David G. Groves

A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios

Robustness is a key criterion for evaluating alternative decisions under conditions of deep uncertainty. However, no systematic, general approach exists for finding robust strategies using the broad range of models and data often available to decision makers. This study demonstrates robust decision making (RDM), an analytic method that helps design robust strategies through an iterative process that first suggests candidate robust strategies, identifies clusters of future states of the world to which they are vulnerable, and then evaluates the trade-offs in hedging against these vulnerabilities. This approach can help decision makers design robust strategies while also systematically generating clusters of key futures interpretable as narrative scenarios. Our study demonstrates the approach by identifying robust, adaptive, near-term pollution-control strategies to help ensure economic growth and environmental quality throughout the 21st century.

Louisiana's 2012 Coastal Master Plan: Overview of a Science-Based and Publicly Informed Decision-Making Process

ABSTRACT Peyronnin, N.; Green, M.; Richards, C.P.; Owens, A.; Reed, D.; Chamberlain, J.; Groves, D.G.; Rhinehart, W.K., and Belhadjali, K., 2013. Louisianas 2012 Coastal Master Plan: overview of a science-based and publicly informed decision-making process. Louisiana is in the midst of a land loss crisis that has claimed more than 4800 km2 since the 1930s. Unless aggressive, large-scale action is taken, Louisiana could lose an additional 4500 km2 in the next 50 years, resulting in a projected increase in annual damages from hurricane storm surge flooding of more than

Moisture budget of the Arctic atmosphere from TOVS satellite data

23 billion. Louisianas 2012 Coastal Master Plan is a long-term plan with clear economic, social, and environmental benefits, such as decreasing potential damages from storm surge by

Paleoclimate Scenarios to Inform Decision Making in Water Resource Management: Example from Southern California’s Inland Empire

5.3 billion to

Planning Tool to Support Planning the Future of Coastal Louisiana

18 billion. Implementation of projects in the master plan should result in no net loss of land after 20 years and an annual net gain of land after 30 years. To develop the plan, the Coastal Protection and Restoration Authority (CPRA) utilized a state-of-the-art systems approach to coastal planning and a science-based decision-making process that resulted in a funding- and resource-constrained plan that makes the greatest progress toward achieving a sustainable coast. A series of integrated, coastwide predictive models were developed to provide data for a new planning tool used to identify the suite of projects that would make the greatest progress toward meeting the master plan objectives while considering uncertainties in future environmental conditions. Recognizing that the success of the plan hinges on stakeholder support, as well as science, the CPRA also implemented a comprehensive outreach plan to obtain input and feedback from key stakeholders and the public. The resulting plan recommends a specific list of restoration and protection projects and has achieved widespread support.

Robust Decision-Making in the Water Sector: A Strategy for Implementing Lima?S Long-Term Water Resources Master Plan

The Arctic atmospheric moisture budget is an important component of the Arctic climate system, and moisture transport is a major mechanism by which both local and hemispheric atmospheric processes affect the Arctic Ocean. The lack of humidity data over the Arctic Ocean severely hampers present understanding of climatological and time-varying features of the Arctic moisture budget. We combine daily satellite precipitable water retrievals from the NASA/NOAA TIROS Operational Vertical Sounder (TOVS) Polar Pathfinder data set with wind fields from the NCEP-NCAR Reanalysis to create a new high-resolution data set of the Arctic atmospheric moisture budget from October 1979 to December 1998. Products are at a horizontal resolution of (100 km) 2 and include daily fields of precipitable water and precipitable water flux profiles at 16 vertical levels and net precipitation (i.e., precipitation minus evaporation, P-E). We show that these retrievals compare well with rawinsonde-derived moisture transport and reanalysis products, yet capture spatial and temporal variability that other data sets cannot owing to the sparse coverage of the conventional observation network in the Arctic Ocean. Our method yields an average annual net precipitation of 15.1 cm yr -1 over the polar cap (poleward of 70°N) and 12.9 cm yr -1 over the Arctic Basin. Poleward moisture transport into the Arctic is greatest from June to August and smallest in December. Over regions of known storm tracks, especially in the North Atlantic sector, we find that transient circulation features account for 32% of the net precipitation in the Greenland-Iceland-Norwegian Seas, 90% in the Nansen Basin, and 74% in the Arctic basin as a whole.

