A multi-criteria geographic information systems approach for the measurement of vulnerability to climate change

A flexible procedure for the development of a multi-criteria composite index to measure relative vulnerability under future climate change scenarios is presented. The composite index is developed using the Weighted Ordered Weighted Average (WOWA) aggregation technique which enables the selection of different levels of trade-off, which controls the degree to which indicators are able to average out others. We explore this approach in an illustrative case study of the United States (US), using future projections of widely available indicators quantifying flood vulnerability under two scenarios of climate change. The results are mapped for two future time intervals for each climate scenario, highlighting areas that may exhibit higher future vulnerability to flooding events. Based on a Monte Carlo robustness analysis, we find that the WOWA aggregation technique can provide a more flexible and potentially robust option for the construction of vulnerability indices than traditionally used approaches such as Weighted Linear Combinations (WLC). This information was used to develop a proof-of-concept vulnerability assessment to climate change impacts for the US Army Corps of Engineers. Lessons learned in this study informed the climate change screening analysis currently under way.     

The regional nature of PM2.5 episodes in the upper Ohio River Valley

From October 1999 through September 2000, particulate matter (PM) with aerodynamic diameter > or =2.5 microm (PM2.5) mass and composition were measured at the National Energy Technology Laboratory Pittsburgh site, with a particle concentrator Brigham Young University-organic sampling system and a tapered element oscillating microbalance (TEOM) monitor. PM2.5 measurements had also been obtained with TEOM monitors located in the Pittsburgh, PA, area, and at sites in Ohio, including Steubenville, Columbus, and Athens. The PM data from all these sites were analyzed on high PM days; PM2.5 TEOM particulate mass at all sites was generally associated with transitions from locally high barometric pressure to lower pressure. Elevated concentrations occurred with transport of PM from outside the local region in advance of frontal passages as the local pressure decreased. During high-pressure periods, concentrations at the study sites were generally low throughout the study region. Further details related to this transport were obtained from surface weather maps and estimated back-trajectories using the hybrid single-particle Lagrangian integrated trajectory model associated with these time periods. These analyses indicated that transport of pollutants to the Pittsburgh site was generally from the west to the southwest. These results suggest that the Ohio River Valley and possible regions beyond act as a significant source of PM and its precursors in the Pittsburgh area and at the other regional sites included in this study.     

Development of a Cropland Management Dataset to Support U.S. Swat Assessments

The Soil and Water Assessment Tool (SWAT) is widely used in the United States (U.S.) to simulate hydrology and water quality simulation. Process‐based models like SWAT require a great deal of data to accurately represent the natural world, including topography, land use, soils, weather, and management. With the exception of management, all these data are available nationally from multiple sources. To date, credible SWAT studies in the U.S. have assembled suitable management data (operation scheduling, fertilization application rates, and plant growth parameterization). In this research, we develop a national management database for SWAT using existing U.S. Department of Agriculture data sources. These data are compatible with existing SWAT interfaces and are relatively easy to use. Although management data from local sources is preferred, these data are not always available. This work is intended to fill this void with more reasonable management data than the existing defaults. This national database covers all major cultivated crops and should facilitate improved SWAT applications in the U.S. These data were tested in two case studies and found to produce satisfactory SWAT predictions. The database developed in this research is freely available on the web.