Use of Numerical Groundwater Modeling to Evaluate Uncertainty in Conceptual Models of Recharge and Hydrostratigraphy

Numerical groundwater models are based on conceptualizations of hydrogeologic systems that are by necessity developed from limited information and therefore are simplifications of real conditions. Each aspect (e.g. recharge, hydrostratigraphy, boundary conditions) of the groundwater model is often based on a single conceptual model that is considered to be the best representation given the available data. However, the very nature of their construction means that each conceptual model is inherently uncertain and the available information may be insufficient to refute plausible alternatives, thereby raising the possibility that the flow model is underestimating overall uncertainty. In this study we use the Death Valley Regional Flow System model developed by the U.S. Geological Survey as a framework to predict regional groundwater flow southward into Yucca Flat on the Nevada Test Site. An important aspect of our work is to evaluate the uncertainty associated with multiple conceptual models of groundwater recharge and subsurface hydrostratigraphy and quantify the impacts of this uncertainty on model predictions. In our study, conceptual model uncertainty arises from two sources: (1) alternative interpretations of the hydrostratigraphy in the northern portion of Yucca Flat where, owing to sparse data, the hydrogeologic system can be conceptualized in different ways, and (2) uncertainty in groundwater recharge in the region as evidenced by the existence of several independent approaches for estimating this aspect of the hydrologic system. The composite prediction of groundwater flow is derived from the regional model that formally incorporates the uncertainty in these alternative input models using the maximum likelihood Bayesian model averaging method. An assessment of the joint predictive uncertainty of the input conceptual models is also produced. During this process, predictions of the alternative models are weighted by model probability, which is the degree of belief that a model is more plausible given available prior information (expert opinion) and site measurements (hydraulic head and groundwater flux). The results indicate that flow simulations in Yucca Flat are more sensitive to hydrostratigraphic model than recharge model. Furthermore, posterior model uncertainty is dominated by inter-model variance as opposed to intra-model variance, indicating that conceptual model uncertainty has greater impact on the results than parametric uncertainty. Without consideration of conceptual model uncertainty, uncertainty in the flow predictions would be significantly underestimated. Incorporation of the uncertainty in multiple conceptual models renders the groundwater flow model predictions more scientifically defensible

Studying Complex Aquifer Systems from Large-Scale Stratigraphy Development to Local Aquifer Storage and Recovery

Hydrostratigraphy model is an essential component of building valid groundwater models. Many challenges are associated with constructing hydrostratigraphy models which include geological complexities such as faults, domes, and angular unconformities. Developing a method with an emphasis on capturing big data to thoroughly inform large-scale models is one of the challenges addressed in the first part of this study. The method is predicated upon discretization of the study domain into tiles based on the geological dip direction and faults. The application of the method in the state of Louisiana with the utilization of more than 114000 well logs demonstrates promising results including identification of hydrostratigraphic characteristics for different aquifers, connections between the Mississippi River and the Red River and their alluviums, connections between state\u27s surface waters and aquifers, and identification of recharge zones. The Louisiana model also demonstrated two different sand patterns in southeast Louisiana which might have been caused by two depositional environments. Employment of the method in a groundwater flow modeling framework to build a flow model for the Chicot aquifer system in southwest Louisiana revealed the complexity of the aquifer system that contains highly interconnected aquifer sands. The groundwater flow analysis of the Chicot aquifer is of great importance because it is the most heavily pumped aquifer in the state as a part of the Coastal Lowland Aquifer System. The modeling results show that the storage loss due to groundwater pumping is offset by inflows from surficial recharge, rivers, and boundaries. The two large cones of depression created by the agricultural pumping in the east and by the industrial pumping in the west represent the key feature in the Chicot aquifer system. As the final goal of this study, an aquifer storage and recovery operation in south of the Chicot aquifer was studied. The focus of this part was on optimal scheduling of an aquifer storage and recovery (ASR) operation while addressing parameter uncertainty for one cycle where an injection season is followed by a pumping season. This end was achieved via utilization of a supervised learning method for surrogated modeling and use of an evolutionary optimization method. The results indicate that artificial neural network (ANN) is a promising tool for evaluation of ASR efficiency. The hydraulic conductivity and longitudinal dispersivity were found to be the most significant parameters which affect ASR

