Due to the arid and semi-arid climate of Iran and the fact that a large share of the countryʹs water resources are consumed in the agricultural sector, proper management of agricultural water resources through continuous monitoring of soil moisture and water depth of irrigation of fields and gardens is necessary. This study was conducted to eva‎luate the soil moisture and irrigation water depth in the center pivot area of Ghiam agro-livestock company located in the northwest of Isfahan with the help of Landsat 8 satellite images and terrestrial data during the 1399-1400 growing season. For this purpose, simultaneously with the days of satellite passage in the study period, soil moisture sampling was done in 4 shifts at 23 specific points and irrigation water sampling was done in 3 shifts with the help of water collection cans in two radial rows. After sampling the soil and determining their moisture in the laboratory and measuring the water depth with the help of a graduated cylinder, numerical values of LST, NDVI, NDWI and SWI indices were extracted from satellite images and using linear multivariate regression technique as independent variables. Soil moisture and irrigation water depth as dependent variables, soil moisture and irrigation water depth were estimated by stepwise method on different days of satellite imagery. Terrestrial data values were checked. The results showed that among the studied indices, NDVI and SWI indices are more suitable for this purpose. Also, the coefficients of explanation (R2) between the estimated models with the ground moisture sampling values of soil moisture on different sampling days show that the estimated models have a good dependence on the percentage of land covered with vegetation. In addition to the study of regression correlations based on various error statistics, including mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), the accuracy of estimated models for soil moisture and irrigation water depth was eva‎luated. The accuracy of the equations related to soil moisture was eva‎luated and soil moisture maps were prepared on different dates, but despite obtaining appropriate correlation coefficients between irrigation water depth and satellite indicators, due to high error statistics and significant error in estimating irrigation water depth, It was not possible to estimate this parameter with the help of satellite images used in this research. In general, LST, NDVI, NDWI and SWI distance measurement indices can be used with good accuracy to assess soil moisture, especially in the early growing season or in low-density vegetation lands, instead of time-consuming terrestrial measurements.

محمد شايان نژاد، محمد حسن رحيميان

منوچهر حيدرپور، فرشيد نوربخش