Reliable estimates of runoff are required as a part of the information sets that help watershed managers make informed decisions on water resources planning and management. This study was carried out in Shafaroud watershed located in the north of Iran. In order to achieve the best runoff simulation in the study area, first rainfall data of four stations during 1998 to 2011 were collected and co...

Abstract This study evaluated the performance and hydrologic utility of four different satellite precipitation datasets (SPDs), including GPM (IMERG_F), PERSIANN_CDR, CHIRPS, CMORPH, to predict daily streamflow SL using SWAT hydrological model as well coupled soft computing models (SCMs) such artificial neural networks (SWAT-ANNs), random forests (SWAT-RFs), support vector regression (SWAT-SVR)...

Soil water content (SWC) and soil temperature are important hydrologic state variables. Accurate model simulation is critical in regimes cold regions dominated by spring snowmelt. In this study, we developed a combined physically-based energy-balance rain-on-snow (ROS) module for the Water Assessment Tool (SWAT) applied it to South Saskatchewan River Basin (SSRB). We calibrated SWAT base (SWAT-...

Kabul River Basin is the most populated and an important source of water resources in Afghanistan. The Soil Water Assessment Tool (SWAT) model, together with ArcGIS SWAT-CUP, employed to predict runoff basin. Nine years meteorological hydrological data are study. DEM, soil cover, land use/cover downloaded from available global database. based classification, use/cover, elevation, drainage, slop...

Hydro-sedimentological models might be useful tools for investigating the effectiveness of soil and water conservation practices. However, evaluating usefulness such requires that predictions are tested against observational data uncertainty from model parameterization is addressed. Here we aimed to evaluate capacity SWAT simulate monthly streamflow sediment load in Posses creek catchment (12 k...