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Modern challenges of stochastic groundwater hydrology: from pore to field scale
Convener: Monica Riva  | Co-Conveners: Alberto Guadagnini , Xavier Sanchez-Vila , Daniel Fernandez-Garcia 
 / Tue, 25 Apr, 13:30–15:00  / Room 2.95
 / Attendance Tue, 25 Apr, 17:30–19:00  / Hall A
Development and application of decision support systems to aquifers and underground reservoirs requires reliable and physically based methods to infer key parameters controlling multiphase flow and contaminant fluxes of conservative or reactive substances in the subsurface. Underground environments are complex and extremely heterogeneous exhibiting variations on a multiplicity of scales. Addressing heterogeneity in all its manifestations is the focus of exciting and intense forefront research and industrial activities. Stochastic models are unique in providing predictions of groundwater flow and transport processes together with assessment of prediction uncertainty. In many situations the information conveyed by each measurement may be far from complete so that one is confronted with the problem of fusing data of various nature to achieve the desired level of knowledge. There is the need to understand how data contribute to the reconstruction of the porous medium and the manner in which measurements from different sources can be merged. This problem can be tackled by new stochastic models able to consider processes arising at different scales. This is opening new avenues for the interpretation of observed processes. This session is aimed at providing an opportunity for specialists to exchange information and to introduce various existing and novel alternative stochastic models of subsurface flow and transport to the general hydrological community, with critical and timely applications to environmental and industrially relevant settings. Focus is placed on recent key developments in new experimental protocols, novel theoretical aspects and associated computational tools, fate of new contaminants, and field/laboratory applications dealing with accurate and efficient prediction and quantification of uncertainty for flow, conservative and reactive transport processes in the subsurface, in the presence of multiple information at different scales, ranging from the pore level to the intermediate and basin scales.