MultiSector Dynamics

MultiSector Dynamics seeks to advance scientific understanding of the complex interactions, interdependencies, and co-evolutionary pathways of human and natural systems, including interdependencies among sectors and infrastructures. This includes advancing relevant socio-economic, risk analysis, and complex decision theory methods to lead insights into earth system science, while emphasizing the development of interoperable data, modeling, and analysis tools for integration within flexible modeling frameworks.

This program area's efforts inform some of the most significant energy, economic, and infrastructure decisions affecting the world today.

Program Area Description

The human-earth system—including settlements, infrastructure, natural resources, socio-economics, and interdependent sectors and natural systems—is highly complex and continuously changing, with stressors, constraints, and other factors that affect change taking many forms and influencing the system at varying spatial and temporal scales, often in unanticipated ways.

Scientific insights and tools emerging from MultiSector Dynamics hold significant potential to inform next-generation U.S. infrastructure and new development pathways for improved energy and economic security, including implications of and for technological and systems innovations.

Topical areas of focus in MultiSector Dynamics include:

  • Multi-model, multi-scale frameworks, software couplers, and component emulators
  • Interdependencies among energy, water, and land systems and the natural environment
  • Infrastructure, sectoral interactions, and resilience under rapid change
  • Urban morphologies, population dynamics, and landscape evolution
  • Simulation complexity in energy-intensive, multisector regions under stress (e.g., coasts)
  • Influences of extreme events and compounding stressors on system shocks and responses
  • Scenarios, sensitivity studies, uncertainty characterization, and interpretation of results
  • Data science, analytics, fusion methods, and machine learning

Research Emphasis

There is a particular emphasis on understanding the energy-water-land nexus under both realistic and idealized forcing scenarios, including the evaluation of scale-aware processes and probabilistic uncertainties that can lead to instability through thresholds and tipping points.

IAR Workshop Report
Latest sponsored workshop report, centered on an interagency activity involving multi-disciplinary science community input, addresses: Understanding Dynamics and Resilience in Complex Interdependent Systems – Prospects for a Multi-Model Framework and Community of Practice.

This major focus area seeks to understand the growing interdependencies and risks at the intersection of the energy, water, and land sectors. The recent disruptive effects and economic losses associated with the growing intensity, frequency, and persistence of droughts, floods, heat waves, and tropical storms in the United States have highlighted the importance of this research and integrated modeling capability. For example, energy is required for water and wastewater treatment, groundwater pumping, and large-scale inter-basin transfers. Needs, risks, and vulnerabilities of the coupled system are large and growing in the face of shifting weather and precipitation patterns, water supplies that depend on increasingly limited groundwater, transitions in regional economic development (including land use), as well as U.S. population shifts. In contrast, approximately 45% of water withdrawals in America’s rivers and streams are for energy applications, ranging from thermo-electric cooling (e.g., fossil and nuclear power plants) to domestic oil and gas recovery. Hydropower is similarly challenged to respond to increasing competition for limited water supply.

Besides the focus to understand the system dynamics governing interdependencies within the natural-human system, this area seeks to advance scientists' understanding of system nonlinearity and instability associated with multiple stressors that can lead to cascading failures in connected sectors and systems. An important characteristic of nonlinearity and system failure is the probabilistic interdependence near thresholds associated with extreme weather, severe drought, and infrastructure vulnerability. Consequently, MultiSector Dynamics supports the development of interoperable tools and methods for integration with agile, flexible earth system modeling frameworks, revealing a basic understanding of different levels of complexity required to analyze interdependency. 

Funding Opportunity Announcements

Announcements are posted on the DOE Office of Science Grants and Contracts Website and at grants.gov. Information about preparing and submitting applications, as well as the DOE Office of Science merit review process, is available at the DOE Office of Science Grants and Contracts Website. For current announcements visit BER Funding Opportunities.

Why MultiSector Dynamics' Research is Important

MultiSector Dynamics efforts are necessary to understand the nonlinear science involving natural-human interdependency and feedbacks on the earth system. This program area helps shape fundamental understanding of complex stressors on human systems and infrastructure, vulnerabilities and risks at the energy-water-land nexus, multisector dynamics, and more generally, implications for regional and global economic development in the face of changing weather patterns and extremes, advances in technology, availability of natural resources, and feedbacks to natural systems, including regional and global climates.  