Analysis to Support Louisiana's Flood Risk and Resilience Program and Application to the National Disaster Resilience Competition

AbstractSouthwestern United States paleoclimate reconstructions feature droughts that are longer and higher in magnitude than any water shortage during the twentieth century, and thus could aid water managers in planning for future severe droughts. This research used the robust decision-making (RDM) analytical framework to incorporate paleoclimate information into an analysis of long-range water management for a Southern California water agency. The analysis leverages a water management model to identify near-term management actions that may help mitigate water shortages over a wide range of future conditions reflecting various assumptions about climate, costs, and planning. Results indicate that a regional urban water management plan for 2005 is vulnerable to extended droughts and that enhancing water management actions in the near term reduces the risk of future unmet demand and shortage costs. Comparing results with previous work with the IEUA using climate model projections indicates some differences ...

Using High-Performance Computing to Support Water Resource Planning: A Workshop Demonstration of Real-Time Analytic Facilitation for the Colorado River Basin

ABSTRACT Groves, D.G. and Sharon, C., 2013. Planning tool to support planning the future of coastal Louisiana. Coastal Louisianas built and natural environment faces risks from catastrophic tropical storms. Concurrently, the region is experiencing a dramatic conversion of coastal land and associated habitats to open water and a loss of important services provided by such ecosystems. Louisianas Coastal Protection and Restoration Authority (CPRA) engaged in a detailed modeling, simulation, and analysis exercise, the results of which informed Louisianas 2012 Comprehensive Master Plan for a Sustainable Coast. The Master Plan defines a set of coastal risk-reduction and restoration projects to be implemented in the coming decades to reduce hurricane flood risk to coastal communities and restore the Louisiana coast. Risk-reduction and restoration projects were selected to provide the greatest level of risk-reduction and land-building benefits under a given budget constraint while being consistent with other objectives and principles of the Master Plan. A RAND project team, with the guidance of CPRA and other members of the Master Plan Delivery Team, developed a computer-based decision-support tool, called the CPRA Planning Tool. The Planning Tool provided technical analysis that supported the development of the Master Plan through CPRA and community-based deliberations. This article provides a summary of the Planning Tool and its application in supporting the development of Louisianas Master Plan.

Using High-Performance Computing to Support Water Resource Planning

How can water resource agencies make smart investments to ensure long-term water reliability when the future is fraught with deep climate and economic uncertainty? This study helped SEDAPAL, the water utility serving Lima, Peru, answer this question by drawing on state of the art methods for decision making under deep uncertainty. These methods provide techniques for evaluating the performance of a water system over a wide range of plausible futures and then developing strategies that are robust across these futures. Rather than weighting futures probabilistically to define an optimal strategy, these methodologies identify the vulnerabilities of a system and then evaluate the key trade-offs among different adaptive strategies. Through extensive iteration and collaboration with SEDAPAL, the study used these methods to define an investment strategy that is robust, ensuring water reliability across as wide a range of future conditions as possible while also being economically efficient. First,on completion, the study helped SEDAPAL realize that not all projects included in the Master Plan were necessary to achieve water reliability, and the utility could save 25 percent (more than

Evaluating Resource Management Strategies for Update 2013 of the California Water Plan

600 million) in investment costs. Second, the study helped focus future efforts on demand-side management, pricing, and soft infrastructure, a refocusing that is difficult to achieve in traditional utility companies. Third, the study helped SEDAPAL gain the support of regulatory and budget agencies through the careful analysis of alternatives. Fourth, the study allowed the utility to postpone lower priority investments, and to analyze future options based on climate and demand information that simply is not available now.