resulting from increasing drought and water scarcity conditions. Population exposed to at moderate water scarcity will grow by 18% and 54% for a raise of 1.5°C and 2°C in air temperature, respectively. The groundwater resources will be affected by an increase in abstraction rates and a decrease in recharge rates. Agriculture, which represents the main water use in the region, may be seriously limited by water availability. Thus, there is a need to improve water management at different scales to cope with the increasing scarcity. At the regional scale, this means the construction of dams and reservoirs to increase water storage, desalination, water reuse, and the adoption of water conservation measures. At the plot scale, that means reallocation to crops more resistant to drought conditions, the improvement of water use efficiency and performance of irrigation systems, and the implementation of soil water conservation practices (Jovanovic et al. 2020 ; Pereira et al. 2009 ).

Decision-support systems (DSSs) have been developed over the last few decades to improve water resource management at different spatial and temporal scales (Teodosiu et al. 2009 ). These tools commonly consist of interactive software-based systems where useful information from raw data sources, documents, simulation models, and other sources is aggregated to identify and solve problems and support decision-making. Considering the plot scale, Smart Irrigation Decision Support System (SIDSS, Navarro-Hellín et al. 2016 ) and IrrigaSys (Simionesei et al. 2020 ) are examples of DSSs for irrigation water management support. SIDSS estimates weekly irrigation needs based on data from soil sensors and/or weather stations using two machine learning techniques. IrrigaSys also estimates weekly irrigation needs using a physically based model fed by weather forecast and hindcast data. When considering larger scales, Zhang et al. ( 2015a ) designed and developed a prototype of a DSS for watershed management by integrating open-source web-based geographical information systems, a modeling component, and a cloud computing platform. Ashrafi and Mahmoudi ( 2019 ) presented a DSS to assist decision-makers in examining the impacts of different operating policies at the basin scale. DSSs are also applied to reservoir flood control operations (Delaney et al. 2020 ) and to early warning and detection, follow-up, and early response to flood events and hazmat pollution occurrences in inland and transitional waters (HAZRUNOFF Project - Layman’s Report 2020 ).

As proposed by Miser and Quade ( 1985 ), one of the steps to design a DSS is the building of models to predict consequences. A good hydrological and/or hydraulic model with reliable results and proved forecast capacity is of paramount importance for water management DSSs. Their results can then feed other models in the DSS. For instance, modeled groundwater levels can be used to estimate irrigation needs, or the simulation of river flows can help in flood forecast. However, modeling results can also be directly used to support decision-making.

Concerning models’ classification, they can be divided into three main groups according to their complexity: (i) empirical models; (ii) conceptual models; and (iii) physical models (Sitterson et al. 2017 ). Empirical models are based on linear and non-linear equations that relate inputs and outputs ignoring the physical processes. These types of models are considered the simplest models. Conceptual models are based on simplified equations to describe the hydrological processes and are characterized by an intermediate level of complexity. Physical-based models, also known as process-based models, are the most complex and rely on physical principles, being suitable to provide insights into physical processes. Usually, physical models use finite difference equations and state variables that can be measured and are time- and space-dependent (Devia et al. 2015 ; Fatichi et al. 2016 ). However, their weakness relies on the large number of parameters required to describe the physical characteristics of the watershed, which leads to high complexity levels that make their correct implementation difficult and laborious calibration and validation processes (Devia et al. 2015 ; Abbott et al. 1986a , b ; Ranatunga et al. 2016 ; Zhang et al. 2015b ; Mehr et al. 2013 ).

The study presented here is included within the framework of a larger work aimed at developing a DSS for supporting water management in the Maranhão and Montargil reservoirs, in southern Portugal. These reservoirs store water that is used mainly for irrigation of the Sorraia Valley, which comprehended a cultivated area of 21,280 ha and an irrigated area of 18,754 ha (ARBVS 2023) in 2021. With a 52% increase in the irrigated area over the last 2 decades (ARBVS 2023) and facing predictions of river flow decrease between 54 and 94% due to climate change (Almeida et al. 2018 ), accurate forecast of streamflow is of extreme importance to improve the management of water availabilities in the region. Taking as example the Maranhão reservoir, the work presented here makes use of two different types of models to estimate the daily inflow to the reservoir and discusses the advantages and weaknesses of both approaches. The applied models were the physically based MOHID-Land model (Trancoso et al. 2009 ; Canuto et al. 2019 ; Oliveira et al. 2020 ) and a convolutional neural network (CNN) (Oliveira et al. 2023 ), i.e., a data-driven model. In both cases, the models were calibrated/trained and validated using data from a hydrometric station that corresponds to 30% of the Maranhão watershed. Because there are no stations monitoring the entire watershed despite the importance of this information for the sustainability of the irrigation district, this study also aims to analyze the capacity of both approaches to represent streamflow generation in the entire watershed. That analysis comprehended the expansion of models results from the referred sub-basin to the full basin scale through the extension of the calibrated parameters in MOHID-Land, or through the replacing of the forcing variables in the CNN model. The results were then validated with a monthly reservoir mass balance. Therefore, this study provides sophisticated modeling tools for streamflow calculation in the Maranhão watershed, which were developed using two distinct modeling approaches. The ultimate aim is their integration into the DSS for supporting water managers in the decision-making of water availabilities in the region.

Materials and methods

Description of the study area.

The Maranhão dam is located at Ribeira da Seda, southern Portugal (39° 0′ 53.846″ N; 7° 58′ 33.149″ W). The corresponding reservoir has a total capacity of 205 hm 3 and drains an area close to 2300 km 2 . The minimum, average, and maximum altitudes are 122, 261, and 723 m, respectively (EU-DEM 2019) (Fig. 1 ).

