Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #353866

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Comparison of agricultural stakeholder survey results and drought monitoring datasets during the 2016 U.S. northern Plains flash drought

Author
item OKTIN, J. - University Of Wisconsin
item HAIGH, T. - University Of Nebraska
item MUCIA, A. - University Of Nebraska
item Anderson, Martha
item HAIN, C. - Goddard Space Flight Center

Submitted to: Weather, Climate, and Society
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/2018
Publication Date: 10/15/2018
Citation: Oktin, J., Haigh, T., Mucia, A., Anderson, M.C., Hain, C. 2018. Comparison of agricultural stakeholder survey results and drought monitoring datasets during the 2016 U.S. northern Plains flash drought. Weather, Climate, and Society. 10:867-883. https://doi.org/10.1175/WCAS-D-18-0051.1.
DOI: https://doi.org/10.1175/WCAS-D-18-0051.1

Interpretive Summary: While many different types of drought maps are currently being generated for the United States and used for identifying impacts on agriculture, it is not often that feedback on these products is solicited from agricultural producers themselves. Particularly with the advent of new drought products based on remote sensing, it is important to understand whether the higher spatial resolution information afforded by satellite imaging systems is adequately capturing real stress events with good spatial and temporal fidelity. This paper describes a result of a survey conducted with agricultural stakeholders regarding drought index portrayal of the 2016 drought in the U.S. northern Plains. The survey asked respondents to estimate when certain events such as decreased topsoil moisture and plant stress initially occurred on their land. These responses were compared, spatially and temporally, to signals identified in drought indices based on remote sensing measures of precipitation, soil moisture and evapotranspiration as well as to the U.S Drought Monitor. Overall, the survey responses revealed that this was a multi-faceted drought event characterized by soil moisture deficits, plant stress, and lowered water levels in ponds, streams, and wells. The soil moisture dataset provided the earliest warning of areas of stress development, but at the expense of high rates of false alarm. Though the evapotranspiration datasets did not provide early warning during this particular event, its spatial extent was more closely aligned with the survey reports of plant stress than the other datasets and also provided a more focused depiction of where the worst drought conditions were occurring based on vegetation impacts. This study demonstrates that qualitative reports obtained via surveys administered to stakeholders after a drought event provide valuable information that can be used to assess the accuracy of drought monitoring datasets.

Technical Abstract: The evolution of a flash drought event characterized by a period of rapid drought intensification is assessed using standard drought monitoring datasets and on-the-ground reports obtained via a written survey of agricultural stakeholders after the flash drought occurred. The flash drought examined during this study impacted agricultural production across a 5-state region centered on the Black Hills of South Dakota during the summer of 2016. The survey asked producers to estimate when certain drought impacts ranging from decreased soil moisture to plant stress and diminished water resources first occurred on their land. The geographic distribution and timing of the survey responses were compared to the U.S. Drought Monitor and to datasets depicting anomalies in evapotranspiration, precipitation, and soil moisture. Overall, the survey responses showed that this was a multi-faceted drought that caused a variety of impacts across the region. Comparisons of the survey reports to the drought monitoring datasets revealed that the topsoil moisture dataset provided the earliest warning of drought development, but at the expense of a high false alarm rate. Anomalies in evapotranspiration were closely aligned to the survey reports of plant stress and also provided a more focused depiction of where the worst drought conditions were located. This study provides evidence that qualitative reports of drought impacts obtained via written surveys provide valuable information that can be used to assess the accuracy of high-resolution drought monitoring datasets.