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首页> 外文期刊>Journal of Hydrology >Understanding space-time patterns of groundwater system by empirical orthogonal functions: A case study in the Choshui River alluvial fan, Taiwan
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Understanding space-time patterns of groundwater system by empirical orthogonal functions: A case study in the Choshui River alluvial fan, Taiwan

机译:通过经验正交函数了解地下水系统的时空格局:以台湾长水河冲积扇为例

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Natural or anthropogenic activities contribute to changes of groundwater levels in space and time. Understanding the major and significant driving forces to changes in space-time patterns of groundwater levels is essential to groundwater management. This study analyzes monthly observations of piezometric heads from 66 wells during 1997-2002 located in the Choshui River alluvial fan of Taiwan, where groundwater has been the important local water resource for myriads of agricultural or industrial demands. Following spatiotemporal estimations of piezometric heads by Bayesian Maximum Entropy method (BME), this work performs rotated empirical orthogonal function (REOF) analysis to decompose the obtained space-time heads into a set of spatially distributed empirical orthogonal functions (EOFs) and their associated uncorrelated time series. Results show that the leading EOFs represent the most significant driving forces to spatiotemporal changes of groundwater levels in the Choshui River aquifer. These include rainfall recharges from upstream Choshui and Pei-Kang River, pumping activities from aquaculture usages in the coastal areas, as well as water exchanges between surface and subsurface flow of Choshui River. In summary, this study shows the strength of the REOF analysis which can effectively provide integrative views of spatiotemporal changes of groundwater, gaining insights of interactions between the groundwater system and other natural and human activities.
机译:自然或人为活动有助于地下水在空间和时间上的变化。了解地下水位的时空变化的主要和重要驱动力对于地下水管理至关重要。这项研究分析了1997年至2002年位于台湾Choshui河冲积扇的66口井的测压压头的月度观测结果,那里的地下水一直是满足各种农业或工业需求的重要本地水资源。在通过贝叶斯最大熵方法(BME)对测压头进行时空估计之后,这项工作执行了旋转经验正交函数(REOF)分析,以将获得的时空头分解为一组空间分布的经验正交函数(EOF)及其相关的不相关项时间序列。结果表明,领先的EOF代表着Choshui河含水层中地下水位的时空变化的最大驱动力。这些措施包括上游Cho水和沛康河的降雨补给,沿海地区水产养殖用途的抽水活动,以及hui水河地表水和地下水之间的水交换。总而言之,这项研究显示了REOF分析的优势,它可以有效地提供地下水时空变化的综合观点,获得地下水系统与其他自然和人类活动之间相互作用的见解。

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