KARST: Predicting flow and transport in complex Karst systems

Karst aquifers are a treasure and a threat: while up to 25% of the world population depends on them for drinking water, they also have capabilities for extremely fast conduction of water and contaminants. In the light of climate change, we need to prepare for extreme flooding and understand the consequences for karst aquifers. Despite their socio-economic importance, decades of research, and high-profile disasters, karst structures and processes remain notoriously difficult to assess. Because of the complexity of karst and its lack of accessibility, the foundations of flow and transport modeling in karst systems are weak. Key phenomena related to extreme events such as flash floods and heavy tails in tracer recovery are still beyond current modeling capabilities. KARST will establish the next generation of coupled stochastic modeling frameworks to predict karst processes, assess the vulnerability of karst aquifers, and forecast their response to extreme events. Our approach will bridge structures and processes on all scales, far beyond the capabilities of current theories and computer simulations. This will be achieved by targeting three key objec- tives: (i) Identification and quantification of flow and transport dynamics at the conduit scale. (ii) Characterization and modeling of karst network structure at the catchment scale. (iii) Derivation of a new upscaled approach to predict karst processes at different resolution scales. Together, this will result in an unprecedented multiscale modeling framework for the prediction of flow and transport in karst.Solving this long-standing problem is possible thanks to the synergy of the KARST PI team combining the set of skills and knowledge (hydrogeology, physics, mathematics) required to make a ground-breaking step in this field. Beyond that, the new approach is expected to impact other real-world systems in medicine (capillary networks), neuroscience (brain microcirculation) or glaciology (meltwater flow in glaciers).