The Drought Monitor

Svoboda, Mark D.; LeComte, Doug; Hayes, Mike; Heim, Richard R.; Gleason, Karin; Angel, James R.; Rippey, Brad; Tinker, Rich; Palecki, Mike; Stooksbury, David E.; Miskus, David; Stephens, Scott L.

doi:10.1175/1520-0477-83.8.1181

Cited by 1,116 publications

(910 citation statements)

References 3 publications

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“…The drought condition is defined as the monthly soil moisture percentile is lower than 20% or the SPI-1 is less than À0.8 [Svoboda et al, 2002]. To validate the performance of remote sensing and reanalysis products in representing drought conditions at in situ [Wilks, 2011]).…”

Section: Methodsmentioning

confidence: 99%

Microwave remote sensing of short‐term droughts during crop growing seasons

Yuan

Pan

et al. 2015

Geophysical Research Letters

159

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Severe short‐term (monthly to seasonal) droughts frequently occurred over China in recent years, with devastating impacts on crop production. This study assesses the capability of microwave remote sensing in detecting soil moisture (agricultural) droughts over China and in providing early warnings. The 22 year (1992–2013) European Space Agency satellite soil moisture retrievals are compared against the in situ observations at 312 stations in China, the global soil moisture reanalysis, and the observed rainfall deficit. Both the reanalysis and remote sensing products can only detect less than 60% of drought months at in situ station scale, but they capture the interannual variations of short‐term drought area at river basin scales quite well. As compared with reanalysis, the passive and merged microwave products have better drought detection over sparsely vegetated regions in northwestern China and the active microwave product with better vegetation penetration works the best in eastern China.

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Section: Methodsmentioning

confidence: 99%

Microwave remote sensing of short‐term droughts during crop growing seasons

Yuan

Pan

et al. 2015

Geophysical Research Letters

159

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“…The U.S. Drought Monitor (USDM), considered to be the current state-of-the art drought monitoring tool for the United States, is developed through expert integration of a diverse set of quantitative drought indicators along with local reports from observers in the field (Svoboda et al 2002). Multiple indicators are required to track the various types of drought, which include 1) meteorological drought, describing short-term precipitation deficits; 2) agricultural drought, reflecting rootzone soil moisture deficits and impacts on crop yields; 3) hydrologic drought, which affects streamflow, groundwater tables, and reservoir levels, and occurs and recovers over much longer time scales (months to years); and 4) socioeconomic drought, incorporating the concept of water supply and demand (Wilhite and Glantz 1985).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

et al. 2011

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The reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–09 growing seasons. Spatial and temporal correlation analyses suggest that the ESI performs similarly to short-term (up to 6 months) precipitation-based indices but can be produced at higher spatial resolution and without requiring any precipitation data. Unique behavior is observed in the ESI in regions where the evaporative flux is enhanced by moisture sources decoupled from local rainfall: for example, in areas of intense irrigation or shallow water table. Normalization by PET serves to isolate the ET signal component responding to soil moisture variability from variations due to the radiation load. This study suggests that the ESI is a useful complement to the current suite of drought indicators, with particular added value in parts of the world where rainfall data are sparse or unreliable.

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“…The thresholds in Table 1 are broadly consistent with those used by USAID FEWS to classify rainfall across SSA as dry, normal, or wet. They also reflect recommendations that the 10th and 90th percentiles are appropriate thresholds for monitoring extreme dry and wet conditions (e.g., Nicholls and Murray 1999;Svoboda et al 2002).…”

Section: Rainwatch Concept and Designmentioning

confidence: 57%