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This study compared simulated values of surface runoff and erosion from two current erosion prediction technologies (WEPP and GLEAMS) to observed data for two grazing pressures on three pasture vegetation types (switchgrass, bermudagrass, and tall fescue) in the Tennessee Valley region of Alabama. Based on the results of statistical analysis for each forage type and grazing pressure, GLEAMS performed better than WEPP, although either model did not predict sediment loss within an acceptable level. Because it was determined that grazing pressure had no significant impact on runoff and erosion from the experiment plots, the data for each forage were pooled over the same grazing pressure and the correlation between observed and simulated data were analyzed. This analysis showed that overall, predicted runoff values for both WEPP and GLEAMS had linear relationship to observed data. When sediment loss was analyzed, GLEAMS predicted value showed significant correlation with observed data, while WEPP predicted values did not. The results indicate that models may be useful as management decisionaids on pastures in the southeastern U.S., but more refinement to the models and available input data is necessary before predictions will be consistently accurate. [ABSTRACT FROM AUTHOR]

Abstract: The field of disaster risk management is relatively new and takes a structured approach to managing uncertainty related to the threat of natural and man-made disasters. Disaster risk management consists primarily of risk assessment and the development of strategies to mitigate disaster risk. This paper will discuss how increasing both Earth observation data and information technology capabilities can contribute to disaster risk management, particularly in Belize. The paper presents the results and recommendations of a project conducted by an international and interdisciplinary team of experts at the 2009 session of the International Space University in NASA Ames Research Center (California, USA). The aim is to explore the combination of current, planned and potential space-aided, airborne, and ground-based Earth observation tools, the emergence of powerful new web-based and mobile data management tools, and how this combination can support and improve the emerging field of disaster risk management. The starting point of the project was the World Bank’s Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) program, focused in Central America. This program was used as a test bed to analyze current space technologies used in risk management and develop new strategies and tools to be applied in other regions around the world. [ABSTRACT FROM AUTHOR]