Integrated spatiotemporal data mining and DInSAR for improved understanding of subsidence related to groundwater depletion impacts  

利用整合时空数据挖掘和DInSAR技术深入理解地下水枯竭造成的地面沉降

作　　者：Jalal KARAMI Fatemeh BABAEE Pouya MAHMOUDNIA Mohammad SHARIFI KIA 

机构地区：[1]Remote Sensing and GIS Department,Tarbiat Modares University,Jalal Ale Ahmad Highway,Nasr,P.O.Box:14115-111,Tehran,Iran

出　　处：《Journal of Geographical Sciences》2025年第3期598-618,共21页地理学报(英文版)

摘　　要：Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental challenges.The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain,Iran,focusing on quantifying subsidence resulting from groundwater extraction.Using Sentinel-1 satellite data(2014–2019)and monthly piezometric measurements(1996–2018),the analysis revealed an average deformation velocity of–6.3 cm yr–1,with accumulated subsidence of–32 cm over the 2014–2019 period.The maximum subsidence rate reached 10.3 cm yr–1 in areas of intensive agricultural activity.A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends.Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75%of the variance(R2=0.75),indicating that intermediate-scale groundwater declines were the primary drivers of subsidence.Furthermore,land use analysis using Landsat data(1999–2021)revealed a 6230-ha increase in irrigated farmland,contributing to heightened groundwater extraction and subsidence rates.These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.

关 键 词：spatiotemporal wavelet-PCA analysis SUBSIDENCE INTERFEROMETRY piezometric data Malayer Plain 

分 类 号：P641.8[天文地球—地质矿产勘探]