Maranhão watershed: location, delineation, elevation, main rivers, and hydrometric stations

The climate is classified as Mediterranean hot-summer (Csa) according to Köppen–Geiger climate classification (Agencia Estatal de Meteorología (España) 2011). The average annual precipitation is 608 mm. The minimum and maximum average monthly precipitation are 4 mm in July and August and 84 mm in December. The average monthly air temperature ranges from 24 °C in July and August, and 9°C in January, while the annual average is 16 °C. The main soil reference groups are Luvisols (67%), Regosols (18%), and Cambisols (11%) (Panagos et al. 2012 ). The main land uses are non-irrigated arable land and agro-forestry areas, both representing 28% of the watershed, broad-leaved forest, occupying 15%, and olive groves, with a representation of 11% (CLC 2012 2019).

The Maranhão watershed has four hydrometric stations (Fig. 1 ), with all measuring daily streamflow in natural regime. Table 1 presents a brief characterization of those stations.

Figure 2 shows the monthly patterns considering the daily streamflow values at the four stations. In accordance with the meteorological characterization, streamflow patterns show higher values between November and April, while lower values occur between May and September, with August presenting the lowest value.

Monthly distribution of streamflow in the four hydrometric stations (source: SNIRH 2021 )

The water stored in the Maranhão reservoir is mainly for irrigation of the Sorraia Valley (ARBVS 2023). Other uses include energy production, industrial supply, and recreation. The stored volumes normally increase during the wet period and decrease in the dry period as expected in hydroagricultural reservoirs (Fig. 3 ).

Monthly pattern of stored volume in Maranhão reservoir (source: SNIRH 2021 )

Convolutional neural network model description

A one-dimensional convolutional neural network (1D-CNN) was used to estimate daily streamflow at Ponte Vila Formosa. This 1D-CNN model was created, developed, optimized, and tuned in Python language (version 3.8.10) using public and free tools (Keras, Chollet et al. 2015 ; TensorFlow, Abadi et al. 2016 ; KerasTuner, O’Malley et al. 2019 ; Pandas, McKinney 2010 ; Scikit-learn, Pedregosa et al. 2011 ). A detailed description about the development of the 1D-CNN model is presented in Oliveira et al. ( 2023 ). In that study, the authors carried out a set of experiments where three different neural network models were tested for streamflow estimation, as well as several combinations of precipitation and air temperature values. The models’ structures and hyper-parameters were optimized and tuned using six different training algorithms. Also, the batch size and the number of epochs were optimized. The best solution for streamflow estimation was obtained with a 1D-CNN model composed of one input 1D convolutional (1D-Conv) layer with 16 filters, a kernel size equal to 1, and an output dense layer activated by a linear function. Between them, two 1D-Conv layers, each having 32 filters and a kernel size of 8, were applied. After each 1D-Conv layer, a MaxPooling1D layer with pool_size set to 2 was placed. The Nadam optimizer was the training algorithm with the best performance combined with a learning rate of 1 × 10 –3 and a ε (constant used for numerical stability) of 1 × 10 –8 . The batch size and the number of epochs were 20 and 200, respectively. Finally, the input variable was the daily precipitation values accumulated in 1, 2, 3, 4, 5, and 10 days and delayed in 1, 2, 3, 4, 5, 6, and 7 days.

The CNN model was tuned, trained, and validated considering the streamflow values available in Ponte Vila Formosa station (30% of the Maranhão watershed) for the period from 01/01/2001 to 01/01/2009. The model performance was considered good, reaching a Nash–Sutcliffe Efficiency (NSE) of 0.86, a coefficient of determination (R 2 ) of 0.87, a percent bias (PBIAS) of 10.5%, and a root-mean-squared error (RMSE) of 4.2 m 3 s −1 for the test dataset. Thus, in this study, the same 1D-CNN model was used by considering the precipitation of the entire Maranhão watershed instead of the sub-basin’s data as in the original version.

Input variables for 1D-CNN model

The precipitation data used to train the 1D-CNN model were obtained from the ERA5-Reanalysis dataset (Hersbach et al. 2017 ). This is a gridded product with a resolution of 31 km and an hourly timestep, making it an appropriate option for the implementation of the physically based model, which requires sub-daily precipitation in small watersheds like Maranhão. Precipitation data were extracted from the dataset considering all the cells within the limits of the watershed. Precipitation hourly values were then averaged within the watershed area and accumulated each day from 01/01/2001 to 31/12/2009. The daily precipitation values in the watershed accumulated in 1, 2, 3, 4, 5, and 10 days and delayed in 1, 2, 3, 4, 5, 6, and 7 days were considered. The average annual precipitation for the period considered in this study was 575 mm, with July (3 mm) and August (8 mm) presenting the minimum monthly values, and October (104 mm) and November and December (both with 67 mm) the months when more precipitation was registered.

Estimation of Maranhão inflow with 1D-CNN

The Maranhão reservoir’s daily inflow was estimated considering the daily precipitation in the corresponding watershed and the trained 1D-CNN model. However, because of the intrinsic random behavior verified in randomly initialized neural networks (Duan et al. 2020 ; Alzubaidi et al. 2021), the 1D-CNN model was trained 100 times. Those 100 runs were performed using the same dataset and division into training, validation, and test datasets presented in Oliveira et al. ( 2023 ). After each run, the results were compared and evaluated considering the observed streamflow in Ponte Vila Formosa station. Based on the statistical evaluation, the model with the best performance was selected.

The selected 1D-CNN model was then exposed to Maranhão watershed daily precipitation, with results representing the daily surface flow generated in the watershed and flowing to the Maranhão reservoir. Those daily values were then aggregated by month and transformed into volume. The estimated monthly volume that reached Maranhão reservoir was incorporated into the reservoir mass balance to estimate the stored volume in the following month. The validation of inflow values was made through the comparison of estimated stored volumes and the corresponding observed values.

MOHID-Land model description

MOHID-Land is an open-source hydrological model, with the code available in an online repository (github.com/Mohid-Water-Modelling-System/Mohid). MOHID-Land (Trancoso et al. 2009 ; Canuto et al. 2019 ; Oliveira et al. 2020 ) is a fully distributed and physically based model. Considering the mass and momentum conservation equations and a finite volume approach, the model simulates the water movement between four main compartments: atmosphere, porous media, soil surface, and river network. To avoid instability problems and save computational time, the model time step is variable being higher during dry seasons and lower in wet periods when water fluxes increase.

