Highs and lows: exploring digital elevation model resolution effects on hydrograph model precision

The ability of hydrological models to estimate hydrological variables such as flood characteristics, mainly depends on the spatial resolution of the input data. Digital Elevation Models (DEMs) are one of the most important datasets used in watershed modelling. This study investigates the effects of spatial resolutions derived from five DEMs, sourced from topographic maps (TOPO; 1:25,000 scale), ALOS PALSAR, ASTER, SRTM, and GTOPO, with spatial resolutions of 10, 12.5, 30, 90, and 1000 m, respectively, on the estimation of the Geomorphological Instantaneous Unit Hydrograph (GIUH) and the GeomorphoClimatic Instantaneous Unit Hydrograph (GCIUH) within the Kasilian Watershed, Iran. A total of 64 flood events recorded between 1978 and 2020 were analyzed. The results indicate that DEM spatial resolution significantly affects the performance of both the models. For the GIUH model, the SRTM DEM produced the best performance, with a Root Mean Square Error (RMSE) of 2.83 m3/s. Similarly, SRTM DEM produced the lowest RMSE of (8.06 m3/s) for the GCIUH model. Overall, the GIUH model outperformed the GCIUH model across all DEM datasets. These findings highlight the importance of selecting an appropriate DEM spatial resolution for estimating peak discharge and Instantaneous Unit Hydrographs, thereby improving flood simulation and supporting more effective flood management and mitigation.