Abstract Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make a significant cost-effective contribution to the progressive abandonment strategy of recently closed coalfields. Applications of DInSAR over coalfields have observed heave in coal measures rocks and temporal correlations between the rise of mine water and deformation time-series. The cessation of systematic dewatering can have a variety of detrimental impacts and knowledge of the time-scales (i.e. the rate of rebound) and structure of the mine system are crucial to the remediation strategy. Although mine plans and borehole measurements provide vital information in this regard, mine plans are often incomplete or inaccurate, whereas monitoring boreholes are spatially sparse. Consequently, groundwater can flow in unanticipated directions via goaf, mine shafts and roadways, making it difficult to determine where the impacts of rebound are likely to occur. In this study, ground deformation data obtained using ISBAS DInSAR on ENVISAT (2002–2009) and Sentinel-1 (2015–2019) data are used to develop a simple method to model groundwater rebound in abandoned coalfields. A forward analytical model based upon the principle of effective stress and mine water ponds is first implemented to estimate surface heave in response to changes in groundwater levels measured in monitoring boreholes. The forward model is then calibrated and validated using the ground deformation data. The DInSAR data were subsequently inverted to map the change in groundwater levels in greater detail across the coalfield and forecast surface discharges in order to support mitigation strategies.

中文翻译：

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使用 DInSAR 模拟最近废弃煤田的地下水回弹

摘要 差分干涉合成孔径雷达 (DInSAR) 处理算法的进步，例如间歇小基线子集 (ISBAS)，以及来自 SAR 系统（例如 Sentinel-1）的数据可用性的提高，为增加空间和时间密度提供了机会。地面变形测量。此类测量与建模相结合，有可能为最近关闭的煤田的逐步废弃战略做出重大的成本效益贡献。DInSAR 在煤田上的应用已经观察到煤系岩石的隆起以及矿井水上升与变形时间序列之间的时间相关性。停止系统性脱水可能会产生各种不利影响和时间尺度的知识（即 回弹率）和矿山系统的结构对修复策略至关重要。尽管采矿计划和钻孔测量提供了这方面的重要信息，但采矿计划通常不完整或不准确，而监测钻孔在空间上很少。因此，地下水可以通过采空区、矿井和巷道向意想不到的方向流动，从而难以确定反弹影响可能发生的位置。在这项研究中，使用 ISBAS DInSAR 在 ENVISAT（2002-2009）和 Sentinel-1（2015-2019）数据上获得的地面变形数据用于开发一种简单的方法来模拟废弃煤田的地下水回弹。首先实施基于有效应力和矿井水池原理的正向分析模型，以估计地表隆起，以响应监测钻孔中测量的地下水位变化。然后使用地面变形数据校准和验证正向模型。DInSAR 数据随后被反转，以更详细地绘制整个煤田的地下水位变化并预测地表排放，以支持缓解策略。