maryam zare; Ommolbanin bazrafshan; Mojtaba Pakparvar; gholamreza Ghahari
Abstract
Limitations of physical and experimental methods for estimating the evapotranspiration have been rationalized the employment of remote sensing technology to solve the energy balance equation in recent years. In this study, in order to investigate the evapotranspiration factor in the application of the ...
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Limitations of physical and experimental methods for estimating the evapotranspiration have been rationalized the employment of remote sensing technology to solve the energy balance equation in recent years. In this study, in order to investigate the evapotranspiration factor in the application of the HEC-HMS model and to optimize the flood estimation, using Landsat 8 Satellite Images (nine images) and the meteorological data related to the Kelestan Station and the SEBS Evapotranspiration Model for the period 2015-2017, ET values were calculated in the region of Kelestan Located in the Northwest of Shiraz, and the results were compared to the FAO Penman-Monteith equation to verify the accuracy of this model in the region of Kolding with water body. Evaporation in HEC-HMS including the direct evaporation of water, evaporation from soil surface, and transpiration of plants was estimated as an average elevation. In this study, we attempted to replace the actual evapotranspiration in the HEC-HMS model, The amount of runoff from the precipitation is calculated more accurately. The results showed that after scrutinizing the ET input, the simulated flood correlation with the measured flood was increased with R2 from 92 to 99%, and RMSE from 0.14 to 0.01, respectively. The results also indicated that the use of Landsat 8 Satellite Images and SEBS model is a suitable tool for estimating actual evapotranspiration in mountainous and field areas in hydrological studies. This research is for the performance of SEBS in determining the spatial and temporal distribution of evapotranspiration in a mountainous and hydrological area. Because the calculation of ET in hydrological models can improve the results and increase the accuracy of these models.
Gholamreza Ghahari; Samad Shadfar; Hamid Hosseini Marandi
Abstract
Erosion and sediment resulting from it, is one of the most important factors in watershed management. The estimation of sediment yield and prioritization of watersheds in terms of water erosion is the main objectives of watershed management. One of the ways to estimate soil erosion and sediment yield ...
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Erosion and sediment resulting from it, is one of the most important factors in watershed management. The estimation of sediment yield and prioritization of watersheds in terms of water erosion is the main objectives of watershed management. One of the ways to estimate soil erosion and sediment yield is to use empirical models. The aim of this research is to evaluate the efficiency of the EPM Model in Fars Province. To examine this, five small watersheds were selected in Fars Province. Five basins in which the earth dams and check dams were built were selected. There is no overflow from these dams in rainfall events and the most of them was made near to 10 years. The amount of sediment deposited in upstream of the reservoirs was calculated by means of precision mapping. Deposit bulk density was determined in the field to convert the volume into the weight. In parallel, the sediment yield of the basins was determined by EPM Model. Results showed that the minimum and maximum sediment yield measurements varied from 0.89 to 2.62 tonh-1y-1, but the estimated sediment was between 3.3 to 6 tonh-1y-1. The results of the relative error of estimation of EPM Model in each of the studied basins showed an over estimation in all basins (minimum 121.5 and maximum 447.2 percent). The Relative Root Mean Square Error (RRMSE) of the model was calculated as 2.39, which indicates a too much error of the model. Statistical analysis results comparison of actual sediment yields of watersheds with estimated values by model, using paired t-test, shows that there is a significant difference between these values (t=8.728 and sig.=0.001). According to the presented findings, the results of this model estimation for the investigated areas are not accepted.
