Drought Characterization Using Multiple Indices over the Abbay Basin, Ethiopia

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study focusing on the drought characterization using multiple indices. SPI, SPEI, DSI, and VCI were used to assess the drought condition. What are the highlights in this study? What the driving factors of the drought in the Abbay Basin? Lack of innovation.

Line 40-42: “The results of this study will not only support farmers but also assist different sectors in enhancing actual climate conditions on the ground for designing climate change adaptation strategies”. How historical SPI support?

Line 27: Why you used three-month timescales and12-month timescales? What is the significance?

Line 15: “What are human actions?”. Human activities?

In the “Discussion” section, no hierarchy. I suggest that you should divide the discussion into several aspects.

There are a few grammar errors. Please check the entire text.

Please improve the resolution of Figure 2. In the Figure 3, why are there no spatial distribution of drought conditions in 2022?

Author Response

Comment # 1: This study focusing on the drought characterization using multiple indices. SPI, SPEI, DSI, and VCI were used to assess the drought condition. What are the highlights in this study? What the driving factors of the drought in the Abbay Basin? Lack of innovation.

This study aims to provide a comprehensive analysis of drought conditions using multiple indices, including SPI, SPEI, DSI, and VCI, to capture different dimensions of drought (meteorological, hydrological, agricultural).  The use of multiple indices allows for a more nuanced understanding of drought impacts on water availability, agricultural productivity, and overall climatic trends. Also, mapping drought-prone areas using geospatial techniques provides valuable insights into the spatial variability of drought.

Comment # 2: Line 40-42: “The results of this study will not only support farmers but also assist different sectors in enhancing actual climate conditions on the ground for designing climate change adaptation strategies”. How historical SPI support?

The historical Standardized Precipitation Index (SPI) plays a key role in supporting the design of climate change adaptation strategies. By analyzing historical SPI data, we identify drought trends and patterns as SPI helps in assessing long-term precipitation deficits or surpluses, providing valuable insights into historical drought events, their duration, intensity, and frequency. Thus, historical SPI provides a foundation for evidence-based adaptation planning by offering insights into past climate variability and guiding proactive responses to future changes.

Comment # 3: Line 27: Why you used three-month timescales and12-month timescales? What is the significance?

The significance of using both timescales lies in providing a more comprehensive understanding of drought. While the short-term (three-month) index is essential for seasonal planning and immediate response measures, the long-term (12-month) index is critical for strategic planning and assessing the sustainability of water resources under prolonged drought conditions.

Comment # 4: 

Line 15: “What are human actions?” Human activities?

Yes, in this context, "human actions" can be understood as "human activities." Human activities refer to various actions and behaviour’s that people engage in, such as:

• Land use changes (e.g., deforestation, urbanization, agricultural practices)
• Water management (e.g., over-extraction of groundwater, dam construction)
• Irrigation practices (which can influence water availability)

These activities can contribute to or exacerbate environmental issues, especially drought, by affecting natural systems and resources. In the revised manuscript we used human activities instead of human action. Thank you again.

Comment # 5: 

In the “Discussion” section, no hierarchy. I suggest that you should divide the discussion into several aspects. There are a few grammar errors. Please check the entire text. Please improve the resolution of Figure 2. In the Figure 3, why are there no spatial distribution of drought conditions in 2022?

Yes, we included some hierarch in the discussion section. The resolution of Fig. 2 is improved in the revised version of our manuscript. Since very small areas were affected by drought in 2022 we didn’t analyze the spatial distributions of drought for this particular year. We only analyze for the years 1982, 1992, 2009, and 2015 based on severity of droughts.

Reviewer 2 Report

Comments and Suggestions for Authors

The article exhibits a commendable structure and organization. Several inquiries are posed to enhance the work:  
1- What implications might a negative numerical value have for NDVI?  
2- Incorporate the adaptation strategies for the agricultural sector derived from the findings of this research within the introduction and discussion sections.  
3- Regarding the drought stress indicators in the agricultural sector, given that various crops possess differing tolerance levels, on what criteria is this index consolidated? This should be elucidated in a paragraph within the introduction.  
4- The range of precipitation variations in the study area should be adjusted by rainfed or dryland farming according to the FAO's definition.  
5- Provide a more detailed explanation of the relationship between the indicators examined.  

Comments on the Quality of English Language

The article exhibits a commendable structure and organization. I suggested some inquiries as:  
1- What implications might a negative numerical value have for NDVI?  
2- Incorporate the adaptation strategies for the agricultural sector derived from the findings of this research within the introduction and discussion sections.  
3- Regarding the drought stress indicators in the agricultural sector, given that various crops possess differing tolerance levels, on what criteria is this index consolidated? This should be elucidated in a paragraph within the introduction.  
4- The range of precipitation variations in the study area should be adjusted by rainfed or dryland farming according to the FAO's definition.  
5- Provide a more detailed explanation of the relationship between the indicators examined.

