Assessing Summer Drought over Oklahoma Mesonet Sites with the MODIS Land Surface Water Index

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 infra-red (NIR) and short wave infra-red (SWIR), is sensitive to vegetation and soil water content. This study was conducted to test the hypothesis that the information rendered from LSWI can be used for drought monitoring under various land covers and soil types of Oklahoma. We used a LSWI-based drought monitoring algorithm to assess summer drought in 113 Oklahoma Mesonet stations. Drought duration and intensity were estimated based on duration of LSWI < 0 (DNLSWI) during summer months (Jun-Aug) and results were compared with the United States Drought Monitor (USDM). Results of LSWI analysis for the period of 2000-2013 revealed a strong correlation (r²= 0.61 – 0.68) and dynamics between LSWI anomalies and summer rainfall anomalies in drought years (2001, 2006, 2011, and 2012). The DNLSWI tracked the longitudinal gradient of summer rainfall in Oklahoma. The LSWI-based drought intensity analysis showed a consistent trend that higher drought intensity tends to have lower LSWI values and lower intensity drought tends to have higher LSWI values regardless of land covers and soil types. However, the accuracy for different drought classes varied substantially from 32% (D2 class) to 77 % (0 and D0 class). Results showed that drought intensity increased as the DNLSWI became longer. As DNLSWI became larger (> 48 days), rapid development of drought intensity was observed. Results also demonstrated that by counting DNLSWI (in days), drought intensity thresholds can be established and used as a simple complementary tool in several drought applications which have currently used a relatively complex, resource intensive USDM drought intensity classification.