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Open AccessArticle

Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil

1
Programa de Pós-Graduação em Recursos Hídricos, Universidade Federal de Mato Grosso, Cuiabá 78060-900, Brazil
2
Instituto de Ciências Agrárias e Ambientais, Universidade Federal de Mato Grosso, Sinop 78557-267, Brazil
3
Departamento de Engenharia Agrícola, Universidade Federal de Viçosa, Viçosa 36570-900, Brazil
4
Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Viçosa, Viçosa 36570-900, Brazil
5
Departamento de Engenharia Rural, Universidade Federal do Espírito Santo, Alegre 29500-000, Brazil
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Programa de Pós-Graduação em Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, São José dos Campos 12227-010, Brazil
7
Departamento de Engenharia Sanitária e Ambiental, Universidade Federal de Mato Grosso, Cuiabá 78060-900, Brazil
*
Author to whom correspondence should be addressed.
Water 2020, 12(12), 3366; https://doi.org/10.3390/w12123366
Received: 9 October 2020 / Revised: 19 November 2020 / Accepted: 23 November 2020 / Published: 30 November 2020
(This article belongs to the Special Issue Applications of Remote Sensing in Agricultural Water Management)
Drought is a natural disaster that affects a country’s economy and food security. The monitoring of droughts assists in planning assertive actions to mitigate the resulting environmental and economic impacts. This work aimed to evaluate the performance of the standardized precipitation index (SPI) using rainfall data estimated by orbital remote sensing in the monitoring of meteorological drought in the Cerrado–Amazon transition region, Brazil. Historical series from 34 rain gauge stations, in addition to indirect measurements of monthly precipitation obtained by remote sensing using the products CHIRPS-2.0, PERSIANN-CDR, PERSIANN-CCS, PERSIANN, GPM-3IMERGMv6, and GPM-3IMERGDLv6, were used in this study. Drought events detected by SPI were related to a reduction in soybean production. The SPI calculated from the historical rain series estimated by remote sensing allowed monitoring droughts, enabling a high detailing of the spatial variability of droughts in the region, mainly during the soybean development cycle. Indirect precipitation measures associated with SPI that have adequate performance for detecting droughts in the study region were PERSIANN-CCS (January), CHIRPS-2.0 (February and November), and GPM-3IMERGMv6 (March, September, and December). The SPI and the use of precipitation data estimated by remote sensing are effective for characterizing and monitoring meteorological drought in the study region. View Full-Text
Keywords: agricultural planning; soybean; climate risk; natural disaster; water resource management agricultural planning; soybean; climate risk; natural disaster; water resource management
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MDPI and ACS Style

Carvalho, M.Â.C.C.d.; Uliana, E.M.; Silva, D.D.d.; Aires, U.R.V.; Martins, C.A.d.S.; Sousa Junior, M.F.d.; Cruz, I.F.d.; Mendes, M.A.d.S.A. Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil. Water 2020, 12, 3366. https://doi.org/10.3390/w12123366

AMA Style

Carvalho MÂCCd, Uliana EM, Silva DDd, Aires URV, Martins CAdS, Sousa Junior MFd, Cruz IFd, Mendes MAdSA. Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil. Water. 2020; 12(12):3366. https://doi.org/10.3390/w12123366

Chicago/Turabian Style

Carvalho, Mairon Â.C.C.d.; Uliana, Eduardo M.; Silva, Demetrius D.d.; Aires, Uilson R.V.; Martins, Camila A.d.S.; Sousa Junior, Marionei F.d.; Cruz, Ibraim F.d.; Mendes, Múcio A.d.S.A. 2020. "Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil" Water 12, no. 12: 3366. https://doi.org/10.3390/w12123366

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