the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 Feb 2026
Role of hydrometeorological variables and catchment area to flood generation over the monsoonal climate region of India
Abstract. Indian River basins experience frequent flooding during the Indian summer monsoon rainfall and pose several challenges to the large population of the region. To effectively manage flood risk in the region, a better understanding of flood-generating mechanisms is essential, yet hydrometeorological and catchment drivers controlling flood processes are poorly explored across India. In this study, we examine the role of hydrometeorological variables (such as precipitation and surface runoff) and catchment area in the flood occurrence in one of the largest river basins (Godavari River basin) of the Indian Subcontinent using observed and VIC-simulated datasets. Based on the temporal analysis of precipitation, runoff, and streamflow, we show that floods caused by multiple high-intensity precipitation days predominantly occur in the semi-humid sub-basins (Tekra, Pathagudam, Perur, and Polavaram) of the Godavari River. The majority of floods in the semi-humid sub-basins are associated with 10 to 11 days of accumulated precipitation, having multiple high-intensity precipitation events prior to the flood. In contrast, the majority of floods in the semi-arid region of Godavari (Mancherial sub-basin) are triggered by a single high-intensity precipitation day and associated with short-duration (2 days) accumulated precipitation. In addition to temporal analysis, we also performed Empirical Orthogonal Functions (EOF) analysis using precipitation, runoff, and streamflow data to identify the flood-dominant catchment area. Our results demonstrate that central and downstream areas of the basin contribute disproportionately to flood occurrence, with the Tekra sub-basin generating substantially higher runoff due to favorable catchment characteristics. Overall, this study advances understanding of flood-generating mechanisms over the Godavari River basin, which can be helpful for flood control and management during the monsoonal climate of the Indian Subcontinent.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-339', Anonymous Referee #1, 02 Apr 2026
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AC1: 'Reply on RC1', Saran Aadhar, 19 May 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-339/egusphere-2026-339-AC1-supplement.pdf
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AC1: 'Reply on RC1', Saran Aadhar, 19 May 2026
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RC2: 'Comment on egusphere-2026-339', Anonymous Referee #2, 05 Apr 2026
General Remarks
The manuscript investigates the flood-generating mechanisms in the Godavari basin using hydroclimatic variables and catchment characteristics. The topic is relevant for monsoon dominated region and large basin flood dynamics. The integration of temporal analysis and EOF-based spatial attribution is a strength, and the findings are potentially useful. Overall, the manuscript is scientifically promising; however, it currently needs revision to explicitly highlight the novelty, provide scientific justification on use of only 5 stations, neglect of the role of human interventions, reliance on VIC outputs and ignoring the use of groundwater on flood generation in the study region.
Major Comments
- The manuscript largely confirms known concepts: Long-duration vs short-duration flood regimes, role of antecedent soil moisture and spatial heterogeneity in runoff contribution. Suggesting authors to clearly articulate what is fundamentally new for large basin of India and why this is beyond previous works.
- The study depends on VIC-simulated runoff and soil moisture without robust validation of extremes. Add a discussion of limitations of VIC in monsoon-dominated basins.
- The study analyzes flood mechanisms using only 5 gauging stations across a very large heterogeneous basin (312, 800 km2). Can these 5 stations (selected on major river reaches) capture the spatial heterogeneity of the Godavari basin? Further, the stations are nested, and the results are not independent samples. Clearly state the limitations in extrapolating the findings to the entire basin.
- The manuscript does not consider baseflow contributions in the analysis, despite using the VIC model which simulated surface runoff and baseflow. For long-duration floods in large monsoonal basins, particularly under wet antecedent conditions, baseflow can significantly contribute to peak discharge. The authors are encouraged to consider separating baseflow and quickflow components or explicitly discuss this limitation.
- EOF used to identify “flood-dominated areas”; however, EOF identifies variance patterns not causality. Please clarify the physical representation of modes.
- Godavari basin is heavily regulated and these structures attenuate flood peaks, alter timing of peak discharge and modify flow accumulation downstream. The assumption that human impacts are negligible is not sufficiently justified especially for downstream stations.
- Discussion section can be strengthened by adding comparison with global studies, process understanding and implications for forecasting systems.
Minor Comments
- Cleary describe the novelty in the abstract.
- Literature review in the introduction section is generic and global, with limited focus on Indian basins. Recent works can be added to sharply define the motivation to this study.