According to his finite volume approach, the domains in MOHID-Land are discretized by a regular grid in the surface plane and by a Cartesian coordinate system in the vertical direction. The land surface considers a 2D domain to simulate the water movement, while the porous media is represented by a 3D domain, which includes the same surface grid and is complemented with the vertical grid with variable thickness layers. Additionally, a 1D domain representing the river network can be derived from a digital terrain model represented in the horizontal grid. The water lines of the river network are then delineated by linking surface cell centers (nodes).

The four compartments referred to before are all explicitly simulated, except the atmosphere which is only responsible for providing the data needed for imposing surface boundary conditions. The atmospheric data can be space and/or time variant, and include precipitation, air temperature, relative humidity, wind velocity, solar radiation, and/or cloud cover.

The amount of water precipitated in each cell is divided into surface and subsurface flow considering the infiltration process and according to the soil saturation state. In this study, the infiltration rate (i, LT −1 ) was computed according to the Darcy’s law

where K sat is the saturated soil hydraulic conductivity (LT −1 ), h is the soil pressure head (L), and z is the vertical space coordinate (L).

The movement of infiltrated water in porous media was simulated using the Richards’ equation, which is applied to the whole subsurface domain and simulates saturated and unsaturated flow using the same grid

where θ is the volumetric water content (L 3 L −3 ), x i represents the xyz directions (–), K is the hydraulic conductivity (LT −1 ), and S is the sink term representing root water uptake (L 3 L −3 T −1 ). The soil hydraulic parameters were described using the van Genuchten–Mualem functional relationships (Mualem 1976 ; van Genuchten 1980 ). When a cell reaches saturation, i.e., when soil moisture in a cell is above a threshold value defined by the user, the model considers the saturated conductivity to compute flow and pressure becomes hydrostatic, corrected by friction. The ratio between the horizontal and vertical hydraulic conductivities is defined by a factor ( f h = K hor / K ver ) that can also be tuned by the user.

The root water uptake was estimated considering the weather conditions and soil water contents. The reference evapotranspiration (ET o ) rates were computed following the FAO Penman–Monteith method (Allen et al. 1998 ). The crop evapotranspiration (ET c ) rates were then estimated by multiplying the ET o first with a crop coefficient ( K c ). The K c values were made to vary as a function of the plant development stage, as follows:

where GFr, GFr1, GFr2, and GFrLAI Sen are the plant growth fractions in the simulated instant, the initial stage, the mid-season stage, and when the LAI senescence starts, respectively, and K c,ini , K c,mid , and K c,end are the crop coefficients during the initial, mid-season and end-season stages, respectively. The plant growth stages are represented as a percentage of maturity heat units, and the values for GFr1, GFr2, and GFrLAI Sen are defined in the plant growth database of MOHID-Land. ET c values are then partitioned into potential soil evaporation (E s ) and crop transpiration (T c ) as a function of the simulated leaf area index (LAI), which is computed using a modified version of the EPIC model (Neitsch et al. 2011 ; Williams et al. 1989 ) and considering the heat units approach for the plant to reach maturity, the crop development stages, and crop stress (Ramos et al. 2017 ). Following the macroscopic approach proposed by Feddes et al. ( 1978 ), root water uptake reductions (i.e., actual crop transpiration rates, T a ) are computed by distributing water extractions along the root zone domain and are estimated considering the presence of depth-varying stressors, such as water stress (Šimůnek and Hopmans 2009 ; Skaggs et al. 2006 ). Finally, the actual soil evaporation is calculated from potential soil evaporation by imposing a pressure head threshold value (ASCE 1996).

The amount of water that is not able to infiltrate is transformed into surface flow which is computed by solving the Saint–Venant equation in its conservative form, accounting for advection, pressure, and friction forces

where Q is the water flow (L 3 T −1 ), A is the cross-sectional flow area ( L 2 ), g is the gravitational acceleration (LT −2 ), ν is the flow velocity (LT −1 ), H is the hydraulic head (L), n is the Manning coefficient (TL −1/3 ), R h is the hydraulic radius (L), and subscripts u and v denote flow directions. The Saint–Venant equation is solved on a 2D domain considering the directions of the horizontal grid except for the river network, where it is solved considering the 1D domain comprehending the water lines. There, the cross-section for each node of the river network is defined by the user.

The water changes between the river network and the soil surface are estimated according to a kinematic approach, neglecting bottom friction, and using an implicit algorithm to avoid instabilities. The water fluxes between the river network and the porous media are driven by the pressure gradient in the interface of these two mediums.

Model set-up

The MOHID-Land model was implemented using a constant horizontal spaced grid with a resolution of 0.006º in longitudinal and latitudinal directions (⁓520 × 666 m). To cover the modeled domain, the grid had 140 columns and 110 rows, with its origin located at 38° 45′ 16.5" N and 8° 03′ 12.4" W.

Elevation data were interpolated to the MOHID-Land grid from the digital elevation model (DEM) provided by the European Environment Agency (EU-DEM 2019) and have a resolution of approximately 30 m (0.00028°). The watershed’s minimum and maximum elevations after the interpolation process were 107 m and 725 m, respectively (Fig. 4 a). The delineation of the watershed and the river network was performed considering the cell where the dam of Maranhão reservoir is located as the outlet. The minimum area to consider the existence of a waterline (minimum threshold area) was 10 km 2 . Additionally, a rectangular geometry was chosen to represent the river cross-sections with width and height defined according to Andreadis et al. ( 2013 ). The cross-section dimensions were related to the drained area and were assigned to the river network according to Table 2 . For the nodes where the drained area relied between the values presented on the table, the cross-section dimensions were linearly interpolated based on the given information.

