فهرست مطالب اصغر عزیزیان قطار

Iran is located in the arid and semi-arid belt of the world, which is characterized by low rainfall, thunderstorms, flood flows, and high evapotranspiration. Therefore, quantitative evaluation of evapotranspiration on a regional scale is necessary for water resources management, crop production, and environmental assessments in irrigated lands. In this study, to estimate ETo in four synoptic stations with arid, semi-arid, humid, and semi-humid climates, meteorological data such as temperature, net radiation, relative humidity, and wind speed were used for 1990-2010. Potational evapotranspiration was calculated using 5 different methods, including Hargreaves-Samani, Blaney-Criddle, Priestly-Tailor, Turc, and Makkink, besides, the standard FAO-56 was used (because there was no Lysimetric regionally data) to evaluate the applied formulas. In order to evaluate these methods, were used the mean absolute error (MAE), root mean squared error (RMSE), mean bias error (MBE), correlation coefficient (r), Nash -Satclif index (N.S). Based on these indices, Blaney-Criddle method, after the FAO-56 method, which was used as the basis, was selected as the superior method for the four climates in Iran.

Due to technical limitations, most satellites cannot simultaneously collect images with high spatial, temporal, and spectral resolution. In this paper, the possibility of using DisTrade and TsHARP downscaling methods and STI-FM method in order to achieve high spatial resolution for MODIS and Landsat8 images was investigated. The RMSE value for sharpened images of 1 km to 30 meters was less than 3.93 ° C. In this study, the surface energy balance algorithm (SEBAL) was investigated to estimate the actual evapotranspiration distribution using a combination of Landsat 7 and MODIS satellite images based on the T-Sharp downscale method. The results showed that the integration of satellite images improved the accuracy of estimating actual evapotranspiration compared to Landsat 7 images. The mean squared error of estimated evapotranspiration during the growth period was determined in comparison with lysimetric data for Modis images of 1.24-2.91 mm / day and for integrated images of 0.81-1.1 mm / day. In general, the results of this study showed that the estimation of evapotranspiration using SEBAL algorithm and based on the combination of images with different temporal and spatial accuracy can provide acceptable results.

Considering the importance of adequate roughness coefficient estimation in river engineering studies, evaluation of image processing technique in estimating Manning’s roughness coefficient in the surface layer of riverbeds carried out in this study. The mentioned approach evaluation conducted by implementing of sieving analysis and digital image processing methods simultaneously for a 7.5km reach of Shalmanrood River of Gilan. The processing of captured images signifies that this technique has an excellent accuracy in estimating the size of sediment particles (particles with a size of d50 or larger) and can be used to estimate Manning’s roughness coefficient of sediment particles of riverbed, utilizing the given empirical formulas. To evaluate the image processing results in estimating Manning’s coefficient values, one-dimensional modeling by HEC-RAS Hydraulic model was used and the model was conducted through different scenarios. Finally, on given cross sections, the comparison of output hydraulic properties with respect to Cowan’s method results showed that Bray’s empirical formula (d90) will have the best efficiency in estimating the Manning’s roughness coefficients in the surface of riverbed, with a maximum relative difference of 13.7% in top width.