Reza Chamani; Mahmood Azari; Sven Kralisch
Abstract
The hydrological effects of climate change are a great challenge for water resources management. Determining climate change impacts on hydrological processes is a prerequisite for adaptation strategies to climate change; which in turn is necessary for water scarcity crisis in future. The purpose of this ...
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The hydrological effects of climate change are a great challenge for water resources management. Determining climate change impacts on hydrological processes is a prerequisite for adaptation strategies to climate change; which in turn is necessary for water scarcity crisis in future. The purpose of this research is to determine climate change impacts on hydrological regime of the Chehelchay watershed in Golestan province. J2000 distributed process based model was used for simulation of the hydrological process. Output results of seven climate models including CanESM2, CCSM, BBC-CSM1.1, CESM1-BG, CESM1-CAM5, ICHEC- EC-EART and MPI-M-MPI-ESM-LR for two Representative Concentration Pathways scenarios (RCP 4.5 and RCP 8.5) for 2071-2100 were used for climate change impact analysis. Study results revealed that the maximum temperature for RCP 4.5 and RCP 8.5 in 2071-2100 will increase by 2.6 and 4.7 °C and the minimum temperature will increase by 2.4 and 4.5 °C respectively by the end of the 21st century. In addition, precipitation for RCP 4.5 will increase by 0.6 percent and for RCP 8.5 will decrease by 0.6 percent. Modeling results show these will lead to significant changes in the hydrological regime. In particular, evapotranspiration will increase by 9.6 and 16.7 percent and stream flow will decrease by 4.2 and 3.2 percent. The results of the hydrological changes will cause a decrease in stream flow in April –June and for RCP 8.5 will be continued till October.
Raziyeh Motamedi; Mahmood Azari; Reza Monsefi
Abstract
Landscape is one of the main factors influencing hydrological processes of the watershed. Changes in structure and spatial pattern of land use play important role in surface runoff and sediment yield. Determining the relationship between landscape patterns and hydrological processes can be used as an ...
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Landscape is one of the main factors influencing hydrological processes of the watershed. Changes in structure and spatial pattern of land use play important role in surface runoff and sediment yield. Determining the relationship between landscape patterns and hydrological processes can be used as an indicator of watershed soil erosion and sediment yield. Therefore, due to the problems in field measurement of sediment yield, its estimation using landscape properties and land use pattern is an appropriate alternative for current estimation methods. The purpose of this research is to determine the relationship between watershed sediment yield and landscape metrics in the selected sub-watersheds of Golestan Province. To this end, suspended sediment concentration data for all hydrometric stations of the studied province were obtained from the relevant resources and appropriate sub-watersheds were selected. Then, using the land use map of Golestan Province, 15 landscape metrics related to sediment yield were determined for different land uses by Fragstats 4.2 software. In order to determine the relationship between watershed sediment yield and landscape metrics, a partial least squares regression was used which combines the methods of principal component analysis and multiple linear regression. The relative importance of landscape metrics was determined through examining the values of Variable Importance for the Projection (VIP) and Regression Coefficients (RCs). The results of this study indicated that the watershed sediment yield is densely associated with land use patterns. The main indices in reducing sediment yield were the Largest Patch Index (LPI), the average of the nearest neighbor distance (ENN-MN) and the average of perimeter-area ratio (PARA –MN) with values of VIPs of 1.296, 1.184 and 1.747, and regression coefficients of -0.014, -0.039, and -0.002, respectively. The main indices in incrising sediment yield were Landscape Shape Index (LSI) and mean patch size (AREA-MN) with regression coefficients of 0.020 and 0.017, respectively. The landscape characteristics in watersheds could account for as much as 71% of the variation in sediment yield of watershed. The results of study showed that the landscape characteristics can be used for watershed sediment yield modeling.
Shahla Tavangar; Hamidreza Moradi; Alireza Massah Bavani; Mahmood Azari
Abstract
Climate is a complex system that changing mostly due to increased greenhouse gases and global warming, leading to intensification of change in climatic factors such as precipitation amount and intensity of extreme precipitation events. In effect of climate change in the future, change amount and volume ...
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Climate is a complex system that changing mostly due to increased greenhouse gases and global warming, leading to intensification of change in climatic factors such as precipitation amount and intensity of extreme precipitation events. In effect of climate change in the future, change amount and volume of the soil erosion is expected which the most important sensitive factor will be the rain fall erosivity. The aim of this study was to determine the effect of climate change on rainfall erosivity factor. For this purpose the HadCM3 model from A1B scenario was used and downscaling with LARS-WG model was used. So monitoring of rainfall erosivity factor for three periods of 2011-2030, 2045-2065, and 2080-2099 in north of Iran was simulated. Results show that rainfall erosivity factor in Sangdeh, Babol, Korkorsar, Anzali, Behshar and Gorgan stations will be increasing during the 2011-2030 period but for stations in Babolsar, Hashtpar, Rasht and Gorgan in the period 2045-2065 and 2080-2099 decreased. According of calculations, maximum changes of the rainfall erosivity factor in future will be occurring during the 2011-2030 and it’s minimum will be occurring period the 2080-2099. So largest rainfall erosivity factor was simulated about 42.6 MJ mm ha-1 h-1 for Hashtpar station during the 2011 to 2030 period. The obtained results show that the erosivity factor increase will be during the current century in the north of Iran.
