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Results for “multi-sector dynamics”

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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29 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins

Droughts across the U.S. have imposed substantial challenges to the management of water resources. Reservoir drought, one type of hydrological drought, is characterized by abnormally low reservoir storage levels, reflecting combined impacts of natural water shortages and water management practices. We investigate how reservoir drought signatures, particularly onset, severity, duration, recovery and frequency, may shift under rising temperatures, and how these shifts vary by reservoir typology and degree of regulation. By coupling atmosphere-land-river models with reservoir operations at ~12-km resolution, we simulated reservoir storage and characterized reservoir droughts across five heavily regulated U.S. basins. Our findings reveal significant regional and functional disparities in reservoir drought resilience under the scenario of rising temperatures. Reservoirs in the Texas-Gulf region are projected to become more resilient, while systems in the Upper Colorado and South Atlantic-Gulf regions face increased risk due to prolonged drought durations and slower recovery. With respect to primary function, reservoirs used for irrigation and hydropower, particularly those with smaller storage capacity and lower degrees of regulation, are most susceptible to future drought stress. These results are valuable in understanding water availability in highly regulated environments, and the influence of hydrometeorological conditions on storage dynamics. Overall, this study provides the first of its kind benchmark for reservoir droughts at a continental scale to support evolving multi-sectoral drought mitigation efforts. Future research is needed to link reservoir drought conditions to actual supply shortages across competing water uses, while leveraging existing adaptive management strategies and coordinated reservoir operations.

reservoir↗
DOE OSTI2025

Tethys Water Demand Data

U.S. water demand varies sharply by sector and region as land use, population, weather patterns, and economic activity co-evolve. High-resolution water demand data is required to capture these dynamics, support integrated energy-water-land modeling, and local-to-regional water scarcity assessments. This dataset contains gridded (1/8 degree), monthly, multi-sector water demand dataset for the contiguous United States (CONUS) covering 1980-2100 across eight future scenarios of human-Earth system change. The dataset covers irrigation, thermoelectric, municipal (public-supply and domestic), livestock, manufacturing, and mining demands, separately for withdrawals and consumption, and includes per-cell renewable vs. non-renewable water source attributions. The dataset is validated against the latest USGS 2010-2020 water-use data for the three largest water demand sectors (Domestic, Electricity, and Irrigation), with correlations ranging from 0.73-0.95 at the HUC6 scale. The two datasets largely agree on an aggregate basis with per-sector bias falling within +/-7%, but they disagree on the spatial allocation of water with individual HUC6 basins having normalized RMSE from 68-171% and median absolute percent difference from 37-86%. This dataset advances prior global products by combining state-resolved sectoral demands from GCAM-USA, future power-plant siting from the CERF model, and scenario-consistent high-resolution climate and population forcing data across the eight scenarios.

GCAM-USA↗
DOE OSTI2021

Evaluating the economic impact of water scarcity in a changing world

Abstract Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems’ adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Summary of Pilot Project State Technical Assistance on Multi-Sector Analysis for Electric and Petroleum Fuels

The Oregon Energy Security Plan, (ODOE 2024) published in September 2024, builds a strong case for the state to give acute attention to the fuel supply chain. In December 2024, Pacific Northwest National Laboratory (PNNL) in partnership with Oregon Department of Energy (ODOE), announced a pilot project to conduct an analysis that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification, sponsored by the Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER). The study, is intended to leverage existing modeling and frameworks from a recent 2024 sector coupling analysis supported by the DOEs Office of Electricity (OE) (B. Mitra, S. Pal, et al., Coupling of the Electricity and Transportation Sectors - Part I: Sector Overviews 2024) (B. Mitra, S. Pal and J. Reeve, et al. 2024). While the PNNL team set out to conduct a quantitative risk analysis driven by detailed data that synthesizes current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors. The intention was to provide an approach that could be extendable to other parts of the country. They encountered data limitations and adjusted their approach accordingly. This report summarizes PNNL's original plan for executing the study, including limitations for obtaining data requirements for fuel flows and interim products, as well as a risk matrix that can be used to identify supply chain risks.

