A novel methodological approach for land subsidence prediction through data assimilation techniques

Abstract Anthropogenic land subsidence can be evaluated and predicted by numerical models, which are often built over deterministic analyses. However, uncertainties approximations present, as in any other modeling activity of real-world phenomena. This study aims at combining data assimilation techniques with a physically-based model anthropogenic novel comprehensive workflow, to overcome the main limitations concerning way traditional analyses use available measurements. The proposed methodology allows reduce affecting model, identify most appropriate rock constitutive behavior characterize significant governing geomechanical parameters. methodological approach has been applied synthetic test case representative Upper Adriatic basin, Italy. integration into appears useful effective tool for more reliable subsidence.