MOHID-Land inputs for Maranhão watershed: a digital terrain model and watershed and river network delineation; b Manning coefficient values; c types of vegetation; d identification number of the types of soil in surface horizon; e identification number of the types of soil in middle horizon; and f identification number of the types of soil in bottom horizon

The CORINE Land Cover 2012, with a resolution of 100 m (CLC 2012, 2019), was interpolated to the MOHID-Land’s grid and was used for representing land use in the watershed. Each land-use class was associated with: (i) a Manning coefficient, which was defined according to Pestana et al. ( 2013 ) (Fig. 4 b), and (ii) a vegetation type class considering MOHID-Land’s database (Fig. 4 c).

The K c values were defined according to Allen et al. ( 1998 ) for agriculture (summer and winter crops), orchard, pasture, and brush, while pine, oak, and forest crop coefficients were defined based on the values proposed by Corbari et al. ( 2017 ) (Table 3 ).

The Mualem–van Genuchten hydraulic parameters were obtained from the European Soil Hydraulic Database (EU Soil Database, Tóth et al. 2017 ). Although the database provides information at 7 different depths, with a resolution of 250 m, the present application only considered data from 0.3, 1.0 and 2.0 m depths. The porous media was divided into 6 layers, with a thickness of 0.3, 0.3, 0.7, 0.7, 1.5, and 1.5 m from surface to bottom (vertical grid), with the maximum total soil depth of 5.0 m. These layers were organized according to 3 different horizons characterized by the soil hydraulic properties acquired from the selected depths of EU Soil Database. The 2 surface layers (0–0.6 m) were associated with the data at 0.3 m depth, the 2 middle layers (0.6–2.0 m) acquired the values at 1.0 m depth, and the information at 2.0 m depth was representative of the 2 bottom layers (2.0–5.0 m) (Table 4 ). The spatial variation of soil properties in the surface, middle, and bottom horizons are shown in Fig. 4 .d, e and f, respectively, with each ID corresponding to a different combination of soil hydraulic data. The f h parameter relating horizontal and vertical hydraulic conductivities was set to 10.

As for the input variables used in the neural network model, meteorological data were obtained from ERA5-Reanalysis dataset (Hersbach et al. 2017 ). For the implementation of MOHID-Land, the meteorological properties incorporated were the total precipitation, air temperature, and dew point temperature (at 2 m height), u and v components of wind velocity (at 10 m height), surface solar radiation downwards, and total cloud cover. Wind velocity was adjusted from 10 to 2 m height and relative humidity was estimated from air and dew point temperatures according to Allen et al. ( 1998 ).

Estimation of Maranhão inflow with MOHID-Land

MOHID-Land was directly implemented in the entire Maranhão watershed, but the lack of daily inflow data at the outlet only allowed model calibration and validation to be performed at Ponte Vila Formosa. There, the estimated daily streamflow data were compared with the observed data, and, when model results are similar to the observed values with the model having a good representation of the streamflow generation on that sub-basin, the calibrated parameters were assumed as representatives of the Maranhão watershed. Hence, the daily streamflow estimated by the model in the outlet section was considered to represent the Maranhão reservoir’s inflow and was transformed to monthly volume. The monthly volumes were then validated with a reservoir mass balance identical to the one presented for the validation of 1D-CNN model’s results.

Models’ evaluation

MOHID-Land and 1D-CNN were calibrated/trained using the average daily streamflow in Ponte Vila Formosa hydrometric station. Validation was performed with daily and monthly timesteps. The dataset was also divided into wet (October–March), and dry (April–September) periods and the results were validated, ignoring the division between calibrated/trained.

In the case of MOHID-Land, the calibration period was from 01/01/2002 to 31/01/2003 and the validation was from 01/01/2004 to 31/12/2009. For the 1D-CNN model, each of the 100 runs was evaluated considering the same test dataset presented by Oliveira et al. ( 2023 ). For both models, streamflow estimation performance was evaluated in Ponte Vila Formosa station. The analysis was made with four different statistical parameters, namely, the R 2 , the PBIAS, the RMSE, and the NSE

where X i obs and X i sim are the flow values observed and estimated by the model on day i , respectively. X mean obs and X mean sim are the average flow considering the observed and the modeled values in the analyzed period, and p is the total number of days/values in this period. According to Moriasi et al. ( 2007 ), a model is considered satisfactory when NSE > 0.5, PBIAS ± 25%, and R 2 > 0.5, while the RMSE represents the standard deviation of the residuals with lower values meaning a better model’s performance.

Maranhão reservoir’s inflow was evaluated with a monthly timestep, since this is the frequency of the data available in the reservoir. Since the models were already calibrated, the validation of the reservoir’s inflow was done for the period comprehended between 01/01/2002 and 31/12/2009.

For the validation process, the monthly water volume reaching the reservoir was incorporated into a mass balance where the observed stored volume from the previous month and the water volume that leaves the reservoir in the current month were also considered

where V i sim represents the estimated stored volume in month i , V i-1 obs represents the observed stored volume in the previous month, V I i sim is the volume that enters the reservoir in month i resulting from the simulations, and VO i obs is the observed volume that leaves the reservoir. The stored volume estimated through the water balance was then compared to the observed stored volume of the corresponding month.

Performance assessment was made by a visual comparison, and it was complemented by the estimation of the R 2 , NSE, PBIAS, RMSE, and the RMSE-observation standard deviation ratio (RSR)

where X i obs and X i sim are the stored volume values observed and estimated on month i, respectively, and X mean obs and X mean sim are the average stored volume in the analyzed period. It is important to note that the typical approach for inflow validation, which considers the direct calculation of inflow values from a massa balance performed in the resevoir, was also tested. However, about 30% of the inflow values estimated with that approach resulted in negative inflow. Because of that, the referred approach was not considered in the study.

1D-CNN at Ponte Vila Formosa

Considering the set of 100 runs performed with the 1D-CNN model and the precipitation of Ponte Vila Formosa watershed, the four statistical parameters used to evaluate model’s performance were calculated for each run and considering the test dataset. Four sets of 100 values were obtained. For each of those sets, the minimum, maximum, average, standard deviation, median, and 1st and 3rd quartiles were estimated and are presented in Table 5 .

