Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time

K H Jensen,R R Møller,F Jørgensen,T O Sonnenborg,X He,A.-S Høyer

doi:10.5194/hess-17-3245-2013

Abstract

Abstract. Uncertainty of groundwater model predictions has in the past mostly been related to uncertainty in the hydraulic parameters, whereas uncertainty in the geological structure has not been considered to the same extent. Recent developments in theoretical methods for quantifying geological uncertainty have made it possible to consider this factor in groundwater modeling. In this study we have applied the multiple-point geostatistical method (MPS) integrated in the Stanford Geostatistical Modeling Software (SGeMS) for exploring the impact of geological uncertainty on groundwater flow patterns for a site in Denmark. Realizations from the geostatistical model were used as input to a groundwater model developed from Modular three-dimensional finite-difference ground-water model (MODFLOW) within the Groundwater Modeling System (GMS) modeling environment. The uncertainty analysis was carried out in three scenarios involving simulation of groundwater head distribution and travel time. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model optimization, where the hydraulic parameters for each of them were estimated by calibration against observations of hydraulic head and stream discharge. In the third scenario each geological model was run with 216 randomized sets of parameters. The analysis documented that the uncertainty on the conceptual geological model was as significant as the uncertainty related to the embedded hydraulic parameters.

Highlights

With the prevalent application of groundwater modeling, the inherent uncertainties associated with model simulation are well acknowledged (Delhomme, 1979; Beven and Binley, 1992; Feyen et al, 2001; Hassan et al, 2008). Dettinger and Wilson (1981) divided uncertainty in groundwater systems into two classes: intrinsic uncertainty and information uncertainty
The primary geostatistical information required in single normal equation simulation algorithm (SNESIM) is the radius of the search template and target proportion, which is related to the mean length, and the proportion of each sedimentary unit
This study has examined the impact of geological and parameter uncertainty on real case simulations of groundwater heads and travel time using the multiple-point geostatistical method (MPS)

Summary

Introduction

With the prevalent application of groundwater modeling, the inherent uncertainties associated with model simulation are well acknowledged (Delhomme, 1979; Beven and Binley, 1992; Feyen et al, 2001; Hassan et al, 2008). Dettinger and Wilson (1981) divided uncertainty in groundwater systems into two classes: intrinsic uncertainty and information uncertainty. A common approach to simulate spatial heterogeneity in hydrogeology is to use geostatistics, and the traditional method is to employ variogram-based techniques (Delhomme, 1979; Wingle and Poeter, 1993; Johnson, 1995; Klise et al, 2009). Despite that these traditional methods have been applied extensively during the last three decades, they only consider correlation between two spatial locations, which often fails to depict distinct largely connected geological structures. Due to mathematical simplifications these methods can only capture a limited number of data types (Caers and Zhang, 2004; Journel, 2005). Renard (2007)

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