A Process-Based Modelling Approach to Evaluate Alternative Sustainable Land Subsidence Adaptation Pathways in the Netherlands

Land subsidence is a slowly progressing phenomenon that often goes unnoticed due to its gradual nature, yet it can significantly compromise long-term sustainability if left unaddressed. This challenge is particularly pronounced in coastal and deltaic regions with limited fluvial sediment input – e.g. the Netherlands, the Po River Basin, the Mekong Delta, the Mississippi Delta – where anthropogenic activities altered water tables, sediment dynamics and ecosystem health, and further such impacts with climate change and sea-level rise are expected. Any robust, future-proof adaptation strategy and spatial planning must therefore account for ongoing land subsidence, if human presence is to be viable.

In the Netherlands, the situation is already severe: approximately 50% of its coastal-deltaic plain now lies below mean sea level (Koster et al., 2018) owing to soft soil consolidation, peat oxidation and mining, accumulated over centuries and never technologically halted. Even more, progressive subsidence has increasing economic costs (Van den Born et. al., 2016). Recognizing the urgency of this problem, the Dutch government and related authorities pay attention and resources at regional and national scale (e.g. platforms, knowledge centres, incentives, directives, regional deals), and several cross-disciplinary research programs have been prompted (e.g. NWA-LOSS, NOBV, DeepNL). Within NWA-LOSS (nwa-loss.nl) our work focuses on the numerical modelling. With partners, we develop and operate the land subsidence model Atlantis (Bootsma et al., 2020) that captures the interplay of soft soil consolidation, peat oxidation, climate change, and human interventions (e.g. agricultural drainage) to predict future spatial and temporal evolution of the Dutch landscape. Employing global sensitivity analyses (Morris screening and Sobol’ indices), we identify the most influential parameters and processes and integrate uncertainty quantification to ensure robust subsidence predictions.

Our results reveal how shallow subsidence evolves under various climate scenarios, pinpointing ‘hotspots’ for targeted adaptation and nature based solutions (e.g. peat regeneration). Critically, our findings underscore the role of subsidence in shaping relative sea-level rise, a driver of coastal vulnerability that can profoundly influence coastal and deltaic biogeochemistry, biomorphodynamics, and hydrodynamics. Incorporating land subsidence into long-term adaptation measures is therefore essential for mitigating climate change impacts and improving the resilience of coastal and estuarine environments worldwide.

References:

Bootsma, H., Kooi, H., Erkens, G. (2020). Atlantis, a tool for producing national predictive land subsidence maps of the Netherlands. Proceedings of the International Association of Hydrological Sciences, 382, 415-420.

Koster K., Stafleu J., Stouthamer E. (2018). Differential subsidence in the urbanised coastal-deltaic plain of the Netherlands. Netherlands Journal of Geosciences. 2018;97(4):215-227. doi:10.1017/njg.2018.11

Van den Born, G. J., Kragt, F., Henkens, D., Rijken, B., Van Bemmel, B., Van der Sluis, S. (2016). Dalende bodems, Stijgende kosten, Report Planning Agency for the Environment (PBL), report nr. 1064, 93 pp., 2016.