Soonthornrangsan Jenny T, Bakker Mark, Vossepoel Femke C
Department of Water Management, Faculty of Civil Engineering and Geoscience, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands.
Department of Geoscience & Engineering, Faculty of Civil Engineering and Geoscience, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, The Netherlands.
Ground Water. 2025 Mar-Apr;63(2):145-159. doi: 10.1111/gwat.13443. Epub 2024 Oct 11.
Research into land subsidence caused by groundwater withdrawal is hindered by the availability of measured heads, subsidence, and forcings. In this paper, a parsimonious, linked data-driven and physics-based approach is introduced to simulate pumping-induced subsidence; the approach is intended to be applied at observation well nests. Time series analysis using response functions is applied to simulate heads in aquifers. The heads in the clay layers are simulated with a one-dimensional diffusion model, using the heads in the aquifers as boundary conditions. Finally, simulated heads in the layers are used to model land subsidence. The developed approach is applied to the city of Bangkok, Thailand, where relatively short time series of head and subsidence measurements are available at or near 23 well nests; an estimate of basin-wide pumping is available for a longer period. Despite the data scarcity, data-driven time series models at observation wells successfully simulate groundwater dynamics in aquifers with an average root mean square error (RMSE) of 2.8 m, relative to an average total range of 21 m. Simulated subsidence matches sparse (and sometimes very noisy) land subsidence measurements reasonably well with an average RMSE of 1.6 cm/year, relative to an average total range of 5.4 cm/year. Performance is not good at eight out of 23 locations, most likely because basin-wide pumping is not representative of localized pumping. Overall, this study demonstrates the potential of a parsimonious, linked data-driven, and physics-based approach to model pumping-induced subsidence in areas with limited data.
由于缺乏实测水头、地面沉降数据以及相关作用力数据，对地下水开采引起的地面沉降的研究受到了阻碍。本文引入了一种简洁的、将数据驱动与基于物理的方法相结合的方式来模拟抽水引起的地面沉降；该方法旨在应用于观测井组。利用响应函数进行时间序列分析来模拟含水层中的水头。以含水层中的水头为边界条件，用一维扩散模型来模拟黏土层中的水头。最后，利用各层模拟水头来模拟地面沉降。所开发的方法应用于泰国曼谷市，在该市23个井组或其附近可获得相对较短时间序列的水头和地面沉降测量数据；且可获得较长时期内全流域抽水的估计值。尽管数据稀缺，但观测井处的数据驱动时间序列模型成功地模拟了含水层中的地下水动态，相对于平均总变化范围21米，平均均方根误差（RMSE）为2.8米。模拟的地面沉降与稀疏（且有时噪声很大）的地面沉降测量值匹配得较好，相对于平均总变化范围5.4厘米/年，平均RMSE为1.6厘米/年。在23个地点中的8个地点表现不佳，最有可能是因为全流域抽水情况不能代表局部抽水情况。总体而言，本研究证明了一种简洁的、将数据驱动与基于物理的方法相结合的方式在数据有限地区模拟抽水引起的地面沉降的潜力。
