Hydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece)

Abstract

SWAT (Soil and Water Assessment Tool) is a continuous-time, semi-distributed, river basin model widely used to evaluate the effects of alternative management decisions on water resources. This study examines the application of the SWAT model for streamflow simulation in an experimental basin with mixed-land-use characteristics (i.e., urban/peri-urban) using daily and hourly rainfall observations. The main objective of the present study was to investigate the influence of rainfall resolution on model performance to analyze the mechanisms governing surface runoff at the catchment scale. The model was calibrated for 2018 and validated for 2019 using the Sequential Uncertainty Fitting (SUFI-2) algorithm in the SWAT-CUP program. Daily surface runoff was estimated using the Curve Number method, and hourly surface runoff was estimated using the Green-Ampt and Mein-Larson method. A sensitivity analysis conducted in this study showed that the parameters related to groundwater flow were more sensitive for daily time intervals, and channel-routing parameters were more influential for hourly time intervals. Model performance statistics and graphical techniques indicated that the daily model performed better than the subdaily model (daily model, with NSEgCombining double low lineg0.86, R2gCombining double low lineg0.87, and PBIASgCombining double low lineg4.2g%; subdaily model with NSEgCombining double low lineg0.6, R2gCombining double low lineg0.63, and PBIASgCombining double low lineg11.7g%). The Curve Number method produced higher discharge peaks than the Green-Ampt and Mein-Larson method and better estimated the observed values. Overall, the general agreement between observations and simulations in both models suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin with high complexity and spatial distribution of input data.