Project Details
Projekt
COMPUtational Framework for Modern Calibration and Validation of Mathematical Models of Subsurface Flows - COMPU-FLOW
Subject Area
Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
Term
from 2017 to 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 359880532
Predicting the behavior of subsurface environments (e.g., groundwater flow and contaminant transport in groundwater) is subject to staggering uncertainties. The latter mainly arise because the subsurface is highly heterogeneous, and it is virtually impossible to characterize all of its details. The resolution of heterogeneity can be improved through new types of experimental data, and the remaining uncertainties may be reduced by calibration of flow/transport models on observed data of state variables. Uncertainty can only be quantified via stochastic/probabilistic inverse modeling techniques instead of conventional model calibration schemes. A large variety of (stochastic) inverse methods is available in the literature. However, a conclusive and convincing assessment of their relative merits and drawbacks is still missing. This fact creates a challenging barrier to all current and future research efforts that seek to further improve inverse modeling. A key reason for this is the lack of well-defined benchmark scenarios against which diverse methods can be compared under standardized, controlled and reproducible conditions. This proposal aims at overcoming this issue by defining a set of benchmark scenarios with highly accurate reference solutions. A community-wide comparison study based on these benchmarks and reference solutions is also planned. Benchmark scenarios, reference solutions and compared solutions will be made available to the research community on a long-term basis for continued future use. The developed benchmark cases will consider fully-saturated transient groundwater flow, low and high spatial variability and multi-Gaussian as well as non-multi-Gaussian hydraulic conductivity fields. Special dedication will be paid to calculating highly accurate reference solutions for the benchmark cases. The reference solutions will be produced with highly specialized algorithms developed during this project. The algorithms will be grounded on the preconditioned Crank-Nicholson variant of Markov Chain Monte Carlo, equipped with adaptive proposal distributions, multi-tempered parallel chains, a randomized version of gradient search and an extension for non-multi-Gaussian distributions. The reference solutions will be calculated on the high performance supercomputing infrastructure in Jülich after adapting the developed algorithms for massive parallel computation. The groundwater inverse modeling community will meet in a workshop to finalize the strategy for the comparison study, which includes important topics like logistics and definition of performance criteria. A total of 12 internationally renowned groups have already committed to participate with their inverse methods in the workshop and comparison study. Altogether, this proposal constitutes a unique effort to bring the international groundwater inverse modeling community together, provide critical insights on existing methods and improve them.
DFG Programme
Research Grants
International Connection
Italy
Cooperation Partners
Professor Dr.-Ing. Alberto Guadagnini; Professorin Dr.-Ing. Monica Riva