Author Response

Reviewer 2# Comments

The article exhibits a commendable structure and organization. Several inquiries are posed to enhance the work:
Comment # 1- What implications might a negative numerical value have for NDVI?  

A negative numerical value for the Normalized Difference Vegetation Index (NDVI) typically implies the presence of non-vegetated surfaces or poor vegetation health. It generally indicates: Water bodies, bare soil or built-up areas, stressed vegetation.

Comment # 2: Incorporate the adaptation strategies for the agricultural sector derived from the findings of this research within the introduction and discussion sections.  

The adaptation strategies for the agricultural sector derived from the findings of this research was included in the introduction and discussion sections. In the introduction, we briefly present the need for adaptation strategies in agriculture, particularly in the context of drought and climate variability. We also discussed in the discussion section (see the highlight in the revised manuscript).

Comment # 3: Regarding the drought stress indicators in the agricultural sector, given that various crops possess differing tolerance levels, on what criteria is this index consolidated? This should be elucidated in a paragraph within the introduction.

Thank you for your valuable comment on the drought stress indicator, regarding the consolidation of different tolerance levels of crops for drought stress indicators, we have now included a paragraph in the introduction elucidating the criteria for this index. The consolidation is based on several factors, including key physiological traits such as root depth, stomatal regulation, and water use efficiency, which vary across crops. Additionally, genetic variation plays a role, with drought-tolerant crops like sorghum and millet demonstrating greater resilience compared to more sensitive species like maize. These traits, along with mechanisms such as osmotic adjustment and early maturation, form the foundation of the index. We have also referenced the FAO's Crop Water Requirement Index, which provides a standardized measure of water-use efficiency across different crops, further supporting the classification of drought tolerance levels (See the 2^nd paragraph in the introduction section on page 4 with highlight).

Comment # 4: The range of precipitation variations in the study area should be adjusted by rainfed or dryland farming according to the FAO's definition.

Thank you for this insightful suggestion, which allows us to refine our discussion on precipitation variability and its implications for agricultural practices. We acknowledge that the classification of precipitation into rainfed or dry land farming systems as defined by the FAO typically considers average annual rainfall levels. According to the FAO, areas receiving less than 500 mm of annual precipitation are generally classified as dry land, whereas regions with more than 500 mm are often considered suitable for rainfed agriculture. The most part of our study area receives high precipitation during the main crop growing season, contributes to diverse agricultural practices that include both rainfed and supplementary irrigation methods. We clarify this point in our manuscript, emphasizing that while the area exceeds the FAO's rainfed classification threshold; the agricultural practices employed are influenced by local conditions and may not strictly align with standard classifications. This distinction is crucial for understanding the adaptive strategies used by farmers in the region (See the highlight text under study area descriptions).

 Comment #5: Provide a more detailed explanation of the relationship between the indicators examined.  

Thank you for your insightful observation. The SPI and SPEI indices are used to capture climate extremes, as they are based on climate variables. In contrast, the VCI and DSI indices are derived from NDVI data, which primarily reflects environmental conditions, particularly vegetation health. Together, these indices offer a comprehensive view of drought, with SPI and SPEI focusing on meteorological conditions, while VCI and DSI emphasize agricultural and hydrological drought impacts.

Reviewer 3 Report

Comments and Suggestions for Authors

Drought Characterization Using Multiple Indices over the Abbay Basin, Ethiopia.

 

The manuscript used a number of indices, including the normalized difference vegetation index, vegetation condition index, drought severity index, standardized precipitation index, and standardized precipitation evapotranspiration index, to evaluate agricultural and hydrological drought in Ethiopia's Abbay Basin. These are typical indexes in these kinds of evaluations.

The article is engaging and shows strong potential for publication in the Water journal. Overall, the manuscript is well-written, effectively outlining both the motivations behind the research and its key findings.

However, I have the following minor observations:

1) The abstract should include more quantitative results.

2) Highlight the original aspects of the manuscript;

3) Why wasn't McKee et al.'s recommended strategy used in the SPI calculation methodology? The SPI is stated in standard deviations, indicating how much the observed precipitation deviates from the long-term average under a normal distribution, and includes a probability distribution fitted to the actual precipitation data. Because precipitation does not typically follow a normal distribution, a transformation is used first, followed by fitting the data to a normal distribution. The computation approach entails converting one frequency distribution (e.g., Gamma distribution) into another, typically a normal distribution. The percentile of the original probability distribution is then transformed to the corresponding value in the new distribution. The parameters of the chosen distribution should be realized using the approach of linear moments (L-moments), especially if two-parameter distributions are utilized (Ilinca et al. 2024).

4) The discussion section could be enhanced by including additional references to relevant studies from the existing literature;

5) A special importance in such analyzes is the verification of the homogeneity, consistency and stationarity of the data. Have you checked the consistency and homogeneity of the observed data?

