Long-Term Innovative Trend Analysis of Hydro-Climatic Data of the Sudd Region of South Sudan

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

• In the discussion section, the originality of the study (e.g. ITA is rarely used in this geography) should be emphasized more. It may also mention socioeconomic impacts or recommendations for policy makers.
• It would be useful to mention data gaps and methodological limitations in the conclusion.
• Considering the findings, recommendations should be made for downstream watershed management, early warning systems and flood prevention policies.
• The references should be reviewed again.

Comments for author File: Comments.pdf

Author Response

Comments 1: In the discussion section, the originality of the study (e.g. ITA is rarely used in this geography) should be emphasized more. It may also mention socioeconomic impacts or recommendations for policy makers.

Response 1: We thank the Reviewer for this important comment. We have added following to the main text.

[line 393-401, page 14]

This finding highlights the significant socioeconomic implications of flooding in South Sudan and informs flood prevention policies. It underscores the need to redirect policy efforts towards regional cooperation, improve forecasting capabilities, and develop infrastructure that addresses external drivers of flooding. Furthermore, it emphasizes the importance of providing sustained support to communities adversely affected by such events.

Comments 2: It would be useful to mention data gaps and methodological limitations in the conclusion.

Response 2: We thank the Reviewer for this comment. We have added following to conclusion part.

[line 418-425, page 15]

This study is subject to data gaps and methodological limitations. The Sudd wetland experiences substantial data gaps due to disruptions in the gauge network for measuring rainfall, river stage, and evaporation caused by civil war. Many monitoring stations ceased operations following the civil wars from 1983 to 2005 and again after 2013, resulting in discontinuous discharge series along the River Nile. Furthermore, the absence of an internally derived significance test in the original ITA, which is primarily descriptive, means that analysts may misinterpret any deviation from the 1:1 line as “significant.” This can inflate false positives in data-sparse contexts.

Comments 3: Considering the findings, recommendations should be made for downstream watershed management, early warning systems and flood prevention policies.

Response 3: We thank the Reviewer for this comment. We have added following to main text.

[line 398-401, page 14]

By integrating real-time data with predictive modeling, decision-makers can establish effective early warning systems, enhance flood forecasting, and implement targeted mitigation strategies such as floodplain zoning and infrastructure planning to strengthen resilience and minimize the impacts of recurrent flooding.

Comments 4: The references should be reviewed again.

Response 4: We thank the reviewer for this comment. We corrected the format of the reference list and checked the contents of the list.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In the manuscript entitled “Long-term Innovative Trend Analysis of Hydro-Climatic Data of the Sudd Region of South Sudan”, authors tried to addresses an important hydrological concern, the recurring floods in the Sudd region of South Sudan, by analyzing hydro-climatic trends using Innovative Trend Analysis (ITA). I appreciate the authors for focusing on South Sudan, a data-scarce and flood-prone region, which is least explored hydro climatic region of importance. The integration of CHIRPS rainfall data, river discharge, and lake water levels adds value to the present study. The contradiction between local rainfall trends (decreasing) and flooding (increasing) is well established and strongly suggests upstream hydrology is the key driver that provides a major policy implication. However, the manuscript requires significant improvements in methodology, statistical rigor, and clarity of presentation before it can be considered for publication. Specific Areas for Improvement are given here,

1. In Methodology, the ITA approach needs more detailed explanation. Further, mathematical justification and assumptions (e.g., data independence, sensitivity to outliers) need more depth description.
2. Though the trends are visually interpreted, statistical testing (confidence intervals or p-values) is required to confirm significance across all spatial grids and parameters.
3. In data, the period of data over Mangala station span 2008–2024, while CHIRPS rainfall data cover 1981–2023. Authors need to clarify whether common period data has been considered while attributing long-term changes in discharge to rainfall or Lake Victoria water level trends. Moreover, authors need to mention how the missing data at Mangala station was filled, which may affect the trend.
4. Most of the figures (e.g., 8–12) are with low in resolution. Authors may consider to improve the better resolution illustrations with more informative spatial maps (with legends, color bars, and statistical annotations) for better understanding.
5. In Figure 13, was there any seasonality decomposition or trend decomposition (e.g., STL) performed on river discharge? This may provide better understanding.
6. In this study, rising river flow entirely is mainly attributed to Lake Victoria water levels. Authors may also consider intermediate catchment contributions, changes in vegetation, or human activities (e.g., dam operations, land use).
7. There are several grammatical and typographical errors found throughout the manuscript, e.g., “PRCTOT” instead of “PRCPTOT”, “Bentui” vs. “Bentiu”.
8. Reference [3] and [2] appear to be duplicated.
9. Authors are advised to thoroughly go through the manuscript for any grammatical and typographical errors while submitting the revised version.

