Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method. 相似文献
Since incorrect site selection has sometimes led to the failure of artificial recharge projects,it is necessary to increase the effectiveness of such projects and minimize their failure by employing new techniques.Therefore,the present research used a combination of decision-making models,numerical groundwater modeling and clustering technique to determine suitable sites for implementation of an artificial recharge project.This hybrid approach was employed for the Yasouj aquifer located in southwestern Iran.In the first stage,by employing an AHP decision-making model,hydraulic conductivity,specific yield,slope,land use,depth to groundwater,and aquifer thickness were selected from 21 criteria used in previous research.The selected criteria were then entered as input into the classical k-means clustering model.Using the output,aquifer was divided into seven different regions or clusters.These clusters were then matched with the land use map,and some of the abandoned land areas were selected as the final option for implementing the artificial recharge project.Finally,the MODFLOW code in the GMS software was used to simulate the groundwater level and cluster the sites selected,with regards to increase in groundwater level.Results indicated that the most significant increases in groundwater level(43 and 27 cm) were those of Clusters 2 and 6 in the northern and western parts of the aquifer,respectively.Therefore,this approach can be used in other similar aquifers in arid and semi-arid regions to select the best sites for artificial recharge and to prevent loss of floodwaters. 相似文献
The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon rank-sum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77 %, while it was 37 % before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version. 相似文献
Natural Hazards - Many landslides occur in the Karun watershed in the Zagros Mountains. In the present study, we employed a novel comparative approach for spatial modeling of landslides given the... 相似文献
Groundwater management has a prominent role in the world especially in arid and semi-arid areas which have a shortage of water, and due to this serious problem, many researchers work on that for prevention and managing the water recourses to conserve and monitor sources. DRASTIC index can be put forward for estimating of groundwater vulnerability to such pollution. The main purpose of using the groundwater vulnerability model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, disregarding the effects of pollution type and characteristics. Thus, this technique must be standardized and approved for Kerman plain. Vulnerability evaluation to explain areas that are more vulnerable to contamination from anthropogenic sources has become a prominent element for land use planning and tangible resource management. This contribution aims at evaluating groundwater vulnerability by applying the DRASTIC index as well as employ sensitivity analyses to evaluate the comparative prominent of the model parameters for groundwater vulnerability in Kerman plain in the southeastern part of Iran. Moreover, the potential of vulnerability to pollution is more accurately assessed by optimizing the weights of the DRASTIC parameters with the single-parameter sensitivity analysis (SPSA). The new weights were calculated. The result of the study revealed that the DRASTIC-Sensitivity analysis exhibit more efficiently than the traditional method for a nonpoint source pollution. Observation of ultimate nitrate showed the result of DRASTIC-SPSA has more accuracy. The GIS method offers an efficient environment for carrying out assessments and greater capabilities for dealing with a huge quantity of spatial data. 相似文献
Relying on the conceptual DPSIR framework and MODFLOW analysis,this study used a mixed approach to produce groundwater resource management solutions for the Najafabad area in central Iran.According to DPSIR results,agricultural activities put the highest pressure on groundwater resources in this region.The results showed the effectiveness of reducing water withdrawal over 30 years in maintaining the aquifer in a state of equilibrium.The best scenario consisted of cutting down extraction by 10% over the said period.Output maps of the water table rise at the Najafabad aquifer clearly showed that the groundwater management scenario involving a 10% reduction of water withdrawal was the most effective solution,as it would raise the water level by 6.7 m.Regarding other scenarios,reducing cultivated area by 20% was found to raise the water table by 5.03 m on average,while cutting down water withdrawal by 5% increased the water table by 3.6 m,and a 10% reduction of the cultivated area resulted in a 1.85 m rise.The combined model proposed here can be used for similar aquifers and can aid decision-makers and managers. 相似文献
The main objective of this study is to integrate adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM) and artificial neural network (ANN) to design an integrated supervised committee machine artificial intelligence (SCMAI) model to spatially predict the groundwater vulnerability to seawater intrusion in Gharesoo-Gorgan Rood coastal aquifer placed in the northern part of Iran. Six hydrological GALDIT parameters (i.e., G groundwater occurrence, A aquifer hydraulic conductivity, L level of groundwater above sea level, D distance from the shore, I impact of the existing status of seawater intrusion in the region, and T thickness of the aquifer) were considered as inputs for each model. In the training step, the values of GALDIT’s vulnerability index were conditioned by using the values of TDS concentration in order to obtain the conditioned vulnerability index (CVI). The CVI was considered as the target for each model. After training the models, each model was tested using a separate TDS dataset. The results indicated that the ANN and ANFIS algorithms performed better than the SVM algorithm. The values of correlation were obtained as 88, 87, and 80% for ANN, ANFIS, and SVM models, respectively. In the testing step of the SCMAI model, the values of RMSE, R2, and r were obtained as 6.4, 0.95, and 97%, respectively. Overall, SCMAI model outperformed other models to spatially predicting vulnerable zones. The result of the SCMAI model confirmed that the western zones along the shoreline had the highest vulnerability to seawater intrusion; therefore, it seems critical to consider emergency protection plans for study area.