Modeling run-off flow hydrographs using remote sensing data: an application to the Bashar basin, Iran

Abstract

Abstract Precipitation, as one of the most significant parameters in hydrological simulations, is often difficult accessible in countries, such as Iran, due to an inadequate number of rain gauge stations. Remote sensing has provided an alternative source using a specific spatial and temporal resolution in rainfall estimation throughout an area. In this study, the effectiveness of the Hydrologic Engineering Center-Hydrologic Modeling System runoff rainfall simulation model was evaluated using the Global Precipitation Measurement (GPM) Mission satellite and rain gauge station precipitation data. The model was calibrated and validated using five flood event data of a hydrometric station at the outlet of the Bashar basin. Most important flood parameters including peak discharge (QP), flood volume (V) and time of concentration (TC) were used to evaluate and compare the application of satellite and ground station data in the model using various statistical indices. The accuracy of QP and V estimations by using rain gauge data was higher than those obtained by satellite data. However, the difference between mean relative error (MRE) in QP estimation was less than 1% (9.9 and 10.6% for rain gauge and satellite data, respectively). Conversely, higher accuracies were met for TC estimation using satellite (with MRE 9.1 and 10.2% for GPM and rain gauge data, respectively).