Author Response

Reviewer #3

The manuscript used a number of indices, including the normalized difference vegetation index, vegetation condition index, drought severity index, standardized precipitation index, and standardized precipitation evapotranspiration index, to evaluate agricultural and hydrological drought in Ethiopia's Abbay Basin. These are typical indexes in these kinds of evaluations.

The article is engaging and shows strong potential for publication in the Water journal. Overall, the manuscript is well-written, effectively outlining both the motivations behind the research and its key findings. However, I have the following minor observations:

Comment 1) The abstract should include more quantitative results.

Thank you. Some quantitative results are included in the abstract.

 

Comment 2) highlight the original aspects of the manuscript;

The original aspects of the manuscript are:

1. Multidimensional drought analysis: By incorporating a combination of drought indices (SPI, SPEI, DSI, and VCI), this study provides a comprehensive analysis that covers multiple dimensions of drought—meteorological, agricultural, and hydrological.

 

2. Geospatial mapping of drought stress: The use of geospatial techniques to map drought-prone areas introduces a good approach in visualizing spatial variability of drought impacts across the study region. This is particularly relevant for policymakers and farmers in identifying high-risk zones.

These original elements demonstrate the manuscript’s contribution to advancing drought assessment methodologies and offering practical solutions for the agricultural sector under climate variability.

Comment 3) Why wasn't McKee et al.'s recommended strategy used in the SPI calculation methodology? The SPI is stated in standard deviations, indicating how much the observed precipitation deviates from the long-term average under a normal distribution, and includes a probability distribution fitted to the actual precipitation data. Because precipitation does not typically follow a normal distribution, a transformation is used first, followed by fitting the data to a normal distribution. The computation approach entails converting one frequency distribution (e.g., Gamma distribution) into another, typically a normal distribution. The percentile of the original probability distribution is then transformed to the corresponding value in the new distribution. The parameters of the chosen distribution should be realized using the approach of linear moments (L-moments), especially if two-parameter distributions are utilized (Ilinca et al. 2024).

While McKee et al.'s approach is a widely accepted method for SPI calculation, we chose an alternative approach to account for the specific characteristics of the study area's precipitation data. The reasoning behind this decision includes the following considerations:

1. Non-normal precipitation distribution: As noted, precipitation data often do not follow a normal distribution. Instead of directly applying McKee et al.'s methodology, which involves fitting the data to a Gamma distribution before transforming it to a normal distribution, we opted to use a more flexible method to better capture the skewness and variability in our data.
2. L-moments for distribution fitting: We employed the L-moments technique (as suggested by Ilinca et al., 2024) to estimate the parameters of the chosen distribution. L-moments are more robust for describing skewed data and outliers compared to traditional moments. This method ensures a better fit for non-normal precipitation distributions, which was a critical factor given the highly variable climate conditions in the study region.

Comment 4) The discussion section could be enhanced by including additional references to relevant studies from the existing literature;

We take this comment in consideration. We critically analyze the works of previous studies. We included some key literatures to enhance the quality of our discussions.

Comment 5) A special importance in such analyzes is the verification of the homogeneity, consistency and stationarity of the data. Have you checked the consistency and homogeneity of the observed data?

We appreciate your insightful comments regarding the verification of data homogeneity, consistency, and stationarity. Addressing these aspects is indeed crucial for ensuring the robustness of the analysis. In response to your query, we have conducted thorough checks for the consistency and homogeneity of the observed data. Specifically, we employed statistical tests such as the Mann-Kendall test to assess the trend consistency over time and the Variance Ratio Test to evaluate homogeneity. The results indicated that the data are consistent and homogeneous, as there were no significant variations detected across the different periods analyzed. Additionally, we assessed stationarity using the Augmented Dickey-Fuller (ADF) test, which confirmed that the data series is stationary. This verification process has strengthened our analysis and underlines the reliability of the findings presented in the study. Thank you once again for your valuable feedback.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The author has made the necessary modifications as requested and agrees to publish.

Author Response

Response to Reviewer 1
1. Summary
Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.
2. Questions for General Evaluation	Reviewer’s Evaluation	Response and Revisions
Does the introduction provide sufficient background and include all relevant references?	Can be improved	Thank you. We revised some section of the introduction
Are all the cited references relevant to the research?	Can be improved	Thank you all cited references are relevant.
Is the research design appropriate?	Yes	Thank you for your recognition
Are the methods adequately described?	Can be improved	Thank you. We perform minor revisions.
Are the results clearly presented?	Yes	Thank you
Are the conclusions supported by the results?   Comments and Suggestions for Authors: The author has made the necessary modifications as requested and agrees to publish.      Thank you	Yes	Thank you

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors addressed my observations appropriately. The manuscript has been enhanced, meeting the criteria and possessing the quality required for publication.