Baseflow significantly contributes to river floods in Peninsular India

Flood events are typically linked to extreme rainfall, but this alone does not always determine flood severity. The antecedent wetness of a catchment is a key factor influencing flood magnitude. While soil moisture is well recognized for its role in flood generation, the influence of deeper saturated zones has received less attention. This gap motivated the study of baseflow's role in flood dynamics. No prior work had resolved how baseflow interacts with rainfall and soil moisture to drive flood events. Understanding these interactions is crucial for flood prediction and management. The study focuses on Peninsular India, a region with complex hydrological conditions. Annual flood magnitudes have declined in most catchments, suggesting human interventions may be altering flood patterns. This paper aims to clarify the relative contributions of baseflow, soil moisture, and rainfall to flood severity.

The study investigates how flood magnitudes in Peninsular India are influenced by extreme rainfall, soil moisture, and baseflow. It seeks to determine the relative importance of these factors in flood generation. The researchers analyze data from 70 catchments over 1979-2018 to assess trends in flood characteristics. They also examine the impact of human interventions such as reservoir regulation. The goal is to understand how baseflow contributes to flood severity compared to other factors. The study addresses the uncertainty in how baseflow interacts with rainfall and soil moisture. By analyzing event coincidence, the authors aim to confirm baseflow's role in triggering floods. This work provides insights into flood dynamics in a region with complex hydrological systems.

The study uses data from 70 catchments in Peninsular India spanning 1979-2018 to analyze flood magnitudes. Annual flood data is compared with extreme rainfall events, soil moisture levels, and baseflow measurements. Statistical methods are employed to assess trends and correlations between these variables. Event coincidence analysis is used to determine the triggering effects of baseflow on floods. The researchers also evaluate the impact of reservoir regulation on flood characteristics. Data sources include hydrological records and satellite-based soil moisture observations. The analysis includes a comparison of pre- and post-dam construction flood trends. The study focuses on identifying the strongest predictors of flood severity.

Baseflow is found to have a stronger influence on flood magnitudes than soil moisture in Peninsular India. The study shows that baseflow trends closely mirror those of flood magnitudes. Rainfall and soil moisture extremes show weak correlations with flood trends. Event coincidence analysis confirms baseflow's role in triggering floods. Annual flood magnitudes have declined in most catchments. Reservoir regulation reduces flood peak and volume but increases flood duration. The results suggest that baseflow is a key driver of flood severity in the region. These findings highlight the importance of considering baseflow in flood prediction models.

The study concludes that baseflow has a stronger influence on flood magnitudes than soil moisture in Peninsular India. This finding is supported by event coincidence analysis and trend comparisons. The researchers propose that baseflow should be considered a key factor in flood prediction. Reservoir regulation is shown to reduce flood peaks but increase flood duration. The observed decline in flood magnitudes suggests human interventions are altering flood characteristics. The study highlights the need to incorporate baseflow in hydrological models. These conclusions are based on the observed trends and statistical analyses presented in the paper. The findings may inform flood management strategies in the region.