Hai Zhu , Kejie Chen , Shunqiang Hu , Ji Wang , Ziyue Wang , Jiafeng Li , Junguo Liu
{"title":"基于全球导航卫星系统和降水的新型干旱综合特征描述框架,包含气象和水文指标","authors":"Hai Zhu , Kejie Chen , Shunqiang Hu , Ji Wang , Ziyue Wang , Jiafeng Li , Junguo Liu","doi":"10.1016/j.rse.2024.114261","DOIUrl":null,"url":null,"abstract":"<div><p>The Global Navigation Satellite System (GNSS) has become instrumental in developing drought indices, particularly meteorological drought indicators derived from atmospheric precipitable water vapor and hydrological drought indicators based on inverted terrestrial water storage changes. However, these indices traditionally focus on individual aspects of droughts, either meteorological or hydrological droughts, and do not fully capture the integrated nature of drought phenomena. Addressing this gap, this study proposes a novel integrated drought characterization framework using the Gringorten plotting position to derive joint probabilities for GNSS-derived meteorological and hydrological drought indicators. This leads to the creation of a comprehensive multivariate drought severity index (GNSS-MDSI). The analysis across the western United States indicates significant spatial variability in multiyear average precipitation efficiency, ranging from 7.51% to 28.1%. This variability corresponds with marked differences in seasonal terrestrial water storage changes, which oscillate between 25 and 123 mm. Applying this framework in eight states, 9–13 comprehensive drought events from January 2006 to December 2021, with durations spanning from 3 to 54 months, were identified. The GNSS-MDSI not only captured these comprehensive drought periods across various temporal and spatial scales but also aligned closely with drought classifications provided by the US Drought Monitor. These results underscore the utility of this framework in providing a more nuanced and multifaceted perspective on drought conditions, surpassing the capabilities of single-indicator systems. Overall, this study presents an innovative framework for drought monitoring by integrating two GNSS-derived drought indicators, enabling precise and comprehensive delineation of drought characteristics, and offering a geodesy-based solution for integrated global and regional drought monitoring.</p></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":null,"pages":null},"PeriodicalIF":11.1000,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel GNSS and precipitation-based integrated drought characterization framework incorporating both meteorological and hydrological indicators\",\"authors\":\"Hai Zhu , Kejie Chen , Shunqiang Hu , Ji Wang , Ziyue Wang , Jiafeng Li , Junguo Liu\",\"doi\":\"10.1016/j.rse.2024.114261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Global Navigation Satellite System (GNSS) has become instrumental in developing drought indices, particularly meteorological drought indicators derived from atmospheric precipitable water vapor and hydrological drought indicators based on inverted terrestrial water storage changes. However, these indices traditionally focus on individual aspects of droughts, either meteorological or hydrological droughts, and do not fully capture the integrated nature of drought phenomena. Addressing this gap, this study proposes a novel integrated drought characterization framework using the Gringorten plotting position to derive joint probabilities for GNSS-derived meteorological and hydrological drought indicators. This leads to the creation of a comprehensive multivariate drought severity index (GNSS-MDSI). The analysis across the western United States indicates significant spatial variability in multiyear average precipitation efficiency, ranging from 7.51% to 28.1%. This variability corresponds with marked differences in seasonal terrestrial water storage changes, which oscillate between 25 and 123 mm. Applying this framework in eight states, 9–13 comprehensive drought events from January 2006 to December 2021, with durations spanning from 3 to 54 months, were identified. The GNSS-MDSI not only captured these comprehensive drought periods across various temporal and spatial scales but also aligned closely with drought classifications provided by the US Drought Monitor. These results underscore the utility of this framework in providing a more nuanced and multifaceted perspective on drought conditions, surpassing the capabilities of single-indicator systems. Overall, this study presents an innovative framework for drought monitoring by integrating two GNSS-derived drought indicators, enabling precise and comprehensive delineation of drought characteristics, and offering a geodesy-based solution for integrated global and regional drought monitoring.</p></div>\",\"PeriodicalId\":417,\"journal\":{\"name\":\"Remote Sensing of Environment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2024-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing of Environment\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0034425724002797\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425724002797","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A novel GNSS and precipitation-based integrated drought characterization framework incorporating both meteorological and hydrological indicators
The Global Navigation Satellite System (GNSS) has become instrumental in developing drought indices, particularly meteorological drought indicators derived from atmospheric precipitable water vapor and hydrological drought indicators based on inverted terrestrial water storage changes. However, these indices traditionally focus on individual aspects of droughts, either meteorological or hydrological droughts, and do not fully capture the integrated nature of drought phenomena. Addressing this gap, this study proposes a novel integrated drought characterization framework using the Gringorten plotting position to derive joint probabilities for GNSS-derived meteorological and hydrological drought indicators. This leads to the creation of a comprehensive multivariate drought severity index (GNSS-MDSI). The analysis across the western United States indicates significant spatial variability in multiyear average precipitation efficiency, ranging from 7.51% to 28.1%. This variability corresponds with marked differences in seasonal terrestrial water storage changes, which oscillate between 25 and 123 mm. Applying this framework in eight states, 9–13 comprehensive drought events from January 2006 to December 2021, with durations spanning from 3 to 54 months, were identified. The GNSS-MDSI not only captured these comprehensive drought periods across various temporal and spatial scales but also aligned closely with drought classifications provided by the US Drought Monitor. These results underscore the utility of this framework in providing a more nuanced and multifaceted perspective on drought conditions, surpassing the capabilities of single-indicator systems. Overall, this study presents an innovative framework for drought monitoring by integrating two GNSS-derived drought indicators, enabling precise and comprehensive delineation of drought characteristics, and offering a geodesy-based solution for integrated global and regional drought monitoring.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.