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

The North Pacific and North Atlantic subtropical highs exert substantial influence on the regional climates over East Asia and North America. Previous studies focusing on the future changes of these two subtropical high-pressure systems during boreal summer did not find consistent changes....
Understanding the driving mechanisms and uncertainties of sea-level changes pose nontrivial geophysical and statistical challenges.  A team of geoscientists and statisticians supported through a Stanford University led, multi-institutional Cooperative Agreement analyzed how improving the method to...
Environmental change is likely to affect global food production, with some regions under heightened risk to droughts, flooding and other disruption. One powerful countermeasure is irrigation: globally, production on a hectare of irrigated land is 2.7 times that on dry land. The future of irrigation...
Extreme weather events such as floods and droughts, are among the costliest natural disasters our society faces. Yet earth system model simulations of extreme precipitation events are not directly comparable to what we measure in our rain gauges. This is primarily due to relatively coarse spatial...
Regional and global changes in crop yields impact land-use change, with implications for carbon sources and sinks and the energy balance and hydrological feedbacks to the Earth system. To assess likely environmental impacts on crop yields, researchers typically run a combination of earth system and...

Publications

The subtropical highs have a zonal mean and a zonally asymmetric component related to the Hadley cell and land‐sea contrast, respectively. Based on 37 Coupled Model Intercomparison Project phase 5 models, relative roles of the Hadley cell and land‐sea contrast in future changes of the North Pacific...
Sea-level rise is a key driver of projected flooding risks. The design of strategies to manage these risks often hinges on projections that inform decision-makers about the surrounding uncertainties. Producing semi-empirical sea-level projections is difficult, for example, due to the complexity of...
While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water...
Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and...
This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding...