Abstract:[1] The uncertainty in the boundary of two-dimensional, steady state well catchments due to the uncertainty of the spatially variable hydraulic conductivity field is investigated. The well discharge rate and the areal recharge rate are assumed constant. The catchment boundary is traced by backward particle tracking in the velocity field. The uncertainty bandwidth of the catchment boundary is approximated in first order by formulating the time-dependent longitudinal and transversal second moments of the particl… Show more
“…Recent applications of first-order methods have been extended to the determinations of stochastic well capture zones (e.g. Kunstmann and Kinzelbach, 2000;Stauffer et al, 2002Stauffer et al, , 2004Lu and Zhang, 2003;Zhang and Lu, 2004;Lessoff and Indelman, 2004;Bakr and Butler, 2005;Riva et al, 2006;Kunstmann and Kastens, 2006;Indelman et al, 2006). Most studies on the subject dealt with depth-averaged two-dimensional problems (Kunstmann and Kinzelbach, 2000;Stauffer et al, 2002Stauffer et al, , 2004Lu and Zhang, 2003;Zhang and Lu, 2004;Bakr and Butler, 2005;Riva et al, 2006;Kunstmann and Kastens, 2006).…”
Abstract. This study presents a numerical first-order spectral model to quantify transient flow and remediation zone uncertainties for partially opened wells in heterogeneous aquifers. Taking advantages of spectral theories in solving unmodeled small-scale variability in hydraulic conductivity (K), the presented nonstationary spectral method (NSM) can efficiently estimate flow uncertainties, including hydraulic heads and Darcy velocities in r-and z-directions in a cylindrical coordinate system. The velocity uncertainties associated with the particle backward tracking algorithm are then used to estimate stochastic remediation zones for scenarios with partially opened well screens. In this study the flow and remediation zone uncertainties obtained by NSM were first compared with those obtained by Monte Carlo simulations (MCS). A layered aquifer with different geometric mean of K and screen locations was then illustrated with the developed NSM. To compare NSM flow and remediation zone uncertainties with those of MCS, three different small-scale K variances and correlation lengths were considered for illustration purpose. The MCS remediation zones for different degrees of heterogeneity were presented with the uncertainty clouds obtained by 200 equally likely MCS realizations. Results of simulations reveal that the first-order NSM solutions agree well with those of MCS for partially opened wells. The flow uncertainties obtained by using NSM and MCS show identically for aquifers with small ln K variances and correlation lengths. Based on the test examples, the remediation zone uncertainties (bandwidths) are not sensitive to the changes of small-scale ln K correlation lengths. However, the increases of remediation zone uncertainties (i.e. the Correspondence to: C.-F. Ni (nichuenfa@geo.ncu.edu.tw) uncertainty bandwidths) are significant with the increases of small-scale ln K variances. The largest displacement uncertainties may have several meters of differences when the ln K variances increase from 0.1 to 1.0. Such conclusions are also valid for the estimations of remediation zones in layered aquifers.
“…Recent applications of first-order methods have been extended to the determinations of stochastic well capture zones (e.g. Kunstmann and Kinzelbach, 2000;Stauffer et al, 2002Stauffer et al, , 2004Lu and Zhang, 2003;Zhang and Lu, 2004;Lessoff and Indelman, 2004;Bakr and Butler, 2005;Riva et al, 2006;Kunstmann and Kastens, 2006;Indelman et al, 2006). Most studies on the subject dealt with depth-averaged two-dimensional problems (Kunstmann and Kinzelbach, 2000;Stauffer et al, 2002Stauffer et al, , 2004Lu and Zhang, 2003;Zhang and Lu, 2004;Bakr and Butler, 2005;Riva et al, 2006;Kunstmann and Kastens, 2006).…”
Abstract. This study presents a numerical first-order spectral model to quantify transient flow and remediation zone uncertainties for partially opened wells in heterogeneous aquifers. Taking advantages of spectral theories in solving unmodeled small-scale variability in hydraulic conductivity (K), the presented nonstationary spectral method (NSM) can efficiently estimate flow uncertainties, including hydraulic heads and Darcy velocities in r-and z-directions in a cylindrical coordinate system. The velocity uncertainties associated with the particle backward tracking algorithm are then used to estimate stochastic remediation zones for scenarios with partially opened well screens. In this study the flow and remediation zone uncertainties obtained by NSM were first compared with those obtained by Monte Carlo simulations (MCS). A layered aquifer with different geometric mean of K and screen locations was then illustrated with the developed NSM. To compare NSM flow and remediation zone uncertainties with those of MCS, three different small-scale K variances and correlation lengths were considered for illustration purpose. The MCS remediation zones for different degrees of heterogeneity were presented with the uncertainty clouds obtained by 200 equally likely MCS realizations. Results of simulations reveal that the first-order NSM solutions agree well with those of MCS for partially opened wells. The flow uncertainties obtained by using NSM and MCS show identically for aquifers with small ln K variances and correlation lengths. Based on the test examples, the remediation zone uncertainties (bandwidths) are not sensitive to the changes of small-scale ln K correlation lengths. However, the increases of remediation zone uncertainties (i.e. the Correspondence to: C.-F. Ni (nichuenfa@geo.ncu.edu.tw) uncertainty bandwidths) are significant with the increases of small-scale ln K variances. The largest displacement uncertainties may have several meters of differences when the ln K variances increase from 0.1 to 1.0. Such conclusions are also valid for the estimations of remediation zones in layered aquifers.
“…Furthermore, procedures were developed, which allow conditioning of the statistical moments of the flow field and, therefore, of travel time moments, on hydraulic heads measurements and/or aquifer architecture (e.g., Hernandez et al, 2003;Winter et al, 2003). Stauffer et al (2002) investigated the uncertainty in the location of twodimensional, steady state catchments of pumping wells due to the uncertainty of the spatially variable hydraulic conductivity field by a semi-analytical Lagrangian technique. For the analysis it is assumed that the aquifer can be modelled as a steady-state horizontal, confined or unconfined system.…”
Source protection zones are increasingly important for securing the long-term viability of drinking water derived from groundwater resources. These may be either time-related capture zones or catchments related to the activity of a pumping well or spring. The establishment of such zones is an indispensable measure for the proper assessment of groundwater resource vulnerability and reduction of risk, which may be induced by human activities. The delineation of these protection zones is usually performed with the aid of models, which are in turn based on site-specific information of the aquifer's geometry, hydraulic parameters and boundary conditions. Owing to the imperfect knowledge of such information, predicting the location of these zones is inherently uncertain. It is possible to quantify this uncertainty in a statistical manner through the development of probability maps, which shows the probability that a particular surface location belongs to the aquifer's capture zone (or catchment area). This publication aims at the investigation of the requirements for the establishment of probabilistic source protection zones, the practical use of stochastic methods in their delineation, and the use of data-assimilation for uncertainty reduction. It also provides a methodology for the implementation of these methods by modelling practitioners.
“…The effect of domain size (in terms of the correlation scale of the log conductivity field) on the prediction uncertainty is also analyzed. The results are then compared with the semi-analytical solution proposed by Stauffer et al [24,25] and an extensive suite of numerical Monte Carlo simulations.…”
Section: Introductionmentioning
confidence: 98%
“…Recently, Stauffer et al [24] proposed a semi-analytical method to compute the uncertainty associated with the prediction of a well catchment. They measured uncertainty of predictions in terms of the standard deviation of the displacement of conservative particles along the direction normal to the mean boundary of the well catchment itself.…”
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.