Uni-Tübingen

P7 Stochastic Modeling Framework of Catchment-Scale Reactive Transport

Principal Investigators

Prof. Dr.-Ing. Olaf A. Cirpka

University of Tübingen, Hydrogeology

Prof. Dr. Thilo Streck

University of Hohenheim, Biogeophysics

Prof. Dr.-Ing. Wolfgang Nowak

University of Stuttgart,

Stochastic Simulation and Safety Research for Hydrosystems

Contact:

Prof. Dr.-Ing. Olaf Cirpka

University of Tübingen, Hölderlinstr. 12, 72074 Tübingen

+49 (7071) 29 78928; olaf.cirpkaspam prevention@uni-tuebingen.de

 

Research Questions

Process-based numerical models of flow, transport, and reactive turnover are necessary tools to understand major influences on water quality, nutrient cycling, and fate of pollutants. To address the impact of internal variability, these models should be based on spatially distributed hydraulic and reactive parameters. At the same time, all parameters are uncertain, and the exact spatial distribution is not known. Thus, a stochastic description, predicting statistical distributions rather than single values, is necessary. The necessity of multiple model runs to address uncertainty is contradicted by the computational effort associated with spatially fully explicit flow-and-reactive-transport models of the land-surface/soil/aquifer continuum, in which the models are based on partial differential equations.

The main objective of project P7 is to develop a modeling framework for flow and reactive transport on the catchment scale that is

Approach

The model framework is based on simulating the strong feedbacks between soils and vegetation at the land-surface with fully coupled 1-D, vertical soil-crop models (Expert-N) that are weekly coupled to and underlying 3-D flow model (HydroGeoSphere) of the deeper subsurface and streamline-based models of reactive transport therein.

While the individual model components honor existing information about soil types, land use, topography/bathymetry, and geology, we address the uncertainty of parameters and geometries by treating all coefficients as random distributions, requiring ensemble calculations of the full system.

We will

At a later stage, we will extend the analysis to the fate of pesticides. Questions regarding the uncertainty of model concepts will be addressed in project P8.