reported by the VCI (Fig. 15.10a) as well as the USDM (Fig. 15.10b). Overall, there
was a good agreement between USDM and VCI with respect to drought intensity
and extent in 2011. In addition to drought in Texas, both USDM and VCI reported
drought concentrated over Georgia, United States, in 2011.
Similarly, the USDM reported more widespread drought across the United States
in 2012 (Fig. 15.11). Drought in varying intensities spread over nearly 80% of the
US according to the USDM (The National Drought Mitigation Center 2017). The
VCI map that shows drought condition for the time period between August 13 and
August 28, 2011, indicated that the most devastating effects of the 2012 drought
were seen in the Corn Belt and Midwest region (Fig. 15.11a) and stretched across the
middle part of the Great Plains, as well. In the same way, the USDM map suggested
similar drought intensity and extent, extreme-to-exceptional dry conditions over the
Midwest region including the US Corn Belt and mid-Great Plains. There was a
disagreement over Georgia, United States that the VCI didn’t signal any drought
while moderate-to-exceptional drought conditions reported by the USDM. For
further investigation of this disagreement, the 3-month precipitation deficit
(Fig. 15.12) of June–August, 2012 was retrieved from the NOAA’s National Climatic Data Center (http://www.ncdc.noaa.gov/temp-and-precip/) because of the
well-known lag of NDVI to precipitation (Di et al. 1994; Ji and Peters 2003;
Yagci 2015). No large departure from normal precipitation (i.e., long-term average)
in 2011 was observed over Georgia, United States (Fig. 15.12), in line with the VCI
that didn’t depict any widespread vegetation (Fig. 15.11a).
Apart from that, the USDM tends to overestimate drought extent because the
USDM focuses on broad-scale (i.e., climate division- or state-level) conditions.
Drought at the local scale (i.e., county-scale) may differ from large-scale drought
patterns while the remote sensing-based methods provide drought conditions in
greater spatial detail (Brown et al. 2008).
15.5 Conclusions
Agricultural drought is one of the major disasters in the twenty-first century as the
world population continues to grow exponentially and the pressure to grow food is
mounting. It is an immediate concern to monitor/predict droughts accurately, and
then inform governments, farmers, and decision-makers as quickly as possible so
that proper actions can be taken on time to mitigate its devastating effects, such as
sharp declines in crop yields.
Soil moisture, ET, and drought are interconnected phenomena. When soil moisture is not sufficient to support optimal crop growth, plants reduce transpiration as a
defense mechanism, and evaporation of water from soil stops. As a result, agricultural drought develops, thereby hindering crop growth and production.
Here, we discussed three robust and proven methods to map soil moisture, ET,
and agricultural drought based on satellite data and methods. Since there are several
existing satellite missions in effect dedicated to collect soil moisture from space, it
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A. L. Yagci and M. T. Yilmaz
was a good agreement between USDM and VCI with respect to drought intensity
and extent in 2011. In addition to drought in Texas, both USDM and VCI reported
drought concentrated over Georgia, United States, in 2011.
Similarly, the USDM reported more widespread drought across the United States
in 2012 (Fig. 15.11). Drought in varying intensities spread over nearly 80% of the
US according to the USDM (The National Drought Mitigation Center 2017). The
VCI map that shows drought condition for the time period between August 13 and
August 28, 2011, indicated that the most devastating effects of the 2012 drought
were seen in the Corn Belt and Midwest region (Fig. 15.11a) and stretched across the
middle part of the Great Plains, as well. In the same way, the USDM map suggested
similar drought intensity and extent, extreme-to-exceptional dry conditions over the
Midwest region including the US Corn Belt and mid-Great Plains. There was a
disagreement over Georgia, United States that the VCI didn’t signal any drought
while moderate-to-exceptional drought conditions reported by the USDM. For
further investigation of this disagreement, the 3-month precipitation deficit
(Fig. 15.12) of June–August, 2012 was retrieved from the NOAA’s National Climatic Data Center (http://www.ncdc.noaa.gov/temp-and-precip/) because of the
well-known lag of NDVI to precipitation (Di et al. 1994; Ji and Peters 2003;
Yagci 2015). No large departure from normal precipitation (i.e., long-term average)
in 2011 was observed over Georgia, United States (Fig. 15.12), in line with the VCI
that didn’t depict any widespread vegetation (Fig. 15.11a).
Apart from that, the USDM tends to overestimate drought extent because the
USDM focuses on broad-scale (i.e., climate division- or state-level) conditions.
Drought at the local scale (i.e., county-scale) may differ from large-scale drought
patterns while the remote sensing-based methods provide drought conditions in
greater spatial detail (Brown et al. 2008).
15.5 Conclusions
Agricultural drought is one of the major disasters in the twenty-first century as the
world population continues to grow exponentially and the pressure to grow food is
mounting. It is an immediate concern to monitor/predict droughts accurately, and
then inform governments, farmers, and decision-makers as quickly as possible so
that proper actions can be taken on time to mitigate its devastating effects, such as
sharp declines in crop yields.
Soil moisture, ET, and drought are interconnected phenomena. When soil moisture is not sufficient to support optimal crop growth, plants reduce transpiration as a
defense mechanism, and evaporation of water from soil stops. As a result, agricultural drought develops, thereby hindering crop growth and production.
Here, we discussed three robust and proven methods to map soil moisture, ET,
and agricultural drought based on satellite data and methods. Since there are several
existing satellite missions in effect dedicated to collect soil moisture from space, it
314
A. L. Yagci and M. T. Yilmaz