1. Summary

This research article analyzes over 130,000 peer-reviewed articles on drought research from 1901 to 2022. It highlights a shift in research priorities towards plant genetic research for drought-tolerant genotypes and methods in drought forecasting, with decreasing focus on ecology, groundwater, and forest research.The study underscores the importance of interdisciplinary research and recommends enhanced interdisciplinary and systemic approaches to address drought as a multi-sectoral risk.

2. General comment

This work undertakes an impressive effort by conducting a review of drought-related literature spanning over a century. The emphasis on interdisciplinary approaches to address multisectoral drought risk deserves particular attention. I found the section discussing the geographical distributions of the topics extremely interesting. While the article is well-written, improvements could be made by addressing certain aspects outlined below, such as, but not limited to, providing more clarifications and references throughout the manuscript, improving explanations in the figure captions, adding additional references to support statements, and ensuring consistency in numerical representation.

3. Specific comment

1 Introduction

Lines 36-37: Might be relevant to additionally reference here the recent preprint looking at drought as a continuum process: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-421/

Lines 40-50: the line 38 provides examples of drought-sensitive sectors, followed by a detailed discussion of impacts on ecosystems and agriculture in the next paragraph (lines 40-50). However, it does not delve into the impacts on health, energy, and socio-political stability mentioned earlier as well.

Lines 51-57: this paragraph concludes the introduction by emphasizing the importance of adaptation strategies and the value of long-term drought research. I think it could benefit from better highlighting this paper's contribution. I think it could benefit from better highlighting this paper's contribution. For example: "The long-term research undertaken by this work helps reveal patterns and gaps in our understanding of drought, enabling the development of more effective adaptation strategies." This would underscore the unique insights and contributions of the paper to the field.

2 Methods

Line 60: are they all scientific publications (the 131,748 abstracts)?

Lines 73-74: while describing the “three Tiers” here for the first time, it would be helpful to refer to Fig. 2 already for a clearer schematic representation. This visual aid will enhance understanding and provide an easier reference for readers.

Line 77: I would emphasize already here in the beginning that the similarity between 2 topics is within a document otherwise its not clear until the reader reads about it on Line 79.

3 Results

3.1 Major and specific topics in drought research

Figure 1: I think this Figure needs a clearer explanation in the caption, stating what exactly is shown on the right x axis and the left x axis (especially on the right – the similarity index corresponds to the degree of intedisciplinarity).

Figure 2: the figure would benefit from adding labels such as "major topics" next to Tier 1 with an indication of "5 topics," "intermediate topics" next to Tier 2 with "12 topics," and "highly specialized topics" next to Tier 3 with "50 topics." This would help readers better orient themselves within the manuscript.

Figure 2: the categorization of topics (M,M,I,M,E) lacks clarity, particularly the selection of "E" (events and historical analysis) for the topic "Precipitation and Drought types." Why wouldn't "Methods and processes" be a fitting category for this topic?

Lines 117 and 119: require consistency in numerical representation, whether as spelled-out words ("twelve topic") or numerals ("12-topic").

Figure 3: a question regarding the sequence of the 12 topics displayed in the box: should they align with the sequence seen in Tier 2 of Figure 2? Additionally, it would enhance clarity to label the box containing the 12 topics as "Intermediate Topics Tier 2" at the top, facilitating a quicker understanding of its connection to the preceding Figure 2.

Lines 144-146: quite hard to read this sentence, I would recommend rephrasing it.

3.2 General and emerging trends

Line 168: would recommend to add ref to Figure 4 here already? And potentially to explain why to focus only on last 4 decades?

Line 178-179: the authors should provide references to support this statement. Additionally, it's crucial to note that while increased drought resilience of crops through genetics is valuable, relying solely on this aspect may not suffice, and other mitigation strategies are equally important.

Figure 4: The color choice for “Plant genetics” seems to have changed and become more orange as compared to more yellow assigned to it in Figure 2.

Lines 191-194: one of the contributing factors is also the technological advancements that have strengthened forecasting methods.

3.3 Interdisciplinarity of drought research

Lines 208-209: “manifested in sedimentary records and tree ring records” is it referring to “Forest and Fire topic? Would recommend to mention it in the text.

Line 236: what exactly does "regional studies" refer to? Isn't it more about spatial characteristics rather than a specific topic?

Figure 6: I'm surprised to find "Drought Palmer Index" listed as a distinct topic rather than under a broader category like "Drought Index." Additionally, I couldn't find anything related to Forecasting among these 50 topics. Could it be that certain topics, such as Forecasting, have been split into smaller segments (e.g. modelling)?

