Hersh Entezami; Sayed Kazem Alavipanah; Hamidreza Matinfar; Ali Darvishi; Kamran Chapi
Abstract
The importance of snow and its water equivalent in water resources supply has caused many studies and researches to measure snow characteristics and runoff. Conducted in the Saqqez Watershed, this research attempted to estimate snow–induced runoff in a mountainous area and the SRM Model was ...
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The importance of snow and its water equivalent in water resources supply has caused many studies and researches to measure snow characteristics and runoff. Conducted in the Saqqez Watershed, this research attempted to estimate snow–induced runoff in a mountainous area and the SRM Model was selected to simulate daily runoff from snow-melt. Based on the data and variables for four consecutive years of 2006 to 2009 collected and snowmelt runoff was estimated. MODIS satellite images were used to calculate the snow coverage area. After segregating the snow coverage from the images, the daily snow area was calculated using GIS, and along with the other variables, imported into the model. For better evaluation of efficiency of the model, the model was calibrated and validated. The process of calibration was led to the best estimate for each parameter. To evaluate the accuracy of model and comparing results with field data Nash-Sutcliffe coefficient and the percentage difference were used. The results of the Nash-Sutcliffe coefficient were between 0.90 to 0.94 and the differences in the volume were 6.8 to 7.2 percent, which indicates the high-performance of modeling.
mohammad mehrabi; Saeid Hamzeh; Seyed Kazem alavipanah; Majid Kiavarz; Ruhollah Ziaee
Abstract
Soil moisture is one of the key parameters in watershed and water resources studies. Field measurement of this parameter is extremely difficult, time-consuming and costly. Hence, in recent years, numerous satellite-based methods for estimating and modeling soil moisture have been developed and presented. ...
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Soil moisture is one of the key parameters in watershed and water resources studies. Field measurement of this parameter is extremely difficult, time-consuming and costly. Hence, in recent years, numerous satellite-based methods for estimating and modeling soil moisture have been developed and presented. Among proposed methods, surface energy models performed better and have a higher degree of accuracy because of their physical nature. But, due to their particular complexity, they have been used rarely. Therefore, this research was carried out to estimate soil moisture using Landsat 8 Satellite imagery and Surface Energy Balance System (SEBS) near the Shadegan Wetland, located in the south-west of Iran. For this purpose, volumetric soil moisture content was measured at 39 points on 27 June 2016, simultaneous with the overpass of Landsat 8 Satellite over the study area. After necessary image processing, the was calculated using the applying the SEBS on satellite image. Then, the evaporation fraction was used as the main input in an experimental model (saturation ratio model) for estimating the soil moisture. Results showed the good ability of the model for estimating soil moisture with the coefficient of determination of 0.69 and the RMSE error value of 0.03 . It can be concluded that combination of remote sensing data, surface energy balance system and the experimental model of soil moisture can be used for modeling soil moisture in a large scale.
