Chaopeng Shen

An investigation of the effect of pore scale flow on average geochemical reaction rates using direct numerical simulation

An Investigation of the Effect of Pore Scale Flow on Average Geochemical Reaction Rates Using Direct Numerical Simulation Sergi Molins 1 David Trebotich 2 Carl I. Steefel 1 Chaopeng Shen 2 Earth Sciences Division Lawrence Berkeley National Laboratory One Cyclotron Road, Mail Stop 90R1116, Berkeley, California 94720, USA Computational Research Division Lawrence Berkeley National Laboratory One Cyclotron Road, Mail Stop 50A-1148, Berkeley, California 94720, USA

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.

Pore-scale controls on calcite dissolution rates from flow-through laboratory and numerical experiments.

A combination of experimental, imaging, and modeling techniques were applied to investigate the pore-scale transport and surface reaction controls on calcite dissolution under elevated pCO2 conditions. The laboratory experiment consisted of the injection of a solution at 4 bar pCO2 into a capillary tube packed with crushed calcite. A high resolution pore-scale numerical model was used to simulate the experiment based on a computational domain consisting of reactive calcite, pore space, and the capillary wall constructed from volumetric X-ray microtomography images. Simulated pore-scale effluent concentrations were higher than those measured by a factor of 1.8, with the largest component of the discrepancy related to uncertainties in the reaction rate model and its parameters. However, part of the discrepancy was apparently due to mass transport limitations to reactive surfaces, which were most pronounced near the inlet where larger diffusive boundary layers formed around grains and in slow-flowing pore spaces that exchanged mass by diffusion with fast flow paths. Although minor, the difference between pore- and continuum-scale results due to transport controls was discernible with the highly accurate methods employed and is expected to be more significant where heterogeneity is greater, as in natural subsurface materials.

Adaptive mesh refinement based on high order finite difference WENO scheme for multi-scale simulations

In this paper, we propose a finite difference AMR-WENO method for hyperbolic conservation laws. The proposed method combines the adaptive mesh refinement (AMR) framework [4,5] with the high order finite difference weighted essentially non-oscillatory (WENO) method in space and the total variation diminishing (TVD) Runge-Kutta (RK) method in time (WENO-RK) [18,10] by a high order coupling. Our goal is to realize mesh adaptivity in the AMR framework, while maintaining very high (higher than second) order accuracy of the WENO-RK method in the finite difference setting. The high order coupling of AMR and WENO-RK is accomplished by high order prolongation in both space (WENO interpolation) and time (Hermite interpolation) from coarse to fine grid solutions, and at ghost points. The resulting AMR-WENO method is accurate, robust and efficient, due to the mesh adaptivity and very high order spatial and temporal accuracy. We have experimented with both the third and the fifth order AMR-WENO schemes. We demonstrate the accuracy of the proposed scheme using smooth test problems, and their quality and efficiency using several 1D and 2D nonlinear hyperbolic problems with very challenging initial conditions. The AMR solutions are observed to perform as well as, and in some cases even better than, the corresponding uniform fine grid solutions. We conclude that there is significant improvement of the fifth order AMR-WENO over the third order one, not only in accuracy for smooth problems, but also in its ability in resolving complicated solution structures, due to the very low numerical diffusion of high order schemes. In our work, we found that it is difficult to design a robust AMR-WENO scheme that is both conservative and high order (higher than second order), due to the mass inconsistency of coarse and fine grid solutions at the initial stage in a finite difference scheme. Resolving these issues as well as conducting comprehensive evaluation of computational efficiency constitute our future work.

Quantifying storage changes in regional Great Lakes watersheds using a coupled subsurface‐land surface process model and GRACE, MODIS products