Citation: https://doi.org/10.5194/egusphere-2026-339-RC2
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- 1
It was a pleasure to read the manuscript on "Role of hydrometeorological variables and catchment area to flood generation over the monsoonal climate region of India" by Aadhar et al.
The manuscript does an extensive investigation on the flood generating mechanisms in the Godavari River basin, focusing on the rainfall characteristics and identification of catchment area that predominantly contributes to flooding in different subbasins in the Godavari River. The authors rely on an event-based approach wherein independent flood events are identified using a POT approach, and the characteristics of rainfall and antecedent soil moisture conditions prior to the flood events are assessed. The authors identify the time window of rainfall duration which is most correlated with the flood events in each subbasin and classify the triggering rainfall event into one-day extreme, multiday extreme and moderate rainfall events. Using an EOF analysis and correlation they also identify the regions in the catchment with higher runoff coefficient or significant contribution to runoff generation. While the role of rainfall duration(Nanditha & Mishra, 2022), and catchment area on flood generation (Nanditha & Mishra, 2024) is well established in the Indian region, the second part of the study demarcating the flood-dominating catchment area in different subbasins is novel and the methodological aspect exhibits rigour and consistency. I only have a few suggestions and clarification to improve the readability and reproducibility of the manuscript.
Methodology
I would expect more detailing on the EOF approach employed. Please provide the relevant equations. Did the authors use accumulated rainfall and runoff for the most correlated window for each pixel for the analysis? I have some reservations on using accumulated runoff. Though runoff measured in mm (length scale) can be treated as an accumulated quantity, the way the VIC model represents it can be different. For instance, the runoff generated at timestep t may not entirely rout to the downstream cell at the end of the day due to the time lag in the routing process (the hill slope routing uses a unit hydrograph approach). So, the runoff generated for the timestep t+1 could have contribution from the previous day. I would suggest using mean runoff instead of accumulated runoff for each cell.
Similarly, peak discharge should be correlated with the mean runoff and not the accumulated runoff. I would suggest consistently use mean runoff throughout the manuscript.
Figures
The caption of Figures 4-6 is disordered. The top panel in the current figure is explained as the last panel.
Other suggestions
Line 145. No need of Moreover here.
Line.295 - Is this surface runoff alone? Did you consider the 75th percentile of entire timeseries or seasonality is taken into account?
Line 299: What is the thickness of soil moisture considered?
95th percentile is considered as the flood peak; this may include flows which are not exactly extreme. Could you please conduct a sensitivity analysis by considering other POT thresholds, say 99 percentile and see if it affects the findings of the manuscript.
Line 377: is located instead of reside
Lines 384-386: The correlation is estimated here between the peak discharge and accumulated rainfall in the relevant regions.
Lines 405-409: The duration mentioned here is different for different subbasins right? If the rainfall occurs for multiple day duration on dry soil vs wet soil it is expected to have difference in runoff coefficient. Are you here comparing different duration scenarios for the same subbasins, if so, multiday duration can increase runoff coefficient compared to single day duration rainfall for dry conditions. I feel there is some lack of clarity here.
Line 432: Initial hydrologic conditions instead of pre
Lines 474-476: Please explain this is not clear to me. In this manuscript, the authors have not considered the spatial pattern of soil moisture wetness as far as my understanding. the soil moisture pattern will also be related to the rainfall pattern in a catchment, and I do not understand how this conclusion of "soil moisture pattern may not affect the pre-event hydrometeorological patterns" is arrived at. What exactly the authors imply by hydrometeorological patterns?
Line 481: Did you mean forest to crop land conversion? If so, please mention it explicitly.
A possible extension is to explore if the identified flood-dominating area is also associated with the spatial rainfall pattern anomalies. That is, to explore if the region is receiving higher intensity rainfall than other parts of the catchment which leads to infiltration excess runoff generation. I would like to see such an analysis if it won’t take much time and effort to corroborate the conclusion of the manuscript that the catchment hydrologic partitioning is the cause for the increase runoff contribution and to rule out that it is not related to the spatial heterogeneity in rainfall distribution.
References
Nanditha, J. S., & Mishra, V. (2022). Multiday Precipitation Is a Prominent Driver of Floods in Indian River Basins. Water Resources Research, 58(7), e2022WR032723. https://doi.org/10.1029/2022WR032723
Nanditha, J. S., & Mishra, V. (2024). Projected increase in widespread riverine floods in India under a warming climate. Journal of Hydrology, 630, 130734. https://doi.org/10.1016/J.JHYDROL.2024.130734