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1.
The groundwater interbasin flow, Qy, from the north of Yucca Flat into Yucca Flat simulated using the Death Valley Regional Flow System (DVRFS) model greatly exceeds assessments obtained using other approaches. This study aimed to understand the reasons for the overestimation and to examine whether the Qy estimate can be reduced. The two problems were tackled from the angle of model uncertainty by considering six models revised from the DVRFS model with different recharge components and hydrogeological frameworks. The two problems were also tackled from the angle of parametric uncertainty for each model by first conducting Morris sensitivity analysis to identify important parameters and then conducting Monte Carlo simulations for the important parameters. The uncertainty analysis is general and suitable for tackling similar problems; the Morris sensitivity analysis has been utilized to date in only a limited number of regional groundwater modeling. The simulated Qy values were evaluated by using three kinds of calibration data (i.e., hydraulic head observations, discharge estimates, and constant‐head boundary flow estimates). The evaluation results indicate that, within the current DVRFS modeling framework, the Qy estimate can only be reduced to about half of the original estimate without severely deteriorating the goodness‐of‐fit to the calibration data. The evaluation results also indicate that it is necessary to develop a new hydrogeological framework to produce new flow patterns in the DVRFS model. The issues of hydrogeology and boundary flow are being addressed in a new version of the DVRFS model planned for release by the U.S. Geological Survey.  相似文献   

2.
The values of parameters in a groundwater flow model govern the precision of predictions of future system behavior. Predictive precision, thus, typically depends on an ability to infer values of system properties from historical measurements through calibration. When such data are scarce, or when their information content with respect to parameters that are most relevant to predictions of interest is weak, predictive uncertainty may be high, even if the model is "calibrated." Recent advances help recognize this condition, quantitatively evaluate predictive uncertainty, and suggest a path toward improved predictive accuracy by identifying sources of predictive uncertainty and by determining what observations will most effectively reduce this uncertainty. We demonstrate linear and nonlinear predictive error/uncertainty analyses as applied to a groundwater flow model of Yucca Mountain, Nevada, the United States' proposed site for disposal of high-level radioactive waste. Linear and nonlinear uncertainty analyses are readily implemented as an adjunct to model calibration with medium to high parameterization density. Linear analysis yields contributions made by each parameter to a prediction's uncertainty and the worth of different observations, both existing and yet-to-be-gathered, toward reducing this uncertainty. Nonlinear analysis provides more accurate characterization of the uncertainty of model predictions while yielding their (approximate) probability distribution functions. This article applies the above methods to a prediction of specific discharge and confirms the uncertainty bounds on specific discharge supplied in the Yucca Mountain Project License Application.  相似文献   

3.
In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.  相似文献   

4.
This study introduces Bayesian model averaging (BMA) to deal with model structure uncertainty in groundwater management decisions. A robust optimized policy should take into account model parameter uncertainty as well as uncertainty in imprecise model structure. Due to a limited amount of groundwater head data and hydraulic conductivity data, multiple simulation models are developed based on different head boundary condition values and semivariogram models of hydraulic conductivity. Instead of selecting the best simulation model, a variance-window-based BMA method is introduced to the management model to utilize all simulation models to predict chloride concentration. Given different semivariogram models, the spatially correlated hydraulic conductivity distributions are estimated by the generalized parameterization (GP) method that combines the Voronoi zones and the ordinary kriging (OK) estimates. The model weights of BMA are estimated by the Bayesian information criterion (BIC) and the variance window in the maximum likelihood estimation. The simulation models are then weighted to predict chloride concentrations within the constraints of the management model. The methodology is implemented to manage saltwater intrusion in the “1,500-foot” sand aquifer in the Baton Rouge area, Louisiana. The management model aims to obtain optimal joint operations of the hydraulic barrier system and the saltwater extraction system to mitigate saltwater intrusion. A genetic algorithm (GA) is used to obtain the optimal injection and extraction policies. Using the BMA predictions, higher injection rates and pumping rates are needed to cover more constraint violations, which do not occur if a single best model is used.  相似文献   

