Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin
Geodetic data, especially from the Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO), are extensively employed in hydrological drought monitoring across various spatial scales due to their unique spatial resolution. In recent years, B...
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MDPI AG
2025-05-01
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| author | Xinyu Luo Tangting Wu Liguo Lu Nengfang Chao Zhanke Liu Yujie Peng |
| author_facet | Xinyu Luo Tangting Wu Liguo Lu Nengfang Chao Zhanke Liu Yujie Peng |
| author_sort | Xinyu Luo |
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| description | Geodetic data, especially from the Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO), are extensively employed in hydrological drought monitoring across various spatial scales due to their unique spatial resolution. In recent years, Brazil has experienced some of the most severe drought events in decades. This study focuses on Brazil and its northeastern Amazon Plain, investigates the spatiotemporal characteristics of terrestrial water storage (TWS) changes, and calculates the hydrological drought severity index (DSI) and meteorological drought index for comprehensive analysis of drought conditions. The results indicate that the time series of TWS changes derived from different data sources are highly correlated, with correlation coefficients exceeding 0.85, and are consistent with the trend of precipitation variation, reflecting notable seasonal fluctuations, i.e., an increase in precipitation during the spring and summer seasons leads to a rise in TWS, while a decrease in precipitation during the autumn and winter seasons triggers a reduction in TWS. In terms of spatial distribution, the annual amplitude of TWS variation is most pronounced in the northeastern Amazon Plain. The highest amplitude, approximately 800 mm, is observed near the Amazon River Basin, and this amplitude gradually weakens from northeast to southwest. GNSS and GRACE/GFO data reveal four hydrological drought events in Brazil from 2013 to 2024, with two of these events detected using GRACE/GFO data. The most severe droughts occurred between 2023 and 2024, primarily driven by prolonged precipitation deficits and the El Niño phenomenon, lasting up to nine months. Additionally, three distinct drought events were identified in the Amazon Plain, suggesting that its hydrological dynamics significantly influenced Brazil’s drought conditions. These results demonstrate the capability of geodetic data to effectively monitor water deficit and drought duration on both small spatial scales and short timeframes, thereby providing crucial support for timely responses to and the management of hydrological drought events. |
| format | Article |
| id | doaj-art-2ae557c1374146b68b1baa8a881bcf25 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-2ae557c1374146b68b1baa8a881bcf252025-08-20T01:56:42ZengMDPI AGRemote Sensing2072-42922025-05-011710167010.3390/rs17101670Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon BasinXinyu Luo0Tangting Wu1Liguo Lu2Nengfang Chao3Zhanke Liu4Yujie Peng5School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, ChinaSchool of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, ChinaSchool of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, ChinaCollege of Marine Science and Technology, China University of Geosciences, Wuhan 430074, ChinaThe First Geodetic Surveying Brigade, Ministry of Natural Resources, Xi’an 710054, ChinaThe First Monitoring and Application Center, China Earthquake Administration, Tianjin 300180, ChinaGeodetic data, especially from the Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO), are extensively employed in hydrological drought monitoring across various spatial scales due to their unique spatial resolution. In recent years, Brazil has experienced some of the most severe drought events in decades. This study focuses on Brazil and its northeastern Amazon Plain, investigates the spatiotemporal characteristics of terrestrial water storage (TWS) changes, and calculates the hydrological drought severity index (DSI) and meteorological drought index for comprehensive analysis of drought conditions. The results indicate that the time series of TWS changes derived from different data sources are highly correlated, with correlation coefficients exceeding 0.85, and are consistent with the trend of precipitation variation, reflecting notable seasonal fluctuations, i.e., an increase in precipitation during the spring and summer seasons leads to a rise in TWS, while a decrease in precipitation during the autumn and winter seasons triggers a reduction in TWS. In terms of spatial distribution, the annual amplitude of TWS variation is most pronounced in the northeastern Amazon Plain. The highest amplitude, approximately 800 mm, is observed near the Amazon River Basin, and this amplitude gradually weakens from northeast to southwest. GNSS and GRACE/GFO data reveal four hydrological drought events in Brazil from 2013 to 2024, with two of these events detected using GRACE/GFO data. The most severe droughts occurred between 2023 and 2024, primarily driven by prolonged precipitation deficits and the El Niño phenomenon, lasting up to nine months. Additionally, three distinct drought events were identified in the Amazon Plain, suggesting that its hydrological dynamics significantly influenced Brazil’s drought conditions. These results demonstrate the capability of geodetic data to effectively monitor water deficit and drought duration on both small spatial scales and short timeframes, thereby providing crucial support for timely responses to and the management of hydrological drought events.https://www.mdpi.com/2072-4292/17/10/1670GNSS vertical displacementGRACE/GFOterrestrial water storagehydrological droughtBrazil |
| spellingShingle | Xinyu Luo Tangting Wu Liguo Lu Nengfang Chao Zhanke Liu Yujie Peng Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin Remote Sensing GNSS vertical displacement GRACE/GFO terrestrial water storage hydrological drought Brazil |
| title | Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin |
| title_full | Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin |
| title_fullStr | Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin |
| title_full_unstemmed | Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin |
| title_short | Using Geodetic Data to Monitor Hydrological Drought at Different Spatial Scales: A Case Study of Brazil and the Amazon Basin |
| title_sort | using geodetic data to monitor hydrological drought at different spatial scales a case study of brazil and the amazon basin |
| topic | GNSS vertical displacement GRACE/GFO terrestrial water storage hydrological drought Brazil |
| url | https://www.mdpi.com/2072-4292/17/10/1670 |
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