Disentangling Subsidence from Shallow Soil Processes and Gas Extraction in a Dutch UNESCO World Heritage Polder with InSAR and Data Assimilation.

Many deltas and coastal plains are densely populated because of their fertile soils and strategic locations. Yet, these areas face substantial subsidence challenges, as a result of human subsurface activities at multiple depths. Subsidence studies so far focus on the effects of individual causes, limiting the understanding of total subsidence. This is also the case in the Netherlands, with much of its coastal land already below mean sea level. This is primarily the result of centuries of water management. The subsurface in these areas is composed of soft soil, making them highly susceptible to subsidence by shrinkage, oxidation, and compaction. The effects of subsidence are locally aggravated by deeper hydrocarbon extraction. This study centers around the Beemster polder, a UNESCO World Heritage site that exemplifies complex human-induced subsidence originating from multiple depths. We distinguish the contributions of the shallow and deep subsidence causes in a joint model. We quantified the contributions and optimized modeling with data assimilation. The results of the combined effects were optimized for 2015-2022 using InSAR data. Locations with the thickest surficial peat layers exhibit over 5 mm/year subsidence, yet the effect of thick clay beds is also substantial. The expected subsidence related to gas extraction is not expected to exceed 30 mm in the period 2020-2050. Findings from this work deepen our understanding of subsidence dynamics, offering an approach that can be applied to similar subsidence-prone coastal and deltaic regions worldwide, where multiple overlapping factors drive subsidence. Graphical Abstract: This study aims to understand and quantify the contributions of different human-induced subsidence processes in a coastal UNESCO World Heritage polder containing several actively producing gas fields. Subsidence is assessed by integrating observational data with information on (sub)surface characteristics and applying subsidence models. The workflow, summarized in the graphical abstract, involves several steps. First, all input datasets are compiled. InSAR and levelling measurements provide observational subsidence data. Subsurface information includes a lithostratigraphic model of the shallow subsurface, gas production data, and geomechanical properties of the gas reservoirs. Both the shallow model and gas extraction at depth are modeled analytically. These analytical models include parameters that are calibrated using the Ensemble Smoother with Multiple Data Assimilation (ES-MDA). This optimization step enables a quantitative separation of contributions from different subsidence processes. The resulting parameter sets are also used to project future subsidence, based on planned gas extraction and assuming that shallow subsidence continues in line with observed trends. The results reveal distinct spatial patterns in subsidence, particularly highlighting the contrast between areas with intact peat layers and those where peat has been removed historically. Subsidence from shallow processes is related to the presence and thickness of surficial peat and clay deposits. Deep subsidence due to gas extraction completes the overall subsidence pattern. These insights are valuable for guiding mitigation strategies by policymakers and stakeholders. Moreover, the study emphasizes the need for a comprehensive, integrated framework for understanding subsidence processes, particularly in vulnerable coastal and deltaic environments worldwide.