this study aims to evaluate effects of two downscaling methods; change-factor and statistical downscaling on therunoff of the azam-harat river located at yazd province (with an arid climate) of iran, under the a2 emission scenariofor the period of 2010-2039. for this purpose, cgcm3-ar4 model; a rainfall-runoff conceptual model, ihacres; twodownscaling models, change factor and lars-wg were appl...

runoff simulation is a vital issue in water resource planning and management. various models with different levels of accuracy and precision are developed for this purpose considering various prediction time scales. in this paper, two models of ihacres (identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data) and ann (artificial neural network) mode...

This study aims to evaluate effects of two downscaling methods; change-factor and statistical downscaling on therunoff of the Azam-Harat River located at Yazd province (with an arid climate) of Iran, under the A2 emission scenariofor the period of 2010-2039. For this purpose, CGCM3-AR4 model; a rainfall-runoff conceptual model, IHACRES; twodownscaling models, Change Factor and LARS-WG were appl...

investigation of drought event has a great importance in the natural resources management and planning water resources management. in this research, the effect of the climate change on drought characteristics in northwest of iran was investigated using the hadcm3 model under a2 scenario. the statistical downscaling was executed using sdsm 4.2.9 and observed daily precipitation, observed predict...

The assessment of local and regional impacts of climate change often requires downscaling of general circulation model (GCM) projections from coarser GCM-scale to finer localor catchmentscale spatial resolution. This paper provides an assessment of two downscaling approaches for simulation of daily rainfall over Sydney, Australia. The two downscaling alternatives compared include a multivariate...

This study aimed to forecast temperature variations in the western and southwestern part of Iran using a general circulation model artificial neural networks (ANN). The data included mean diurnal temperatures from synoptic stations, National Centers for Environmental Prediction/ Center Atmospheric Research (NCEP/NCAR) reanalysis data, outputs third-generation global climate model, Hadley Centre...

Statistical downscaling methods seek to model the relationship between large scale atmospheric circulation, on say a European scale, and climatic variables, such as temperature and precipitation, on a regional or subregional scale. Downscaling is an important area of research as it bridges the gap between predictions of future circulation generated by General Circulation Models (GCMs) and the e...

Abstract The frequency and severity of climatic extremes is expected to escalate in the future primarily because increasing greenhouse gas concentrations atmosphere. This study aims assess impact climate change on extreme temperature precipitation scenarios using indices Kashmir Himalaya. analysis has been carried out for twenty-first century under different representative concentration pathway...

Evapotranspiration is sensitive to climate change. The main objective of this study was examine the response reference evapotranspiration (ET0) under various change scenarios using artificial neural networks and Canadian Earth System Model Second Generation (CanESM2). Hargreaves method used calculate ET0 for western, central, eastern parts Prince Edward Island their two input parameters: daily ...