Suburban Runoff\nModeling for Seasonal Water Management\nin Rice Paddy Fields: An Elaborated Application of Unmanned Aerial\nVehicle Photogrammetry

This study developed a runoff model considering water\nflow conditions\nin paddy fields using high-resolution geospatial data obtained via\nunmanned aerial vehicle (UAV) photogrammetry. The model spans from\nthe rice transplanting to the harvesting period, accounting for different\nwater management systems. The methodology involved UAV photogrammetry\nto create a digital surface model (DSM), followed by a detailed catchment\nanalysis. A 1D drainage network model and a 2D ground surface model\nwere combined to simulate the runoff, incorporating Honma’s\nequations for model coupling. Calibration included adjusting the initial\nloss, infiltration rate, and link roughness coefficients. The results\nshowed high prediction accuracy with Nash-Sutcliffe efficiency (NSE)\nvalues of 0.92 and 0.82 for the August 30, 2019 and June 13, 2020\nevents, respectively, particularly under extreme rainfall (>50\nmm).\nWhen the initial loss of 4 mm was set as the no water field condition,\nhigh reproducibility for initial water depth could be derived (NSE\n= 0.82). Further, the initial loss in paddy fields and the roughness\ncoefficient for agricultural channels, considering the water level,\nsignificantly improved the model accuracy. The study demonstrates\nthat UAV-derived geospatial data can enhance runoff simulations, highlighting\nthe potential for improved water management and flood risk assessment\nin suburban regions with complex land-use conditions.