A spread range of results were obtained for the statistical parameters, with RMSE ranging from 1.44 to 3.13 m 3 s −1 , PBIAS from – 40 to 67%, R 2 from 0.59 to 0.90, and NSE from 0.42 to 0.88. Although some simulations did not reach the minimum requirements to be classified as satisfactory, most of them got acceptable values, with the 1st quartile presenting a NSE of 0.71 and a R 2 of 0.75. This means that 75% of the simulations had higher values for NSE and R 2 . However, considering the PBIAS results, the table shows that the value of the 3rd quartile was 25%, which means that a quarter of the simulations present higher PBIAS. In turn, the 1st quartile of this statistical parameter was – 3.5% and the minimum value was – 40.3%, which indicates that from the 25 simulations that present lower PBIAS values, a significant part of them is still considered as having a satisfactory behavior.

The simulation considered as the best in fitting the observed streamflow in Ponte Vila Formosa station presented an NSE of 0.88, a R 2 of 0.88, a PBIAS of – 7.8%, and a RMSE of 1.44 m 3 s −1 (Table 5 ). Although the R 2 of this model was not the maximum presented in the table, the combined values of the four statistical parameters represented the best solution, since the simulation with the maximum R 2 presented a PBIAS of 25%, which relies in the limit of the range for a satisfactory performance.

For an easier comparison with MOHID-Land, the four statistical parameters were also estimated considering the entire dataset, neglecting the first year (2001). Streamflow results show that the model outputs included negative values for 1.5% of the dataset. Since these negative values occurred in isolated days, they were replaced by simply averaging the estimated streamflow from the previous and the next days. Table 6 presents those statistical parameters, while Fig. 5 allows a visual assessment of model’s performance. Table 6 also presents the goodness-of-fit indicators when the simulated interval was divided into wet and dry periods and considering the average monthly streamflow.

Comparison between observed and estimated streamflow values (using the 1D-CNN model) in Ponte Vila Formosa between 01/01/2002 and 31/12/2009

When considering daily results, the 1D-CNN model demonstrated a very good performance, with the NSE and R 2 reaching values of 0.65, the PBIAS being – 7.21% and the RMSE as 4.75 m 3 s −1 . Results were better when average monthly streamflow were considered, with NSE, R 2 , PBIAS, and RMSE of 0.87, 0.87, 2.23%, and 2.01 m 3 s −1 , respectively. This is justified, because the estimation of the average monthly values smooths out the daily errors. Considering the dry and wet periods, the 1D-CNN model shows a much better performance for the wet period. With the NSE and R 2 having both values of 0.79 and a PBIAS of 8.62% for the wet period, the dry period obtained only an NSE value of 0.26, the R 2 decreased to 0.57, and the PBIAS presents a value of -53%.

MOHID-Land at Ponte Vila Formosa

MOHID-Land’s calibration focused on a large number of different parameters related to the porous media, river network, and plant development processes. Among them, the f h factor and the soil hydraulic parameters were a calibration target. In the river network, the minimum threshold area, the cross-section dimensions, and the Manning coefficient were evaluated, and for the vegetation development, the K c for different stages, and maximum root depth were also subjected to calibration.

The best solution obtained with MOHID-Land comprehended a river Manning coefficient of 0.035 s m −1/3 and a minimum threshold area of 1 km 2 . The calibrated cross-section dimensions are presented in Table 2 , being clearly larger than those of the model set-up. In porous media, the f h adopted the value 500, while the saturated water content of each soil type was increased by 10%. Finally, the maximum root depth was 25% to 60% lower than the default values of MOHID-Land’s growth database.

The comparison between the streamflow values registered in Ponte Vila Formosa station and those estimated by MOHID-Land is presented in Fig. 6 , with the corresponding statistical parameters shown in Table 7 . Table 7 also shows NSE, R 2 , PBIAS, and RMSE for the average monthly streamflow and for the division of the analyzed period into wet and dry seasons.

Comparison between observed and estimated streamflow values (using MOHID-Land model) in Ponte Vila Formosa between 01/01/2002 and 31/12/2009

MOHID-Land’s results show the satisfactory performance obtained with this model. It reached an NSE and an R 2 of 0.65 for the calibration period with a slight decrease in the validation period (0.62 for NSE and 0.63 for R 2 ). PBIAS demonstrated an underestimation of streamflow in calibration and an overestimation during validation, while RMSE values were similar in both periods. When considering the monthly aggregation, the model reached a very good performance, with NSE and R 2 values above 0.85 in calibration and validation periods. The RMSE showed a decrease in both periods when compared with the daily values. Finally, PBIAS did not suffer significant changes. During the wet period, the performance of the model was better than in the dry period. Although R 2 showed a better value for the dry period, NSE and PBIAS demonstrated an accentuated decrease in model’s performance in that period, with the first going from 0.61 to 0.39 and the second indicating an overestimation of about 9% in wet period and an underestimation of about 30% in dry period.

Maranhão reservoir’s inflow

The characterization of Maranhão reservoir’s inflow obtained with MOHID-Land and 1D-CNN models from 01/01/2002 until 31/12/2009 is presented in Table 8 . The respective flow duration curves are presented in Fig. 7 .

Flow duration curve for Maranhão reservoir's inflow estimated with MOHID-Land (blue line) and 1D-CNN (red line)

Results from Table 8 showed a very similar behavior for both models apart from the maximum streamflow value. In that case, the 1D-CNN model presented a maximum streamflow more than twice the maximum streamflow estimated by MOHID-Land. However, MOHID-Land had a slightly higher streamflow average. It indicates that for the middle streamflow values, MOHID-Land tends to overestimate 1D-CNN model. It is also demonstrated in Fig. 7 , where it is possible to confirm that for streamflow values with non-exceedance probability between 0 and 0.3, higher values are observed for MOHID-Land.

Regarding the validation of stored volumes considering the reservoir’s mass balance, NSE, R 2 , PBIAS, RMSE, and RSR were estimated for the entire period, and the results are presented in Table 9 . Figure 7 presents the graph with the comparison between the two models and the observed stored volumes.

