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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2023

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗
DOE OSTI2013

The Future of Energy from Nuclear Fission

Nuclear energy is an important part of our current global energy system, and contributes to supplying the significant demand for electricity for many nations around the world. There are 433 commercial nuclear power reactors operating in 30 countries with an installed capacity of 367 GWe as of October 2011 (IAEA PRIS, 2011). Nuclear electricity generation totaled 2630 TWh in 2010 representing 14% the world’s electricity generation. The top five countries of total installed nuclear capacity are the US, France, Japan, Russia and South Korea at 102, 63, 45, 24, and 21 GWe, respectively (WNA, 2012a). The nuclear capacity of these five countries represents more than half, 68%, of the total global nuclear capacity. The role of nuclear power in the global energy system today has been motivated by several factors including the growing demand for electric power, the regional availability of fossil resources and energy security concerns, and the relative competitiveness of nuclear power as a source of base-load electricity. There is additional motivation for the use of nuclear power because it does not produce greenhouse gas (GHG) emissions or local air pollutants during its operation and contributes to low levels of emissions throughout the lifecycle of the nuclear energy system (Beerten, J. et. al., 2009). Energy from nuclear fission primarily in the form of electric power and potentially as a source of industrial heat could play a greater role for meeting the long-term growing demand for energy worldwide while addressing the concern for climate change from rising GHG emissions. However, the nature of nuclear fission as a tremendously compact and dense form of energy production with associated high concentrations of radioactive materials has particular and unique challenges as well as benefits. These challenges include not only the safety and cost of nuclear reactors, but proliferation concerns, safeguard and storage of nuclear materials associated with nuclear fuel cycles. In March of 2011, an unprecedented earthquake of 9 magnitude and ensuing tsunami off the east coast of Japan caused a severe nuclear accident in Fukushima, Japan (Prime Minister of Japan and His Cabinet, 2011). The severity of the nuclear accident in Japan has brought about a reinvestigation of nuclear energy policy and deployment activities for many nations around the world, most notably in Japan and Germany (BBC, 2011; Reuter, 2011). The response to the accident has been mixed and its full impact may not be realized for many years to come. The nuclear accident in Fukushima, Japan has not directly affected the significant on-going nuclear deployment activities in many countries. China, Russia, India, and South Korea, as well as others, are continuing with their deployment plans. As of October 2011, China had the most reactors under construction at 27, while Russia, India, and South Korea had 11, 6, and 5 reactors under construction, respectively (IAEA PRIS, 2011). Ten other nations have one or two reactors currently under construction. Many more reactors are planned for future deployment in China, Russia, and India, as well as in the US. Based on the World Nuclear Association’s data, the realization of China’s deployment plan implies that China will surpass the US in total nuclear capacity some time in the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Data and Code for 'GHG Mitigation and Land Use Change Implications of Sustainable Aviation Fuel in the United States'

BEPAM, Biofuel and Environmental Policy Analysis Model, models the agricultural sector and determines economically optimal land-use and feedstock mix at the US scale by maximizing the sum of agricultural sector consumers’ and producers’ surplus subject to various resource balances, land availability, and technological constraints under a range of biomass prices, from zero to $140 Mg-1 over the 2016-2030 period. Here BEPAM is used to model SAF production using energy crops and crop residues. BEPAM uses the GAMS format and uses yield and GHG balance projections from the biogeochemical model, DayCent.

09 BIOMASS FUELS↗
DOE OSTI2021

Machine Learning Model Geotiffs - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk), input rasters of feature sets, and positive/negative training sites. See readme .txt files and final report for additional metadata. A submission linking the full codebase for generating machine learning output models is available under "related resources" on this page.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Growing field of materials informatics: databases and artificial intelligence