5.
Considering complexity in groundwater modeling can aid in selecting an optimal model, and can avoid over parameterization, model uncertainty, and misleading conclusions. This study was designed to determine the uncertainty arising from model complexity, and to identify how complexity affects model uncertainty. The Ajabshir aquifer, located in East Azerbaijan, Iran, was used for comprehensive hydrogeological studies and modeling. Six unique conceptual models with four different degrees of complexity measured by the number of calibrated model parameters (6, 10, 10, 13, 13 and 15 parameters) were compared and characterized with alternative geological interpretations, recharge estimates and boundary conditions. The models were developed with Model Muse and calibrated using UCODE with the same set of observed data of hydraulic head. Different methods were used to calculate model probability and model weight to explore model complexity, including Bayesian model averaging, model selection criteria, and multicriteria decision-making (MCDM). With the model selection criteria of AIC, AICc and BIC, the simplest model received the highest model probability. The model selection criterion, KIC, and the MCDM method, in addition to considering the quality of model fit between observed and simulated data and the number of calibrated parameters, also consider uncertainty in parameter estimates with a Fisher information matrix. KIC and MCDM selected a model with moderate complexity (10 parameters) and the best parameter estimation (model 3) as the best models, over another model with the same degree of complexity (model 2). The results of these comparisons show that in choosing between models, priority should be given to quality of the data and parameter estimation rather than degree of complexity.  相似文献   

6.
The modeling of groundwater flow in karst aquifers is a challenge due to the extreme heterogeneity of its hydraulic parameters and the duality in their discharge behavior, that is, rapid response of highly conductive karst conduits and delayed drainage of the low‐permeability fractured matrix after recharge events. There are a number of different modeling approaches for the simulation of the karst groundwater dynamics, applicable to different aquifer as well as modeling problem types, ranging from continuum models to double continuum models to discrete and hybrid models. This study presents the application of an equivalent porous model approach (EPM, single continuum model) to construct a steady‐state numerical flow model for an important karst aquifer, that is, the Western Mountain Aquifer Basin (WMAB), shared by Israel and the West‐Bank, using MODFLOW2000. The WMAB was used as a catchment since it is a well‐constrained catchment with well‐defined recharge and discharge components and therefore allows a control on the modeling approach, a very rare opportunity for karst aquifer modeling. The model demonstrates the applicability of equivalent porous medium models for the simulation of karst systems, despite their large contrast in hydraulic conductivities. As long as the simulated saturated volume is large enough to average out the local influence of karst conduits and as long as transport velocities are not an issue, EPM models excellently simulate the observed head distribution. The model serves as a starting basis that will be used as a reference for developing a long‐term dynamic model for the WMAB, starting from the pre‐development period (i.e., 1940s) up to date.  相似文献   

7.
A cross‐sectional model, based on the two dimensional groundwater flow equation of Edelman, was applied at seven transects distributed over four geological cross sections to estimate groundwater heads and recharge from/or groundwater discharge to Lake Nasser. The lake with a length of 500 km and an average width of 12 km was created over the period 1964–1970, the time for constructing the Aswan High Dam (AHD). The model, constrained by regional‐scale groundwater flow and groundwater head data in the vicinity of the lake, was successfully calibrated to timeseries of piezometeric heads collected at the cross sections in the period 1965–2004. Inverse modeling yielded high values for the horizontal hydraulic conductivity in the range of 6.0 to 31.1 m day?1 and storage coefficient between 0.01 and 0.40. The results showed the existence of a strong vertical anisotropy of the aquifer. The calibrated horizontal permeability is systematically higher than the vertical permeability (≈1000:1). The calibrated model was used to explore the recharge from/or groundwater discharge to Lake Nasser at the seven transects for a 40‐year period, i.e. from 1965 to 2004. The analysis for the last 20‐year period, 1985–2004, revealed that recharge from Lake Nasser reduced by 37% compared to the estimates for the first 20‐year period, 1965–1984. In the period 1965–2004, seepage of Lake Nasser to the surrounding was estimated at 1.15 × 109 m3 year?1. This led to a significant rise of the groundwater table. Variance‐based sensitivity and uncertainty analysis on the Edelman results were conducted applying quasi‐Monte Carlo sequences (Latin Hypercube sampling). The maximum standard deviation of the total uncertainty on the groundwater table was 0.88 m at Toshka (west of the lake). The distance from the lake, followed by the storage coefficient and hydraulic conductivity, were identified as the most sensitive parameters. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

