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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Full Implementation of Matrix Approach to Biogeochemistry Module of CLM5

Abstract Earth system models (ESMs) have been rapidly developed in recent decades to advance our understanding of climate change‐carbon cycle feedback. However, those models are massive in coding, require expensive computational resources, and have difficulty in diagnosing their performance. It is highly desirable to develop ESMs with modularity and effective diagnostics. Toward these goals, we implemented a matrix approach to the Community Land Model version 5 (CLM5) to represent carbon and nitrogen cycles. Specifically, we reorganized 18 balance equations each for carbon and nitrogen cycles among the 18 vegetation pools in the original CLM5 into two matrix equations. Similarly, 140 balance equations each for carbon and nitrogen cycles among the 140 soil pools were reorganized into two additional matrix equations. The vegetation carbon and nitrogen matrix equations are connected to soil matrix equations via litterfall. The matrix equations fully reproduce simulations of carbon and nitrogen dynamics by the original model. The computational cost for forwarding simulation of the CLM5 matrix model was 26% more expensive than the original model, largely due to calculation of additional diagnostic variables, but the spin‐up computational cost was significantly saved. We showed a case study on modeled soil carbon storage under two forcing data sets to illustrate the diagnostic capability that the matrix approach uniquely offers to understand simulation results of global carbon and nitrogen dynamics. The successful implementation of the matrix approach to CLM5, one of the most complex land models, demonstrates that most, if not all, the biogeochemical models can be reorganized into the matrix form to gain high modularity, effective diagnostics, and accelerated spin‐up.

58 GEOSCIENCES↗
DOE OSTI2019

Hillslope Hydrology in Global Change Research and Earth System Modeling

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope-scale terrain structures that have been long recognized by hydrologists as the fundamental organizers of water, energy, and biogeochemical stores and fluxes. Here, we bring together hydrologists, Critical Zone scientists and ESM developers, to explore how hillslope structures may modulate ESM grid-level water, energy and biogeochemical fluxes. In contrast to the traditional one-dimensional (1D), vertical, 2-3m deep, and free-draining soil hydrology in current ESM land models, we argue that 3D, lateral ridge-to-valley flow through shallow and deep paths, and insolation contrasts between sunny and shady slopes, are the top two basic, long-acknowledged, and readily quantifiable organizers of water and energy (and hence vegetation) within an ESM grid cell. We argue that these two processes will be most consequential where (and when) water and/or energy are limiting. We further hypothesize that if they are implemented in ESM land models, they will increase continental water storage and residence time, buffering land ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited view of the subsurface, where water is stored to support vegetation and released to stream baseflow and aquatic ecosystems. We conclude with a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.

Fan, Ying↗
DOE OSTI2021

Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate

Abstract Plant growth and distribution in high-latitude tundra ecosystems is strongly limited by nutrient availability and is critical for quantifying centennial-scale carbon-climate interactions. However, land model representations of plant–nutrient interactions are uncertain, leading to poor comparisons with high-latitude observations. Although it has been recognized for decades in the observational community that plants continue to acquire nutrients well past when aboveground activity has ceased, most large-scale land models ignore this process. Here we address the role tundra plant nutrient acquisition during the non-growing season (NGS) has on centennial-scale vegetation growth and dynamics, with a focus on shrub expansion. We apply a well-tested mechanistic model of coupled plant, microbial, hydrological, and thermal dynamics that explicitly represents nutrient acquisition based on plant and microbial traits, thereby allowing a prognostic assessment of NGS nutrient uptake. We first show that the model accurately represents observed seasonality of NGS plant nutrient uptake in a northern Alaskan tundra site. Applying the model across the North America tundra indicates that NGS nutrient uptake is consistent with observations and ranges between ∼5% and 50% of annual uptake, with large spatial variability and dependence on plant functional type. We show that NGS plant nutrient acquisition strongly enhances modeled 21 st century tundra shrub growth and expansion rates. Our results suggest that without NGS nutrient uptake, total shrub aboveground dominance would be ∼50% lower, limited primarily by their inability to grow tall enough to maximize their inherent capacity for light competition. Evergreen shrubs would be more strongly affected because of their relatively lower capacity for nutrient remobilization and acquisition compared to deciduous shrubs. Our results highlight the importance of NGS plant and soil processes on high-latitude biogeochemistry and vegetation dynamics and motivate new observations and model structures to represent these dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Measurement and modeling of land mobile satellite propagation at UHF and L-band