02 PETROLEUM↗
DOE OSTI2024

GCAM–GLORY v1.0: representing global reservoir water storage in a multi-sector human–Earth system model

Abstract. Reservoirs play a significant role in modifying the spatiotemporal availability of surface water to meet multi-sector human demands, despite representing a relatively small fraction of the global water budget. Yet the integrated modeling frameworks that explore the interactions among climate, land, energy, water, and socioeconomic systems at a global scale often contain limited representations of water storage dynamics that incorporate feedbacks from other systems. In this study, we implement a representation of water storage in the Global Change Analysis Model (GCAM) to enable the exploration of the future role (e.g., expansion) of reservoir water storage globally in meeting demands for, and evolving in response to interactions with, the climate, land, and energy systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition among renewable water (now including reservoirs), non-renewable groundwater, and desalination. Our approach consists of developing the GLObal Reservoir Yield (GLORY) model, which uses a linear programming (LP)-based optimization algorithm and dynamically linking GLORY with GCAM. The new coupled GCAM–GLORY approach improves the representation of reservoir water storage in GCAM in several ways. First, the GLORY model identifies the cost of supplying increasing levels of water supply from reservoir storage by considering regional physical and economic factors, such as evolving monthly reservoir inflows and demands, and the leveled cost of constructing additional reservoir storage capacity. Second, by passing those costs to GCAM, GLORY enables the exploration of future regional reservoir expansion pathways and their response to climate and socioeconomic drivers. To guide the model toward reasonable reservoir expansion pathways, GLORY applies a diverse array of feasibility constraints related to protected land, population, water sources, and cropland. Finally, the GLORY–GCAM feedback loop allows evolving water demands from GCAM to inform GLORY, resulting in an updated supply curve at each time step, thus enabling GCAM to establish a more meaningful economic value of water. This study improves our understanding of the sensitivity of reservoir water supply to multiple physical and economic dimensions, such as sub-annual variations in climate conditions and human water demands, especially for basins experiencing socioeconomic droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

United States multi-sector land use and land cover base maps to support human and Earth system models

Abstract Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Oliver, Jay↗
DOE OSTI2022

rmap: An R package to plot and compare tabular data on customizable maps across scenarios and time

`rmap` is an R package that allows users to easily plot tabular data (CSV or R data frames) on maps without any Geographic Information Systems (GIS) knowledge. Maps produced by `rmap` are `ggplot` objects and thus capitalize on the flexibility and advancements of the `ggplot2` package and all elements of each map are thus fully customizable. Additionally `rmap` automatically detects and produces comparison maps if the data has multiple scenarios or time periods as well as animations for time series data. Advanced users can load their own shapefiles if desired. `rmap` comes with a range of pre-built color palettes but users can also provide any `R` color palette or create their own as needed. Four different legend types are available to highlight different kinds of data distributions. The input spatial data can be both gridded or polygon data. `rmap` is desgined in particular for comparing spatial data across scenarios and time periods and comes preloaded with standard country, state, and basin maps as well as custom maps compatible with the Global Change Analysis Model (GCAM) spatial boundaries. `rmap` has a growing number of users and its products have been used in multiple multisector dynamics publications as well as a required dependency in other R packages such as `rfasst` and `metis`. `rmap's` automatic processing of tabular data using pre-built map selection, difference map calculations, faceting, and animations offers unique functionality which makes it a powerful and yet simple tool for users looking to explore multi-sector, multi-scenario data across space and time.

