Publications

Zhou, YT; Xiao, XM; Zhang, GL; Wagle, P; Bajgain, R; Dong, JW; Jin, C; Basara, JB; Anderson, MC; Hain, C; Otkin, JA (2017). Quantifying agricultural drought in tallgrass prairie region in the US Southern Great Plains through analysis of a water-related vegetation index from MODIS images. AGRICULTURAL AND FOREST METEOROLOGY, 246, 111-122.

Abstract
Severe droughts in the Southern Great Plains (SGP: Kansas, Oklahoma, and Texas) in recent years have reduced the productivity of tallgrass prairie and resulted in substantial economic losses to the beef cattle industry in this region. Understanding spatial and temporal patterns of agricultural drought in the SGP can help ranchers to develop and implement drought mitigation strategies. In this study, the Land Surface Water Index (LSWI), calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) near infrared and shortwave infrared bands, was used to assess agricultural drought in the tallgrass prairie region of the SGP during 2000-2013. The number of consecutive days with LSWI < 0 (DNLSWI) during the growing season was defined as the drought duration, which, was then used to identify and analyze frequency of summer drought and whole growing season drought (WGSD). The spatial pattern of DNLSWI was consistent with the east-to-west decreasing precipitation gradient across the SGP region. Summer drought duration as depicted by the DNLSWI in the western portion of the study area was around one and a half month. The occurrence of WGSD increased from one year in the east to up to six years in the west, demonstrating the susceptibility of the tallgrass prairie region to drought. In addition to the total amount of precipitation, its intra-annual distribution also played an important role in drought development. A comparison with other widely used national drought products, namely the Evaporative Stress Index (ESI), the Vegetation Drought Response Index (VegDRI), and the United States Drought Monitor (USDM), shows that LSWI-based drought has good agreement with ESI and USDM. Quantitative analyses indicate that LSWI-based drought agreed better with ESI in severe drought conditions than in moderate or pre-drought conditions. Severe drought periods characterized by the USDM also had low LSWI values. The areas affected by drought derived from the LSWI-based drought index were significantly correlated with hay production. As an indicator of vegetation water stress at moderate spatial resolution (similar to 500 m), the LSWI has the potential to show drought conditions for an individual ranch and offer guidance for drought mitigation activities and livestock production.

DOI:
10.1016/j.agrformet.2017.06.007

ISSN:
0168-1923