Probabilistic assessment of peak discharge and debris flow concentration in the Surma River using Monte Carlo simulation

ABSTRACT Rivers, vital for household and industrial needs, vary in size due to erosion and sedimentation and are significantly impacted by climate variations. Accurate estimation of river characteristics like discharge and debris flow concentration is essential for designing hydraulic systems in flood-prone areas. This study assesses these factors in the Surma River, located in Sylhet, Bangladesh, by using Monte Carlo simulation to reduce uncertainty. The simulation optimized the time of concentration against water level height. Peak discharge results for 5-, 10-, 25-, 50-, and 100-year return periods were 1,904.66, 2,174.77, 2,543.63, 2,846.72, and 3,124.25 m3/s, with corresponding debris flow concentrations (Cv) of 0.5499989, 0.5499976, 0.5499967, 0.5499940, and 0.5499147. During the monsoon season, the maximum peak discharge reached 5,095.58 m3/s with a Cv of 0.7886368. Model validation using the F test and R2 test demonstrated high accuracy, indicated by low mean squared error (MSE), mean absolute error (MAE), and root mean square error (RMSE), along with a coefficient of determination (R2) of 0.7097. The p-value from the F test (0.197852) indicated strong alignment between predicted and observed discharges. This study enhances understanding of flow dynamics, improves prediction precision, and underscores the importance of historical data in flood risk assessment.