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

被引:16
作者
Bajgain, Rajen [1 ]
Xiao, Xiangming [1 ,2 ]
Basara, Jeffrey [3 ,4 ]
Wagle, Pradeep [1 ]
Zhou, Yuting [1 ]
Zhang, Yao [1 ]
Mahan, Hayden [3 ]
机构
[1] Univ Oklahoma, Dept Microbiol & Plant Biol, Ctr Spatial Anal, 101 David L Boren Blvd, Norman, OK 73019 USA
[2] Fudan Univ, Inst Biodivers Sci, Key Lab Biodivers Sci & Engn, Minist Educ, Shanghai 200433, Peoples R China
[3] Univ Oklahoma, Sch Meteorol, Norman, OK 73019 USA
[4] Oklahoma Climate Survey, Norman, OK USA
关键词
Drought duration; Drought intensity; Land surface water index; Summer drought; WHEAT; RISK; PART;
D O I
10.1007/s00484-016-1218-8
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
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 similar to 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.
引用
收藏
页码:377 / 390
页数:14
相关论文
共 36 条
  • [1] [Anonymous], 1987, REMOTE SENSING IMAGE
  • [2] OBSERVATIONS OF THE OVERLAND REINTENSIFICATION OF TROPICAL STORM ERIN (2007)
    Arndt, Derek S.
    Basara, Jeffrey B.
    McPherson, Renee A.
    Illston, BrAdley G.
    McManus, Gary D.
    Demko, David B.
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2009, 90 (08) : 1079 - +
  • [3] Sensitivity analysis of vegetation indices to drought over two tallgrass prairie sites
    Bajgain, Rajen
    Xiao, Xiangming
    Wagle, Pradeep
    Basara, Jeffrey
    Zhou, Yuting
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 108 : 151 - 160
  • [4] Basara J. B., 2013, International Journal of Geosciences, V4, P72
  • [5] BROCK FV, 1995, J ATMOS OCEAN TECH, V12, P5, DOI 10.1175/1520-0426(1995)012<0005:TOMATO>2.0.CO
  • [6] 2
  • [7] Detecting vegetation leaf water content using reflectance in the optical domain
    Ceccato, P
    Flasse, S
    Tarantola, S
    Jacquemoud, S
    Grégoire, JM
    [J]. REMOTE SENSING OF ENVIRONMENT, 2001, 77 (01) : 22 - 33
  • [8] Ceccato P, 2002, REMOTE SENS ENVIRON, V82, P198, DOI [10.1016/S0034-4257(02)00036-6, 10.1016/S0034-4257(02)00037-8]
  • [9] Chandrasekar K, 2011, INT ARCH PHOTOGRAMM, V38-8, P50
  • [10] Drought and Pluvial Dipole Events within the Great Plains of the United States
    Christian, Jordan
    Christian, Katarina
    Basara, Jeffrey B.
    [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2015, 54 (09) : 1886 - 1898