Thomas Ptak University of Tübingen Germany Consortium co-ordinator: Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Thomas Ptak University of Tübingen Germany CO POLIMI (I) CR ETHZ (CH) DUT (NL) ULP (F) ICSTM (UK) TUE (D) AC SEABO (I) COBO (I) AGSM (I) Consortium co-ordinator: Prof. Alberto Guadagnini – POLITECNICO DI MILANO (I) 5 Universities from 5 different EU countries 1 University from an Associated Country 3 Private - Public Sector Organisations from Italy Period of activity: April 2000 – October 2003

Stochastic Analysis of Well Head Protection and Risk Assessment Problem: Assessing uncertainty in modelling wellhead protection zones in heterogeneous aquifers – motivation and general idea "It would be difficult to find a branch of science and technology where the dominant parameter spans as many orders of magnitude as permeability" [Freeze and Cherry, 1979] Efficient use and protection of groundwater requires ability to understand and analyse quantitatively fluid flow and solute transport in natural soils and rocks. In practice: random spatial variability of hydrogeologic medium properties, stochastic nature of corresponding flow and transport variables, and (model) parameter uncertainty are often ignored. With increasing frequency, the popular deterministic approach to hydrogeologic analysis is proving to be inadequate.

Stochastic Analysis of Well Head Protection and Risk Assessment Drinking Water Well Protection Zones Europe: different regulations Switzerland: federal law on water pollution control, size and time related zones Italy: recommendation at regional level The Netherlands: size and time related protection zones Germany: zone I – 10 m, zone II - 50 days, zone IIIa – 2 km, zone IIIb - catchment area United Kingdom: UK Environmental Agency (maps of 50 and 400 days travel times and total catchment area) Industrial / public administration partners: more than 40 % and 100 % of water production comes from the groundwater.

Stochastic Analysis of Well Head Protection and Risk Assessment Key Features and Methods Probabilistic computational methods / experimental procedures for prediction of flow and well catchment extent prediction of contaminant residence time assessment of vulnerability / risk, relevant parameters, prediction uncertainty development of methods to reduce uncertainty in heterogeneous aquifers under data scarcity and uncertainty Major axes of W-SAHaRA: understanding, experimenting & monitoring, and managing Experiments, method development Laboratory scale Field scale Theory / concepts Numerical Monte Carlo Moment Equations Model development Deterministic Probabilistic Protocols Guidelines

The “Lauswiesen” field site The “Bologna” field site Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Two Test Sites (Germany and Italy) The “Lauswiesen” field site The “Bologna” field site Deterministic model of well catchment Probabilistic analysis of aquifers interconnections Field experiments, development of subsurface investigation methods Monte Carlo modelling (2D and 3D)

Scientific Achievements – Numerical Monte Carlo Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Scientific Achievements – Numerical Monte Carlo Development and comparison of models and codes Theoretical analysis of influence of uncertainty of hydrogeological quantities (recharge, boundaries, hydraulic conductivity / transmissivity) Inclusion of information in predictive models (hydraulic conductivity and hydraulic heads, concentrations) to reduce uncertainty Field application

Three-Dimensional Monte Carlo Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Three-Dimensional Monte Carlo Local 3D model Facies-based approach aquifer reconstruction Unique set of 3D simulations Determination of uncertainty Theoretical and experimental methods to reduce uncertainty (where and how to measure what, conditioning) 20-days mean capture zone, uncertainty bounds, and MC results

Scientific Achievements – Moment Equations Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Scientific Achievements – Moment Equations Development of models and codes (deterministic PDEs applied to moments of random state variables; head, flux, travel time, trajectory) Theoretical analysis of influence of uncertainty of hydrogeological quantities (boundaries, hydraulic conductivity / transmissivity, aquifer architecture) Comparison with Monte Carlo – based solutions Analytical solutions for simple geometries Novel methods for pumping test interpretation Inclusion of information in predictive models (hydraulic conductivity and hydraulic heads, material distribution) Reduction of uncertainty  increased confidence in predictions Cooperation with SALTRANS (heterogeneities, modelling, experiments)

Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Guidelines (a) Modelling spatial variability and uncertainty of parameters Which statistical parameters need to be evaluated? (b) Use of Monte Carlo techniques Field-based stochastic analysis of a well capture zone or catchment with a spatially variable hydraulic conductivity field (c) Use of moment equations Unconditional / conditional stochastic analysis of well capture zones with spatially variable hydraulic / hydrogeologic parameters Use of moment equations in a fully nonlinear formalism for the evaluation of travel time and trajectory moments of solutes in heterogeneous aquifers (d) Impact of recharge uncertainty (e) Impact of uncertainty in geostatistical parameters, average hydraulic conductivity, and boundary conditions

Stochastic Well Capture Zone Analysis Decision System (SWECADS) Identify groundwater abstraction and potential sources of pollution Possible input from other Projects Delineate capture zones NO Have well capture/ catchment zones been demarcated D18 YES D21 Simple analytical solution (e.g. Bear and Jacobs, etc.) Method of derivation Existing numerical model (2/3D) (e.g. MODPATH, MODFLOW, etc.) Is there a need to quantify uncertainy? NO STOP Stochastic Well Capture Zone Analysis Decision System (SWECADS) D16, D18 Collect and/or collate data Develop new/modified numerical model (2/3D) Probabilistic analysis – Identify sources of uncertainty (e.g. Conceptual model, hydrogeological parameters) D2, D11 Preliminary unconditional simulations D5, D6, D16 Incorporate data for uncertainty reduction Select type and location of additional input measurements D3, D4, D7 NO Can a pdf of uncertain input be inferred? YES Moment Equations analysis D7, D10 Monte Carlo Analysis YES Further reduce uncertainty? NO STOP

Policy Implications (I) Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Policy Implications (I) Natural formation heterogeneities are always uncertain. Need to change water management concepts. W-SAHaRA developed tools to facilitate decision making: explicit recognition and quantification of uncertainty associated to predictions of groundwater flow and contaminant movement. Also applicable at other scales (catchment, basin)! Probabilistic methodologies / concepts are viable tools to quantify uncertainty and danger related to given situations. Introduction into regulations needed. A (traditional) deterministic analysis of flow and transport represents smooth predicting values. Prediction error.

Policy Implications (II) Seabo S.p.A. University of Tuebingen Municipality of Bologna Université Louis Pasteur de Strasbourg A.G.S.M. S.p.A. Imperial College of Science, Technology and Medicine Delft University of Technology Politecnico di Milano Swiss Federal Institute of Technology W-SAHaRA web-site: www.diiar.polimi.it/franz/EU-W-SAHaRA/index.htm Stochastic Analysis of Well Head Protection and Risk Assessment Policy Implications (II) Probabilistic capture zone maps usable for delineation of protection zones. Information obtained identifies the danger associated to a given situation (or, in other words, the probability of occurrence of a dangerous situation). Together with the concepts of (a) value and (b) vulnerability of elements at risk the degree of risk associated to a given situation can be defined (based on specific political, ecological, and / or economical aspects). Renders risk based assessments that are frequently required for groundwater management decisions. Well capture zones / catchments: the decision system SWECADS provides managers with a method for determining which stochastic tools are required and how these may be used to assess risk and to reduce uncertainty (i.e. increase confidence) in the result. Further development suggested! Combination with INCORE (Ptak et al., 2003, 2004) suggested!