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International Journal of Biometeorology

, Volume 61, Issue 2, pp 377–390 | Cite as

Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS

  • Rajen Bajgain
  • Xiangming XiaoEmail author
  • Jeffrey Basara
  • Pradeep Wagle
  • Yuting Zhou
  • Yao Zhang
  • Hayden Mahan
Original Paper

Abstract

Agricultural drought, a common phenomenon in most parts of the world, is one of the most challenging natural hazards to monitor effectively. Land surface water index (LSWI), calculated as a normalized ratio between near infrared (NIR) and short-wave infrared (SWIR), is sensitive to vegetation and soil water content. This study examined the potential of a LSWI-based, drought-monitoring algorithm to assess summer drought over 113 Oklahoma Mesonet stations comprising various land cover and soil types in Oklahoma. Drought duration in a year was determined by the number of days with LSWI <0 (DNLSWI) during summer months (June–August). Summer rainfall anomalies and LSWI anomalies followed a similar seasonal dynamics and showed strong correlations (r 2 = 0.62–0.73) during drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the east-west gradient of summer rainfall in Oklahoma. Drought intensity increased with increasing duration of DNLSWI, and the intensity increased rapidly when DNLSWI was more than 48 days. The comparison between LSWI and the US Drought Monitor (USDM) showed a strong linear negative relationship; i.e., higher drought intensity tends to have lower LSWI values and vice versa. However, the agreement between LSWI-based algorithm and USDM indicators varied substantially from 32 % (D 2 class, moderate drought) to 77 % (0 and D 0 class, no drought) for different drought intensity classes and varied from ∼30 % (western Oklahoma) to >80 % (eastern Oklahoma) across regions. Our results illustrated that drought intensity thresholds can be established by counting DNLSWI (in days) and used as a simple complementary tool in several drought applications for semi-arid and semi-humid regions of Oklahoma. However, larger discrepancies between USDM and the LSWI-based algorithm in arid regions of western Oklahoma suggest the requirement of further adjustment in the algorithm for its application in arid regions.

Keywords

Drought duration Drought intensity Land surface water index Summer drought 

Notes

Acknowledgments

This study was supported in part by a research grant (Project No. 2012-02355) through the USDA National Institute for Food and Agriculture (NIFA)’s Agriculture and Food Research Initiative (AFRI), Regional Approached for Adaptation and Mitigation of Climate Variability and Change grant (IIA-1301789), NOAA Climate Office’s Sectoral Applications Research Program (SRP) grant NA130AR4310122, and Oklahoma’s taxpayers fund for the Oklahoma Mesonet through the Oklahoma State Regents for Higher Education and the Oklahoma Department of Public Safety. We would also like to acknowledge the National Drought Mitigation Center at the University of Nebraska-Lincoln, the US Department of Agriculture, and the National Oceanic and Atmospheric Administration for the dataset.

Supplementary material

484_2016_1218_MOESM1_ESM.docx (43 kb)
Table S1 (DOCX 42 kb)

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Copyright information

© ISB 2016

Authors and Affiliations

  • Rajen Bajgain
    • 1
  • Xiangming Xiao
    • 1
    • 2
    Email author
  • Jeffrey Basara
    • 3
    • 4
  • Pradeep Wagle
    • 1
  • Yuting Zhou
    • 1
  • Yao Zhang
    • 1
  • Hayden Mahan
    • 3
  1. 1.Department of Microbiology and Plant Biology, Center for Spatial AnalysisUniversity of OklahomaNormanUSA
  2. 2.Ministry of Education Key Laboratory for Biodiversity Science, and Engineering, Institute of Biodiversity of SciencesFudan UniversityShanghaiChina
  3. 3.School of MeteorologyUniversity of OklahomaNormanUSA
  4. 4.Oklahoma Climate SurveyNormanUSA

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