基于多源数据的吉木萨尔县地下水位动态变化与驱动因素定量识别

    Quantitative Identification of Dynamic Changes and Driving Factors of Groundwater Level in Jimsar County based on Multi-source Data

    • 摘要: 地下水位控制指标是水资源刚性约束制度要建立的一系列硬指标之一,系统识别地下水位动态变化特征及其主控因子,是科学合理地确定地下水位控制指标的重要基础。以吉木萨尔县平原区为例,基于2003—2023年地下水位监测数据、气象、径流、土地利用及人类活动强度等多源数据,采用克里金插值法和趋势分析法识别地下水位时空变化特征,采用小波相干分析、双变量空间自相关以及人类活动强度指数法揭示地下水位变化原因,并采用地理探测器量化各影响因素贡献度。结果表明:1)吉木萨尔县平原区地下水位年内动态变化特征以开采型为主,多年地下水位变化总体呈波动下降趋势,其中2003—2008年呈波动变化,2009—2014年显著下降,2015—2017年呈上升趋势,2018—2023年又转为下降趋势;2)在不同时间尺度下地下水位变化与降水量和径流量均存在显著共振周期和时滞效应,共振周期范围为10~14月,呈显著正相关关系,位相角范围在0°~60°,地下水位变化较降水与径流变化滞后0~2个月;3)2003—2023年,随着耕地面积逐渐扩大,人类活动高强度区域呈现扩张趋势,人类活动强度与地下水位变化存在明显的局部空间自相关关系;4)地下水位动态变化主要受地表径流、人类活动、降水、土地利用等因素影响,其交互作用对地下水位动态变化的影响更显著。研究成果有助于深化干旱区地下水系统动态响应机制的理解,为区域实现地下水管控指标的制定与可持续开发利用提供理论支撑与技术依据。

       

      Abstract: This study focuses on systematically investigating the dynamic characteristics of groundwater level changes and quantifying their dominant controlling factors in the plain area of Jimsar County, a research topic of great significance for arid and semi-arid regions where groundwater serves as a critical water supply source. Such an investigation is fundamental to scientifically and rationally determining groundwater level control indicators, which are core components of the national rigid water resources constraint system aimed at regulating sustainable water use. To achieve this research objective, the plain area of Jimsar County was explicitly designated as the study area, and a comprehensive set of multi-source data were integrated for in-depth analysis, including long-term groundwater level monitoring data spanning 2003 to 2023, detailed meteorological data (e.g., precipitation and temperature), surface runoff data, land use/land cover change data, and human activity intensity evaluation data. Specifically, Kriging interpolation was utilized to map the spatial distribution of groundwater levels, while trend analysis was applied to capture the temporal evolution patterns, thereby comprehensively characterizing the spatiotemporal variations of groundwater level; wavelet coherence analysis was employed to explore the time-frequency correlation between groundwater level changes and hydrometeorological factors, bivariate spatial autocorrelation was used to examine the spatial coupling relationship between human activities and groundwater level variations, and the human activity intensity index method was adopted to assess the degree of human disturbance, collectively revealing the driving mechanisms of groundwater level changes; additionally, a geographical detector model was applied to quantify the individual and interactive contribution of each influencing factor to groundwater level dynamics. The results indicated that the intra-annual dynamic variation of groundwater level in the study area was predominantly dominated by an exploitation-driven pattern, closely associated with the seasonal characteristics of agricultural irrigation. Meanwhile, the long-term groundwater level showed an overall fluctuating downward trend, which could be clearly divided into four distinct stages: a relatively stable fluctuating variation stage (2003–2008), a rapid and significant decline stage (2009–2014), a slight recovery and upward trend stage (2015–2017), and a reversion to a gradual downward trend stage (2018–2023). Across different time scales, significant resonance periods (ranging from 10 to 14 months) and obvious time-lag effects were observed between groundwater level changes and precipitation/runoff, presenting a significant positive correlation; the phase angle ranging from 0° to 60° further suggested that groundwater level changes lagged behind precipitation and runoff changes by approximately 0–2 months. From 2003 to 2023, with the gradual expansion of cultivated land area driven by agricultural development, regions with high-intensity human activities showed a continuous expansion trend, and a distinct local spatial autocorrelation existed between human activity intensity and groundwater level changes, indicating a strong spatial coupling between human disturbance and groundwater evolution. Additionally, the dynamic changes of groundwater level were mainly influenced by multiple factors including surface runoff, human activities, precipitation, and land use types; notably, the interactive effects of these factors exerted a more significant synergistic impact on groundwater level dynamics compared to their individual effects. The findings of this study not only contribute to deepening the understanding of the dynamic response mechanisms of groundwater systems in arid areas but also provide important theoretical support and practical technical references for formulating scientific and reasonable regional groundwater control indicators and realizing the long-term sustainable development and utilization of groundwater resources.

       

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