Uruguay Agriculture II – NASA DEVELOP Spring 2015 @ the IRI


0:08-0:20
>>Alex: The importance of monitoring drought is indispensable for countries whose economic
viability is strongly tied to agriculture. Droughts are a major concern for the country
of Uruguay, affecting their agricultural and energy sectors. 0:21-0:31
>>Alex: The development of a remotely sensed drought-monitoring tool that can aid government
agencies in disseminating drought information to local stakeholders will be helpful in sustaining
these important economic sectors. 0:32-0:40
>>Alex: This research is a continuation of a previous develop project from fall of 2013,
which created a drought severity index for the country of Uruguay. 0:41-0:57
>>Pietro: So the project is important for the end user in this case the Ministry of
Agriculture in Uruguay to monitor the risk of drought and see how it impacts the agriculture.
Especially for the production of corn, soybeans, and wheat and also for the pastures. 0:58-1:09
>>Pietro: Uruguay is a major exporter of beef and so the pasture is important and any drought
that might impact agriculture and livestock is important for the ministry of agriculture. 1:10-1:26
>>Alex: For this project we compared and validated the DSI developed in the fall of 2013 to in
situ station data provided to us by INIA. Additionally we substituted different vegetation
indices and precipitation data into the DSI in order to determine the most aptly suited
DSI for use in Uruguay 1:27-1:41
>>Alex: The station data provided from INIA consisted of a soil water balance model, which
contained percent available water data for the country from 2003-2014. Percent available
water was used as a standard drought indicator to compare against the DSI�s. 1:42-1:47
>>Alex: Percent available water is used to monitor drought because it indicates when
vegetation is stressed. 1:48-1:57
>>Jerrod: Most satellite products used in this study were NASA products but we also
used NOAA�s CPC Morphing Technique global precipitation estimate in substitution for
TRMM data. 2:01-2:22
>>Pietro: So for the project on monitoring drought in Uruguay we a series of satellites
based first on the TRMM to monitor rainfall. And we use MODIS land surface temperature
to monitor the temperature and evapotranspiration. And finally we use also MODIS sensors to monitor
vegetation. 2:23-2:35
Vegetation status in terms of chlorophyll activity using vegetation indices like NDVI
or EVI and also looking at the vegetation water content using the normalized difference
water index. 2:36-2:51
>>Jerrod: We obtained point data for the dsi�s, corresponding to the regridded station data
through the iri data library which was then correlated to the station data. The final
product showed the monthly correlations with respect to their coordinates over the study
period of 2003 to 2014. 2:52-3:00
>>Jerrod: The DSI correlated well to the station data during the Uruguayan summer. However,
the DSI underperformed during their winter for all variations of the DSI. 3:01-3:11
>>Jerrod: We feel that this underperformance during the winter months though is acceptable
because there is little variability in the percent available water while the precipitation
continues to vary therefore making the correlations low. 3:12-3:23
>>Jerrod: Our results show that there is little difference between using the CMORPH precipitation
data vs the TRMM precipitation data and that NDVI and NDWI were the highest correlated
vegetation indices within the DSI. 3:25-3:35
>>Jerrod: We concluded that CMORPH would be superior to TRMM due to its near real time
operational status and that NDWI would be more applicable because of its slightly higher
correlation to the station data. 3:36-3:47
>>Pietro: So for this project we hope that we can provide to the Ministry of Agriculture
in Uruguay a system that improves the monitoring of drought for agriculture and pastures.

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