Comments on the Quality of English Language

Quality of the English is fine, but there are typographical and grammatical errors in the manuscript. Authors are advised to thoroughly go through the manuscript for any grammatical and typographical errors while submitting the revised version.

Author Response

Comments 1: In Methodology, the ITA approach needs more detailed explanation. Further, mathematical justification and assumptions (e.g., data independence, sensitivity to outliers) need more depth description.

Response 1: We thank the Reviewer for this important comment. We have added following to the main text.

[line 196-199, page 6]

Unlike the most commonly used classical methods of trend analysis, the ITA is free from assumptions such as serial correlation, non-normality, and length of the record [34][35]. Moreover, by using ITA method significant subseries trends (sub-trends) can be observed from the graphical representations [36].

Comments 2: Though the trends are visually interpreted, statistical testing (confidence intervals or p-values) is required to confirm significance across all spatial grids and parameters.

Response 2: We thank the Reviewer for this important comment. In this analysis, the significance of trends was graphically checked by comparing the distribution of the plot with the 95% CL/DCL, and the significance of trends in spatially average precipitation in Jonglei & Unity can be confirmed in Figures 8 and 9. Although not all grid points were checked, significance checks were performed at representative points within each area (grid points with the maximum & median value of ITA slope), and we confirmed a significant trend for some elements (PRCTOT, R20mm, SDII) and points. Based on these results, the following has been added to the main text. We would like to examine the significance of ITA trends at all grid points and its spatial distribution in the future study.

[line 318-323, page 11]

As shown in Figure 8 and 9, ITA trends for areal averaged precipitation in Jonglei and Unity were mostly not statistically significant, except R20mm in Unity. However, we could observe a significant trend at certain grid points within each region (e.g., significant decreasing trend in the first half at the grid point with regional maximum ITA slope for R20mm and SDII in Jonglei, for PRCTOT in Unity).

Comments 3: In data, the period of data over Mangala station span 2008–2024, while CHIRPS rainfall data cover 1981–2023. Authors need to clarify whether common period data has been considered while attributing long-term changes in discharge to rainfall or Lake Victoria water level trends. Moreover, authors need to mention how the missing data at Mangala station was filled, which may affect the trend.

Response 3: We thank the Reviewer for this very important comment. As you pointed out, the data periods for CHIRPS precipitation, Mangala site river flow, and Lake Victoria water level are different, so we are looking at trends over different time periods. In this study, we focus on long-term precipitation data as the primary analysis target. However, despite the limited data period, we also examined the inflow to the Sudd region and the trends in Lake Victoria water levels as a proxy of river flow, in order to not only investigate the relationship between flood conditions in the Sudd region and local precipitation trends but also consider the influence of upstream areas (while taking into account changes in upstream precipitation).

In addition, missing data of flow measurements at the Mangala were estimated using water level-flow relationship (H-Q curve) based on water level data at the same location.

Based on the above, the following has been added to the main text.

[lines 209-220, page 6, section 2.2]

It is noted that the data periods for CHIRPS precipitation, Mangala river flow, and Lake Victoria water levels used in the above ITA analysis differ. CHIRPS precipitation data spans from 1981 to 2023, whereas the other three datasets cover 2008 to 2024. Overlap between CHIRPS precipitation and Lake Victoria water level data exists from 1994 to 2023. The analysis results for Mangala river flow reflect recent trends only. By using Lake Victoria water level as a proxy, we aimed to capture longer-term trends in river flow from the upstream area. Further, by analyzing long-term precipitation trends in the upper catchment (Victoria Lake basin and Mangala’s upper catchment), we examine the relationship between flood conditions in the target region (Sudd region: Jonglei and Unity States) and both local precipitation and upstream influences.

Additionally, missing flow data at Mangala were estimated using water level–flow rate (H-Q) curves derived from observed river water levels

Comments 4: Most of the figures (e.g., 8–12) are with low in resolution. Authors may consider to improve the better resolution illustrations with more informative spatial maps (with legends, color bars, and statistical annotations) for better understanding.

Response 4: We thank the reviewer for this suggestion. In accordance with this comment, we have improved the resolution (DPI) of the figures, revised the legends, and changed the font size and color to improve the visibility and readability of the figures.

Comments 5: In Figure 13, was there any seasonality decomposition or trend decomposition (e.g., STL) performed on river discharge? This may provide better understanding.

