Death valley regional ground-water flow model calibration using optimal parameter estimation methods and geoscientific information systems

D'Agnese, F. A.; Faunt, Claudia C.; Hill, Mary C.; Turner, Anne I.

doi:10.1016/s0309-1708(98)00053-0

Cited by 55 publications

(32 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But they may be overparameterized (Poeter and Hill, 1997;Carrera et al, 2005). It is clear that the heterogeneity assumption is required to reproduce geologic observations, which is valuable information in itself (D'Agnese et al, 1999), and to model mixing (Le Borgne et al, 2010). It is also clear, however, that parameterizing heterogeneity causes non-uniqueness.…”

Section: Tracer Test Modelmentioning

confidence: 99%

Tracer test modeling for characterizing heterogeneity and local-scale residence time distribution in an artificial recharge site

Valhondo

Martinez-Landa

Carrera

et al. 2016

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Artificial recharge of aquifers is a technique for improving water quality and increasing groundwater resources. Understanding the fate of a potential contaminant requires knowledge of the residence time distribution (RTD) of the recharged water in the aquifer beneath. A simple way to obtain the RTDs is to perform a tracer test. We performed a pulse injection tracer test in an artificial recharge system through an infiltration basin to obtain the breakthrough curves, which directly yield the RTDs. The RTDs turned out to be very broad and we used a numerical model to interpret them, to characterize heterogeneity, and to extend the model to other flow conditions. The model comprised nine layers at the site scaled to emulate the layering of aquifer deposits. Two types of hypotheses were considered: homogeneous (all flow and transport parameters identical for every layer) and heterogeneous (diverse parameters for each layer). The parameters were calibrated against the head and concentration data in both model types, which were validated quite satisfactorily against 1,1,2-Trichloroethane and electrical conductivity data collected over a long period of time with highly varying flow conditions. We found that the broad RTDs can be attributed to the complex flow structure generated under the basin due to three-dimensionality and time fluctuations (the homogeneous model produced broad RTDs) and the heterogeneity of the media (the heterogeneous model yielded much better fits). We conclude that heterogeneity must be acknowledged to properly assess mixing and broad RTDs, which are required to explain the water quality improvement of artificial recharge basins.

show abstract

Section: Tracer Test Modelmentioning

confidence: 99%

Tracer test modeling for characterizing heterogeneity and local-scale residence time distribution in an artificial recharge site

Valhondo

Martinez-Landa

Carrera

et al. 2016

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…However, large-scale groundwater models, especially for large aquifers and basins of multiple countries, are still rare, mainly due to lack of hydro-geological data. Some existing large-scale groundwater models, such as in the Death Valley area, USA (D'Agnese et al, 1999), and in the MIPWA region, the Netherlands (Snepvangers et al, 2007), were developed on the basis of highly detailed information (e.g. elaborate 3-D geological models).…”

Section: Introductionmentioning

confidence: 99%

Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

Sutanudjaja

Beek

Jong

et al. 2011

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The current generation of large-scale hydrological models does not include a groundwater flow component. Large-scale groundwater models, involving aquifers and basins of multiple countries, are still rare mainly due to a lack of hydro-geological data which are usually only available in developed countries. In this study, we propose a novel approach to construct large-scale groundwater models by using global datasets that are readily available. As the test-bed, we use the combined Rhine-Meuse basin that contains groundwater head data used to verify the model output. We start by building a distributed land surface model (30 arc-second resolution) to estimate groundwater recharge and river discharge. Subsequently, a MODFLOW transient groundwater model is built and forced by the recharge and surface water levels calculated by the land surface model. Results are promising despite the fact that we still use an offline procedure to couple the land surface and MODFLOW groundwater models (i.e. the simulations of both models are separately performed). The simulated river discharges compare well to the observations. Moreover, based on our sensitivity analysis, in which we run several groundwater model scenarios with various hydro-geological parameter settings, we observe that the model can reasonably well reproduce the observed groundwater head time series. However, we note that there are still some limitations in the current approach, specifically because the offline-coupling technique simplifies the dynamic feedbacks between surface water levels and groundwater heads, and between soil moisture states and groundwater heads. Also the current sensitivity analysis Correspondence to: E. H. Sutanudjaja (e.sutanudjaja@geo.uu.nl) ignores the uncertainty of the land surface model output. Despite these limitations, we argue that the results of the current model show a promise for large-scale groundwater modeling practices, including for data-poor environments and at the global scale.

