the objective of this study was to evaluate the ability of ten gcms and three emission scenarios to reproduce the rainfall and temperature parameters in kermanshah, ravansar and west islamabad stations located inside qaresou basin in iran using the average weighting method, over 1989-2008 period. at first, the models output and the scenarios were provided for this period. then, the models valid...

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical exper...

Stochastic weather generators are useful for producing daily sequences that reproduce climatic statistics aggregated to, e.g., a monthly time scale, for use with biological simulation models. This paper describes a stochastic weather generator that disaggregates monthly rainfall by adjusting input parameters or by constraining output to match target rainfall totals, and demonstrates its use wit...

In this study, urban pluvial flood risk is studied in an actual study area using scenario simulation method based on hydrodynamics. Real weather data and GIS (Geographic Information System) data are adopted to make the results reliable. A region in Haidian District of Beijing is selected as the study area. All the rainfall scenarios (about 200 scenarios) during an 8-year period (from January 1,...

Flood estimation can be performed on the basis of event-based simulation or continuous simulation. A model with continuous water balance accounting has the attractive feature that dynamic factors affecting runoff production may be represented explicitly (Lamb 1999). In particular, a conceptual rainfall-runoff model can simulate the changing antecedent moisture conditions that determine the catc...

Precipitation is a major input in hydrological models. Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolutions. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in reflectivity-rainfall Z-R relationships, variation in vertical profile of reflectivity, and spatial and temporal sampling among oth...