Response 5: Thank you very much for the valuable comment. As you pointed out, using methods such as STL to perform seasonality decomposition or trend decomposition on flow data is expected to provide deeper insights. However, considering that including this analysis would make the manuscript too long and that the time available for revision is limited, we would like to leave this point as a topic for future research. We will continue to examine the points you raised, taking into account the seasonality of precipitation, in our future research.

Comments 6: In this study, rising river flow entirely is mainly attributed to Lake Victoria water levels. Authors may also consider intermediate catchment contributions, changes in vegetation, or human activities (e.g., dam operations, land use).

Response 6: Thank you very much for your important comments. Various factors influence changes in inflow from the upper reaches, and research examples on the impact of land use changes in the Victoria Lake catchment area (Ali et al., 2024) have also been reported. We plan to investigate the potential impact of land use changes and human activities in the upper watershed of the Victoria Lake catchment area and the intermediate watershed from Victoria Lake to Mangala, as well as changes in inflow to the Sudd wetlands, using a hydrological model in the future.

Ali et al. (2024): The Analysis of Land Use and Climate Change Impacts on Lake Victoria Basin Using Multi-Source Remote Sensing Data and Google Earth Engine (GEE), Remote Sens. 2024, 16, 4810. https://doi.org/10.3390/rs16244810

We will briefly describe this as a future challenge in the Conclusion section.

[line 427-429, page 15]

In addition, we plan to use a hydrological model to examine not only long-term changes in precipitation in the upper reaches, but also the effects of land use changes and human impacts in the region on the inflow to the Sudd region.

Comments 7: There are several grammatical and typographical errors found throughout the manuscript, e.g., “PRCTOT” instead of “PRCPTOT”, “Bentui” vs. “Bentiu”.

Response 7: We thank the Reviewer for this comment. We have revised in accordance with your comments.”

Comments 8: Reference [3] and [2] appear to be duplicated.

Response 8: We thank the Reviewer for this comment. We have revised in accordance with your comments.”

Comments 9: Authors are advised to thoroughly go through the manuscript for any grammatical and typographical errors while submitting the revised version.

Response 9: We thank the Reviewer for this comment. We have revised in accordance with your comments.”

 

Comments on the Quality of English Language:

Quality of the English is fine, but there are typographical and grammatical errors in the manuscript. Authors are advised to thoroughly go through the manuscript for any grammatical and typographical errors while submitting the revised version.

Response:

Thank you for pointing this out. The manuscript has been checked by the following English proofreading service prior to submission.

https://www.textcheck.com/login

However, we are very sorry that the manuscript contained several typos and other errors. We will check more carefully the revised manuscript to avoid these errors.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Comments:

This study documented the long-term trend of Hydroclimate at the Sudd Region of South Sudan, including annual total precipitation, days with precipitation greater than 20mm/day, and simple precipitation intensity during the past four decades, by utilization of the innovative trends analysis approach. The results are interesting and of importance for deepen the scientific knowledge of flood causes and features. I recommend it minor revision before acceptance.

1. Lines 34-38: Previous studies have shown that the flood risk are projected to exacerbated under a future warmer world (e.g.,  https://doi.org/10.1002/joc.5553), which could be added to suggest the importance of this study.
2. Section 2, Materials and Methods, the common time periods should be added.
3. Figure 3. Was Figure 3 cited from Tiitmamer (2019)? If so, I strongly suggested to delete it of remove to the supplementary
4. Lines 215-217: “the PRCPTOT varied over the years but declined in recent years (Fig. 4a)”: 4a should be Fig 4b. “The R20 mm also decreased in recent years (Fig. 4b) ” Fig. 4b should be Fig 4a.
5. What did the authors mean by “varied over the years” or “varies over time”?
6. Figures 4 and 5: Please add long-term trend lines.
7. What did the authors mean by “the precipitation histogram pattern in Jonglei State in remarkable” ?
8. What did “The moderate correlation” mean?
9. Lines 254-255: This sentence is incompleted. Please rewrite it.
10. Figures 8, 9, 10 and 13: How did the authors select the first and second periods?
11. Lines 273, 275: “R25”→“R20”？

 

Comments for author File: Comments.pdf

Author Response

Comments 1:  Lines 34-38: Previous studies have shown that the flood risk are projected to exacerbated under a future warmer world (e.g.,  https://doi.org/10.1002/joc.5553), which could be added to suggest the importance of this study

Response 1:

Thank you for your comment. We agree and have added the suggested sentence and reference in the revised manuscript.