The paradigm of molecular discovery in the chemical and pharmaceutical industry has followed a repetitive succession of screening and synthesis, involving the analysis of individual molecules that were both natural and produced. This ability to generate and screen libraries of compounds has found an echo in solid-state physics with the demand to explore and produce new materials for testing. In response to this demand, a golden age of materials discovery is being developed, with progress on important areas of both basic science and device applications. The confluence of theoretical and simulation methods, together with the availability of computation resources, has established the “materials genome” approach that is used by a growing number of research groups around the world with the goal of innovating on materials through systematic discovery. Here, an overview of this group of methodologies in tackling the ever-increasing complexity of computational materials science simulations is provided. Computational simulation is highlighted as a major component of rational design and synthesis of new materials with targeted properties, describing progress on databases and large data treatment. Tools for new materials discovery, including progress on the deployment of new data repositories, the implementation of high-throughput simulation approaches, and the development of artificial intelligence algorithms, are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Portfolio Approach to Massively Parallel Bayesian Optimization

One way to reduce the time of conducting optimization studies is to evaluate designs in parallel rather than just one-at-a-time. For expensive-to-evaluate black-boxes, batch versions of Bayesian optimization have been proposed. They work by building a surrogate model of the black-box to simultaneously select multiple designs via an infill criterion. Still, despite the increased availability of computing resources that enable large-scale parallelism, the strategies that work for selecting a few tens of parallel designs for evaluations become limiting due to the complexity of selecting more designs. It is even more crucial when the black-box is noisy, necessitating more evaluations as well as repeating experiments. Here we propose a scalable strategy that can keep up with massive batching natively, focused on the exploration/exploitation trade-off and a portfolio allocation. We compare the approach with related methods on noisy functions, for mono and multi-objective optimization tasks. These experiments show orders of magnitude speed improvements over existing methods with similar or better performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Feasibility study on AFR-100 fuel conversion from uranium-based fuel to thorium-based fuel

Although thorium has long been considered as an alternative to uranium-based fuels, most of the reactors built to-date have been fueled with uranium-based fuel with the exception of a few reactors. The decision to use uranium-based fuels was initially made based on the technology maturity compared to thorium-based fuels. As a result of this experience, lot of knowledge and data have been accumulated for uranium-based fuels that made it the predominant nuclear fuel type for extant nuclear power. However, following the recent concerns about the extent and availability of uranium resources, thorium-based fuels have regained significant interest worldwide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

FY2011 Status Report on SN2ND Neutronics Solver Development

A change in focus of NEAMS to a broader set of reactor types necessitated significant effort being diverted away from SN2ND development in FY2011. Nevertheless, significant gains were made with regard to building the new preconditioner and meeting the objectives of 1) parallelism in energy, 2) a spatial multigrid concept, 3) using SN vector spaces to accommodate the adjoint and time dependent functionalities needed for NEAMS work, and 4) complete manuals and documentation. While the desired goal of an exportable SN2ND solver usable within the NEAMS community for neutronics analysis was not completed, we can be confident that this year’s work puts the SN2ND solver well on its way to meeting that objective. It is important to note that SN2ND is just as capable as any other methodology for doing thermal reactor analysis, but the motivation to execute on smaller scale machines has initiated focused development on simplified treatments such as those proposed in the MOCARV tool. All of the cited coding tasks were completed but not all are fully working (i.e. debugged). The spatial multigrid technique was by far the most time consuming part of the SN2ND development process. It required multiple new data structure concepts along with identifying the necessary changes in the vectors and their associated functions. Combining the spatial multigrid as part of a GMRES preconditioner operating on the full vector space, necessary for parallelization in energy, increased the complexity of that development. Research into spatial multigrid techniques for unstructured meshes, void treatments, and code optimization and acceleration are key development needs for SN2ND. Similar to previous years, a considerable amount of effort was spent on validation work. Again we focused on fast reactor problems such as ZPR experiments and the MONJU reactor in Japan. Conventional drawer homogenized models and partially heterogeneous models were used on the ZPR calculations. The drawer homogenized models produced excellent results for both eigenvalue and foil measurements on four loadings of ZPR-6/7. The partially heterogeneous models of ZPR-6/7 also produced good results, but additional work is necessary to generate consistent effective cross section data. Calculations for MONJU were homogeneous and also gave excellent results. Finally, mock-up heterogeneous calculations were setup and attempted to scope out the performance limitations of SN2ND on whole core heterogeneous calculations. Specifically, heterogeneous models of a PWR, a VHTR, and the MONJU reactor were created using anywhere from 2 group to 33 group cross section data. Meshes with greater than 100,000,000 vertices are necessary for accuracy and a specific non-scaling memory issue in PETSc restricted the SN2ND modeling (VHTR and PWR could not be solved). All of the calculations performed this year indicate that significant computational resources beyond those available today are required to obtain a high fidelity solution possible with SN2ND. The future goals for SN2ND are to get the new version fully working, reliable in execution, and to have comparable performance to the old solver such that it can be released within the NEAMS community. After its export to RSICC, we will rely upon further preconditioner research to be done in collaboration with university partners and through the exascale hub activities. Some of that research will focus on making SN2ND applicable to thermal reactor problems, spatial multigrid, and void treatments.

