نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار گروه جغرافیا طبیعی دانشکده علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان.
2 دانشجوی سابق کارشناسی ارشد ژئومورفولوژی، دانشگاه اصفهان.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Introduction
Soil is one of the most important natural resource and a place for cultivation. Soil erosion is the main cause of the decline in global available land resources. Water erosion is a major problem because of its socioeconomic impact and the reduction in the agriculture productivity by soil loss, leaching of organic matter, and soil nutrients as well as by reducing water availability and water retention. Quantitative estimates of soil erosion by water are a key component of land-use management plans, which are designed to protect and recover soils. The impact of soil erosion and related sediments decreases dramatically water quality and reservoir capacity in a quantitative and qualitative way. Empirical models such as the Erosion Potential Method (EPM, Flanagan and Nearing 1995), the Modified Pacific Southwest Interagency Committee Model (MPSIAC, Pacific Southwest Interagency Committee 1968 or the most commonly used Universal Soil Loss Equation (USLE, Wischmeier and Smith 1978) and its reviewed version (RUSLE, Renard et al. 1997).Water erosion is one of the most important of soil loss as one type of land degradation and desertification in many part of Iran. In this study we have applied the Revised Universal Soil Loss Equation (RUSLE) model in Alamarvdasht watershed in the south of Fars province in Iran. This study area is actually effect by different type of water erosion (sheet, rill and gullies). In this study we have applied RUSLE model in Alamarvdasht watershed with focus on gully erosion to produce a potential risk map of water erosion for the whole area.
Methodology
Our study area in this research is Alaamarvdasht watershed in south of Fars province. This area is actually effect by different type of water erosion (sheet, rill and gullies). For evaluating the severity of soil loss in our study area we have applied the RUSLE model. The input layers of the this model are, Rainfall erosivity (R-factor) is an index that describes the power of rainfall to cause soil erosion, the soil erodibility index or the K factor is defined as the rate of soil loss, the combined LS-factor describes the effect of topography on soil erosion, C is the cover-management factor, is used to reflect the effect of cropping and management practices on erosion rates and management practice factor (P-factor). The R factor has been prepared by the annual perception from the near climate stations of the study area. For K factor we have collected 23 soil samples from different part of the area and then we have determined the soil texture for each sample in laboratory and in sequence the K-factor for each point have been calculated. We have then interpolated the K-factor for whole the study area (by IDW). For C-factor also we used the Sentinel-2 data for making a LULC for the study area and then for each land use the proper score has been given. LS factor has been prepared from SRTM-30m digital elevation model (DEM) in SAGA-GIS. P-factor in this research because of any soil conservation practice in the study area assume score 1 for the whole of this layer. In the next step, by using resample function in ArcGIS10.8, all the layers have been resampled into 30m resolution then with using the raster calculator we have multiplied all the layers for generate the potential soil erosion map.
Results and Discussion
The results of the final map showed that the largest areas of the study area (54.44 %) is in the category of very high erosion class (more than 75 tons / ha/y), which includes many parts of the northeast, east, and parts of the center and southeast of the study area. While 32.22% of the total area of the basin is in the class of less than 20 tons / ha/y, these areas are mostly located in the low slope and central areas. In the end, due to the weakness of this model in estimating the low amount of erosion in areas with gully erosion, the gully density map was prepared using the Kernel Density function in the Arc GIS10.8. Finally, this map was merged with the water erosion map, and then areas with gully erosion were also classified in severe erosion class. According to the results of this research, it is very necessary to carry out soil protection and watershed management works. The RUSLE model and it combination with the index for assessment of gully erosion can be useful for evaluating of water erosion rate especially in area with deficiency of available data.
Conclusion
Empirical soil erosion models, though relatively simple, are easy to interpret physically, need minimal resources and can be worked out with readily available inputs to precisely the area with high level of soil erosion and degredation. This paper demonstrates the application of empirical soil erosion model such as RUSLE integrated with GIS and Gully density to estimate soil erosion potential and the potential zones in Almarvdasht watershed in south of Iran. The erosion severity map revealed that about 49% of the area comes under high and very high erosion category. The result would help to take appropriate erosion control methods in the severely affected areas. The results acquired from the study can assist in developing management scenarios and provide selections to policy makers for managing soil erosion risks in the most effective method for arrangement of different areas of the study area.
Keywords: Soil erosion, RUSLE model, GIS.
کلیدواژهها [English]
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