Reed M. Maxwell

Development of a Coupled Land Surface and Groundwater Model

Abstract Traditional land surface models (LSMs) used for numerical weather simulation, climate projection, and as inputs to water management decision support systems, do not treat the LSM lower boundary in a fully process-based fashion. LSMs have evolved from a leaky-bucket approximation to more sophisticated land surface water and energy budget models that typically have a specified bottom layer flux to depict the lowest model layer exchange with deeper aquifers. The LSM lower boundary is often assumed zero flux or the soil moisture content is set to a constant value; an approach that while mass conservative, ignores processes that can alter surface fluxes, runoff, and water quantity and quality. Conversely, groundwater models (GWMs) for saturated and unsaturated water flow, while addressing important features such as subsurface heterogeneity and three-dimensional flow, often have overly simplified upper boundary conditions that ignore soil heating, runoff, snow, and root-zone uptake. In the present stud...

Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model

[1] The influence of groundwater dynamics on the energy balance at the land surface is studied using an integrated, distributed watershed modeling platform. This model includes the mass and energy balance at the land surface; three-dimensional variably saturated subsurface flow; explicit representation of the water table; and overland flow. The model is applied to the Little Washita watershed in Central Oklahoma, USA and compared to runoff, soil moisture and energy flux observations. The connection between groundwater dynamics and the land surface energy balance is studied using a variety of conventional and spatial statistical measures. For a number of energy variables a strong interconnection is demonstrated with water table depth. This connection varies seasonally and spatially depending on the spatial composition of water table depth. A theoretical critical water table depth range is presented where a strong sensitivity between groundwater and land-surface processes may be observed. For this particular watershed, a critical depth range is established between 1 and 5 m in which the land surface energy budget is most sensitive to groundwater storage. Finally, concrete recommendations are put forth to characterize this interconnection in the field.

Multiphysics simulations: Challenges and opportunities

We consider multiphysics applications from algorithmic and architectural perspectives, where “algorithmic” includes both mathematical analysis and computational complexity, and “architectural” includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

Regional Differences in the Influence of Irrigation on Climate

Abstract A global climate model experiment is performed to evaluate the effect of irrigation on temperatures in several major irrigated regions of the world. The Community Atmosphere Model, version 3.3, was modified to represent irrigation for the fraction of each grid cell equipped for irrigation according to datasets from the Food and Agriculture Organization. Results indicate substantial regional differences in the magnitude of irrigation-induced cooling, which are attributed to three primary factors: differences in extent of the irrigated area, differences in the simulated soil moisture for the control simulation (without irrigation), and the nature of cloud response to irrigation. The last factor appeared especially important for the dry season in India, although further analysis with other models and observations are needed to verify this feedback. Comparison with observed temperatures revealed substantially lower biases in several regions for the simulation with irrigation than for the control, sug...

Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks

There are a growing number of large-scale, complex hydrologic models that are capable of simulating integrated surface and subsurface flow. Many are coupled to land-surface energy balance models, biogeochemical and ecological process models, and atmospheric models. Although they are being increasingly applied for hydrologic prediction and environmental understanding, very little formal verification and/or benchmarking of these models has been performed. Here we present the results of an intercomparison study of seven coupled surface-subsurface models based on a series of benchmark problems. All the models simultaneously solve adapted forms of the Richards and shallow water equations, based on fully 3-D or mixed (1-D vadose zone and 2-D groundwater) formulations for subsurface flow and 1-D (rill flow) or 2-D (sheet flow) conceptualizations for surface routing. A range of approaches is used for the solution of the coupled equations, including global implicit, sequential iterative, and asynchronous linking, and various strategies are used to enforce flux and pressure continuity at the surface-subsurface interface. The simulation results show good agreement for the simpler test cases, while the more complicated test cases bring out some of the differences in physical process representations and numerical solution approaches between the models. Benchmarks with more traditional runoff generating mechanisms, such as excess infiltration and saturation, demonstrate more agreement between models, while benchmarks with heterogeneity and complex water table dynamics highlight differences in model formulation. In general, all the models demonstrate the same qualitative behavior, thus building confidence in their use for hydrologic applications.