Smith, M. A.↗
DOE OSTI2012

Quantifying the Value of Hydropower in the Electric Grid: Final Report

The report summarizes research to Quantify the Value of Hydropower in the Electric Grid. This 3-year DOE study focused on defining value of hydropower assets in a changing electric grid. Methods are described for valuation and planning of pumped storage and conventional hydropower. The project team conducted plant case studies, electric system modeling, market analysis, cost data gathering, and evaluations of operating strategies and constraints. Five other reports detailing these research results are available a project website, www.epri.com/hydrogrid. With increasing deployment of wind and solar renewable generation, many owners, operators, and developers of hydropower have recognized the opportunity to provide more flexibility and ancillary services to the electric grid. To quantify value of services, this study focused on the Western Electric Coordinating Council region. A security-constrained, unit commitment and economic dispatch model was used to quantify the role of hydropower for several future energy scenarios up to 2020. This hourly production simulation considered transmission requirements to deliver energy, including future expansion plans. Both energy and ancillary service values were considered. Addressing specifically the quantification of pumped storage value, no single value stream dominated predicted plant contributions in various energy futures. Modeling confirmed that service value depends greatly on location and on competition with other available grid support resources. In this summary, ten different value streams related to hydropower are described. These fell into three categories; operational improvements, new technologies, and electricity market opportunities. Of these ten, the study was able to quantify a monetary value in six by applying both present day and future scenarios for operating the electric grid. This study confirmed that hydropower resources across the United States contribute significantly to operation of the grid in terms of energy, capacity, and ancillary services. Many potential improvements to existing hydropower plants were found to be cost-effective. Pumped storage is the most likely form of large new hydro asset expansions in the U.S. however, justifying investments in new pumped storage plants remains very challenging with current electricity market economics. Even over a wide range of possible energy futures, up to 2020, no energy future was found to bring quantifiable revenues sufficient to cover estimated costs of plant construction. Value streams not quantified in this study may provide a different cost-benefit balance and an economic tipping point for hydro. Future studies are essential in the quest to quantify the full potential value. Additional research should consider the value of services provided by advanced storage hydropower and pumped storage at smaller time steps for integration of variable renewable resources, and should include all possible value streams such as capacity value and portfolio benefits i.e.; reducing cycling on traditional generation.

13 HYDRO ENERGY↗
DOE OSTI2015

TECHNCIAL REPORT

The outcomes of these upgrades include an estimated savings to the City and the power grid of 720 kilowatts in peak energy load. This outcome includes the benefit of lower operating costs for the City, conservation of energy resources and increased availability of energy to the grid during peak times of energy use. The goals and objectives of the HVAC upgrades are to replace equipment as old as twenty-three (23) years in five different facilities. The project will upgrade some facilities from SEER ratings of 9 to SEER ratings of 14 at a savings of 556 kilowatt hours per ton (savings depends on specific size of the system). In addition to these objectives, the project will also install comprehensive HVAC control systems to maximize the efficiency of all HVAC upgrades. The expected outcomes of these upgrades emphasize savings capture; it is anticipated to save the City’s 42% in space heating and cooling costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Improving Distribution Resiliency with Microgrids and State and Parameter Estimation

