Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water er...Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water erosion (rainfall and/or runoff) forces. In fact, K factor is the rate of soil loss per rainfall erosion index unit and affected by 6 parameters including soil primary particles (silt, sand and clay), organic matter content and also permeability and structure of soil. The USLE nomograph is one of the most rapid and common methods for calculating K factor based on mentioned parameters. In this study, 38 samples of surface soil (0 - 15 cm) were collected from Yamchi watershed and the percentage of silt, sand, clay and organic matter content were determined in soil laboratory. Also textures of soil samples were determined to choice soil permeability and structure class codes based on United States Department of Agriculture (USDA) published information. Using USLE nomograph equation, K factor was calculated for each soil sample and based on kriging interpolation method, soil erodibility factor (K) map was constructed for entire study area which average soil erodibility factor and average standard error of interpolated map were 0.442 and 0.0076 t·ha·h·ha-1·Mj-1·mm-1, respectively.展开更多
Modeling and forecasting of the groundwater water table are a major component of effective planning and management of water resources. One way to predict the groundwater level is analysis using a non-deterministic mod...Modeling and forecasting of the groundwater water table are a major component of effective planning and management of water resources. One way to predict the groundwater level is analysis using a non-deterministic model. This study assessed the performance of such models in predicting the groundwater level at Kashan aquifer. Data from 36 piezometer wells in Kashan aquifer for 1999 to 2010 were used. The desired statistical interval was divided into two parts and statistics for 1990 to 2004 were used for modeling and statistics from 2005 to 2010 were used for valediction of the model. The Akaike criterion and correlation coefficients were used to determine the accuracy of the prediction models. The results indicated that the AR(2) model more accurately predicted ground water level in the plains;using this model, the groundwater water table was predicted for up to 60 mo.展开更多
文摘Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water erosion (rainfall and/or runoff) forces. In fact, K factor is the rate of soil loss per rainfall erosion index unit and affected by 6 parameters including soil primary particles (silt, sand and clay), organic matter content and also permeability and structure of soil. The USLE nomograph is one of the most rapid and common methods for calculating K factor based on mentioned parameters. In this study, 38 samples of surface soil (0 - 15 cm) were collected from Yamchi watershed and the percentage of silt, sand, clay and organic matter content were determined in soil laboratory. Also textures of soil samples were determined to choice soil permeability and structure class codes based on United States Department of Agriculture (USDA) published information. Using USLE nomograph equation, K factor was calculated for each soil sample and based on kriging interpolation method, soil erodibility factor (K) map was constructed for entire study area which average soil erodibility factor and average standard error of interpolated map were 0.442 and 0.0076 t·ha·h·ha-1·Mj-1·mm-1, respectively.
文摘Modeling and forecasting of the groundwater water table are a major component of effective planning and management of water resources. One way to predict the groundwater level is analysis using a non-deterministic model. This study assessed the performance of such models in predicting the groundwater level at Kashan aquifer. Data from 36 piezometer wells in Kashan aquifer for 1999 to 2010 were used. The desired statistical interval was divided into two parts and statistics for 1990 to 2004 were used for modeling and statistics from 2005 to 2010 were used for valediction of the model. The Akaike criterion and correlation coefficients were used to determine the accuracy of the prediction models. The results indicated that the AR(2) model more accurately predicted ground water level in the plains;using this model, the groundwater water table was predicted for up to 60 mo.