8.
Stochastic environmental risk assessment considers the effects of numerous biological, chemical, physical, behavioral and physiological processes that involve elements of uncertainty and variability. A methodology for predicting health risks to individuals from contaminated groundwater is presented that incorporates the elements of uncertainty and variability in geological heterogeneity, physiological exposure parameters, and in cancer potency. An idealized groundwater basin is used to perform a parametric sensitivity study to assess the relative impact of (a) geologic uncertainty, (b) behavioral and physiological variability in human exposure and (c) uncertainty in cancer potency on the prediction of increased cancer risk to individuals in a population exposed to contaminants in household water supplied from groundwater. A two-dimensional distribution (or surface) of human health risk was generated as a result of the simulations. Cuts in this surface (fractiles of variability and percentiles of uncertainty) are then used as a measure of relative importance of various model components on total uncertainty and variability. A case study for perchloroethylene or PCE, shows that uncertainty and variability in hydraulic conductivity play an important role in predicting human health risk that is on the same order of influence as uncertainty of cancer potency.  相似文献   

9.
This paper proposes an approach to estimate groundwater recharge using an optimization‐based water‐table fluctuation method combined with a groundwater balance model in an arid hardrock‐alluvium region, located at the Oman–United Arab Emirates border. We introduce an “effective hardrock thickness” term to identify the percentage of the considered hardrock thickness in which effective groundwater flow takes place. The proposed method is based upon a Thiessen polygon zoning approach. The method includes subpolygons to represent specific geologic units and to enhance the confidence of the estimated groundwater recharge. Two linear and 1 nonlinear submodels were developed to evaluate the model components for the calibration (October 1996 to September 2008) and validation (October 2008 to September 2013) periods. Long‐term annual groundwater recharge from rainfall and return flow over the model domain are estimated as 24.62 and 5.71 Mm3, respectively, while the effective groundwater flow circulation is found to occur in the upper 7% of the known hardrock thickness (42 m), confirming conclusions of previous field studies. Considering a total difference in groundwater levels between eastern and western points of the study area of the order of 220 m and a 12‐year monthly calibration period, a weighted root mean squared error in predicted groundwater elevation of 2.75 m is considered quite reasonable for the study area characterized by remarkable geological and hydrogeological diversity. The proposed approach provides an efficient and robust method to estimate groundwater recharge in regions with a complex geological setting in which interaction between fractured and porous media cannot be easily assessed.  相似文献   

10.
The use of detailed groundwater models to simulate complex environmental processes can be hampered by (1) long run‐times and (2) a penchant for solution convergence problems. Collectively, these can undermine the ability of a modeler to reduce and quantify predictive uncertainty, and therefore limit the use of such detailed models in the decision‐making context. We explain and demonstrate a novel approach to calibration and the exploration of posterior predictive uncertainty, of a complex model, that can overcome these problems in many modelling contexts. The methodology relies on conjunctive use of a simplified surrogate version of the complex model in combination with the complex model itself. The methodology employs gradient‐based subspace analysis and is thus readily adapted for use in highly parameterized contexts. In its most basic form, one or more surrogate models are used for calculation of the partial derivatives that collectively comprise the Jacobian matrix. Meanwhile, testing of parameter upgrades and the making of predictions is done by the original complex model. The methodology is demonstrated using a density‐dependent seawater intrusion model in which the model domain is characterized by a heterogeneous distribution of hydraulic conductivity.  相似文献   

