عنوان مقاله [English]
Classification is one of the most important methods of extracting information from digital satellite images, and today image classification using object-oriented processing using various techniques is widely used. In this research, the object-oriented method in preparing the land use map of Darrehrood catchment area using Landsat 5 images with TM sensor and Landsat 8 with OLI sensor in a period of 30 years, from 1990 to 2019 and its effects on Changes in the discharge of the Darrehrood River were examined. Landsat satellite images are atmospherically corrected with Envi5.3 software and in ecognition software by object-oriented method and nearest neighbor technique using four spectral indices (NDVI, GVMI, EVI, CIG) and average bandwidth characteristics and luminosity characteristics. The image and shape of the objects The images were classified into fourteen classes and the land use of the basin was extracted in the two periods of 1990 and 2019. Object-oriented classification with a kappa coefficient of 93% and based on the overall classification accuracy of 0.9235, The result of the classification by object-oriented method is more accurate and the classification accuracy is at an acceptable level, which among the parameters that were considered to achieve this accuracy can be parameters such as, class neighborhood, band values and Use of spectral indices used to separate units and the number of repetitions of classification operations. According to the changes in the area of the classrooms in the 30-year dimension, it was found that most of the uses are primarily related to the rangeland class, which occupies an area of approximately 1391.42 square kilometers. Then, the use of rainfed and fallow agriculture with an area of 850.55 square kilometers and barren lands with an area of 665.40 square kilometers are the most common areas. These land uses have the most areas in 2019, with the difference that the land use of the rangeland has an area of 1137.06 square kilometers and dryland agriculture has an area of 1013.08 square kilometers, and barren lands have been reduced to an area of/2015 / 35 square kilometers, and instead the area Irrigation has increased from 45.69 to 387.82 square kilometers. Gardens and forests in 1990 occupied an area of 59.79 and 8.78 square kilometers, respectively. In 2019, garden lands will increase to 65.50 square kilometers and forest lands will decrease to 5.49 square kilometers. Increasing the residential land area compared to 1990 has been associated with a decrease in rangelands, which indicates the destruction of rangelands and the creation of residential areas. Eastern was prepared. Rainfall histogram method was used to enter the data into the model. In order to evaluate the land use change in the runoff of Darrehrood catchment in HEC-HMS model, SCS method was used which was implemented in HEC_HMS model and Darrehroud catchment was divided into four sub-basins of Mashiran, Horand, Sambor and Buran and then in the environment. ArcGis software was drawn digitally and the physical properties of the basin and sub-basins were used as parameters required in the present study. Using the SCS method, a soil hydrology group map is required to estimate the CN curve number. Therefore, the map of soil hydrology groups was prepared by the Natural Resources Organization of East Azerbaijan Province to be used to calculate the CN curve number. According to land use in 1990 and 2019, the CN curve number and runoff delay time of sub-basins along with K and X coefficients were introduced to the model and implemented. In Buran sub-basin, there will be a decrease in water permeability and consequently a decrease in initial rainfall losses and an increase in runoff, while in Mashiran, Horand and Sambor sub-basins, a decrease in water permeability and an increase in initial rainfall losses and a decrease in rainfall will decrease. Runoff will be observed. The result of these changes on the runoff of the basin was obtained using the HEC_HMS model. In Darrehrood catchment simulation in HEC_HMS model, calibration of the basin in four sub-basins was calibrated based on runoff peak and runoff height and runoff volume per year. The calculated results with the observed results on average in the runoff height element of 93.15 Percentage and in the runoff peak element 94.35% and in the runoff volume element 94.95% show the correspondence of the correct implementation of the model on the basin, which includes the acceptability of the results (the results showed that the runoff peak in the sub-basin of Mashiran with Reduction of 7 cubic meters and reduction of 8.5 mm of runoff volume in Horand sub-basin with reduction of 8.6 cubic meters of runoff peak and reduction of 12 mm of runoff volume and sub-basin of Sambor with reduction of 2.2 cubic meters of runoff peak and reduction of 12 mm of runoff volume While in the Buran basin, unlike the previous three sub-basins, the increase of runoff peak by 10 cubic meters per second and the increase of runoff volume by 9.6 mm has been estimated.