[line 38-39, page 1]:

Previous studies further demonstrate that these flood risks are projected to increase under future climate warming [3].

Comments 2: Section 2, Materials and Methods, the common time periods should be added

Response 2: Thank you for your comment. We have, accordingly, revised the sentence and added the common periods.

[Line 209-213, page 6]

It is noted that the data periods for CHIRPS precipitation, Mangala river flow, and Lake Victoria water levels used in the above ITA analysis differ. CHIRPS precipitation data spans from 1981 to 2023, whereas the other three datasets cover 2008 to 2024. Overlap between CHIRPS precipitation and Lake Victoria water level data exists from 1994 to 2023.

Comments 3: Figure 3. Was Figure 3 cited from Tiitmamer (2019)? If so, I strongly suggested to delete it or remove to the supplementary

Response 3: I agree, as strongly suggested, Figure 3 has been deleted, and the following sentence has been added:

[Line 164-166, page 5]

Previous studies have emphasized instances of floods and droughts since 1900, highlighting a significant increase in flood occurrences [30].

Comment 4: Lines 215-217: “the PRCPTOT varied over the years but declined in recent years (Fig. 4a)”: 4a should be Fig 4b. “The R20 mm also decreased in recent years (Fig. 4b) ” Fig. 4b should be Fig 4a

Response 4: Thank you for your comment. However, Figures 4a and 4b remain unchanged. The following revised sentence has been added to the manuscript:
[Line 231–232, page 7]

Note that in Jonglei State, PRCPTOT decreased in recent years (Fig3a). R20 mm varied from year to year but declined in recent years (Fig. 3b)

Comments 5: What did the authors mean by “ varied over the years” or “ varies over time”?

Response 5: Thank you for your comment. The phrase “varied over the years” or “varies over time” refers to the presence of different patterns rather than a consistent or unchanging situation. “Varied  over the years” was changed to “varied from year to year” [Line 231–232, page 7]

Comments 6: Figures 4 and 5: Please add long-term trend lines.

Response 6: I agree, the long-term trend lines have been added to Figures 3 and 4 [line 236 and 239, page 7] and the following text was added to the figure caption: “The dashed line in the figure indicates a linear trend.”

Comments 7: What did the authors mean by “the precipitation histogram pattern in Jonglei State in remarkable” ?

Response 7: Thank you for your comment. It means that the rainfall distribution (how much, how often, and in what amounts) in Jonglei State is noteworthy or particularly interesting. The word [remarkable] has been replaced by “especially remarkable” in the revised manuscript [line 248, page 8]

Comments 8: What did “The moderate correlation” mean?

Response 8: Thank you for your comment. The phrase “The moderate correlation” refers to a statistical relationship between two variables that is neither weak nor strong but falls somewhere in the middle between [0.3 – 0.7] in terms of strength. In the revised manuscript, the word ‘Moderate’ has been replaced by ‘moderate strength’ [line 265, page 9].

Comment 9: Lines 254-255: This sentence is incompleted. Please rewrite it.

Response 9: Thank you for your comment. The sentence has been rewritten as follows: ‘that as the frequency of rainy days changed, so did the rainfall intensity’ [lines 264-265, page 9]

Comment 10: Figures 8, 9, 10 and 13: How did the authors select the first and second periods?

Response 10: Thank you for your comment. In the innovative trend analysis (ITA) method, the selection of the first and second periods is typically based on dividing the entire time series into two equal parts [line 183-185, page 6]. Each period is then analyzed to compare data points from the first half with those in the second half. In graphical terms, the first period values are plotted on the x-axis and the second period values on the y-axis of a Cartesian coordinate system. For example, data period of CHIRPS data is 1981 to 2023 (43-years), and entire period can be divided into two series with 2002 as the dividing year. Furthermore, in order to ensure that the first/second half are completely same period while incorporating the most recent data, the CHIRPS data used in the ITA analysis covers the period from 1982 to 2002 for the first half and from 2003 to 2023 for the second half. The specific periods for the first half and second half are indicated in the axis labels of each ITA analysis graph.

Comment 11: Lines 273, 275: “R25”→“R20”？

Response 11: Thank you for your comment. Lines 288, 289 have been corrected ‘R25 mm -> R20 mm’

12. Response to Comments on the Quality of English Language

Point 1:

Response 12: Thank you for pointing this out. The manuscript has been checked by the following English proofreading service prior to submission.

https://www.textcheck.com/login

However, we are very sorry that the manuscript contained several typos and other errors. We will check the revised manuscript more carefully to avoid these errors

 

Author Response File: Author Response.pdf