The changes of development and utilization of karst groundwater in Sangu Spring Basin have made the original groundwater resource evaluation unable to meet the needs of future economic development.Based on analysis of...The changes of development and utilization of karst groundwater in Sangu Spring Basin have made the original groundwater resource evaluation unable to meet the needs of future economic development.Based on analysis of existing data,combined with the characteristics of supplement,runoff and draining of regional karst groundwater,the Visual Modelflow software was used to build a numerical simulation model of Sangu spring Basin.The amount of karst groundwater resource and groundwater environment of the Basin were evaluated under different exploitation schemes,and the changes of karst groundwater environment in the future ten years were also predicted.The fitting error which is less than 0.5 m between the calculated value and measured value of the water level in the fitted borehole accounts for 93%.For the lithologically and structurally complex Sangu Spring Basin,the fitting effect of numerical simulation model was ideal.On the basis of the current mining amount of 111.80 million m3/a,the total redistributed exploited amount in the spring region was 61.79 million m3/a.Under the condition that the quantity of recoverable resources reached 173.59 million m3/a and under different precipitation schemes,all constraint conditions were satisfied,such as regional water level drawdown,maximum allowable water level drawdown in every simulated water source area and the flow rate of Guobi Spring.The results will provide a scientific basis for the rational development and utilization of karst groundwater in Sangu Spring Basin.展开更多
Grain-size distribution data,as a substitute for measuring hydraulic conductivity(K),has often been used to get K value indirectly.With grain-size distribution data of 150 sets of samples being input data,this study c...Grain-size distribution data,as a substitute for measuring hydraulic conductivity(K),has often been used to get K value indirectly.With grain-size distribution data of 150 sets of samples being input data,this study combined the Artificial Neural Network technology(ANN)and Markov Chain Monte Carlo method(MCMC),which replaced the Monte Carlo method(MC)of Generalized Likelihood Uncertainty Estimation(GLUE),to establish the GLUE-ANN model for hydraulic conductivity prediction and uncertainty analysis.By means of applying the GLUE-ANN model to a typical piedmont region and central region of North China Plain,and being compared with actually measured values of hydraulic conductivity,the relative error ranges are between 1.55%and 23.53%and between 14.08%and 27.22%respectively,the accuracy of which can meet the requirements of groundwater resources assessment.The global best parameter gained through posterior distribution test indicates that the GLUEANN model,which has satisfying sampling efficiency and optimization capability,is able to reasonably reflect the uncertainty of hydrogeological parameters.Furthermore,the influence of stochastic observation error(SOE)in grain-size analysis upon prediction of hydraulic conductivity was discussed,and it is believed that the influence can not be neglected.展开更多
基金This work was supported by the Fundamental Research Funds for the Chinese Academy of Geosciences(No.JYYWF20180401)the China Geological Survey project(No.DD20160296,DD20201123).
文摘The changes of development and utilization of karst groundwater in Sangu Spring Basin have made the original groundwater resource evaluation unable to meet the needs of future economic development.Based on analysis of existing data,combined with the characteristics of supplement,runoff and draining of regional karst groundwater,the Visual Modelflow software was used to build a numerical simulation model of Sangu spring Basin.The amount of karst groundwater resource and groundwater environment of the Basin were evaluated under different exploitation schemes,and the changes of karst groundwater environment in the future ten years were also predicted.The fitting error which is less than 0.5 m between the calculated value and measured value of the water level in the fitted borehole accounts for 93%.For the lithologically and structurally complex Sangu Spring Basin,the fitting effect of numerical simulation model was ideal.On the basis of the current mining amount of 111.80 million m3/a,the total redistributed exploited amount in the spring region was 61.79 million m3/a.Under the condition that the quantity of recoverable resources reached 173.59 million m3/a and under different precipitation schemes,all constraint conditions were satisfied,such as regional water level drawdown,maximum allowable water level drawdown in every simulated water source area and the flow rate of Guobi Spring.The results will provide a scientific basis for the rational development and utilization of karst groundwater in Sangu Spring Basin.
基金This study was supported by Key Laboratory of Groundwater Sciences and Engineering,Ministry of Natural Resources(MNR)and the China Geological Survey project(No.DD20190252).
文摘Grain-size distribution data,as a substitute for measuring hydraulic conductivity(K),has often been used to get K value indirectly.With grain-size distribution data of 150 sets of samples being input data,this study combined the Artificial Neural Network technology(ANN)and Markov Chain Monte Carlo method(MCMC),which replaced the Monte Carlo method(MC)of Generalized Likelihood Uncertainty Estimation(GLUE),to establish the GLUE-ANN model for hydraulic conductivity prediction and uncertainty analysis.By means of applying the GLUE-ANN model to a typical piedmont region and central region of North China Plain,and being compared with actually measured values of hydraulic conductivity,the relative error ranges are between 1.55%and 23.53%and between 14.08%and 27.22%respectively,the accuracy of which can meet the requirements of groundwater resources assessment.The global best parameter gained through posterior distribution test indicates that the GLUEANN model,which has satisfying sampling efficiency and optimization capability,is able to reasonably reflect the uncertainty of hydrogeological parameters.Furthermore,the influence of stochastic observation error(SOE)in grain-size analysis upon prediction of hydraulic conductivity was discussed,and it is believed that the influence can not be neglected.
