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Spatiotemporally non-stationary evolution of groundwater levels in Poyang Lake Basin driven by meteorological and hydrological factors.
Liu, Yu; Lu, Chengpeng; Qiu, Baozhong; Wang, Jianliang; Chen, Jing; Zhang, Yong; Wu, Chengcheng; Liu, Bo; Shu, Longcang.
Afiliação
  • Liu Y; College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China.
  • Lu C; College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China. Electronic address: luchengpeng@hhu.edu.cn.
  • Qiu B; Pinghu City Hydrology Station, Jiaxing 314200, Zhejiang, China.
  • Wang J; Pinghu City Hydrology Station, Jiaxing 314200, Zhejiang, China.
  • Chen J; Hydrology Bureau of Jiangxi Province, Nanchang 330000, Jiangxi, China.
  • Zhang Y; Department of Geological Sciences, University of Alabama, Tuscaloosa, AL 35487, USA. Electronic address: yzhang264@ua.edu.
  • Wu C; College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China.
  • Liu B; College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China.
  • Shu L; College of Hydrology and Water Resources, Hohai University, Nanjing 210098, Jiangsu, China.
Sci Total Environ ; 950: 175244, 2024 Nov 10.
Article em En | MEDLINE | ID: mdl-39111440
ABSTRACT
The complex relationship between wet-dry transition in the Poyang Lake basin and groundwater storage significantly affects the lake's hydrology, downstream ecological state, and overall security along the Yangtze River in China. There is, however, a notable lack of systematic exploration into how various factors drive spatiotemporal variability in groundwater level (GWL). Using local indicators of spatial association (LISA), spatial non-stationarity models, and multi-source data, our analysis explores the spatial distribution of GWL and quantifies the influence of driving factors on its spatiotemporal non-stationarity at annual and monthly scales. We also compare driving factor contributions in hilly, plain, and local areas within the Poyang Lake basin. Our findings reveal significant local clustering of GWL, indicating substantial spatial autocorrelation and geographic heterogeneity in GWL. Influencing factors exhibit non-stationary effects on GWL at spatial and temporal scales, with precipitation (P), ground surface elevation (GSE), and soil moisture (SM) being primary contributors, generally exerting positive effects. SM contributes most during dry years and normal periods. P and the Palmer Drought Severity Index (PDSI) have greater impacts in hilly areas, while GSE shows the opposite trend. Rainfall is a source of groundwater recharge, with a lagged response observed in GWL to rainfall in this basin. The lag time is about 1-2 months. Evapotranspiration is not the dominant discharge pathway. The decrease in GWL during the dry season is mainly due to reduced precipitation recharge and increased lateral groundwater discharge from areas of high hydraulic head to areas of low hydraulic head.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Total Environ Ano de publicação: 2024 Tipo de documento: Article