A propagation experiment is described in which a stratospheric balloon served as a transmitter platform at 870 and 1502 MHz in simulation of a land mobile satellite. A vehicle followed the drifting balloon along roads of western Texas and New Mexico, collecting at L-band amplitude and phase, and at UHF amplitude information only for elevation angles between 25 and 45 deg. The data obtained have been analyzed and are presented along with results from modeling of multipath scattering and roadside tree attenuation. The signal, with variations caused by multipath propagation and tree shadowing, was reduced by 3 dB at L-band and 2 dB at UHF for one percent of all locations. A median ratio of 3.9 was found between peak-to-peak phase (degrees) and power (dB) fluctuations. The ratio between L-band and UHF dB attenuation averages varied from 1.3 to 1.0 at fade levels from 6 to 23 dB. Optical sky brightness was measured and used to predict fade distribution with great accuracy. A single-scatterer multipath model is introduced. It is used to duplicate some of the measured data and to show the dependence of power variations on satellite elevation angle. Using Fresnel diffraction theory, the attenuation caused by a model tree was calculated to be near 10 dB and the maximum fade was found to increase by the logarithm of the number of branches.

Vogel, Wolfhard J.↗
DOE OSTI2026

NGEE Arctic Authorship Guidelines

Authorship Guidelines were developed to help facilitate trust among team members as we span multiple institutions, scientific disciplines, and career stages. NGEE Arctic was built on a foundation of open science, data sharing, and collaboration. In Phase 4 of the project, it was particularly important to keep this foundation in mind as we develop new collaborations across the Arctic. Included in this package is one *.pdf. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

Iversen, Colleen [ORNL] (ORCID:0000000182933450)↗
DOE OSTI2018

Deep Unsaturated Zone Contributions to Carbon Cycling in Semiarid Environments

Understanding terrestrial carbon cycling has relied primarily on studies of topsoils that are typically characterized to depths shallower than 0.5 m. At a semiarid site instrumented down to 7 m, here we measured seasonal- and depth-resolved carbon inventories and fluxes and groundwater and unsaturated zone flow rates. Measurements showed that ~30% of the CO 2 efflux to the atmosphere (60% in winter) originates from below 1 m, contrary to predictions of less than 1% by Earth System Model land modules. Respiration from deeper roots and deeper microbial communities is supported by favorable subsurface temperatures, moisture, and oxygen availability. Below 1 m, dissolved organic carbon fluxes from the overlying soil and C from deep roots and exudates are expected to be important in sustaining microbial respiration. Finally, because these conditions are characteristic of semiarid climate regions, we contend that Earth System Model land modules should incorporate such deeper soil processes to improve CO 2 flux predictions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

LEO Sensor to GEO Sensor Algorithm Transfer Models for Land Surface Temperature

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Communicating diurnal LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Marie Duffy↗
DOE OSTI2016

Final report of “A Detailed Study of the Physical Mechanisms Controlling CO2-Brine Capillary Trapping in the Subsurface” (University of Arizona, DE-SC0006696)