Modern society relies on low-cost reliable electrical power, both to maintain industry, as well as provide basic social services to the populace. When major disturbances occur, such as Hurricane Katrina or Hurricane Sandy, the nation’s electrical infrastructure can experience significant outages. To help prevent the spread of these outages, as well as facilitating faster restoration after an outage, various aspects of improving the resiliency of the power system are needed. Two such approaches are breaking the system into smaller microgrid sections, and to have improved insight into the operations to detect failures or mis-operations before they become critical. Breaking the system into smaller sections of microgrid islands, power can be maintained in smaller areas where distribution generation and energy storage resources are still available, but bulk power generation is no longer connected. Additionally, microgrid systems can maintain service to local pockets of customers when there has been extensive damage to the local distribution system. However, microgrids are grid connected a majority of the time and implementing and operating a microgrid is much different than when islanded. This report discusses work conducted by the Pacific Northwest National Laboratory that developed improvements for simulation tools to capture the characteristics of microgrids and how they can be used to develop new operational strategies. These operational strategies reduce the cost of microgrid operation and increase the reliability and resilience of the nation’s electricity infrastructure. In addition to the ability to break the system into microgrids, improved observability into the state of the distribution grid can make the power system more resilient. State estimation on the transmission system already provides great insight into grid operations and detecting abnormal conditions by leveraging existing measurements. These transmission-level approaches are expanded to using advanced metering infrastructure and other distribution-level measurements to create a three-phase, unbalanced distribution state estimation approach. With distribution-level state estimation, the grid can be operated more efficiently, and outages or equipment failures can be caught faster, improving the overall resilience and reliability of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Transported Low-Temperature Geothermal Energy for Thermal End Uses Final Report

The use of geothermal energy is an emerging area for improving the nation’s energy resiliency. Conventionally, geothermal energy applications have focused on power generation using high temperature hydrothermal resources or enhanced geothermal systems. However, many low temperature (below 150°C/300°F) geothermal resources are also available but have not been fully utilized. For example, it is estimated that 25 billion barrels of geothermal fluid (mostly water and some dissolved solids) at 176°F to 302°F (80°C to 150°C) is coproduced annually at oil and gas wells in the United States (DOE 2015). The heat contained in coproduced geothermal fluid (also referred as “coproduced water”) is typically wasted because the fluid is reinjected back into the ground without extracting the heat.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030

This study describes an assessment of the spatial variation of levelized cost of energy (LCOE) and levelized avoided cost of energy to understand the economic viability of fixed-bottom and floating offshore wind technologies across major U.S. coastal areas between 2015 and 2030. In particular, this study offers insights into the available offshore wind resource by region at different levels of LCOE and an assessment of the economically viable resource capacity in the United States.

17 WIND ENERGY↗
DOE OSTI2017

Interrelationship between Plasma Experiments in the Laboratory and in Space

Funds were expended to offset the travel costs of three students and three postdoctoral research associates to participate in and present work at the 2015 International Workshop on the Interrelationship between Plasma Experiments in the Laboratory and in Space (IPELS2015), 23-28 August 2015, Pitlochry, Scotland, UK. Selection was priority-ranked by lab-space engagement, first, and topic relevance, second. Supplementary selection preference was applied to under-represented populations, applicants lacking available travel-resources in their home research group, applicants unusually distant from the conference venue, and the impact of the applicant’s attendance in increasing the diversity of conference participation. One support letter per student was required. The letters described the specific benefit of IPELS2015 to the student dissertation or the postdoc career development, and document the evidence for the ordering criteria.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Summary Report for the Evaluation of Current QA Processes Within the FRMAC FAL and EPA MERL.

The Federal Radiological Monitoring and Assessment Center (FRMAC) relies on accurate and defensible analytical laboratory data to support its mission. Therefore, FRMAC must ensure that the environmental analytical laboratories providing analytical services maintain an ongoing capability to provide accurate analytical results to DOE. It is undeniable that the more Quality Assurance (QA) and Quality Control (QC) measures required of the laboratory, the less resources that are available for analysis of response samples. Being that QA and QC measures in general are understood to comprise a major effort related to a laboratory’s operations, requirements should only be considered if they are deemed “value-added” for the FRMAC mission. This report provides observations of areas for improvement and potential interoperability opportunities in the areas of Batch Quality Control Requirements, Written Communications, Data Review Processes, Data Reporting Processes, along with the lessons learned as they apply to items in the early phase of a response that will be critical for developing a more efficient, integrated response for future interactions between the FRMAC and EPA assets.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business units have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Implementation of ANL’s Mechanics Based Evolutionary Fatigue Modeling Through ABAQUS-WARP3D Based High-Performance Computing Framework

