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Modified DRASTIC model for groundwater vulnerability to nitrate contamination in the Dagujia river basin, China
Due to rapid economic growth and over-exploitation of groundwater, nitrate pollution in groundwater has become very serious. The main objective of this study is to modify the DRASTIC model to identify groundwater vulnerability to nitrate pollution. The DRASTIC model was firstly used to analyze the intrinsic vulnerability. The DRASTIC model with the inclusion of a land-use factor (DRASTIC-LU) was put forward to map the specific vulnerability of groundwater. Furthermore, the support vector machine (SVM) was introduced to avoid the drawback of the overlay and index methods, and the improved integrated models of DRASTIC + SVM and DRASTIC-LU + SVM were built. Moreover, 103 groundwater samples were collected for building and validating the models. The Root Mean Squared Error (RMSE) of DRASTIC, DRASTIC-LU, DRASTIC + SVM, and DRASTIC-LU + SVM was found to be 0.853, 0.755, 0.631, and 0.502, respectively. The model DRASTIC-LU was more precise than the original one. The results also showed that the integrated model using SVM exhibited better correlation between the vulnerability value and the nitrate pollution. The study indicated that the modified models including the land-use factor as well as SVM in the DRASTIC model were more suitable to assess the groundwater vulnerability to nitrate. HIGHLIGHTS The improved DRASTIC-LU model was put forward to delineate groundwater specific vulnerability.; Support vector machine was introduced to further build the novel integrated model to analyze the intrinsic and specific vulnerability of groundwater.;
Modified DRASTIC model for groundwater vulnerability to nitrate contamination in the Dagujia river basin, China
Due to rapid economic growth and over-exploitation of groundwater, nitrate pollution in groundwater has become very serious. The main objective of this study is to modify the DRASTIC model to identify groundwater vulnerability to nitrate pollution. The DRASTIC model was firstly used to analyze the intrinsic vulnerability. The DRASTIC model with the inclusion of a land-use factor (DRASTIC-LU) was put forward to map the specific vulnerability of groundwater. Furthermore, the support vector machine (SVM) was introduced to avoid the drawback of the overlay and index methods, and the improved integrated models of DRASTIC + SVM and DRASTIC-LU + SVM were built. Moreover, 103 groundwater samples were collected for building and validating the models. The Root Mean Squared Error (RMSE) of DRASTIC, DRASTIC-LU, DRASTIC + SVM, and DRASTIC-LU + SVM was found to be 0.853, 0.755, 0.631, and 0.502, respectively. The model DRASTIC-LU was more precise than the original one. The results also showed that the integrated model using SVM exhibited better correlation between the vulnerability value and the nitrate pollution. The study indicated that the modified models including the land-use factor as well as SVM in the DRASTIC model were more suitable to assess the groundwater vulnerability to nitrate. HIGHLIGHTS The improved DRASTIC-LU model was put forward to delineate groundwater specific vulnerability.; Support vector machine was introduced to further build the novel integrated model to analyze the intrinsic and specific vulnerability of groundwater.;
Modified DRASTIC model for groundwater vulnerability to nitrate contamination in the Dagujia river basin, China
2021
Article (Journal)
Electronic Resource
Unknown
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