Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/113373
Title: Spatiotemporal Analysis of Rainfall and Droughts in a Semiarid Basin of Brazil: Land Use and Land Cover Dynamics
Authors: de Barros de Sousa, Lizandra
de Assunção Montenegro, Abelardo Antônio
da Silva, Marcos Vinícius
Almeida, Thayná Alice Brito
de Carvalho, Ailton Alves
da Silva, Thieres George Freire
Lima, João L. M .P. de 
Keywords: spatial dependence; temporal variability; sequential Gaussian simulation; kriging; cokriging; CHIRPS
Issue Date: 2023
Publisher: MDPI
Project: The Coordination for the Improvement of Higher Education Personnel (CAPES), the Foundation for the Support of Science and Technology of the State of Pernambuco (FACEPE— APQ-0300-5.03/17 and IBPG-0855-5.03/20), the National Council for Scientific and Technological Development (CNPq—308890/2018-3; 140281/2022-3), and the CAPES-PrInt/UFRPE financed and provided scholarships. 
UIDB/04292/2020 
UIDP/04292/2020 
LA/P/0069/2020 
Serial title, monograph or event: Remote Sensing
Volume: 15
Issue: 10
Abstract: Precipitation estimation is a challenging task, especially in regions where its spatial distribution is irregular and highly variable. This study evaluated the spatial distribution of annual rainfall in a semiarid Brazilian basin under different regimes and its impact on land use and land cover dynamics. Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) records and observed data from 40 weather stations over a time series of 55 years were used, in addition to the Standardized Precipitation Index. Spatiotemporal analysis was carried out based on geostatistics. Remote sensing images were also interpreted for different rainfall regimes using the Normalized Difference Vegetation Index and Modified Normalized Difference Water Index. The Gaussian semivariogram model best represented the rainfall spatial structure, showing strong spatial dependence. Results indicated that rainfall amount in the basin significantly increases with elevation, as expected. There is high variation in the dynamics of water storage that can threaten water security in the region. Our findings point out that the application of geostatistics for mapping both the annual precipitation and the Standardized Precipitation Index provides a powerful framework to support hydrological analysis, as well as land use and land cover management in semiarid regions.
URI: https://hdl.handle.net/10316/113373
ISSN: 2072-4292
DOI: 10.3390/rs15102550
Rights: openAccess
Appears in Collections:FCTUC Eng.Civil - Artigos em Revistas Internacionais
I&D MARE - Artigos em Revistas Internacionais

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