Although Dehui City has excellent agricultural conditions, long-term large-scale over-cultivation and human activities in recent years have caused significant changes in the local groundwater chemical characteristics. This study analyzes the causes, evolution, and prediction of groundwater chemistry via multi-disciplinary theoretical cross-cutting methods, such as groundwater ion composition-ratio analysis and groundwater influencing factor analysis, and artificial neural networks. The lithological characteristics of the groundwater aquifer were combined with ion composition-ratio mapping to explore the cause of groundwater chemistry composition in the study area. Piper three-line diagrams and Gibbs diagrams were used to analyze the evolution characteristics and influencing factors of groundwater chemistry in the study area. Based on these data, time series predictions were made for hydrochemical data. The results demonstrate that the chemical origins of groundwater in the study area are mainly background stratum and cation exchange, influenced by human activities. The main factors of groundwater chemical characteristics have changed from rock weathering to evaporation/precipitation in the past two decades. The hydrochemical characteristics changed from secondary alkalinity to secondary salinity. The predicted data from long short-term memory neural networks indicated that groundwater would continue salinization without the changes in the conditions, leading to land degradation in the study area.
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