Results showed good agreement between both models and observed values. In fact, 1D-CNN and MOHID-Land presented very similar R 2 (1D-CNN: 0.84; MOHID-Land: 0.85) and RMSE (1D-CNN: 18.62 hm 3 ; MOHID-Land: 18.61 hm 3 ) values. NSE and RSR were equal in both cases, while PBIAS was the parameter in which some difference is observed. With a PBIAS of -0.55% for 1D-CNN model and -1.18% for MOHID-Land model, both models were slightly underestimating the reservoir’s inflow. MOHID-Land showed a higher tendency for that underestimation.

1D-CNN model

The 1D-CNN model had already demonstrated its adequacy to predict streamflow in the sub-basin of Ponte Vila Formosa station as demonstrated in Oliveira et al. ( 2023 ). The approach presented here, where 100 simulations were performed with the same 1D-CNN structure, allowed to slightly improve the results obtained in that study. Thus, the best solution had an NSE and an R 2 of 0.88, a PBIAS of – 7.80%, and an RMSE of 1.44 m 3 s −1 , considering the test dataset. Results also show that half of the 100 simulations obtained a NSE higher than 0.74 and/or a R 2 above 0.79. The same number of simulations got a PBIAS lower than 9.52%. It indicates the suitability of the developed structure for streamflow estimation.

The results of the 1D-CNN model are in accordance with the results of several authors. Barino et al. ( 2020 ) used two 1D-CNN models to predict multi-day ahead river flow in Madeira River, a tributary of the Amazon River, Brazil. One of those models considered only the river flow in previous days, while the other considered that same variable combined with the turbidity. Both models obtained NSE and R 2 values higher than 0.92, while mean absolute percentage error (MAPE) and normalized RMSE were lower than 25% and 0.20, respectively. Among the models analyzed by Huang et al. ( 2020 ), two CNN models were studied to forecast a day ahead streamflow. Considering the lagged streamflow values of the past 16 days in the site to be forecasted and in the neighborhood, a generic CNN model and a CNN model trained with a transfer learning procedure were tested. With four different locations in the United Kingdom being the studied, the generic CNN model obtained MAPE values between 14.36% and 41.95%, while the MAPE of the other CNN model laid between 12.29% and 32.17%. Duan et al. ( 2020 ) considered the watersheds within the Catchment Attributes for Large-Sample Studies (CAMELS dataset), in California, USA, to test a temporal CNN model. The model was developed for long-term streamflow projection and consisted of a one-dimensional network that used dilated causal convolutions. As input variables, authors elected precipitation, temperature, and solar radiation and tested different time window sizes to delay the values. After performing 15 runs for each watershed in the CAMELS dataset, the average NSE was 0.55, while the average NSE for the best run over all basins was 0.65. Finally, a CNN model was employed by Song ( 2020 ) to estimate daily streamflow in Heuk River watershed, in South Korea. Using rainfall, runoff, soil map, and land-use data, authors generated a hydrological image based on curve number method to feed the neural network and estimate streamflow in the watershed. Model evaluation resulted on a coefficient of correlation of 0.87 and a NSE of 0.60.

Usually, in machine learning methods, better results are verified when antecedent streamflow is considered as a forcing variable (Barino et al. 2020 ; Khosravi et al. 2022 ). However, when the model is used in the simulation of future scenarios or periods when no observed data are available, the antecedent streamflow values to feed the model are those already calculated by the model in the previous iterations. Consequently, the propagation and exacerbation of errors in the estimates can lead to a degradation of the results in the long-term. There are also other types of machine learning methods for streamflow estimation emerging in the last few years. For instance, Si et al. (2021) considered a graphical convolutional GRU model to predict the streamflow in the next 36 h hours, while Szczepanek ( 2022 ) used three different models, namely, XGBoost, LightGBM, and CatBoost, for daily streamflow forecast. Additionally, hybrid solutions considering different machine learning algorithms, such as Di Nunno et al. ( 2023 ) and Yu et al. ( 2023 ), are becoming widely used and with improved results.

MOHID-Land model

MOHID-Land daily results demonstrated to be satisfactory. With an NSE and an R 2 higher than 0.62 and 0.63, respectively, and a PBIAS between – 7% and 4%, and an average RMSE of 5.6 m 3 s −1 , these results were substantially better than those presented by Almeida et al. ( 2018 ) for the same study area. Using Soil Water Assessment Tool (SWAT), the authors compared the daily streamflow also in Ponte Vila Formosa station. They obtained an NSE, an R 2 , a bias, and an RMSE of – 3.05, 0.31, 2.93, and 12.61 m 3 s −1 , respectively, for the calibration period. For the validation, the NSE was 0.11, the R 2 was 0.24, and the bias and RMSE were – 0.46 and 15.21 m 3 s −1 , respectively. Almeida et al. ( 2018 ) also made a daily comparison in Moinho Novo hydrometric station, which is located in Montargil watershed and is very similar to Maranhão watershed sharing boundaries between them. For Moinho Novo station, the authors obtained for calibration and validation periods, respectively, an NSE of 0.22 and 0.39, an R 2 of 0.41 in both cases, a bias of 0.90 and – 1.07, and an RMSE of 13.1 and 16.6 m 3 s −1 . Bessa Santos et al. ( 2019 ) estimated the daily streamflow in Sabor River watershed, placed in Northeast Portugal and with an area of 3170 km 2 . Using SWAT model, they compared the modeled and observed river flow values and the results reached an NSE of 0.62 and 0.61 for calibration and validation periods, respectively, and a R 2 for those same periods of 0.63 and 0.80. The PBIAS was 2.7% for calibration and -24% for validation, while RSR for calibration and validation was 0.62 and 0.63, respectively. Considering Pracana watershed, located in Central Portugal, Demirel et al. ( 2009 ) also used SWAT model to predict daily streamflow. Authors classified the model as having a poor peak magnitude estimation.