Carbon capture and storage (CCS) of carbon dioxide emissions generated by production or combustion of fossil fuels is a technologically viable means to reduce the build-up of CO2 in the atmosphere and oceans. Using advantages of scale and location, CCS is particularly suitable for large point sources near ubiquitous deep saline aquifers, depleted gas reservoirs, or at production reservoirs for enhanced oil recovery (EOR). In the BES-funded research project, Oregon State University (OSU) carried out capillary trapping experiments with proxy fluids that mimic the properties of the scCO2/brine system under ambient temperatures and pressures, and successfully developed a unique and novel x-ray compatible, high-pressure, elevated temperature setup to study the scCO2/brine system under challenging reservoir conditions. Both methodologies were applied to a variety of porous media, including synthetic (glass bead) and geologic (Bentheimer sandstone) materials. The University of Arizona (UA) developed pore-scale lattice Boltzmann (LB) models which are able to handle the experimental conditions for proxy fluids, as well as the scCO2/brine system, that are capable of simulating permeability in volumes of tens of millions of fluid elements. We reached the following summary findings (main institute indicated): 1. (OSU/UA) To understand capillary trapping in a multiphase fluid-porous medium system, the system must be analyzed from a pore-scale force balance perspective; trapping can be enhanced by manipulating wetting and nonwetting phase fluid properties. 2. (OSU) Pore-scale fluid connectivity and topology has a clear and direct effect on nonwetting phase capillary trapping efficiency. 3. (OSU) Rock type and flow regime also have a pronounced effects on capillary trapping. 4. (OSU/UA) There is a predictable relationship between NWP connectivity and NWP saturation, which allows for development of injection strategies that optimize trapping. The commonly used Land model (Land, 1968) does not predict amount of trapped NWP accurately. 5. (UA) There are ambiguities regarding the segmentation of large-volume gray-scale CT data into pore-volumes suitable for pore-scale modeling. Simulated permeabilities vary by three orders of magnitude and do not resemble observed values very well. Small-volume synchrotron-based CT data (such as produced by OSU) does not suffer significantly from segmentation ambiguities. 6. (UA) A standard properly parameterized Shan-Chen model LB model is useful for simulating porous media with proxy fluids as well as the scCO2/brine system and produces results that are consistent with tomographic observations. 7. (UA) A LB model with fluid-interactions defined by a (modified) Peng-Robinson Equation of State is able to handle the scCO2/brine system with variable solid phase wettability. This model is numerically stable at temperatures between 0 and 250 °C and pressures between 3 and 50 MPa, and produces appropriate densities above the critical point of CO2 and exhibits three-phase separation below. Based on above findings OSU and UA have proposed continued experimentation and pore-scale modeling of the scCO2/brine system. The reported research has extensively covered capillary trapping using proxy fluids, but due to limited beam-time availability we were unable to apply our high-pressure CO2 setup to sufficient variation in fluid properties, and initial scCO2 connectivity. New data will also allow us to test, calibrate and apply our LB models to reservoir conditions beyond those that are currently feasible experimentally. Such experiments and simulations will also allow us to provide information how suitable proxy fluids are for the scCO2/brine system. We believe it would be worthwhile to pursue the following new research questions: 1. What are the fundamental differences in the physics underlying capillary trapping at ambient vs. supercritical conditions? 2. Do newly developed pore-scale trapping interactions and relationships translate to continuum scales? A motivation for these questions was elaborated in “Capillary Trapping of Super-Critical CO2: Linking Pore and Continuum Scales to Verify new Relationships” that was submitted to DOE-BES in 2015.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2018

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. In this study, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model predictions better agreed (higher R 2 , lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~ 10 cm shallower and ~ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ~ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Impacts of microtopographic snow-redistribution and lateral subsurface processeson hydrologic and thermal states in an Arctic polygonal ground ecosystem

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the ACME Earth System Model (ESM) to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ALMv0-3D). Three 10-years long simulations were performed for a transect across polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model results show a better agreement (higher R 2 with lower bias and RMSE) for the observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59 &deg;C, 1.82 &deg;C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~10 cm shallower and ~5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on active layer depths was modest with mean absolute difference of ~3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the ACME land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Few multi-year precipitation-reduction experiments find a shift in the productivity-precipitation relationship

Well-defined productivity–precipitation relationships of ecosystems are needed as benchmarks for the validation of land models used for future projections. The productivity–precipitation relationship may be studied in two ways: the spatial approach relates differences in productivity to those in precipitation among sites along a precipitation gradient (the spatial fit, with a steeper slope); the temporal approach relates interannual productivity changes to variation in precipitation within sites (the temporal fits, with flatter slopes). Precipitation–reduction experiments in natural ecosystems represent a complement to the fits, because they can reduce precipitation below the natural range and are thus well suited to study potential effects of climate drying. Here, we analyse the effects of dry treatments in eleven multiyear precipitation–manipulation experiments, focusing on changes in the temporal fit. We expected that structural changes in the dry treatments would occur in some experiments, thereby reducing the intercept of the temporal fit and displacing the productivity–precipitation relationship downward the spatial fit. Seventy two percent of expiriments showed that dry treatments did not alter the temporal fit. This implies that current temporal fits are to be preferred over the spatial fit to benchmark land-model projections of productivity under future climate within the precipitation ranges covered by the experiments. Moreover, in two experiments, the intercept of the temporal fit unexpectedly increased due to mechanisms that reduced either water loss or nutrient loss. The expected decrease of the intercept was observed in only one experiment, and only when distinguishing between the late and the early phases of the experiment. This implies that we currently do not know at which precipitation–reduction level or at which experimental duration structural changes will start to alter ecosystem productivity. Our study highlights the need for experiments with multiple, including more extreme, dry treatments, to identify the precipitation boundaries within which the current temporal fits remain valid.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Abstract Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil–plant–atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests

