SPATIOTEMPORAL CHARACTERISTICS OF GROUNDWATER DEPTH IN XINGTAI CITY ON THE NORTH CHINA PLAIN: CHANGING PATTERNS, CAUSES AND PREDICTION

作者：Rui Cao, Rengui Jiang, Yong Zhao, Jiancang Xie, Xiang Yu · 发表于：Applied Ecology and Environmental Research · 年份：2020 · DOI：10.15666/aeer/1805_66056622 · 被引用次数：6 · 研究领域：Hydrology and Watershed Management Studies、Flood Risk Assessment and Management、Remote Sensing and Land Use

The analysis of spatiotemporal characteristics for groundwater depth can provide a theoretical basis for comprehensive management of groundwater and sustainable development of ecology and environment. The paper investigated the changing patterns of groundwater depth, and further explored the linear and nonlinear relationships between groundwater depth and four potential influencing factors using grey relational analysis and wavelet coherence during 2000-2017. The multiple linear regression and Random Forest (RF) models were proposed to predict the groundwater depth. Taking Xingtai city on the North China Plain as an example, the results indicate that: (1) The groundwater depth in a shallow aquifer has deepened significantly after 2006, and decreased from northwest to southeast. A clear upward trend was detected in the southeast region of the study area. (2) The change of groundwater depth is related to the consumption during agricultural irrigation period and the supply of heavy rainfall during flood season, and the deepest groundwater depth was detected in June. (3) The cross-correlation analysis demonstrated that main influencing factors of groundwater depth are precipitation and temperature. (4) The comparison between actual value and prediction value indicated that the RF model has better accuracy in predicting the groundwater depth than the multiple linear regression model.