title: Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS.
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 (r2= 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 % (D2class, moderate drought) to 77 % (0 and D0class, 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.
authors: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, OK, 73019, USA.
authors: Rajen
authors: R
authors: Bajgain
authors: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, OK, 73019, USA. xiangming.xiao@ou.edu.|Ministry of Education Key Laboratory for Biodiversity Science, and Engineering, Institute of Biodiversity of Sciences, Fudan University, Shanghai, 200433, China. xiangming.xiao@ou.edu.
authors: Xiangming
authors: X
authors: Xiao
authors: School of Meteorology, University of Oklahoma, Norman, OK, USA.|Oklahoma Climate Survey, Norman, OK, USA.
authors: Jeffrey
authors: J
authors: Basara
authors: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, OK, 73019, USA.
authors: Pradeep
authors: P
authors: Wagle
authors: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, OK, 73019, USA.
authors: Yuting
authors: Y
authors: Zhou
authors: Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, 101 David L. Boren Blvd, Norman, OK, 73019, USA.
authors: Yao
authors: Y
authors: Zhang
authors: School of Meteorology, University of Oklahoma, Norman, OK, USA.
authors: Hayden
authors: H
authors: Mahan
mesh_terms: D000383:Agriculture; D000465:Algorithms; D055864:Droughts; D009825:Oklahoma; D011891:Rain; D063809:Satellite Imagery; D012621:Seasons; D014867:Water
chemical_list: D014867:Water
keywords: Drought duration; Drought intensity; Land surface water index; Summer drought