Qingzhi Zhao , Kang Liu , Tingting Sun , Yibin Yao , Zufeng Li
{"title":"A novel regional drought monitoring method using GNSS-derived ZTD and precipitation","authors":"Qingzhi Zhao , Kang Liu , Tingting Sun , Yibin Yao , Zufeng Li","doi":"10.1016/j.rse.2023.113778","DOIUrl":null,"url":null,"abstract":"<div><p>The drought monitoring indexes, such as SPEI<span> and SPCI, have been proposed previously. However, these indexes are established at specific station and unsuitable to evaluate the regional drought, which becomes the focus of this study. A novel drought monitoring method using the zenith troposphere<span> delay (ZTD) derived from global navigation satellite system<span> (GNSS) and precipitation is proposed, and a new index, which is named regional precipitation and ZTD index (RPZI), is established. The station-based precipitation and ZTD index (PZI) is first proposed by considering the data selection, expression, multi-time scale and standardization. The RPZI is then calculated by using the Thiessen Polygon method to determine the weighting of each station in the located area. The proposed PZI is first validated in 8 climatic regions<span> of China over the period of 2006–2018 at 801 metrological stations. The RPZI is further evaluated in arid, semiarid, humid, and semi humid areas of China over the period of 2006–2018 and Townsville, Queensland in Australia over the period of 1998–2018, respectively. Comparison results show that the proposed RPZI has a good consistency with the regional precipitation smoothing index (RPSI) when compared with station-based SPEI, station-based PZI, and regional SPEI (RSPEI), and the correlation coefficient is the highest between the RPZI and RPSI with values of 0.81, 0.90, 0.93, and 0.85 in four areas of China, and the corresponding value reaches 0.964 in Queensland, Australia. Such results show the good capacity of the proposed RPZI for regional drought monitoring, which is of great importance for global drought disaster prevention.</span></span></span></span></p></div>","PeriodicalId":417,"journal":{"name":"Remote Sensing of Environment","volume":"297 ","pages":"Article 113778"},"PeriodicalIF":11.4000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing of Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0034425723003292","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}
引用次数: 3
Abstract
The drought monitoring indexes, such as SPEI and SPCI, have been proposed previously. However, these indexes are established at specific station and unsuitable to evaluate the regional drought, which becomes the focus of this study. A novel drought monitoring method using the zenith troposphere delay (ZTD) derived from global navigation satellite system (GNSS) and precipitation is proposed, and a new index, which is named regional precipitation and ZTD index (RPZI), is established. The station-based precipitation and ZTD index (PZI) is first proposed by considering the data selection, expression, multi-time scale and standardization. The RPZI is then calculated by using the Thiessen Polygon method to determine the weighting of each station in the located area. The proposed PZI is first validated in 8 climatic regions of China over the period of 2006–2018 at 801 metrological stations. The RPZI is further evaluated in arid, semiarid, humid, and semi humid areas of China over the period of 2006–2018 and Townsville, Queensland in Australia over the period of 1998–2018, respectively. Comparison results show that the proposed RPZI has a good consistency with the regional precipitation smoothing index (RPSI) when compared with station-based SPEI, station-based PZI, and regional SPEI (RSPEI), and the correlation coefficient is the highest between the RPZI and RPSI with values of 0.81, 0.90, 0.93, and 0.85 in four areas of China, and the corresponding value reaches 0.964 in Queensland, Australia. Such results show the good capacity of the proposed RPZI for regional drought monitoring, which is of great importance for global drought disaster prevention.
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.