Considering the monthly values, MOHID-Land’s performance increased substantially when compared with the daily values. The results reached an NSE of 0.85 and 0.92 and a R 2 of 0.86 and 0.95 for calibration and validation periods, respectively. PBIAS and RMSE also demonstrated the very good behavior of the model. Those parameters obtained very good results for the calibration and validation periods, with PBIAS indicating a slight underestimation during calibration (-6.59%) and an overestimation (4.15%) during validation, and the RMSE being about 2 m 3 s −1 for both periods. In line with this work, Brito et al. ( 2018 ) used SWAT for long-term forecasts of monthly Enxoé reservoir’s inflow. With that watershed located in South Portugal and draining an area of 60 km 2 , authors reached an NSE of 0.78 and an R 2 of 0.77. Almeida et al. ( 2018 ) also presented a monthly analysis for Ponte Vila Formosa station, with SWAT obtaining an NSE of – 1.26 and 0.40 for calibration and validation periods. For calibration and validation, respectively, R 2 reached values of 0.58 and 0.54, the bias was 2.97 and – 0.42, and the RMSE 6.04 and 5.93 m 3 s −1 . Ponte Vila Formosa streamflow was also modeled by van der Laan et al. ( 2023 ) with SWAT model. They obtained an NSE, an R 2 , and a PBIAS for calibration period of 0.76, 0.77, and – 7.1%, respectively. For the validation period, the NSE was 0.89, the R 2 was 0.9, and PBIAS was 15%.

The comparisons presented above allowed to conclude that MOHID-Land’s performance is in line with the other studies carried out in Portuguese watersheds for daily streamflow estimation. The exception was the study performed by Almeida et al. ( 2018 ) where the simulation of the same sub-basin that was being modeled here obtained a much poorer performance there. When monthly streamflow was considered, MOHID-Land’s performance surpassed the results obtained with SWAT model for the same or identical sub-basins. The difference in the performance of the models is justified by the fact that SWAT is more empirically parametrized than MOHID-Land. For instance, MOHID-Land explicitly estimates the infiltration and porous media fluxes based on Darcy’s law and Richards equation, respectively, with the remaining water transformed into surface runoff where fluxes are estimated based on Saint–Venant equation. On the other hand, in SWAT, a baseflow factor, which is a direct index of groundwater flow response to changes in recharge, or a surface runoff lag coefficient to control the fraction of the total available water that will be allowed to enter the reach on 1 day, needs to be defined. The empirical parametrization of some processes prevents a more accurate representation of reality, leading to more errors in estimates and the degradation of the overall performance, especially beyond the period of calibration.

Nonetheless, MOHID-Land has its own limitations. In one hand, the implementation effort is significatively high, with several parameters needing to be defined, such as the six hydraulic parameters of all the soil types, the crop coefficients for each type of vegetation, the surface and the river Manning coefficients, and others. The high number of input data, parameters, and variables that the user should define conduces to an extremely high number of parameters that can be calibrated, which can be time-consuming. A consequence of this is reflected in the number of simulations performed to reach the best solution. In this study, more than 70 simulations were made to test the sensitivity of the MOHID-Land to other parameters than those studied by Oliveira et al. ( 2020 ), and to obtain the combination that allows a good fit between modeled and observed streamflow. On the other hand, the empirical representation of parts of the hydrological processes or the generalization of some parameters can make the representation of the modeled system difficult, leading to values of the calibrated parameters outside the normal ranges. That condition is here verified with the crop coefficients calibrated for the summer and winter crops, which are considered too low.

Models’ comparison

Overall, the 1D-CNN model demonstrated a better performance than MOHID-Land model for daily streamflow estimation in Ponte Vila Formosa station. However, when the results are aggregated by month, MOHID-Land’s performance surpassed the 1D-CNN results.

Focusing on wet and dry periods, it is interesting to verify that the results of both models complement each other. If on one hand, the 1D-CNN obtained a performance for the wet period better than that obtained by MOHID-Land, on the other hand, during the dry period, MOHID-Land demonstrated a better performance. Thus, in the first case, both models achieved satisfactory performances, but the 1D-CNN, with an NSE and R 2 of 0.79, was better than MOHID-Land, which obtained an NSE of 0.61 and an R 2 of 0.63. In the second case, the dry period, both models experienced a decrease in their performances, but MOHID-Land, with an NSE of 0.39 and an R 2 of 0.69, performed better than the 1D-CNN model, which obtained an NSE of 0.26 and an R 2 of 0.56. These results put in evidence the difficulty of MOHID-Land in estimating the peak flow events, but also a better ability to simulate the transitions between the wet and dry periods when compared to the 1D-CNN. It can also be verified in Figs. 5 and 6 , where the results for MOHID-Land demonstrate a more natural behavior than those obtained for 1D-CNN model.

The more irregular behavior of 1D-CNN model is in part justified by the fact that these types of models have not a physical basis, which means that the streamflow estimation does not consider physical laws or limitations. This characteristic of neural network models also justifies the difficulty in avoiding the existence of negative streamflow values. Although other authors did not refer to this issue, it was verified in this study and should not be ignored, since it can limit the application of the model.

Models’ extension to Maranhão watershed

The streamflow estimated by the extension of 1D-CNN and MOHID-Land models to the entire Maranhão watershed was made by the adaptation of the trained and calibrated models to that watershed. Thus, the 1D-CNN presents a maximum inflow value substantially higher than the maximum predicted by MOHID-Land, which is related to the fact that MOHID-Land demonstrated some difficulty in reproducing peaks flow (Table 8 ). The remaining statistics are similar between both models, with the minimum streamflow near 0 m 3 s −1 , the average is between 3.6 and 3.9 m 3 s −1 , and the median is 1.9 and 1.6 m 3 s −1 for 1D-CNN and MOHID-Land.

The evaluation of the inflow values based on the mass balance at the reservoir scale showed a very good performance when using 1D-CNN and MOHID-Land (Table 9 ). Both models have NSE and RSR of 0.79 and 0.46, respectively. R 2 is 0.84 for 1D-CNN and 0.85 for MOHID-Land and the RMSE is 18.6 m 3 s −1 for both models. The higher difference in the statistical parameters is in the PBIAS with the 1D-CNN underestimating – 0.55% and the MOHID-Land also presenting an underestimation, but a little higher, of about – 1.18%. Visually, it is also possible to verify slight differences between the stored volume estimated with inflow from 1D-CNN model and from MOHID-Land model (Fig. 8 ), with the main differences occurring in the wet season (October–March).

