地下水
地下水补给
含水层
水文学(农业)
环境科学
地下水模型
地下水流
地质统计学
水文地质学
水文模型
水流
比例(比率)
空间变异性
空间生态学
地下水流
降水
地质学
流域
气候学
地理
岩土工程
气象学
统计
生态学
数学
地图学
生物
作者
Xiaomei Fan,Gwynn R. Johnson,Jun Xu,Gaohuan Liu
标识
DOI:10.1061/jhyeff.heeng-5701
摘要
Analysis of the various hydrologic features responsible for the spatial and temporal variability in large scale subsurface systems is a critical component of water resources engineering and management. Traditionally, modeling large-scale groundwater flow patterns includes simulations with underlying parameter estimations and associated overarching assumptions. More recently, subsurface hydrologists are using empirical orthogonal function analysis to separate and quantify the primary hydrologic components contributing to observed regional and local-scale groundwater hydrodynamics. In this case study, modern spatiotemporal geostatistics plus primary hydrologic component analysis were conducted on spatially and temporally distributed groundwater levels measured in the Yellow River Delta. The results demonstrate the significant interplay between surface water hydrodynamics, overall groundwater quality, and groundwater utilization at the local scale, plus the significant impact of regional-scale aquifer recharge on groundwater level seasonal variation, largely driven by precipitation events. With increased accessibility to remote sensing data, additional research using these or similar statistical approaches to interpolate, compress, and decompose those features driving subsurface fluid-flow variability will prove to be highly beneficial to water resource engineers and managers.
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