3.4 Geographic patterns and priorities

Figure 7: Is it built on 40 or 100 years review, need to mention this. Additionally, wasn't "forecasting" previously indicated in blue but now appears in yellow? Consistency in color usage throughout the manuscript is recommended. Regarding the figure caption, isn’t  “forecasting”  positioned at the top everywhere, not only in Europe and Asia (same as mentioned in the abstract).

4. Discussion and Future Directions

4.1 Implications for research, policy and institutions

Line 288: its not clear which indicators are meant here? Drought indicators or agricultural impact indicators?

Lines 288-290: what about the priorities of research community as well and their influence on the trend?

Line 291: to advance drought impact forecasting, it's crucial to consider several related topics besides genetics.

Line 298: “knowledge reviews as are required …” spelling

Line 303: here written as “drought indices” but its only “Palmer Drought Index?” within the 50 topics?

Supplementary

Couldn’t find Figure A and and Figure B (Lines 187 and 190) in the Supplementary, I only see Figures S1, S2, S3, S4

The article describes an analysis of bibliographic information (abstracts, keywords, title, publication year, language) performed for the period 1901-2022 to identify trends and focus areas in drought research. In general, the article is well written, contains high quality figures for illustration and addresses an interesting topic. I find in particular the consideration of trends and regional priorities in drought research very interesting. However, I have a number of concerns and suggestions that may be considered to improve the manuscript:

General comments:

• The methods applied by the authors are based on a number of important assumptions that should be made transparent to the readers and also being discussed. First of all, the authors limit their analysis to abstract and keywords. This has the advantage that a large number of articles can be considered but the disadvantage, that it is not clear at all how well the specific abstracts and keywords really reflect the content of the articles and the research results. Second, it assumes, that terms and definitions used in drought research have been similar across time, regions, disciplines and scales.  Certainly, these are strong assumptions. To my experience it is frequently not clear whether statements in the abstract section represent the present understanding in the research community, opinions of the authors, or really conclusions drawn from the research results that are justified by real data. One example is the abstract of the present manuscript. In the last sentence the authors state: “In future, we recommend research and funding agencies to strengthen the track of more interdisciplinary and systemic cross-topic drought research in order to cope with drought as a multi-sectoral risk requiring multi-sectoral response frameworks.” Is this recommendation justified by the results of the present analysis? Certainly not. Instead it is the opinion of the authors and reflects well a popular believing of a large part of the drought research community. Nevertheless, this statement can also be challenged. Interdisciplinary, systemic, cross-topic and multi-sectoral research is more expensive and requires more effort than targeted disciplinary research. Funding agencies may have to decide therefore in practice whether they fund 5 small disciplinary projects or one big interdisciplinary project. It seems therefore, that such a general statement is not appropriate. Certainly, to provide solutions for very specific problems (that nevertheless can have a big impact) such as to improve drought tolerance of crops, to develop more efficient water use technologies or to develop new approaches to improve groundwater recharge, disciplinary research will likely be sufficient. In contrast, to improve drought management in large basins, a multidisciplinary approach may be appropriate. This example shows that the approach to simply extract words and terms from the abstract without considering the other sections and the context of the article may result in misleading conclusions.
• One interesting result of the present study is that the majority of drought related articles address either plant genetics and physiology or drought forecasting. These domains address completely different scales and, even more relevant, may use different definitions what a drought is. At large spatial scales, the terminology is distinguishing drought as an extreme event from aridity as a climate indicator. At plant level drought stress is usually when the water supply is lower than needed for optimal growth. Here, no difference is made between water deficits caused by the fact that crops grow in arid regions and water deficits caused by droughts. Consequently, drought has a different meaning and drought research has another context at these two scales. 3 out of the 12 topics presented in figure 3 (plant stress response, crop breeding, plant genetics) are in a context where drought is understood as a water deficit in general, 7 topics are in contexts that consider drought to be an extreme event and 2 topics (farming, water use efficiency) may use one or the other understanding, depending on the context. While it is as it is, this example shows that the use and meaning of terms may be context specific, a difference that likely cannot be detected by a simple analysis of article abstracts. I also think that the use of terms in the literature has changed over time. For example, most of the large body of historical articles related to dryland research will have drought in the list of keywords although, according to the present understanding, this research is more linked to aridity and therefore not to drought as an extreme event. Consequently, the results of the trend analysis performed by the authors also have to be taken with care.