Comparison between observed stored volume (black line) and stored volumes estimated considering the streamflow simulated by MOHID-Land (blue line) and 1D-CNN model (red line)

In a similar approach but considering the continuous simulation of the stored water in two reservoirs included in the same modeled watershed, Rocha et al. ( 2020 ) found identical results. Using SWAT model to Monte Novo and Vigia reservoirs, in South Portugal, the authors validated the stored volume of both reservoirs with a monthly timestep, obtaining an NSE of 0.44 and a PBIAS of 6.3% for Monte Novo reservoir and an NSE of 0.70 and PBIAS of 10.1% for Vigia reservoirs.

In this case, models were extended to an ungauged watershed, which physical characteristics and the rainfall regime are similar to those verified in the sub-basin where the models were trained or calibrated. In that sense, the question that arises from this study is about the behavior of this expanding approach when larger watersheds, marked by diversified characteristics and rainfall regimes, are the target of the study. In those cases, the calibrated parameters cannot be representative or even represented in the expanded area, for the typical hydrological models, or the differences in the rainfall regime when considering the expanded area cannot be correctly related with the runoff values, which was already referred to by Parisouj et al. ( 2020 ).

Finally, it is important to note that several sources of uncertainty are involved in modeling Ponte Vila Formosa watershed, but also in expanding the optimized models to the entire watershed. Besides difficulties in correctly considering the differences between monitored and unmonitored areas, models also have their own uncertainty. On one hand, the limitations of model developers and users in correctly representing real systems through the structure of a hydrologic model and approximations made by numerical methods result in residual model errors and, therefore, in model output uncertainties (Loucks and van Beek 2017 ). However, the attempt of improve the representation of reality through the increase of model complexity results in adding the cost of data collection and may also introduce more parameters needing to be defined, which can then result in more potential sources of error in model output. On the other hand, Gal and Ghahramani ( 2016 ) focused on the high levels of uncertainty when using deep learning tools for regression and classification, even with simple modeling structures. In that sense, further investigation should be carried out concerning the expansion of both models and the involved uncertainty. For a better understanding, for example, several instances of the same model, with slight but coherent differences in the parametrization, can be taken into account, with the calculation of the streamflow resulting from the combination of those instances and considering the estimation of confidence intervals.

Conclusions

The proposed approach showed the adequateness of implementing a 1D-CNN model and a physically based model for estimating daily streamflow generation at the outlet of an ungauged watershed after prior calibration/validation of those models in a sub-basin of the same catchment. Considering the sub-basin modeling, the 1D-CNN model demonstrated a better performance than MOHID-Land when considering the daily values and the wet period. The MOHID-Land model showed a better performance in estimating streamflow values during dry periods and for a monthly analysis. When the validation of the reservoir mass balance was considered, the results showed an identical behavior for both models, with only a slight difference in the PBIAS. That difference indicates a smaller underestimation of inflow by the 1D-CNN than that estimated by MOHID-Land.

Although the results were considered from satisfactory to very good in all the steps taken during the validation process, the generation of negative values by the 1D-CNN is of concern. In that sense, the model presented here should be a target of improvement in future applications. In turn, MOHID-Land model revealed a lower performance for daily streamflow estimation, but its physical basis contributes to avoiding unpredictable and incomprehensible results.

Finally, it is worth noting that neural network models are developed and trained for present and/or past conditions, and their application to future scenarios can be limited. Also, the prediction of events that go beyond the observations can be problematic. This limitation is mainly related to its lack of capacity to absorb information about future conditions in cases where neural networks were not prepared to be forced by variables that include the impact of those future changes. Nonetheless, the changes in future conditions can be easily imposed in physically based models, with the main problems being: (i) the detail of the characterization of future conditions, that most of the time is too coarse for the detail adopted on physical models; and (ii) the high computational time needed to run long-term simulations, usually performed in analysis of future scenarios. Thus, hybrid solutions, combining different types of models or different models, can be used to incorporate the predicted changes in neural network models.

Data availability

Not applicable.

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Open access funding provided by FCT|FCCN (b-on). This research was supported by FCT/MCTES (PIDDAC) through project LARSyS–FCT pluriannual funding 2020–2023 (UIDP/50009/2020). T. B. Ramos was supported by a CEEC-FCT Contract (CEECIND/01152/2017).

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A.R.O. was responsible for the conceptualization, software, formal analysis, and writing of the original draft. The methodology was elaborated by A.R.O., L.S., and T.B.R. T.B.R., L.S., and R.N. revised the manuscript.

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Oliveira, A.R., Ramos, T.B., Simionesei, L. et al. Assessing the reliability of a physical-based model and a convolutional neural network in an ungauged watershed for daily streamflow calculation: a case study in southern Portugal. Environ Earth Sci 83 , 215 (2024). https://doi.org/10.1007/s12665-024-11498-1

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A case study is indeterminate and boundless; a case analysis is predetermined and confined. A case study can be almost anything [see item 9 below] as long as it relates directly to examining the research problem. This relationship is the only limit to what a researcher can choose as the subject of their case study.
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Introduction. The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological ...
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A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...
Assessing the reliability of a physical-based model and a ...
The main goal of this study was to estimate inflows to the Maranhão reservoir, southern Portugal, using two distinct modeling approaches: a one-dimensional convolutional neural network (1D-CNN) model and a physically based model. The 1D-CNN was previously trained, validated, and tested in a sub-basin of the study area where observed streamflow values were available. The trained model was here ...
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Introduction to Case Study
Introduction to Case Study by Winston Tellis + The Qualitative Report, Volume 3, Number 2, July, 1997 . Abstract . This paper is the first of a series of three articles relating to a case study conducted at Fairfield University to assess aspects of the rapid introduction of Information Technology at the

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