Estimating extreme flood magnitudes in the Upper Krishna River Basin using multiple probabilistic methods

Area of Science:

• Hydrology and Water Resource Management
• Environmental Science
• Civil Engineering

Background:

• Floods pose significant societal and environmental risks, necessitating accurate understanding of their frequency and magnitude.
• The Upper Krishna River Basin (UKRB) has experienced major floods in recent decades, highlighting the need for localized flood analysis.
• Effective water resource management, infrastructure planning, and risk mitigation depend on reliable flood prediction.

Purpose of the Study:

• To analyze flood frequency and predict future peak discharge scenarios in a UKRB sub-basin.
• To evaluate the suitability of different probability distribution functions for flood prediction in the study area.
• To provide data for informed infrastructure planning and flash flood risk mitigation.

Main Methods:

• Utilized annual peak discharge data spanning 50 years (1970-2019) from five gauging stations in the UKRB.
• Applied log-normal, Gumbel Max, and Log Pearson Type III (LP3) probability distributions to estimate discharge for various return periods (2 to 200 years).
• Assessed goodness-of-fit using Kolmogorov-Smirnov (K-S), Anderson-Darling (A-D), and chi-square tests to determine the best-suited distribution for each site.

Main Results:

• Estimated discharges for return periods greater than 5 years exceeded the mean annual peak discharge at all five sites.
• Discharge exceeding the 25-year return period is projected to surpass the river's carrying capacity across all studied locations.
• Log-normal distribution best fitted Warunji and Samdoli, LP3 for Kurundwad and Sadalga, and Gumbel Max for Arjunwad, with high correlation (R²=0.98) to actual data.

Conclusions:

• All three probability distribution methods satisfactorily projected river discharge, with specific distributions showing better site-specific fits.
• Predicted peak discharges indicate a significant flood risk, especially for return periods beyond 25 years, potentially exceeding river capacities.
• The study's findings offer crucial data for future infrastructure development and flood risk management strategies in the UKRB.