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

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• 作者：Rajen Bajgain ; Xiangming Xiao ; Jeffrey Basara…
• 关键词：Drought duration ; Drought intensity ; Land surface water index ; Summer drought
• 刊名：International Journal of Biometeorology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：61
• 期：2
• 页码：377-390
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment, general; Biological and Medical Physics, Biophysics; Meteorology; Animal Physiology; Plant Physiology; Environmental Health;
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-1254
• 卷排序：61

文摘

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 % (D₂ class, moderate drought) to 77 % (0 and D₀ 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.