Views of the 2016 Northern Plains Flash Drought: Farmer Perspectives and Remote Sensing Data

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1 Views of the 2016 Northern Plains Flash Drought: Farmer Perspectives and Remote Sensing Data PRESENTATION BY TONY MUCIA RESEARCH CONDUCTED BY JASON OTKIN, TONYA HAIGHT, AND TONY MUCIA

2 Project Overview Summer 2016 flash drought event Impacted agriculture across 5-state region centered on Black Hills, SD Goal of this project is to compare timing and severity of several drought products (USDM, ESI, GRACE) to agricultural stakeholder s perception My research focus is on GRACE drought products

3 Agricultural Survey Survey sent to 2389 producers in SD, WY, NE, and MT counties that experienced at least abnormally dry (D0) conditions by July were returned by agricultural stakeholders Survey data grouped by zip code

4 Agricultural Survey - Results MEAN N/A NO YES DATE A. Decreased topsoil moisture (n=329) 2% 4% 94% May 14 B. Decreased subsoil moisture (n=319) 3% 7% 90% May 21 C. Delayed or lack of plant emergence (n=317) 9% 26% 65% May 20 D. Delayed or lack of plant growth (n=321) 2% 11% 87% May 31 E. Plant stress (crop or pasture) (N=318) 2% 6% 92% Jun 16 F. Plant death (crop or pasture) (N=302) 9% 40% 51% June 27 G. Poor grain fill (n=301) 46% 15% 39% June 29 Focus on a single, multi-part question regarding: Did certain drought conditions occur? If so, when did it start? Date of first occurrence for each condition were average by zip code and plotted H. Deteriorating range conditions (n=319) 5% 8% 86% June 17 I. Decreased forage productivity (n=316) 5% 9% 86% June 13 J. Lowered water levels in ponds, streams, or other water sources 11% 9% 80% June 6 (n=318) K. Lack of water in ponds, streams, or other water sources (n=317) 13% 16% 70% June 16 L. Wells unable to keep up with livestock or irrigation needs 28% 56% 16% June 30 (n=307) M. Fire (n=311) 23% 59% 17% July 6 N. Infestations of insects or other pests (n=305) 18% 57% 25% June 15

5 GRACE Gravity Recover and Climate Experiment Sense changes in Earth s gravity by measuring distance change between the two satellites using a microwave laser Most of the gravity changes are caused by water GRACE TWS is assimilated into the Catchment Land Surface Model Each week the assimilated data can be ranked as a percentile of the total historical record Catchment outputs: GWS Groundwater Storage SWE Snow Water Equivalent RZMC Root Zone Moisture Content Credit: NASA Eyes

6 Evaporative Stress Index (ESI) Standardized anomalies in ratio of actual ET to reference ET Actual ET flux estimated from remote sensed land surface temperature* Conveys useful information about vegetation health and soil moisture availability *Anderson et al. 1997, 2007a,b, 2011

7 Time Series Look at survey responses, USDM, ESI, and GRACE RZMC and GWS at monthly intervals Blue outlines represent first occurrence of conditions in that month Black outlines represent first occurrence of conditions previous to that month

8 March QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

9 April QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

10 May QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

11 June QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

12 July QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

13 August QA Decreased TS Moisture QB Decreased SS Moisture QJ Lowered Water Levels 4 Week ESI GRACE RZMC GRACE GWS

14 Quantitative Results USDM, ESI, and GRACE values were over each zip code Zip code values were extracted based on each individual reports of first occurrence (348) then averaged over all reports Temporal trends between 6 weeks prior to 6 weeks after first occurrence were plotted based on these values Only use weeks 9 39 to avoid winter reports

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18 Conclusion Like ESI, GRACE RZMC shows widespread rapid deteriorating conditions after most zip codes first saw decreasing soil moisture Averaged over all zip codes, RZMC showed steady decrease up to six weeks before first occurrence reports Generally good agreement between USDM, RZMC, and ESI GRACE GWS showed ~10% decrease over the drought period Flash droughts typically don t have great effects on long-term groundwater trends GRACE products show promise as a standalone drought indicator and as part of a suite of modeled drought tools

19 Questions? Contact: Tony Mucia

20 Citations Anderson, M. C., J. M. Norman, G. R. Diak, W. P. Kustas, and J. R. Mecikalski, 1997: A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ., 60, Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas, 2007a: A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: 1. Model formulation. J. Geophys. Res., 112, D10117, doi: /2006jd Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas, 2007b: A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: 2. Surface moisture climatology. J. Geophys. Res., 112, D11112, doi: /2006jd Anderson, M. C., C. Hain, B. Wardlow, A. Pimstein, J. R. Mecikalski, and W. P. Kustas, 2011: Evaluation of drought indices based on thermal remote sensing and evapotranspiration over the continental United States. J. Climate, 24, Houborg, R., Rodell, M., Li, B., Reichle, R., & Zaitchik, B. F. (2012). Drought indicators based on model-assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations. Water Resources Research, 48(7). Otkin, J. A., M. C. Anderson, C. Hain, M. Svoboda, D. Johnson, R. Mueller, T. Tadesse, B. Wardlow, and J. Brown, 2016: Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought. Agr. Forest Meteorol., , Otkin, J. A., M. C. Anderson, C. Hain, and M. Svoboda, 2014: Examining the relationship between drought development and rapid changes in the Evaporative Stress Index. J. Hydrometeor., 15, Otkin, J. A., M. Svoboda, E. D. Hunt, T. W. Ford, M. C. Anderson, C. Hain, and J. B. Basara, 2018: Flash droughts: A review and assessment of the challenges imposed by rapid onset droughts in the United States. Bull. Am. Meteorol. Soc., in press. Su, H., Yang, Z. L., Dickinson, R. E., Wilson, C. R., & Niu, G. Y. (2010). Multisensor snow data assimilation at the continental scale: The value of Gravity Recovery and Climate Experiment terrestrial water storage information. Journal of Geophysical Research Atmospheres, 115(10), Svoboda, M., and Coauthors, 2002: The drought monitor. Bull. Am. Meteorol. Soc., 83, Swenson, S. C. and J. Wahr, Post-processing removal of correlated errors in GRACE data, Geophys. Res. Lett., 33, L08402, doi: /2005gl025285, Wahr, J., Molenaar, M., & Bryan, F. (1998). Time variability of the Earth s gravity field: Hydrological and oceanic effects and their possible detection using GRACE. Journal of Geophysical Research: Solid Earth, 103(B12),