| Title |
Assessing agricultural drought in summer over Oklahoma Mesonet sites using the water-related vegetation index from MODIS
|
|---|---|
| Published in |
International Journal of Biometeorology, August 2016
|
| DOI | 10.1007/s00484-016-1218-8 |
| Pubmed ID | |
| Authors |
Rajen Bajgain, Xiangming Xiao, Jeffrey Basara, Pradeep Wagle, Yuting Zhou, Yao Zhang, Hayden Mahan |
| 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 (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 ∼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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 2% |
| Unknown | 44 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 20% |
| Student > Bachelor | 7 | 16% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 3 | 7% |
| Student > Ph. D. Student | 3 | 7% |
| Other | 6 | 13% |
| Unknown | 11 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 22% |
| Engineering | 9 | 20% |
| Earth and Planetary Sciences | 7 | 16% |
| Environmental Science | 3 | 7% |
| Computer Science | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 15 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 December 2017.
All research outputs
#13,476,553
of 22,882,389 outputs
Outputs from International Journal of Biometeorology
#909
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#193,591
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Outputs of similar age from International Journal of Biometeorology
#18
of 22 outputs
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