This report presents an update on the environmental fatigue research that is being conducted at Argonne National Laboratory in support of the Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Argonne is developing a fully mechanistic fatigue evaluation approach without using empirical fatigue (S~N) curves. This approach is based on the fundamental concept of the time evolution of progressive fatigue damage rather than on the conventional S~N curve approaches using end-of-life data. In FY 2017, we performed extensive validation of this approach with respect to fatigue test data for 316 stainless steel [1]. This validation was performed for different loading cases, including constant, variable, and random amplitude. In the present FY 2018 semi-annual report, we present the further advances of Argonne’s environmental fatigue research work in the context for more practical applications. In this report, we discuss a methodology for fully mechanistic (i.e., not using S~N curves) fatigue life evaluation of reactor components subjected to realistic loading cycles, namely, design-basis loading cycles. The loading cycles include plant heat-up, full-power, and cool-down operations. As a test case, we considered a typical pressurized water reactor surge line, which is made of 316 SS. To perform the fatigue simulation for thousands of fatigue cycles in a computationally cost effective way, we modified our previous desktop-based finite element (FE) modeling approach to work in a high-performance computing (HPC) framework. For the HPC implementation, we developed a hybrid framework based on commercial FE software (ABAQUS), open-source FE software (WARP3D), and Argonne-developed evolutionary cyclic-plasticity modeling methods. We validated this HPC-based cycle-by-cycle damage model for the entire fatigue life of a Pressurized Water Reactor (PWR) surge line (SL) pipe with respect to assumed loading cycles. The simulated fatigue life was found to be 5855 cycles, which is 85% accurate as compared to the corresponding small-specimen-based experimental fatigue life (6914 cycles). Also, the simulated stress history captures the cyclic hardening and softening behavior of the material for entire fatigue cycles. The FE simulation of the PWR SL pipe was conducted in a reasonable time of 12.5 days. These results show the promise that a fully mechanistic (not using S~N curves) fatigue life evaluation of a safety-critical nuclear reactor component (or even other safety critical components like those in aircraft, aero-engines, etc.) is possible. We anticipate that this type of methodology will drastically reduce the uncertainly associated with conventional fatigue life estimates based on empirical S~N curves. We also proposed an FE model that is based on a hybrid full-component and single-element approach and that can readily be used by industry if HPC resources are not available. In this approach, a single-cycle FE simulation has to be performed first for the required loading cycle. Then, the resulting strain/stress profile at the hotspot (highest strain/stress location) is used as input strain/stress loading to the single-element FE model. The single-element FE model is run under multiple fatigue cycles as long as the failure criteria are achieved. The cycle number at failure gives the fatigue life of the component in question. This cost-effective framework does not require expensive HPC hardware and can be performed in a reasonable time by using a desktop computer. We demonstrated this approach with respect to PWR SL fatigue evaluation under two realistic design-basis loading cycles (simple and detailed). The associated results were validated with respect to test data obtained through fatigue testing of uniaxial specimens under the in-air condition at 300 °C. The approach is in the development stage and requires further improvement and validation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Surface Atmosphere Integrated Field Laboratory (SAIL) Science Plan

Mountains are the natural water towers of the world, effectively turning water vapor into readily available fresh water through precipitation, snowpack, and runoff. Unfortunately, Earth system models (ESMs) have persistently been unable to predict the timing and availability of water resources from mountains because the source(s) of model error are difficult to isolate in complex terrain with limited atmospheric or land-surface observations. Further complications arise from the gross scale mismatch between ESM grid box sizes and the relevant scales of mountainous hydrological processes. The mountain hydrometeorology community has repeatedly called for integrated atmospheric and land observations of water and energy budgets in complex terrain that span these scales to establish benchmarks against which scale-dependent models can be further developed.

54 ENVIRONMENTAL SCIENCES↗