Multiple‑point statistical modeling of three‑dimensional glacial aquifer heterogeneity for improved groundwater management

Quaternary glacial aquifers are important water sources for irrigation in many agricultural regions, including eastern Nebraska, USA. Quaternary glacial aquifers are heterogeneous, with juxtaposed low-permeability and high-permeability hydrofacies. Managing groundwater in such aquifers requires a realistic groundwater-flow model parameterization, and characterization of the aquifer geometry, spatial distribution of aquifer properties, and local aquifer interconnectedness. Despite its importance in considering uncertainty during decision-making, hydrofacies probabilities generated from multiple-point statistics (MPS) are not widely applied for groundwater model parameterization and groundwater management zone delineation. This study used a combination of soft data, a cognitive training image, and hard data to generate 100 three-dimensional (3D) conditional aquifer heterogeneity realizations. The most probable model (probability of hydrofacies) was then computed at node spacing of 200 × 200 × 3 m and validated using groundwater-level hydrographs. The resulting hydrofacies probability grids revealed variations in aquifer geometry, locally disconnected aquifer systems, recharge pathways, and hydrologic barriers. The profiles from hydrofacies probability at various locations show spatial variability of the streambed and aquifer connectivity. Groundwater-level hydrographs show evidence of these aquifer characteristics, verifying the general structure of the model. Using the MPS-generated 3D hydrofacies probability and hydrologic data, a novel workflow was developed in order to better define high-resolution groundwater management zones and strategies. In general, the conditional probability of hydrofacies helps improve the understanding of glacial aquifer heterogeneity, the characterization of aquifer-to-aquifer and streambed-aquifer connections, and the delineation of groundwater management zones. This MPS workflow can be adapted to other areas for modeling 3D aquifer heterogeneity using multisource data

Simulating dioxane transport in a heterogeneous glacial aquifer system (Washtenaw County, Michigan) using publicly available models and data

The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model\u27s ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality\u27s residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained

Investigation of modern leakage based on numerical and geochemical modeling near a municipal well field in Memphis, Tennessee.

Local leakage processes and potential migration pathways of modern water (\u3c60 \u3eyears) from the shallow aquifer, into the underlying semiconfined Memphis aquifer, were evaluated to assess the vulnerability of groundwater in Memphis Light, Gas and Water’s (MLGW) Sheahan well field. To identify the source(s) and pathways of modern water, integrated hydrostratigraphic analysis, numerical modeling, hydrologic tracers, and geochemical modeling were utilized. The percentage of modern water present in Memphis aquifer production wells is estimated using inverse geochemical modeling, lumped parameter modeling, and solute transport modeling with Modular Transport, 3-Dimensional, Multi-Species model (MT3DMS). The mixing percentages determined from lumped parameter modeling and MT3DMS are generally in agreement except well 87A, estimating up to 14.3% and 15.3%, respectively. The significant mixing fraction difference at 87A might account for the missing hydrogeologic connection in the groundwater model on the eastern part of the well field. Estimates for the apparent age of the modern water derived from MT3DMS fall within the age range obtained from environmental tracer data (3H/3He). However, the age distributions from the MT3DMS model are limited to 60 years or less, resulting in a younger mean age than the tracer-based apparent ages. Thus, the MT3DMS model, calibrated with long-term tracer data could simulate the mean age and mixing percentage of modern water while emphasizing the importance of accurate hydrogeologic conceptualizations at the Sheahan well field. As a result, tracer data and solute transport modeling can identify vulnerabilities and ensure the long-term sustainability of the Sheahan well field