Uncertainties surrounding vegetation response to increased disturbance rates associated with climate change remains a major global change issue for Amazonian forests. Additionally, turnover rates computed as the average of mortality and recruitment rates in the western Amazon basin are doubled when compared to the central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB) between these two regions. This study investigates the extent to which the variation in disturbance regimes contributes to these regional gradients. To address this issue, we evaluated disturbance–recovery processes in a central Amazonian forest under two scenarios of increased disturbance rates using first ZELIG-TROP, a dynamic vegetation gap model which we calibrated using long-term inventory data, and second using the Community Land Model (CLM), a global land surface model that is part of the Community Earth System Model (CESM). Upon doubling the mortality rate in the central Amazon to mirror the natural disturbance regime in the western Amazon of ~2% mortality, the two regions continued to differ in multiple forest processes. With the inclusion of elevated natural disturbances, at steady state, AGB significantly decreased by 41.9% with no significant difference between modeled AGB and empirical AGB from the western Amazon data sets (104 vs. 107 Mg C ha -1 , respectively). However, different processes were responsible for the reductions in AGB between the models and empirical data set. The empirical data set suggests that a decrease in wood density is a driver leading to the reduction in AGB. While decreased stand basal area was the driver of AGB loss in ZELIG-TROP, a forest attribute that does not significantly vary across the Amazon Basin. Further comparisons found that stem density, specific wood density, and basal area growth rates differed between the two Amazonian regions. Last, to help quantify the impacts of increased disturbances on the climate and earth system, we evaluated the fidelity of tree mortality and disturbance in CLM. Similar to ZELIG-TROP, CLM predicted a net carbon loss of 49.9%, with an insignificant effect on aboveground net primary productivity (ANPP). Decreased leaf area index (LAI) was the driver of AGB loss in CLM, another forest attribute that does not significantly vary across the Amazon Basin, and the temporal variability in carbon stock and fluxes was not replicated in CLM. Our results suggest that (1) the variability between regions cannot be entirely explained by the variability in disturbance regime, but rather potentially sensitive to intrinsic environmental factors; or (2) the models are not accurately simulating all tropical forest characteristics in response to increased disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in better agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d -1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological dynamics in CLM4.5.

58 GEOSCIENCES↗
DOE OSTI2019

Combining a land surface model with groundwater model calibration to assess the impacts of groundwater pumping in a mountainous desert basin

The quantification of recharge and trans-valley underflow is needed in arid regions to estimate the impacts of new water withdrawals on the water table. However, for mountainous desert areas, such estimates are highly challenging, due to data scarcity, heterogeneous soils, and long residence times. Conventional assessment employs isolated groundwater models configured with simplified uniform estimates of recharge. Here, we employed a data-constrained surface-subsurface process model to provide an ensemble of spatially distributed recharge and underflow estimates using perturbed parameters. Then, the Model-Independent Parameter Estimation and Uncertainty Quantification (PEST) package was used to calibrate the aquifer hydraulic conductivity field in MODFLOW for this ensemble and reject implausible recharge values. This novel dual-model approach, broadly applicable to mountainous arid regions, was designed to maximally exploit available data sources. It can assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns due to pumping. We applied this approach to the Chuckwalla basin in California, USA to determine natural recharge. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where run-off water infiltrates. If an evenly distributed recharge was employed as in conventional studies, it would result in regional biases in estimated drawdown and larger uncertainty bounds. Here, we also note that the speed of groundwater recovery does not guarantee sustainability: heavy pumping induces large hydraulic gradients that initially recover quickly when pumping is halted, but the system may not ultimately recover to pre-pumping levels.

54 ENVIRONMENTAL SCIENCES↗