11.
The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance‐constrained (CC) programming with Bayesian model averaging (BMA) as a BMA‐CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA‐CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA‐CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the “1500‐foot” sand and the “1700‐foot” sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive.  相似文献   

12.
Simulating groundwater flow in basin‐fill aquifers of the semiarid southwestern United States commonly requires decisions about how to distribute aquifer recharge. Precipitation can recharge basin‐fill aquifers by direct infiltration and transport through faults and fractures in the high‐elevation areas, by flowing overland through high‐elevation areas to infiltrate at basin‐fill margins along mountain fronts, by flowing overland to infiltrate along ephemeral channels that often traverse basins in the area, or by some combination of these processes. The importance of accurately simulating recharge distributions is a current topic of discussion among hydrologists and water managers in the region, but no comparative study has been performed to analyze the effects of different recharge distributions on groundwater simulations. This study investigates the importance of the distribution of aquifer recharge in simulating regional groundwater flow in basin‐fill aquifers by calibrating a groundwater‐flow model to four different recharge distributions, all with the same total amount of recharge. Similarities are seen in results from steady‐state models for optimized hydraulic conductivity values, fit of simulated to observed hydraulic heads, and composite scaled sensitivities of conductivity parameter zones. Transient simulations with hypothetical storage properties and pumping rates produce similar capture rates and storage change results, but differences are noted in the rate of drawdown at some well locations owing to the differences in optimized hydraulic conductivity. Depending on whether the purpose of the groundwater model is to simulate changes in groundwater levels or changes in storage and capture, the distribution of aquifer recharge may or may not be of primary importance.  相似文献   

13.
The estimation of recharge through groundwater model calibration is hampered by the nonuniqueness of recharge and aquifer parameter values. It has been shown recently that the estimability of spatially distributed recharge through calibration of steady‐state models for practical situations (i.e., real‐world, field‐scale aquifer settings) is limited by the need for excessive amounts of hydraulic‐parameter and groundwater‐level data. However, the extent to which temporal recharge variability can be informed through transient model calibration, which involves larger water‐level datasets, but requires the additional consideration of storage parameters, is presently unknown for practical situations. In this study, time‐varying recharge estimates, inferred through calibration of a field‐scale highly parameterized groundwater model, are systematically investigated subject to changes in (1) the degree to which hydraulic parameters including hydraulic conductivity (K) and specific yield (Sy) are constrained, (2) the number of water‐level calibration targets, and (3) the temporal resolution (up to monthly time steps) at which recharge is estimated. The analysis involves the use of a synthetic reality (a reference model) based on a groundwater model of Uley South Basin, South Australia. Identifiability statistics are used to evaluate the ability of recharge and hydraulic parameters to be estimated uniquely. Results show that reasonable estimates of monthly recharge (<30% recharge root‐mean‐squared error) require a considerable amount of transient water‐level data, and that the spatial distribution of K is known. Joint estimation of recharge, Sy and K, however, precludes reasonable inference of recharge and hydraulic parameter values. We conclude that the estimation of temporal recharge variability through calibration may be impractical for real‐world settings.  相似文献   

14.
We consider the response of a deep unconfined horizontal aquifer to steady, annual, and monthly recharge. A groundwater divide and a zero head reservoir constrain the aquifer, so that sinusoidal monthly and aperiodic annual recharge fluctuations create transient specific discharge near the reservoir and an unsteady water table elevation inland. One existing and two new long-term data sets from the Plymouth-Carver Aquifer in southeastern Massachusetts calibrate and confirm hydraulic properties in a set of analytical models. [Geohydrology and simulated groundwater flow, 1992] data and a new power law for tritiugenic helium to tritium ratios calibrate the steady recharge that drives the classical parabolic model of steady hydraulics [Applied Hydrogeology, 2001]. Observed water table and gradient fluctuations calibrate the transient recharge models. In the latter regard, monitoring wells within 1 km of Buttermilk Bay exhibit appreciable specific discharge and reduced water table fluctuations. We apply [Trans Am Geophys Union 32(1951)238] periodic model to the monthly hydraulics and a recharge convolution integral [J Hydrol 126(1991)315] to annual flow. An infiltration fraction of 0.79 and a consumptive use coefficient of 1.08×10−8 m/s °C relate recharge to precipitation and daylight weighted temperature across all three time scales. Errors associated with this recharge relation decrease with increasing time scale.  相似文献   

15.
Highly detailed physically based groundwater models are often applied to make predictions of system states under unknown forcing. The required analysis of uncertainty is often unfeasible due to the high computational demand. We combine two possible solution strategies: (1) the use of faster surrogate models; and (2) a robust data worth analysis combining quick first-order second-moment uncertainty quantification with null-space Monte Carlo techniques to account for parametric uncertainty. A structurally and parametrically simplified model and a proper orthogonal decomposition (POD) surrogate are investigated. Data worth estimations by both surrogates are compared against estimates by a complex MODFLOW benchmark model of an aquifer in New Zealand. Data worth is defined as the change in post-calibration predictive uncertainty of groundwater head, river-groundwater exchange flux, and drain flux data, compared to the calibrated model. It incorporates existing observations, potential new measurements of system states (“additional” data) as well as knowledge of model parameters (“parametric” data). The data worth analysis is extended to account for non-uniqueness of model parameters by null-space Monte Carlo sampling. Data worth estimates of the surrogates and the benchmark suggest good agreement for both surrogates in estimating worth of existing data. The structural simplification surrogate only partially reproduces the worth of “additional” data and is unable to estimate “parametric” data, while the POD model is in agreement with the complex benchmark for both “additional” and “parametric” data. The variance of the POD data worth estimates suggests the need to account for parameter non-uniqueness, like presented here, for robust results.  相似文献   

16.
A key point in the application of multi‐model Bayesian averaging techniques to assess the predictive uncertainty in groundwater modelling applications is the definition of prior model probabilities, which reflect the prior perception about the plausibility of alternative models. In this work the influence of prior knowledge and prior model probabilities on posterior model probabilities, multi‐model predictions, and conceptual model uncertainty estimations is analysed. The sensitivity to prior model probabilities is assessed using an extensive numerical analysis in which the prior probability space of a set of plausible conceptualizations is discretized to obtain a large ensemble of possible combinations of prior model probabilities. Additionally, the value of prior knowledge about alternative models in reducing conceptual model uncertainty is assessed by considering three example knowledge states, expressed as quantitative relations among the alternative models. A constrained maximum entropy approach is used to find the set of prior model probabilities that correspond to the different prior knowledge states. For illustrative purposes, a three‐dimensional hypothetical setup approximated by seven alternative conceptual models is employed. Results show that posterior model probabilities, leading moments of the predictive distributions and estimations of conceptual model uncertainty are very sensitive to prior model probabilities, indicating the relevance of selecting proper prior probabilities. Additionally, including proper prior knowledge improves the predictive performance of the multi‐model approach, expressed by reductions of the multi‐model prediction variances by up to 60% compared with a non‐informative case. However, the ratio between‐model to total variance does not substantially decrease. This suggests that the contribution of conceptual model uncertainty to the total variance cannot be further reduced based only on prior knowledge about the plausibility of alternative models. These results advocate including proper prior knowledge about alternative conceptualizations in combination with extra conditioning data to further reduce conceptual model uncertainty in groundwater modelling predictions. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

