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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 #327409

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

Location: Hydrology and Remote Sensing Laboratory

Title: Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought

Author
item OTKIN, J. - UNIVERSITY OF WISCONSIN
item Anderson, Martha
item HAIN, C. - UNIVERSITY OF MARYLAND
item SVOBODA, M. - UNIVERSITY OF NEBRASKA
item JOHNSON, D. - NATIONAL AGRICULTURAL STATISTICAL SERVICE (NASS, USDA)
item MUELLER, RICK - NATIONAL AGRICULTURAL STATISTICAL SERVICE (NASS, USDA)
item TADESSE, T. - UNIVERSITY OF NEBRASKA
item WARDLOW, B. - UNIVERSITY OF NEBRASKA
item BROWN, J. - U.S. GEOLOGICAL SURVEY (USGS)

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/28/2015
Publication Date: 1/6/2016
Citation: Otkin, J., Anderson, M.C., Hain, C., Svoboda, M., Johnson, D., Mueller, R., Tadesse, T., Wardlow, B., Brown, J. 2016. Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought. Agricultural and Forest Meteorology. 218-219, 230-242.

Interpretive Summary: The rapid onset, or "flash", drought that rapidly enveloped much of the Cornbelt in 2012 was not well predicted in advance by standard drought indicators (e.g., precipitation deficits). The US Drought Monitor (USDM) was also delayed in its depiction of this drought, due the reliance to date on these standard indicators. As a result, growers were observing stress in the field well before the event was revealed in standard sources. This was due in part to the unique nature of flash droughts, which result in part from lower rainfall but are rapidly exacerbated by hot, dry windy atmospheric conditions which drive rapid evaporation of available soil moisture. Thermal signs of crop stress, detectable, may preceed physical degradation of the vegetation canopy in such cases. This paper investigates the relative response time of several drought indicators and the USDM to rapidly developing drought conditions during the 2012 growing season. County-level observations of crop condition, collected and distributed by the National Agricultural Statistics Service (NASS), were used as independent verification of actual stress conditions experienced on the ground. The study found that a thermal infrared based Evaporative Stress Index (ESI) provided early indication of drought onset and good spatial correlation with the evolution of sub-standard crop conditions from the NASS dataset. These findings are being used to improve response time of vegetation condition indicators that can be used in the USDM in the future, integrating rapid response information from the ESI.

Technical Abstract: This study examines the evolution of several model-based and satellite-derived drought metrics sensitive to soil moisture and vegetation conditions during the extreme flash drought event that impacted major agricultural areas across the central U.S. during 2012. Standardized anomalies from the remote sensing based Evaporative Stress Index (ESI) and Vegetation Drought Response Index (VegDRI) and soil moisture anomalies from the North American Land Data Assimilation System (NLDAS) are compared to the United States Drought Monitor (USDM), surface meteorological conditions, and crop and soil moisture data compiled by the National Agricultural Statistics Service (NASS). Overall, the results show that rapid decreases in the ESI and NLDAS anomalies often preceded drought intensification in the USDM by up to 6 weeks depending on the region. Decreases in the ESI tended to occur up to several weeks before deteriorations were observed in the crop condition datasets. The NLDAS soil moisture anomalies were similar to those depicted in the NASS soil moisture datasets; however, some differences were noted in how each model responded to the changing drought conditions. The VegDRI anomalies tracked the evolution of the USDM drought depiction in regions with slow drought development, but lagged the USDM and other drought indicators when conditions were changing rapidly. Comparison to the crop condition datasets revealed that soybean conditions were most similar to ESI anomalies computed over short time periods (2-4 weeks), whereas corn conditions were more closely related to longer-range (8-12 week) ESI anomalies. Crop yield departures were consistent with the drought severity depicted by the ESI and to a lesser extent by the NLDAS and VegDRI datasets.