Models for managing the deep aquifer in Bangladesh

In southern Bangladesh excessive levels of As in shallow groundwater have led to deeper groundwater becoming the main alternative source of As-free potable water. Hydrogeological configuration indicates that tube-wells pumping from these depths may be vulnerable to As breakthrough from shallow levels. The thesis explores a range of methods of representing lithological heterogeneity of the Bengal Aquifer System (BAS) in models of groundwater flow and travel time. The aim is to support models of arsenic (As) flux to the deep groundwater flow-system of BAS, and hence to aid assessment of the vulnerability of deep groundwater to invasion by As. The research uses an array of geological information including geophysical logs (n=12), hydrocarbon exploration data (n=11), and drillers' logs (n=589) from a 5000 km2 area to characterise the aquifer heterogeneity as a basis for alternative representations of hydrogeological structure in groundwater flow modelling. Groundwater samples from southern Bangladesh were analysed for 14C in order to determine groundwater age (n=23) and for hydrochemical (n=75) and isotopic (n=50) characterisation. A new hypothesis `SiHA (Silt-clay layers influence Hierarchical groundwater flow systems and Arsenic progression in aquifer)' is presented which integrates sedimentological heterogeneities, groundwater flow, and geochemical processes to explain the distribution and geological evolution of groundwater As in the aquifer. The hypothesis explains the spatio-vertical variability of groundwater As concentration by 'groundwater flow systems and differential flushing' in the aquifer. Groundwater flow models based on eight different yet plausible aquifer representations provide adequate simulations of hydraulic head, but contrasting implications for well catchments and travel times. The better representations are judged by comparing model outcomes of travel time with groundwater age determination using 14C. Comparisons demonstrate the importance of incorporating hydrostratigraphy and spatial heterogeneity in order to optimise model representations, and implications for the security of As-free deep groundwater in the BAS

A Groundwater Flow Model to Aid in Water Resource Management for the Carraipia Basin in the coastal semi-arid region of La Guajira state (Colombia)

About 160,000 inhabitants live in the 1,600 square kilometers Carraipia River Basin located in northeastern Colombia and northwestern Venezuela. Historically, water has been supplied to the inhabitants in this arid coastal region by shallow dug wells. Water supplied by these wells is frequently of poor quality due to high concentrations of total dissolved solids (TDS). Recently, due to the increasing demand for water, numerous deep wells have been drilled in the region to supply water to rural and urban areas from deep aquifers. Colombian agencies seek more quantitative information on groundwater resources, driven by increasingly severe water shortages over the past decade that have adversely affected the quality of life for the people living in La Guajira state. A groundwater flow computer model has been constructed to provide a tool for assisting with the management of groundwater resources in the Carraipia River Basin. This model is based on geologic maps, hydraulic test wells, geologic field data, and other sparse information to create a highly idealized model of the hydrostratigraphy of this basin. Before creating the three-dimensional groundwater model, stratigraphic columns and cross sections were prepared to guide conceptualization of the idealized groundwater flow model. Available data used to develop the conceptual hydrogeological model includes the following: precipitation data measured in the drainage basin (CORPOGUAJIRA et al., 2006), evapotranspiration data calculated from temperature measurements (CORPOGUAJIRA et al., 2006), hydraulic well tests (Colombian Geological Survey, personal communication), and hydraulic head data measured in shallow wells. The model includes interpreted and conceptualized aquifer parameters, such as hydraulic conductivity (K), and estimated current and future pumping rates. Finally, water table data scattered over the basin area are used to calibrate the model. The regional groundwater system is represented mathematically, using the software ModelMuse and MODFLOW-2005 that discretizes the volume of the basin and the timing of the hydraulic stresses, and balances groundwater flow equations based on input files that define hydraulic stresses. The goal of this project is to use the current stipulated pumping regime in the Carraipia Basin to determine if this groundwater extraction is environmentally sustainable. A secondary goal is to assess how groundwater extraction and other hydraulic stresses impacts the extent of saltwater intrusion. Currently, data are very sparse and topography is poorly constrained. The groundwater model is an idealized representation to establish a starting point for future refinement. In addition, improving the understanding of groundwater flow processes, this model: Can be used to help estimate sustainable yields, Can simulate the impact of different pumping scenarios, Can help identify critical data needed to improve the hydrogeologic characterization of the Carraipia Basin