Integrated Assessment Research

The goal of the Integrated Assessment Research (IAR) program is to advance scientific understanding of the complex interactions, interdependencies, and co-evolutionary pathways of human and natural systems, including interdependencies among sectors and infrastructures. 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. The program additionally considers the role of socio-economics, risk analysis, and complex decision theory, as they pertain to describing the evolution and feedbacks within earth system science.        

Program Description

IAR Workshop Report
Latest IAR 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.

The human-Earth system, including settlements, infrastructure, natural resources, socio-economics, and importantly, interdependent sectors and natural systems, is highly complex and continuously changing.   Both strong and weak linkages define the oftentimes non-linear behaviors among components. Stressors, constraints, and other factors affecting change can take many forms and influence the system at varying spatial and temporal scales, oftentimes in unanticipated ways when viewed within the larger system. Consider, for example, the individual and combined effects of changing patterns of weather and its extremes, demographic distributions, economic growth and changes in industrial structure, improvements in technologies (e.g., for producing electricity), depletion of natural resources such as groundwater, or the discovery of new resources or means for resource extraction such as unconventional natural gas, and the evolution of regulatory and other institutional structures. All of these factors influence infrastructures and sectors that in turn can exhibit nonlinear regional responses as part of the earth system.   

One major focus of the IAR program is in understanding 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 program focus to understand the system dynamics governing interdependencies within the natural-human system, the program seeks to advance our 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, the program 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. 

Program 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.

The most recently closed Announcement (DE-FOA-0000219) requested applications for a single, coordinated research effort that would: 1) advance progress on a select set of major scientific challenges in the field of Integrated Assessment that are widely recognized and confronting the major Integrated Assessment modeling teams, 2) advance methods and capabilities for inter-model testing and diagnostics, and 3) enhance capabilities for multi-model, "ensemble-like" analyses for improved insights in science studies and science-based analyses.

Why the Program's Research is Important

IAR is necessary to understand the nonlinear science involving natural-human interdependency and feedbacks on the earth system. The program helps shape our fundamental understanding of complex stressors on human systems and infrastructure, vulnerabilities and risks at the energy-water-land nexus, multi-sector 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

Land cover conversion uncertainty constitutes a 5 ppmv range in estimated 2004 atmospheric CO2 concentration, a range of 2004 terrestrial carbon stock uncertainty that is 80% of net historical CO2 and climate effects on this stock, and over 1 °C range in local surface temperature estimates (1984-...
Flood frequency curve (FFC)—a mathematical expression of the probability distribution of floods—is an important tool for estimating flood risk, with a conventional assumption of stationary flood series data. However, environmental changes in the past decades are changing that assumption. A research...
Although often perceived as a natural hazard, drought can be affected by both climate anomalies and human activities such as water management. Using a high-resolution integrated modeling framework applied to the contiguous United States, a research team including scientists from the U.S. Department...
To estimate building energy demand by region, researchers typically use data from a limited number of “representative” weather stations for their model simulations. This reduces computational costs in order to make simulations easier to manage, but at the expense of capturing the full spatial...
Freshwater resources are finite and unevenly distributed, yet the demand—and competition—for freshwater is expected to grow, which may affect future freshwater resources. A team at the U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) developed Xanthos, an open-source...

Publications

Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the...
Reservoir operations may alter the characteristics of Flood Frequency Curve (FFC) and challenge the basic assumption of stationarity used in flood frequency analysis. This paper presents a combined data-modeling analysis of reservoir as a nonlinear filter of runoff routing that alters the FFCs. A...
Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the...
Numerical building models are typically forced with weather data from a limited number of “representative cities” or weather stations representing different climate regions. The use of representative weather stations reduces computational costs, but often fails to capture spatial heterogeneity in...