عنوان مقاله [English]
Evaluation and investigation of the impact of land use changes in a period of twenty years on the amount of soil erosion in the Shafaroud Basin using the RUSLE model
Soil erosion is a natural process that causes soil loss due to various environmental factors such as weather, soil, topography and vegetation (Obayat et al., 1400). However, human interventions through land use change and agricultural and construction activities can accelerate this flow (Wenker et al., 2019). For this reason, soil erosion caused by land use change has become the most important problem of land degradation all over the world, and the transformation of the land form and the disruption of the main functions of the ecosystem are the consequences of these geomorphic reactions. Therefore, the purpose of this research is to investigate the impact of land use changes in a period of twenty years on the amount of erosion and sedimentation in Shafa Roud basin.
Shafarood watershed is between 48 degrees and 41 minutes to 49 degrees and 6 minutes and 30 seconds from the Greenwich meridian in the eastern hemisphere and between 37 degrees and 25 minutes to 37 degrees and 41 minutes and 30 seconds from the equator and in the northern hemisphere and in It is located in the west of Gilan province and Talash region. The highest peak of this basin called Sharaf in the northwest of the studied area is 2892 meters high, and its lowest point is about 71 meters above the surface of open water.In this research, the data of rain gauge stations nearby and inside the basin were used to analyze the rainfall data. It should be noted that the quality of the data used was checked before entering the statistical analysis stages, and after removing the possible statistical deficiencies and also checking the outliers of the data, it entered the statistical analysis stage. In the processing of satellite images, it is very important to choose the right time of the images taken to prepare the land use map, so in the present study, the multi-temporal images of the Landsat series in cloudless conditions (Bascula et al., 2017) in the middle of June 2011 and 1401 Shamsi (2004 and 2022 AD) was obtained through the United States Geological Survey (USGS) website. Considering the growing season of pasture plants and the timing of planting and harvesting crops, it seems that the images from mid-June are suitable for preparing land use maps. In this research, the information of all the spectral bands of the mentioned images was used for land use classification. Also, in this research, Excel, 5.4 Arc GIS, Archydo and ENVI 5.3 software were used to analyze data and prepare maps. In this research, the RUSLE model was used to estimate the annual average soil erosion. RUSLE model is a function of 6 input factors including rain erosion (R), soil erodibility (K), slope length and degree (LS), vegetation management (C) and conservation operations (P).
In this research, the supervised classification method and the support vector machine classification method, which has high accuracy, were used to monitor the changes that occurred during the 20-year period. The classification accuracy of both images was evaluated with the Kappa index and overall accuracy, and according to the research of Mather (2005), the results of the current research are statistically acceptable. Based on the results of the classification accuracy in the two images, the classification accuracy in the order of the date of receiving the image had an increasing trend, which is due to the up-to-date information of the region for the 2022 image and the possibility of direct access to the current land use in the region for selecting educational samples. It was natural. In addition, the accuracy obtained in both images is acceptable and shows the high ability of Landsat images to prepare land use maps with acceptable accuracy, which is in line with the research results (Sengari and Broumand, 2013; El Kawi et al., 2011). Correspond. Of course, it should be noted that the high accuracy of classification is not the only result of the implementation of the classification process, in addition to these cases, the collection of educational samples with appropriate distribution and number at the basin level has played a significant role in improving the classification process. In general, the accuracy of the results obtained from the two images had similar results for all applications, which can be attributed to the collection of suitable educational samples and the simultaneous date of the collection of the two images (June). The results of the survey of land use changes during 20 years in the region showed (Table 3), agricultural lands and pastures have decreased in the region. The reason for this can be related to the droughts of recent decades in the region and also the decrease in the level of underground water tables, which has reduced the amount of water available to farmers. This result is in line with the research results (Sultanian et al., 2013), but it is against the research results (Nazari Samani et al., 2006 and Rajesh and Yoji, 2006) that the agricultural land has decreased in a period, of course, It seems that the reduction of agricultural lands in his research was due to the increase of residential constructions in the agricultural lands of the region. On the other hand, the level of residential land in the region has increased, which seems natural due to the increase in population in the region and new construction in the villages. The obtained results show that the amount of erosion in 2011 varies from -0.84 to 5.63 tons per hectare per year and in 1401 from -1.33 to 8.37 tons per hectare per year. These results show that the amount of erosion in This basin has increased slightly in 20 years.
The obtained results show that the amount of erosion in 2011 varies from -0.84 to 5.63 tons per hectare per year and in 1401 from -1.33 to 8.37 tons per hectare per year. These results show that the amount of erosion in This basin has increased slightly in 20 years.