introduction: planning and management of water resource and river basins needs use of conceptual hydrologic models which play a significant role in predicting basins response to different climatic and meteorological processes. evaluating watershed response through mathematical hydrologic models requires finding a set of parameter values of the model which provides thebest fit between observed a...

Recent studies have shown that Bayesian Neural Networks (BNNs) are powerful tools for providing reliable hydrologic prediction and quantifying the prediction uncertainty. The reasonable estimation of the prediction uncertainty, a valuable for decision making to address water resources management and design problems, is influenced by the techniques used to deal with different uncertainty sources...

Spatial accuracy of hydrologic modeling inputs influences the output from hydrologic models. A pertinent question is to know the optimal level of soil sampling or how many soil samples are needed for model input, in order to improve model predictions. In this study, measured soil properties were clustered into five different configurations as inputs to the Soil and Water Assessment Tool (SWAT) ...

there is different methods for simulating river flow. some of thesemethods such as the process based hydrological models need multiple input data and high expertise about the hydrologic process. but some of the methods such as the regression based and artificial inteligens modelsare applicable even in data scarce conditions. this capability can improve efficiency of the hydrologic modeling in u...

This paper describes and evaluates an automated riverflow forecasting system for the prediction of peak flows during the cool season of 1998–99 over six watersheds in western Washington. The forecast system is based on the Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) fifthgeneration Mesoscale Model (MM5) and the University of Washington Distributed-Hy...

The main goal of this study is to use "top-down"? approach to simulate catchment scale hydrologic processes, in terms of water partitioning, runoff generation, storage dynamics and human/water interaction, and therefore to obtain a comprehensive understanding on intra-annual water balance of watersheds. An evaporation model at seasonal scale is developed based on Budyko framework. A runoff gene...

The main goal of this study is to use "top-down"? approach to simulate catchment scale hydrologic processes, in terms of water partitioning, runoff generation, storage dynamics and human/water interaction, and therefore to obtain a comprehensive understanding on intra-annual water balance of watersheds. An evaporation model at seasonal scale is developed based on Budyko framework. A runoff gene...

The main goal of this study is to use "top-down"? approach to simulate catchment scale hydrologic processes, in terms of water partitioning, runoff generation, storage dynamics and human/water interaction, and therefore to obtain a comprehensive understanding on intra-annual water balance of watersheds. An evaporation model at seasonal scale is developed based on Budyko framework. A runoff gene...