Spatial estimation of water-table depth by artificial neural networks in light of ancillary data

Proper estimation of the spatial distribution of water-table depth is highly important in most groundwater studies. Groundwater depth is measured at specific and limited points and it is estimated for other parts using spatial estimation methods. In this study, two multivariate methods, artificial neural network (ANN) and multiple linear regression (MLR), are examined to estimate water-table depth in an unconfined aquifer located in Shibkooh, Iran. The different ancillary data, including spatial coordinates, digital elevation model (DEM), aquifer bed elevation, specific resistivity and aquifer thickness were used to improve estimates based on these methods. It was proved that performance of the ANN surpasses that of the MLR method. Using the spatial coordinates, the aquifer bed elevation and aquifer thickness resulted in the optimum spatial estimation of the water-table depth. These parameters, directly or indirectly, affect the water-table depth estimation through techniques such as ANN capable of modelling of nonlinear relationships.     

Investigating effects of land use change scenarios on soil erosion using CLUE-s and RUSLE models

Predicting soil erosion change is an important strategy in watershed management. The objective of this research was to evaluate land use change effects on soil erosion in the north of Iran using five land use scenarios. Three land use maps were created for a period of 25 years (1986–2010) to investigate land use transition and to simulate land use for the year 2030. Additionally, the RUSLE model was used to estimate erosion and the effect of land use change. The results showed that CLUE-s is suitable for modeling future land use transition using ROC curve. The median soil loss in the basis period was 104.52 t ha^?1 years^?1. Results indicate that the range of soil loss change is 2–32% in simulated period and soil loss value was higher than basis period in all scenarios. Thirty percent decrease in demand scenario has the lowest soil loss in simulated period, and the soil loss value under this scenario will be only 2% more than the basis period. Thus, the soil conversion effects resulted from the demand of each land use.     

Compilation simulation of surface water and groundwater resources using the SWAT-MODFLOW model for a karstic basin in Iran

Modeling of karstic basins can provide a better understanding of the interactions between surface water and groundwater, a more accurate estimation of infiltrated water amount, and a more reliable water balance calculation. In this study, the hydrological simulation of a karstic basin in a semiarid region in Iran was performed in three different stages. In the first stage, the original SWAT model was used to simulate surface-water flow. Then, the SWAT-MODFLOW conjunctive model was implemented according to the groundwater characteristics of the study area. Finally, due to the karstic characteristics of the region and using the CrackFlow (CF) package, the SWAT-MODFLOW-CF conjunctive model was developed to improve the simulation results. The coefficient of determination (R²) and the Nash-Sutcliffe efficiency coefficient (NSE) as error evaluation criteria were calculated for the models, and their average values were 0.63 and 0.57 for SWAT, 0.68 and 0.61 for SWAT-MODFLOW, 0.73 and 0.7 for SWAT-MODFLOW-CF, respectively. Moreover, the mean absolute error (MAE) and root mean squared error (RMSE) of the calibration for groundwater simulation using the SWAT-MODFLOW model were 1.23 and 1.77 m, respectively. These values were 1.01 and 1.33 m after the calibration of the SWAT-MODFLOW-CF model. After modifying the CF code and keeping the seams and cracks open in both dry and wet conditions, the amount of infiltrated water increased and the aquifer water level rose. Therefore, the SWAT-MODFLOW-CF conjunctive model can be proposed for use in karstic areas containing a considerable amount of both surface water and groundwater resources.

     

Adsorption of Cd ions from aqueous solutions by iron modified pomegranate peel carbons: kinetic and thermodynamic studies

The experimental conditions for preparation of pomegranate peel carbon and Fe(III) modified pomegranate peel carbon were studied. The effects of main experimental parameters on carbon preparation such as carbonization time, carbonization temperature and Fe(III) impregnation ratio in pomegranate peel were investigated. The prepared carbons in various conditions were characterized by consideration of the production yield, ash content, iodine number, pH of zero point charge and their ability for adsorption of methylene blue. After preparation of carbons, their efficiency for removal of Cd²⁺ species from aqueous solution was investigated. The effect of experimental parameters such as Cd²⁺ initial concentration, pH of solution and contact time was studied by batch adsorption experiments. The fitting of experimental data in thermodynamic isotherms matched the linear results with Langmuir and Freundlich isotherms. The adsorption capacity for Cd²⁺ species on Fe(III) modified pomegranate peel carbon was 22.72 mg/g and the adsorption kinetic presented the pseudo-second-order kinetic model.