Specific comments:

Abstract: see general comment 1

Introduction: is very general and mainly describes why drought research itself is relevant. Research questions are not mentioned and the reader will not be prepared for the analysis described later. There is hardly any link between the introduction and the methods section. Consequently, the reader does not know what the authors what to find out and why they use the specific methods described in the Methods-section. The specific gap of knowledge is not described so that it is difficult for the readers to see the novelty. There are so many review papers in the literature about drought research, please make more clear what the innovation of the present article is and what you make differently compared to the review papers that have been published before.

Methods: It is well described which methods have been used but not why. What is the advantage of using LDA in that specific case, compared to other alternatives?

Results: The first four lines are a summary of the methods but not results.

Figure 1: Many of the readers will not know what cosine similarity means. Please explain that in the figure caption. That the number of drought related articles has increased over time is not surprising since there are more researchers who write more articles per year, compared to former times. I would find it more interesting to see the change in the relative share in drought related articles in the whole scientific literature.

Discussion: Please add one section describing the limitations of data and methods used in the present research.

The authors use a well-known method to give an overview of drought research topics and their development over time. While the method is not new, I find the results and the added thoughts by the authors to be of interest to the research community.

In order to make a topic model research overview interesting and relevant the analysis needs to go beyond reporting and interpret the conclusions for the research community. The authors do this very well. For example, I really like the discussion on including plant genetics into future yield prediction in Section 3.2.  My only criticism would be where these interesting discussions currently happen. At the moment these very relevant findings and interpretations are hiding at the end of the individual results sections and are only briefly picked up in the discussion section. I would recommend a clearer split between results and discussion, meaning that e.g. Lines 191 to 196 should be part of the discussion, not the results. Same with other paragraphs. E.g. the discussion around missing topics in L156 to 164 then repeats in L301 to 306.

The discussion section on drought resilience frameworks makes an important point (L308). But at the moment it feels more like an afterthought. It could, for example, already be introduced in the introduction as a motivation for a drought research overview and then elaborated more in the discussion.

Minor points:

L18: Please already mention that the generative model you are using is LDA, e.g. “using a generative model (topic model)”, as for some people that term will be more familiar.

Introduction: Please expand on the motivation for this study. The first three paragraphs repeat well-known information that summarises why drought is a relevant topic. This could be shortened into one paragraph. And then the introduction should introduce the motivation for this specific analysis. Why do we need an analysis of drought research topics? (relevant for drought resilience frameworks?). What is the problem with past drought reviews? (Too many publications to humanly read? (Stein et al, 2022)). There are a lot of bad scientometric reviews out there. What makes this one different?

L64: Scopus is not the largest database (see https://help.openalex.org/coverage for a comparison).

L70: “LDA did cluster” is a strange grammar. Consider rephrasing.

L96: The description of the methods repeats here. Consider shortening.

L129: Can you add a range? How many papers did the smallest/largest topic include?

L133/140: This might be an editing problem, but there should not be a paragraph break between these two, as the thought continues. In the next line.

L152: It would be good to see which topics the author classifies as impact, event and methods related. I would this categorisation also helpful in structuring Figure 6. However, I would understand if a clear categorisation for some topics is difficult.

L161: A keyword search across the articles might give an indication which of the two explanations are true.

Section 3.2. I think the labels for Figures A and B have been switched for the entire section.

Figure 5/6. The upper triangle of the plot only mirrors the lower triangle. Consider removing.

L213: Can you elaborate on the surprising geomorphology and water use efficiency connection? In what kind of research do they overlap?

L235: This is the only discussion I did not really like. It sounds a little bit like you are advocating for interdisciplinarity for interdisciplinarity’ sake, which I do not agree with. Plus you are only looking at abstracts. A full-text analysis will likely reveal the specialised research to be more interdisciplinary as well.

Section 3.4. The low numbers of drought research in North America are surprising and need to be checked. The US is always a major contributor in previous research distribution analyses  (e.g. Emmer (2018) and Callaghan et al, 2021). Particularly for drought research, I would expect a lot of research with the megadrought in California in recent years.

L306: Is it possible that the diversity of terms in use for these topics might prevent a clear topic (e.g. compound vs multi-hazard vs hazard cascade…)?

Callaghan, M., Schleussner, C. F., Nath, S., Lejeune, Q., Knutson, T. R., Reichstein, M., ... & Minx, J. C. (2021). Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies. Nature climate change, 11(11), 966-972.

Emmer, A. (2018). Geographies and scientometrics of research on natural hazards. Geosciences, 8(10), 382.

Stein, L., Mukkavilli, S. K., & Wagener, T. (2022). Lifelines for a drowning science‐improving findability and synthesis of hydrologic publications. Hydrological Processes, 36(11), e14742.