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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #304373

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Using temporal changes in drought indices to generate probabilistic drought intensification forecasts

item OTKIN, J. - University Of Wisconsin
item Anderson, Martha
item HAIN, C. - University Of Maryland
item SVOBODA, M. - University Of Nebraska

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/28/2014
Publication Date: 2/1/2015
Citation: Otkin, J., Anderson, M.C., Hain, C., Svoboda, M. 2015. Using temporal changes in drought indices to generate probabilistic drought intensification forecasts. Journal of Hydrometeorology. 16:88-105.

Interpretive Summary: Current emphasis in the development of new drought monitoring tools is early detection and forecasting of drought onset and evolution. Early warning of impending severe drought facilitates better adaptive response on the part of growers, markets, and water resource managers. While static satellite-based drought monitoring products provide useful information about current anomalies in, e.g., soil moisture or crop water use (evapotranspiration), there is also predictive value in looking at changes in these products – are soil moisture and crop stress conditions improving or disimproving with time? This paper explores the utility of a “Rapid Change Index”, or RCI, which effectively distills information from time-series of satellite-based moisture products to identify areas where conditions are most rapidly evolving for better or for worse. In retrospective analyses, the RCI is in many cases able to effectively isolate areas of rapid drought onset or “flash drought” that have occurred within the US over the past decade. In addition, statistical analyses were performed to use the RCI values to assess the probability that drought severity classes in the U.S. Drought Monitor would improve or degrade by one or more classes over a two to eight week period in the future. Skill and accuracy assessments suggest that in many parts of the US these “forecasts” have value in terms of predicting future near-term evolution in drought conditions in the absence of major relieving rainfall.

Technical Abstract: In this study, the potential utility of using rapid temporal changes in drought indices to provide early warning of an elevated risk for drought development over sub-seasonal time scales is assessed. Standardized change anomalies were computed each week during the 2000-2012 growing seasons for drought indices depicting anomalies in evapotranspiration, precipitation, and soil moisture. A Rapid Change Index (RCI) that encapsulates the accumulated magnitude of rapid changes in the weekly anomalies was computed each week for each drought index, and then a simple statistical method was used to convert the RCI values into drought intensification probabilities depicting the likelihood that drought severity as analyzed by the United States Drought Monitor (USDM) would worsen in subsequent weeks. Local and regional case study analyses revealed that elevated drought intensification probabilities often occur several weeks prior to changes in the USDM and in topsoil moisture and crop condition datasets compiled by the National Agricultural Statistics Service. Statistical analyses showed that the RCI-derived probabilities have reasonable reliability and forecast skill, especially over the central and eastern United States in regions most susceptible to rapid drought development. Taken together, these results suggest that tools used to identify areas experiencing rapid changes in drought indices may be useful components of future drought early warning systems.