A novel drought index integrating GNSS and precipitation data for drought monitoring in Brazil
We develop a novel composite drought index, the GNSS and Precipitation based Multivariate Standardized Drought Index (GP-MSDI), integrating Global Navigation Satellite System (GNSS) and precipitation data to improve drought characterization in Brazil. GP-MSDI combines meteorological and hydrological...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2543572 |
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| Summary: | We develop a novel composite drought index, the GNSS and Precipitation based Multivariate Standardized Drought Index (GP-MSDI), integrating Global Navigation Satellite System (GNSS) and precipitation data to improve drought characterization in Brazil. GP-MSDI combines meteorological and hydrological variables using the Copula function, enabling multidimensional evaluation of drought events. Applied from January 2010 to December 2022, GP-MSDI identified 7–9 drought events across four major basins in Brazil, with Sao Francisco River Basin (SRB) experienced the longest drought duration (116 months, 74.4% of the study period). Compared to other drought indices, GP-MSDI effectively captures compound drought events. Spatial analysis highlighted that the Amazon River Basin (ARB) and eastern Brazil faced more severe droughts. Following the spatial analysis, we introduced the Drought Severity Exposure Risk Index (DSERI), which combines GP-MSDI drought severity with population density to assess socio-environmental vulnerability. DSERI revealed high-risk areas in southeastern and northeastern Brazil, where severe droughts overlap with densely populated regions, underscoring the urgent need for targeted mitigation strategies. This study introduces GP-MSDI as a comprehensive tool for drought monitoring, offering an integrated approach by combining meteorological and hydrological data through geodetic methods, thereby enhancing our understanding of drought dynamics in Brazil. |
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| ISSN: | 1753-8947 1753-8955 |