58 GEOSCIENCES↗
DOE OSTI2024

statemodify: a Python framework to facilitate accessible exploratory modeling for discovering drought vulnerabilities

The Colorado River Basin (CRB) is experiencing an unprecedented water shortage crisis brought upon by a combination of factors arising from interactions across the region’s coupled human and natural systems. Allocation of water to the seven states that rely on the Colorado River was settled in the Colorado River Compact of 1922 during a period now known to be characterized by atypically high flows (Christensen et al., 2004). Since then, aridification due to anthropogenic-driven warming has steadily reduced the overall water supply available in the basin, with a 10% decrease in the river’s flow occurring over just the past two decades (Bass et al., 2023). The river is further strained by increasing demands associated with a growing population and diverse multi-sectoral demands. Navigating these challenges also requires accounting for the complex prior appropriation water rights system governing water allocation across the region’s diverse users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I—Harnessing theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5-10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? In conclusion, the analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Advancing uncertainty characterization for understanding projected water scarcity in multi-sector, multi-actor river basins across scales.

Invited Talk at AGU Fall Meeting 2023 Modeling how human institutions and infrastructure interact with the water cycle is essential to better understand the vulnerability, and resilience of water resources systems from the local to the global scale. This is especially true when investigating multi-sector, multi-actor responses to the effects of long-term changes and short-term shocks. It is also well recognized that uncertainty present throughout the modeling cycle (e.g., in data, functional relations, and model coupling approaches) limits our ability to trace the interactive dynamics of human-water systems, as well as to quantify their implications for management and planning. Systems with large numbers of diverse stakeholders further compound this challenge, as uncertain drivers and complex dynamics might have very disparate effects on water users. The work presented is conducted through the Integrated Multisector Multiscale Modeling (IM3) Science Focus Area, which explores how human and natural systems co-evolve in response to change. Through this multi-year effort, we have developed exploratory modeling methods to better characterize how the uncertain human and natural drivers of water scarcity yield consequential vulnerabilities in institutionally complex, multi-sectoral systems. This talk will specifically present on a series of uncertainty characterization experiments performed in the Upper Colorado River Basin, a sub-basin of the Colorado with thousands of water users. These complementary and systematic experiments are aimed at understanding: How are various uncertain stressors (e.g., climate change, demand growth) affecting the diverse water users of this basin in terms of water shortage? What are the key drivers of this shortage for each user? Methods and results from this work are used to address additional questions on the ability of adaptation to modulate the effects of these uncertain drivers, and on their compounding effects across spatial scales and through sectoral interactions.

Hadjimichael, Antonia↗
DOE OSTI2026

Pathways of bio-jet adoption in the US aviation industry with implications for the overall transportation and energy sectors: an integrated, multi-sectoral analysis of future scenarios

Bio-jet adoption has emerged as an attractive option to complement and supplement the use of refined fossil liquid fuels in the aviation industry in the US. However, there are significant uncertainties surrounding the costs of bio-jet including but not limited to costs of feedstock, transformation costs and the competition with co-products of bio-jet that may be demanded elsewhere in the transportation or energy sectors. This study models alternative trajectories of bio-jet adoption in the US aviation industry by 2050 through the use of a global integrated multi sector dynamics model. Three bio-jet production and consumption pathways are presented- soybean oil to jet, corn ethanol to jet (ETJ) and Fisher–Tropsch-based bio-jet, with each pathway explicitly considering the co-production of renewable diesel and renewable gasoline alongside the bio-jet. Without explicit actions or technology changes to offset the technology cost of bio-jet, scenarios where bio-jet displaces refined liquids result in higher aviation fuel prices (ranging from a 25% increase to 120% increase by mid-century) and lower demand (ranging from −14% to −43%). Corn ethanol will play an important role in the US if large scale amounts of bio-jet are to be produced with smaller effects on demand and prices. While scenarios with high levels of bio-jet availability without the availability of ETJ in the US can significantly reduce emissions in the aviation sector, these reductions are achieved more through the reduction in overall aviation fuel demand rather than technology adoption.

09 BIOMASS FUELS↗