The concept of block-effective macrodispersivity and a unified approach for grid-scale- and plume-scale-dependent transport

We present a new approach for modelling macrodispersivity in spatially variable velocity fields, such as exist in geologically heterogeneous formations. Considering a spectral representation of the velocity, it is recognized that numerical models usually capture low-wavenumber effects, while the large-wavenumber effects, associated with subgrid block variability, are suppressed. While this suppression is avoidable if the heterogeneity is captured at minute detail, that goal is impossible to achieve in all but the most trivial cases. Representing the effects of the suppressed variability in the models is made possible using the proposed concept of block-effective macrodispersivity. A tensor is developed, which we refer to as the block-effective macrodispersivity tensor, whose terms are functions of the characteristic length scales of heterogeneity, as well as the length scales of the models homogenized areas, or numerical grid blocks. Closed-form expressions are developed for small variability in the log-conductivity and unidirectional mean flow, and are tested numerically. The use of the block-effective macrodispersivities allows conditioning of the velocity field on the measurements on the one hand, while accounting for the effects of unmodelled heterogeneity on the other, in a numerically reasonable set-up. It is shown that the effects of the grid scale are similar to those of the plume scale in terms of filtering out the effects of portions of the velocity spectrum. Hence it is easy to expand the concept of the block-effective dispersivity to account for the scale of the solute body and the pore-scale dispersion.

A methodology to integrate site characterization information into groundwater‐driven health risk assessment

A methodology is presented that incorporates site characterization information (in the form of hydraulic conductivity measurements) into a health risk assessment to individuals utilizing contaminated household water developed from groundwater sources. This methodology explicitly incorporates uncertainty (including the statistical parameter uncertainty arising from a limited number of hydraulic conductivity measurements) and variability (such as the variability in individual physiology) in all parameters, resulting in a nested Monte Carlo procedure. The methodology is demonstrated using a hypothetical case study where the sensitivity of various end points (including human health risk) to increased sampling of hydraulic conductivity are explored. It is shown that an increase in the number of measurements of hydraulic conductivity decreases the error in and uncertainty of predicted human health risk. Cost-benefit curves are developed and incorporated into a simple decision framework to determine the number of samples of hydraulic conductivity that are needed to accurately predict the human health risk from a contaminated site.

Bark beetle infestation impacts on nutrient cycling, water quality and interdependent hydrological effects

Bark beetle populations have drastically increased in magnitude over the last several decades leading to the largest-scale tree mortality ever recorded from an insect infestation on multiple wooded continents. When the trees die, the loss of canopy and changes in water and nutrient uptake lead to observable changes in hydrology and biogeochemical cycling. This review aims to synthesize the current research on the effects of the bark beetle epidemic on nutrient cycling and water quality while integrating recent and relevant hydrological findings, along with suggesting necessary future research avenues. Studies generally agree that snow depth will increase in infested forests, though the magnitude is uncertain. Changes in evapotranspiration are more variable as decreased transpiration from tree death may be offset by increased understory evapotranspiration and ground evaporation. As a result of such competing hydrologic processes that can affect watershed biogeochemistry along with the inherent variability of natural watershed characteristics, water quality changes related to beetle infestation are difficult to predict and may be regionally distinct. However, tree-scale changes to soil–water chemistry (N, P, DOC and base cation concentrations and composition) are being observed in association with beetle outbreaks which ultimately could lead to larger-scale responses. The different temporal and spatial patterns of bark beetle infestations due to different beetle and tree species lead to inconsistent infestation impacts. Climatic variations and large-scale watershed responses provide a further challenge for predictions due to spatial heterogeneities within a single watershed; conflicting reports from different regions suggest that hydrologic and water quality impacts of the beetle on watersheds cannot be generalized. Research regarding the subsurface water and chemical flow-paths and residence times after a bark beetle epidemic is lacking and needs to be rigorously addressed to best predict watershed or regional-scale changes to soil–water, groundwater, and stream water chemistry.

On the development of a new methodology for groundwater-Driven health risk assessment

A methodology and hypothetical case study are presented for incorporation of uncertainty and variability into calculations of human health risk appropriate for regional, or basin-scale, groundwater management problems. Uncertainty in well water concentration is introduced through complex contaminant migration patterns in the subsurface. Variability is considered in parameters related to individual behavior patterns and biological effects and to groundwater extraction and distribution networks. A joint uncertainty and variability (JUV) analysis is used to generate a two-dimensional distribution or risk surface that spans both transport uncertainty as well as individual variability. Cuts in this distributional surface (fractiles of variability and percentiles of uncertainty) are presented and discussed. Comparisons with alternative approaches based upon deterministic transport models are also made. In addition, important distinctions are made between the case where household water is derived from the nearest well and the case where household water is mixed from many wells in a distribution system.

Development of a Coupled Groundwater–Atmosphere Model

Abstract Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface, and lower atmosphere. PF.WRF is a new model that is a combination of the Weather Research and Forecasting (WRF) atmospheric model and a parallel hydrology model (ParFlow) that fully integrates three-dimensional, variably saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the Noah land surface model (LSM). Here, the coupled model formulation and equations are presented and a balance of water between the subsurface, land surface, and atmosphere is verified. The improvement in important physical processes afforded by the coupled model using a number of semi-idealized simulations over the Little Washita watershed in the southern Great Plains is demonstrated. These simulations are initialized with a set of offline spinups to achieve a balanced state of ini...