17.
The integrated hydrological modelling system, IHMS, has been described in detail in Part 1 of this paper. The system comprises three models: Distributed Catchment Scale Model (DiCaSM), MODFLOW (v96 and v2000) and SWI. The DiCaSM simulates different components of the unsaturated zone water balance, including groundwater recharge. The recharge output from DiCaSM is used as input to the saturated zone model MODFLOW, which subsequently calculates groundwater flows and head distributions. The main objectives of this paper are: (1) to show the way more accurate predictions of groundwater levels in two Cyprus catchments can be obtained using improved estimates of groundwater recharge from the catchment water balance, and (2) to demonstrate the interface utility that simulates communication between unsaturated and saturated zone models and allows the transmission of data between the two models at the required spatial and temporal scales. The linked models can be used to predict the impact of future climate change on surface and groundwater resources and to estimate the future water supply shortfall in the island up to 2050. The DiCaSM unsaturated zone model was successfully calibrated and validated against stream flows with reasonable values for goodness of fit as shown by the Nash‐Sutcliffe criterion. Groundwater recharge obtained from the successful tests was applied at various spatial and temporal scales to the Kouris and Akrotiri catchments in Cyprus. These recharge values produced good estimates of groundwater levels in both catchments. Once calibrated, the model was run using a number of possible future climate change scenarios. The results showed that by 2050, groundwater and surface water supplies would decrease by 35% and 24% for Kouris and 20% and 17% for Akrotiri, respectively. The gap between water supply and demand showed a linear increase with time. The results suggest that IHMS can be used as an effective tool for water authorities and decision makers to help balance demand and supply on the island. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

18.
Methods for the analysis of the formation of river water chemistry based on mixing models are discussed. An analytical solution for a mixing model of four recharge sources is given along with the results of its adaptation based on the materials of hydrochemical and hydrological observations over 2013 and 2014 in drainage basins in Primorski Krai. The analysis and calculations revealed four components of river recharge in these years: rainwater, two types of subsoil water, and groundwater, the latter forming the base runoff. The estimates of the mixing model with four sources and its tests showed a high quality of modeling.  相似文献   

19.
In distributed and coupled surface water–groundwater modelling, the uncertainty from the geological structure is unaccounted for if only one deterministic geological model is used. In the present study, the geological structural uncertainty is represented by multiple, stochastically generated geological models, which are used to develop hydrological model ensembles for the Norsminde catchment in Denmark. The geological models have been constructed using two types of field data, airborne geophysical data and borehole well log data. The use of airborne geophysical data in constructing stochastic geological models and followed by the application of such models to assess hydrological simulation uncertainty for both surface water and groundwater have not been previously studied. The results show that the hydrological ensemble based on geophysical data has a lower level of simulation uncertainty, but the ensemble based on borehole data is able to encapsulate more observation points for stream discharge simulation. The groundwater simulations are in general more sensitive to the changes in the geological structure than the stream discharge simulations, and in the deeper groundwater layers, there are larger variations between simulations within an ensemble than in the upper layers. The relationship between hydrological prediction uncertainties measured as the spread within the hydrological ensembles and the spatial aggregation scale of simulation results has been analysed using a representative elementary scale concept. The results show a clear increase of prediction uncertainty as the spatial scale decreases. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

20.
Groundwater modeling is undergoing a change from traditional stand-alone studies toward being an integrated part of holistic water resources management procedures. This is illustrated by the development in Denmark, where comprehensive national databases for geologic borehole data, groundwater-related geophysical data, geologic models, as well as a national groundwater-surface water model have been established and integrated to support water management. This has enhanced the benefits of using groundwater models. Based on insight gained from this Danish experience, a scientifically realistic scenario for the use of groundwater modeling in 2020 has been developed, in which groundwater models will be a part of sophisticated databases and modeling systems. The databases and numerical models will be seamlessly integrated, and the tasks of monitoring and modeling will be merged. Numerical models for atmospheric, surface water, and groundwater processes will be coupled in one integrated modeling system that can operate at a wide range of spatial scales. Furthermore, the management systems will be constructed with a focus on building credibility of model and data use among all stakeholders and on facilitating a learning process whereby data and models, as well as stakeholders' understanding of the system, are updated to currently available information. The key scientific challenges for achieving this are (1) developing new methodologies for integration of statistical and qualitative uncertainty; (2) mapping geological heterogeneity and developing scaling methodologies; (3) developing coupled model codes; and (4) developing integrated information systems, including quality assurance and uncertainty information that facilitate active stakeholder involvement and learning.  相似文献   

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