a methodology is presented for the stochastic generation of daily rainfall which accounts for changes to the climatic inputs. the focus of the study is an example catchment in iran. the methodology addresses the inability of gcms to provide suitable future scenarios for the time and space scales required for a water resource impact assessment for a small catchment. one stochastic model for rain...

flood is one of the most calamitous natural disasters that causes extensive property and life damages across theworld. it however, could be a blessing due to its special natural water resources recharging value. by simulating themagnitude of probable floods considering the anthropogenic and natural effects and implementing contingency plans,their damages could be reduced. in this paper, the gen...

In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...

hairsine and rose (1991) developed a process-based soil erosion model which described the erosion transport of multiparticle sizes in sediment for rain-impacted flow in the absence of entrainment in overland flow. in order to test this model laboratory experiments were carried out in a detachment tray using simulated rainfall. three contrasting soil types were subjected to simulated rainfall at...

precipitation data is of utmost importance to carry out many hydro-meteorological studies. observed warming over several decades has been linked to changes in the large-scale hydrological cycle such as: increasing atmospheric water vapour content, changing precipitation patterns, intensity and extremes, reduced snow cover and widespread melting of ice, and changes in soil moisture and runoff. p...

climate change is found to be the most important global issue in the 21st century, so to monitor its trend is of great importance. atmospheric general circulation models because of their large scale computational grid are not able to predict climatic parameters on a point scale, so small scale methods should be adapted. among downscaling methods, statistical methods are used as they are easy to...

A framework for short-term probabilistic forecasting of watershed flood stage conditions using a distributed rainfall-runoff model is proposed. A stochastic rainfall pattern simulation model capable of generating input for a distributed rainfall-runoff model is developed. Generation of rainfall patterns over a 6-hour period is achieved using a translation vector rainfall forecasting process mod...

Most hydrologic/water quality (H/WQ) models that use rainfall as input assume spatial homogeneity of rainfall. Under this assumption this study assesses the variability induced in calibrated model parameters solely due to rainfall spatial variability. The AGNPS model and a network of 17 raingauges were used. Model parameters were estimated using rainfall observed at each gauge location, one at ...