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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 the dynamic changes and driving factors of groundwater level in Jimsar County based on multi-source data

  • 摘要: 地下水位控制是水资源刚性约束硬指标之一,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。为探究吉木萨尔县平原区地下水动态并定量识别其驱动因素,该研究基于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年呈下降趋势,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共振周期和时滞效应,共振周期范围为10~14个月,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大。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: Groundwater level driving factors are the most important components of the national water resources in modern agriculture. Sustainable water use can be expected to regulate in the arid and semi-arid regions. In this study, a systematic investigation was implemented on the dynamic characteristics of the groundwater level. Their controlling factors were also quantified after optimization. The groundwater serves as a critical water supply source. The study area was designated as the plain area of Jimsar County, Changji Hui Autonomous Prefecture, Xinjiang, China. A multi-source dataset was integrated, including the long-term groundwater level monitoring from 2003 to 2023, meteorological data (e.g., precipitation and temperature), surface runoff, land use/land cover change, and human activity intensity evaluation. Specifically, the Kriging interpolation was utilized to map the spatial distribution of the groundwater levels. While the trend analysis was applied to capture the temporal evolution patterns, thereby characterizing the spatiotemporal variations of the groundwater level, Wavelet coherence analysis was employed to explore the time-frequency correlation between groundwater level and hydrometeorological factors. Bivariate spatial autocorrelation was used to examine the spatial coupling relationship between human activities and groundwater level variations. The human activity intensity index was adopted to assess the degree of human disturbance. There were the driving mechanisms of the groundwater level. Additionally, a geographical detector model was applied to quantify the individual and interactive contributions of each influencing factor to groundwater level dynamics. The results indicated that the intra-annual dynamic variation of the groundwater level was predominantly dominated by an exploitation-driven pattern, which was closely associated with the seasonal characteristics of the agricultural irrigation. Meanwhile, the long-term groundwater level shared an overall fluctuating downward trend. Four stages were divided: A relatively stable fluctuating variation (2003–2008), a rapid and significant decline (2009–2014), a slight recovery and upward trend (2015–2017), and a reversion to a gradual downward trend (2018–2023). Significant resonance periods and time-lag effects were observed between groundwater level and precipitation/runoff at different time scales, indicating a significant positive correlation. The groundwater level was lagged behind precipitation and runoff by approximately 0–2 months at the phase angle from 0° to 60°. The gradual expansion of the cultivated land area was driven by agricultural development from 2003 to 2023. The regions with high-intensity human activities shared a continuous expansion trend. A local spatial autocorrelation existed between human activity intensity and groundwater level, indicating a strong spatial coupling between human disturbance and groundwater evolution. Additionally, the dynamic groundwater level was mainly influenced by multiple factors, including surface runoff, human activities, precipitation, and land use types. Notably, the interactions of these factors exerted a more significant synergistic impact on the groundwater level dynamics, compared with their individual effects. The findings can greatly contribute to the dynamic response mechanisms of the groundwater in the arid areas. Theoretical support and practical technical references can also be used to formulate the regional groundwater indicators, and then realize the long-term sustainable utilization of the groundwater resources.

     

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