As a direct measure of watershed resilience, watershed storage is important for understanding climate change impacts on water resources. In this paper we quantify water budget components and storage changes for two of the largest watersheds in the State of Michigan, USA (the Grand River and the Saginaw Bay watersheds) using remotely sensed data and a process-based hydrologic model (PAWS) that includes detailed representations of subsurface and land surface processes. Model performance is evaluated using ground-based observations (streamflows, groundwater heads, soil moisture, and soil temperature) as well as satellite-based estimates of evapotranspiration (Moderate-resolution Imaging Spectroradiometer, MODIS) and watershed storage changes (Gravity Recovery and Climate Experiment, GRACE). We use the model to compute annual-average fluxes due to evapotranspiration, surface runoff, recharge and groundwater contribution to streams and analyze the impacts of land use and land cover (LULC) and soil types on annual hydrologic budgets using correlation analysis. Watershed storage changes based on GRACE data and model results showed similar patterns. Storage was dominated by subsurface components and showed an increasing trend over the past decade. This work provides new estimates of water budgets and storage changes in Great Lakes watersheds and the results are expected to aid in the analysis and interpretation of the current trend of declining lake levels, in understanding projected future impacts of climate change as well as in identifying appropriate climate adaptation strategies.

Quantifying the effects of data integration algorithms on the outcomes of a subsurface-land surface processes model

Trans-disciplinary hydrologic models oriented toward practical questions must be accompanied by accurate parameterization techniques. This paper describes the effects of different choices in the integration of various data sources on outcomes of the model Process-based Adaptive Watershed Simulator coupled with the Community Land Model (PAWS + CLM). Using our Hierarchical Stochastic Selection method, the represented land use percentages are much closer to the raw dataset, and lead to a 26% difference in carbon flux from that of the traditional dominant classes method. River bed elevations extracted using a novel algorithm agree well with the groundwater table and significantly increase baseflow contribution to streams relative to a coarse-DEM-based model. The inclusion of additional information in the soil pedotransfer functions drastically shifts ET, Net Primary Production and recharge. These results indicate that judicious treatment of input data has strong impacts on hydrologic and ecosystem fluxes. We emphasize the need to report details of data integration procedures.

High-Resolution Simulation of Pore-Scale Reactive Transport Processes Associated with Carbon Sequestration

New investigative tools, combined with experiments and computational methods, are being developed to build a next-generation understanding of molecular-to-pore-scale processes in fluid-rock systems and to demonstrate the ability to control critical aspects of flow and transport in porous rock media, in particular, as applied to geologic sequestration of CO2. Of scientific interest is to establish the rules governing emergent behavior at the porous-continuum macroscale under far from equilibrium conditions by carefully understanding the behavior at the underlying pore microscale. To this end, the authors present a direct numerical simulation modeling capability that can resolve flow and transport processes in geometric features obtained from the image data of realistic pore space at unprecedented scale and resolution. Here, they focus on scaling a new algorithmic approach based on embedded boundary, finite-volume methods and algebraic multigrid. They demonstrate the scalability of this new capability, known as Chombo-Crunch, to more than 100,000 processor cores and show results from pore-scale flow and transport in the realistic pore space obtained from image data.

The fan of influence of streams and channel feedbacks to simulated land surface water and carbon dynamics

Author(s): Shen, C; Riley, WJ; Smithgall, KR; Melack, JM; Fang, K | Abstract:

Improving Budyko curve‐based estimates of long‐term water partitioning using hydrologic signatures from GRACE

The Budyko hypothesis provides a first-order estimate of water partitioning into runoff (Q) and evapotranspiration (E). Observations, however, often show significant departures from the Budyko curve; moreover, past improvements to Budyko curve tend to lose predictive power when migrated between regions or to small scales. Here to estimate departures from the Budyko curve, we use hydrologic signatures extracted from Gravity Recovery And Climate Experiment (GRACE) terrestrial water storage anomalies. The signatures include GRACE amplitude as a fraction of precipitation (A/P), interannual variability, and 1-month lag autocorrelation. We created a group of linear models embodying two alternate hypotheses that departures can be predicted by (a) Taylor series expansion based on the deviation of physical characteristics (seasonality, snow fraction, and vegetation index) from reference conditions and (b) surrogate indicators covarying with E, e.g., A/P. These models are fitted using a mesoscale USA data set (HUC4) and then evaluated using world data sets and USA basins 1000 km2 and, according to comparison with other global data sets, is suitable for data fusion purposes, with GRACE error as estimates of uncertainty.

Accurate and efficient prediction of fine‐resolution hydrologic and carbon dynamic simulations from coarse‐resolution models

Author(s): Pau, GSH; Shen, C; Riley, WJ; Liu, Y | Abstract: