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Bearup L.A.,Integrated Groundwater Modeling Center | Maxwell R.M.,Integrated Groundwater Modeling Center | Mccray J.E.,Colorado School of Mines
Ecohydrology | Year: 2016

Current understanding of streamflow composition in mountain watersheds is often limited by inherent uncertainties and collection limitations in field data and assumptions associated with modelling techniques. Additional complexity arises in catchments experiencing land-cover change. Here, a hillslope model with fully integrated processes from the subsurface through the canopy is combined with Lagrangian particle tracking through the surface and subsurface domains to understand changes in flow paths and source waters with insect-induced tree death. This approach explicitly simulates end-member mixing by tracking parcels of water tagged as rain, snow, and pre-simulation ('old') groundwater and provides a method of separating outflows from these sources. Model simulations identify increases in subsurface water availability resulting from transpiration loss and altered canopy processes that increase throughfall and land-surface energy. Combined with changes in snowmelt timing, the shallower depth to saturation associated with tree death results in increased old groundwater contributions to streamflow. This shift in the source of outflow is consistent with prior field analysis of changing streamflow contributions with tree mortality from widespread insect infestation in the Rocky Mountains of North America. Model results also highlight mixing of old water and new precipitation within the groundwater end-member. Mixed hillslope outflows indicate that combinations of topography and precipitation can drive a range of signatures in groundwater inputs over meaningful time periods. Ultimately, this work and analysis of field observations provide insight into hillslope hydrologic processes and can serve as a platform for more complex simulations of land-cover perturbations to streamflow source partitioning. © 2016 John Wiley & Sons, Ltd.


Williams J.L.,Colorado School of Mines | Maxwell R.M.,Colorado School of Mines | Maxwell R.M.,Integrated Groundwater Modeling Center
Journal of Hydrometeorology | Year: 2011

Feedbacks between the land surface and the atmosphere, manifested as mass and energy fluxes, are strongly correlated with soil moisture, making soil moisture an important factor in land-atmosphere interactions. It is shown that a reduction of the uncertainty in subsurface properties such as hydraulic conductivity (K) propagates into the atmosphere, resulting in a reduction in uncertainty in land-atmosphere feedbacks that yields more accurate atmospheric predictions. Using the fully coupled groundwater-to-atmosphere model ParFlow-WRF, which couples the hydrologic model ParFlow with the Weather Research and Forecasting (WRF) atmospheric model, responses in land-atmosphere feedbacks and wind patterns due to subsurface heterogeneity are simulated. Ensembles are generated by varying the spatial location of subsurface properties while maintaining the global statistics and correlation structure. This approach is common to the hydrologic sciences but uncommon in atmospheric simulations where ensemble forecasts are commonly generated with perturbed initial conditions or multiple model parameterizations. It is clearly shown that different realizations of K produce variation in soil moisture, latent heat flux, and wind for both point and domain-averaged quantities. Using a single random field to represent a control case, varying amounts of K data are sampled and subsurface data are incorporated into conditional Monte Carlo ensembles to show that the difference between the ensemble mean prediction and the control saturation, latent heat flux, and wind speed are reduced significantly via conditioning of K. By reducing uncertainty associated with land-atmosphere feedback mechanisms, uncertainty is also reduced in both spatially distributed and domain-averaged wind speed magnitudes, thus improving the ability to make more accurate forecasts, which is important for many applications such as wind energy. © 2011 American Meteorological Society.


Maxwell R.M.,Integrated Groundwater Modeling Center
Advances in Water Resources | Year: 2013

A terrain-following grid formulation (TFG) is presented for simulation of coupled variably-saturated subsurface and surface water flow. The TFG is introduced into the integrated hydrologic model, ParFlow, which uses an implicit, Newton Krylov solution technique. The analytical Jacobian is also formulated and presented and both the diagonal and non-symmetric terms are used to precondition the Krylov linear system. The new formulation is verified against an orthogonal stencil and is shown to provide increased accuracy at lower lateral spatial discretization for hillslope simulations. Using TFG, efficient scaling to a large number of processors (16,384) and a large domain size (8.1 Billion unknowns) is shown. This demonstrates the applicability of this formulation to high-resolution, large-spatial extent hydrology applications where topographic effects are important. Furthermore, cases where the analytical Jacobian is used for the Newton iteration and as a non-symmetric preconditioner for the linear system are shown to have faster computation times and better scaling. This demonstrates the importance of solver efficiency in parallel scaling through the use of an appropriate preconditioner. © 2012 Elsevier Ltd.


Siirila E.R.,Colorado School of Mines | Maxwell R.M.,Colorado School of Mines | Maxwell R.M.,Integrated Groundwater Modeling Center
Water Resources Research | Year: 2012

The interplay between regions of high and low hydraulic conductivity, degree of aquifer stratification, and rate-dependent geochemical reactions in heterogeneous flow fields is investigated, focusing on impacts of kinetic sorption and local dispersion on plume retardation and channeling. Human health risk is used as an endpoint for comparison via a nested Monte Carlo scheme, explicitly considering joint uncertainty and variability. Kinetic sorption is simulated with finely resolved, large-scale domains to identify hydrogeologic conditions where reactions are either rate limited (nonreactive), in equilibrium (linear equilibrium assumption is appropriate), or are sensitive to time-dependent kinetic reactions. By utilizing stochastic ensembles, effective equilibrium conditions are examined, in addition to parameter interplay. In particular, the effects of preferential flow pathways and solute mixing at the field-scale (marcrodispersion) and subgrid (local dispersion, LD) are examined for varying degrees of stratification and regional groundwater velocities (v). Results show effective reaction rates of kinetic ensembles with the inclusion of LD yield disequilibrium transport, even for averaged (or global) Damkholer numbers associated with equilibrium transport. Solute behavior includes an additive tailing effect, a retarded peak time, and results in an increased cancer risk. The inclusion of LD for nonreactive solutes in highly anisotropic media results in either induced solute retardation or acceleration, a new finding given that LD has previously been shown to affect only the concentration variance. The distribution, magnitude, and associated uncertainty of cancer risk are controlled by the up scaling of these small-scale processes, but are strongly dependent on v and the source term.


Siirila E.R.,Colorado School of Mines | Maxwell R.M.,Colorado School of Mines | Maxwell R.M.,Integrated Groundwater Modeling Center
Science of the Total Environment | Year: 2012

We present a new Time Dependent Risk Assessment (TDRA) that stochastically considers how joint uncertainty and inter-individual variability (JUV) associated with human health risk change as a function of time. In contrast to traditional, time independent assessments of risk, this new formulation relays information on when the risk occurs, how long the duration of risk is, and how risk changes with time. Because the true exposure duration (. ED) is often uncertain in a risk assessment, we also investigate how varying the magnitude of fixed size durations (ranging between 5 and 70. years) of this parameter affects the distribution of risk in both the time independent and dependent methodologies. To illustrate this new formulation and to investigate these mechanisms for sensitivity, an example of arsenic contaminated groundwater is used in conjunction with two scenarios of different environmental concentration signals resulting from rate dependencies in geochemical reactions. Cancer risk is computed and compared using environmental concentration ensembles modeled with sorption as 1) a linear equilibrium assumption (LEA) and 2) first order kinetics (Kin). Results show that the information attained in the new time dependent methodology reveals how the uncertainty in other time-dependent processes in the risk assessment may influence the uncertainty in risk. We also show that individual susceptibility also affects how risk changes in time, information that would otherwise be lost in the traditional, time independent methodology. These results are especially pertinent for forecasting risk in time, and for risk managers who are assessing the uncertainty of risk. © 2012 Elsevier B.V..

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