Omid Kavoosi; Khaled Ahmadaali; Aliakbar Nazari Samani
Abstract
Soil erosion and its consequences, such as soil destruction at the source, silting of rivers and filling of reservoirs of dams, are one of the most important natural hazards in watersheds, which reduce ecosystem durability. To be one of the most important practical solutions to control sedimentation ...
Read More
Soil erosion and its consequences, such as soil destruction at the source, silting of rivers and filling of reservoirs of dams, are one of the most important natural hazards in watersheds, which reduce ecosystem durability. To be one of the most important practical solutions to control sedimentation and reduce peak flow is to build a check dam. Therefore, determining the quantitative variables affecting the volume of the structure is an important factor in determining the construction costs and their effectiveness. The present study was conducted to model checkdam volumes at the level of 100 sub-basins in different provinces of Iran (Alborz, East Azerbaijan, Ilam, Isfahan, Bushehr, Tehran, Qazvin, Fars, Mazandaran, and Hamadan). The database used for modeling includes 27 environmental features extracted in each of 100 sub-basins and the modeling was done using Genetic Expression Algorithm (GEP). The results of modeling showed that the most important characteristics in estimating the volume of checkdam among the 27 characteristics are: precipitation, temperature, TWI index, shape factor, height difference, concentration time, slope, drainage density and NDVI index. The results of estimating the volume of the structures using the nine selected variables showed that the R2, RRMSE and NSE values for the training phase are .088, .035 and 0.92, respectively, and for the test phase, they are 0.91, 0.29 and 0.91, respectively. Also, based on the results, the characteristics of environmental precipitation can be used with great accuracy to estimate the volume of sediment control structures in a short time, and therefore, before their implementation, the related costs were known in order to prioritize the areas.
