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The chapter focuses on the dynamics of groundwater levelsGroundwater level in Xi’an, aiming to evaluate groundwater resources and enhance their utilization. Using groundwater levelGroundwater level monitoring data from 2010 to 2020, this research systematically analyzed the interannual and annual changes in groundwater levelsGroundwater level through statistical analysis methodsMethod. The study investigated two primary factorsFactors influencing groundwater levelGroundwater level dynamics: precipitationPrecipitation and artificial exploitationExploitation, employing mathematical and statistical approaches. Furthermore, prediction modelsModel based on regression analysis and the BP neural networkNetwork methodMethod were developed to forecast groundwater levelGroundwater level trendsTrend and provide a rational frameworkFramework for groundwater development and utilization. Measures and suggestions for groundwater resources management were also proposed in this chapter. The findings indicate an overall decreasing trendTrend in groundwater levelsGroundwater level from 2010 to 2016, followed by a rebounding trendTrend from 2016 to 2020 due to reduced groundwater exploitationExploitation and improved water supply infrastructure. Both precipitationPrecipitation and anthropogenicAnthropogenic exploitationExploitation significantly impact groundwater levelGroundwater level changes in Xi'an, with different landforms exhibiting varying responses to precipitationPrecipitation. Correlation analysis reveals correlation coefficients of 0.673 and 0.843 between precipitationPrecipitation, exploitationExploitation, and groundwater levelsGroundwater level, respectively, indicating a stronger correlation between groundwater exploitationExploitation and water table depth compared to precipitationPrecipitation. The BP neural networkNetwork modelModel demonstrates higher prediction accuracy than the regression modelModel. Based on these modelsModel, the projected average depths of groundwater levelGroundwater level in Xi’an for 2030 are estimated to be 14.778 m and 14.823 m, respectively, indicating a rebound to levels observed a decade ago. Measures on sustainable groundwater resources management in Xi’an are further proposed to ensure a stabilized groundwater levelGroundwater level. These results provide valuable insights for groundwater resource management and sustainable developmentSustainable development in Xi’an.

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Characteristics of Groundwater Level Dynamics in Xi’an (2010–2020) and Groundwater Level Prediction for 2030 Using Regression Analysis and BP Neural Network: Implication to Groundwater Resources Management

  • 章节

  • 发表日期：

    2025年

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  • Junyan Yang,
  • Jianhua Wu,
  • Yan Tian,
  • Xiaomei Kou,
  • Song He

摘要

The chapter focuses on the dynamics of groundwater levelsGroundwater level in Xi’an, aiming to evaluate groundwater resources and enhance their utilization. Using groundwater levelGroundwater level monitoring data from 2010 to 2020, this research systematically analyzed the interannual and annual changes in groundwater levelsGroundwater level through statistical analysis methodsMethod. The study investigated two primary factorsFactors influencing groundwater levelGroundwater level dynamics: precipitationPrecipitation and artificial exploitationExploitation, employing mathematical and statistical approaches. Furthermore, prediction modelsModel based on regression analysis and the BP neural networkNetwork methodMethod were developed to forecast groundwater levelGroundwater level trendsTrend and provide a rational frameworkFramework for groundwater development and utilization. Measures and suggestions for groundwater resources management were also proposed in this chapter. The findings indicate an overall decreasing trendTrend in groundwater levelsGroundwater level from 2010 to 2016, followed by a rebounding trendTrend from 2016 to 2020 due to reduced groundwater exploitationExploitation and improved water supply infrastructure. Both precipitationPrecipitation and anthropogenicAnthropogenic exploitationExploitation significantly impact groundwater levelGroundwater level changes in Xi'an, with different landforms exhibiting varying responses to precipitationPrecipitation. Correlation analysis reveals correlation coefficients of 0.673 and 0.843 between precipitationPrecipitation, exploitationExploitation, and groundwater levelsGroundwater level, respectively, indicating a stronger correlation between groundwater exploitationExploitation and water table depth compared to precipitationPrecipitation. The BP neural networkNetwork modelModel demonstrates higher prediction accuracy than the regression modelModel. Based on these modelsModel, the projected average depths of groundwater levelGroundwater level in Xi’an for 2030 are estimated to be 14.778 m and 14.823 m, respectively, indicating a rebound to levels observed a decade ago. Measures on sustainable groundwater resources management in Xi’an are further proposed to ensure a stabilized groundwater levelGroundwater level. These results provide valuable insights for groundwater resource management and sustainable developmentSustainable development in Xi’an.