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.
Ommolbanin Bazrafshan; Azimeh Chashmberahm; Arashk Holisaz
Abstract
Evaporation is one of the most important and effective factors in water resources planning and management in arid and semi-arid areas and examining it's changes in time scales and different years as one of the most important climatic parameters, has an important role in planning and water resource management ...
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Evaporation is one of the most important and effective factors in water resources planning and management in arid and semi-arid areas and examining it's changes in time scales and different years as one of the most important climatic parameters, has an important role in planning and water resource management in agriculture section and determining cultivation pattern and proper water resource management. One of the methods to assess and forecast changes in evaporation is time series models by the generic name of ARIMA models. Therefore, in order to determine the best model to predict pan evaporation, after considering the climate using improved Domarton climatic classification method, in each climatic sample, one evaporation station was selected and standardized pan evaporation index (SPEI) was calculated for each of the stochastic model for estimation the amount of future monthly time series SPEI in the period of 1954-1955 to 2009-2010 over the next 12 months. Results showed that the Auto Regressive Moving Average model (ARMA) and Auto Regressive (AR) had the best performance, in Hormozgan province, so that, in the hot and dry, hyper hot arid and hyper hot hyper arid climates, in the next month, had the highest standard coefficient of determination (R) of 0.83, 0.71, 0.7 and the lowest value RMSE of 0.59, 0.8, 0.88, respectively and the AR model was able to predict the next 11 months, well. The results showed that AR model has better performance compared to ARMA model in estimating monthly pan evaporation in hot and dry climates in coastal wilderness areas.