show abstract

“…The goodness-of-fit is usually used to optimize the calibration of the computer model's adjustable parameters and to serve as a measure by which to compare alternate models. This is an inverse problem, for which the main problem is the non-uniqueness of the solution that gives rise to obtaining different parameter values that yield solutions with similar accuracies (e.g., Poeter and Hill, 1997;Hill et al, 1998;D'Agnese et al, 1999). The most common goodness-of-fit parameter appears to be some form of weighted root-mean-square error, with the error describing the difference between calculated and measured values.…”

Section: Subjective Versus Objective Judgmentmentioning

confidence: 99%

A Validation Process for the Groundwater Flow and Transport Model of the Faultless Nuclear Test at Central Nevada Test Area

Hassan¹

2003

View full text Add to dashboard Cite

EXECUTIVE SUMMARYMany sites of groundwater contamination rely heavily on complex numerical models of flow and transport to develop closure plans. This has created a need for tools and approaches that can be used to build confidence in model predictions and make it apparent to regulators, policy makers, and the public that these models are sufficient for decision making. This confidence building is a long-term iterative process and it is this process that should be termed "model validation." Model validation is a process not an end result. That is, the process of model validation cannot always assure acceptable prediction or quality of the model. Rather, it provides safeguard against faulty models or inadequately developed and tested models. Therefore, development of a systematic approach for evaluating and validating subsurface predictive models and guiding field activities for data collection and long-term monitoring is strongly needed. This report presents a review of model validation studies that pertain to groundwater flow and transport modeling. Definitions, literature debates, previously proposed validation strategies, and conferences and symposia that focused on subsurface model validation are reviewed and discussed. The review is general in nature, but the focus of the discussion is on site-specific, predictive groundwater models that are used for making decisions regarding remediation activities and site closure. An attempt is made to compile most of the published studies on groundwater model validation and assemble what has been proposed or used for validating subsurface models. The aim is to provide a reasonable starting point to aid the development of the validation plan for the groundwater flow and transport model of the Faultless nuclear test conducted at the Central Nevada Test Area (CNTA).The review of previous studies on model validation shows that there does not exist a set of specific procedures and tests that can be easily adapted and applied to determine the validity of site-specific groundwater models. This is true for both deterministic and stochastic models, with the latter posing a more difficult and challenging problem when it comes to validation. This report then proposes a general validation approach for the CNTA model, which addresses some of the important issues recognized in previous validation studies, conferences, and symposia as crucial to the process. The proposed approach links model building, model calibration, model predictions, data collection, model evaluations, and model validation in an iterative loop. The approach focuses on use of collected validation data to reduce model uncertainty and narrow the range of possible outcomes of stochastic numerical models. It accounts for the stochastic nature of the numerical CNTA model, which used Monte Carlo simulation approach. The proposed methodology relies on the premise that absolute validity is not even a theoretical possibility and is not a regulatory requirement. Rather, it highlights the importance of testing as many aspect...

show abstract

Death valley regional ground-water flow model calibration using optimal parameter estimation methods and geoscientific information systems

Cited by 55 publications

References 5 publications

Tracer test modeling for characterizing heterogeneity and local-scale residence time distribution in an artificial recharge site

Tracer test modeling for characterizing heterogeneity and local-scale residence time distribution in an artificial recharge site

Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin

A Validation Process for the Groundwater Flow and Transport Model of the Faultless Nuclear Test at Central Nevada Test Area

Contact Info

Product

Resources

About