Featured Reports

Recent Content

Recent Highlights

Energy is critical for human wellbeing and continued economic development and is also one of the human systems most directly influenced by changes in climate. Previous studies have tended to focus on a single country, world region or economic sector (e.g., households), and rely on projections from...
Power system operations are usually evaluated through system reliability and economic perspectives, with assumptions based on average market prices and normal water availability. However, fuel price volatility and changes in water availability can greatly affect localized and inter-regional...
Earth system models (ESMs) provide the best predictions of future climate trajectories by simulating all of the physical processes that drive the climate system. However, they require a large amount of computing time, memory, and power. As a result, researchers are generally limited to running a...
Future climate and land use conditions are two major drivers of crop consumption of green water (precipitation) and blue water (irrigation). However, projections of crop green and blue water consumption under an internally consistent set of future climate and land use conditions are still lacking....
High-resolution regional climate simulations coupled with a satellite-driven urban canopy model are used to investigate the interacting effects of climate change, population growth, and urban heat mitigation measures on exposure to extreme heat events and associated energy demands.
Predicting environmental conditions several weeks to months in advance has significant socioeconomic value. However, a gap exists between current short-term weather forecasts and subseasonal forecasts made two weeks to three months in advance, respectively. Further complicating the latter challenge...
The climate in the western United States is characterized by temperate, wet winters; warm, dry summers; and a pronounced wet season from October to April. Understanding potential future changes in seasonal precipitation due to warming in the western U.S. can help in predicting wildfires, droughts,...
Atmospheric rivers (ARs) are long, narrow bands of intense moisture that originate in the tropics and travel long distances through the sky. Scientists have confirmed a link between ARs and extreme precipitation events on the U.S. West Coast. However, the likelihood and the characteristics of ARs...
Although the occurrence of positive correlations between SST and near-surface wind speed over oceanic mesoscale ranges is well-known, the intrinsic spatial and temporal scales over which this air–sea coupling regime takes place are not well established. The contribution of the near-ubiquitous...
Modeling water resource management is a challenge because of the interactions between human decisions, the natural hydrologic cycle, and the impact of risk perception on human decision-making.  A study by scientists at Lehigh University, Sandia National Laboratories, and the National Renewable...

Recent Publications

Future energy demand is likely to increase due to climate change, but the magnitude depends on many interacting sources of uncertainty. We combine econometrically estimated responses of energy use to income, hot and cold days with future projections of spatial population and national income under...
The energy sector is heavily dependent on surface water availability for reliable electricity generation. Power system operations are usually evaluated through system reliability and economic perspectives, with assumptions based on market prices and normal water availability. As natural gas...
One near-term expression of climate change is increased occurrence and intensity of extreme heat events. The evolution of extreme heat risk in cities depends on the interactions of large-scale climate change with regional dynamics and urban micro-climates as well as the distribution and demographic...
Changes in subseasonal precipitation variability have important implications for predictability of weather and climate extreme. Here we explore the mechanisms that lead to future changes in subseasonal precipitation variability in North America during winter based on 20 state‐of‐the‐art climate...
The mean precipitation along the U.S. West Coast exhibits a pronounced seasonality change under warming. Here we explore the characteristics of the seasonality change and investigate the underlying mechanisms, with a focus on quantifying the roles of moisture (thermodynamic) versus circulation (...
We quantified the relationship between atmospheric rivers (ARs) and occurrence and magnitude of extreme precipitation in western U.S. watersheds, using ARs identified by the Atmospheric River Tracking Method Intercomparison Project and precipitation from a high‐resolution regional climate...
Agriculture accounts for 90% of global freshwater consumption and it is expected to intensify in the future. Climate and land use changes are two major factors affecting crop green and blue water consumption, and in this study we explicitly consider the effects of both factors in a consistent...
Reduced complexity climate models are useful tools for quantifying decision‐relevant uncertainties, given their flexibility, computational efficiency, and suitability for large‐ensemble frameworks necessary for statistical estimation using resampling techniques (e.g., Markov chain Monte Carlo)....
Earth system models (ESMs) are the gold standard for producing future projections of climate change, but running them is difficult and costly, and thus researchers are generally limited to a small selection of scenarios. This paper presents a technique for detailed emulation of the Earth system...
Many of the world's major freshwater aquifers are being exploited unsustainably, with some projected to approach environmentally unsafe drawdown limits within the 21st century. Given that aquifer depletion tends to occur in important crop producing regions, the prospect of running dry poses a...