{"title":"Development of Trivariate Multiscalar–Standardized Drought Index (TMSDI) for assessing drought characteristics","authors":"Aamina Batool, Veysi KARTAL, Zulfiqar Ali","doi":"10.1007/s10661-025-13742-y","DOIUrl":null,"url":null,"abstract":"<div><p>Drought is an extensive natural hazard influenced by human activities. Drought has a substantial impact on environmental systems and socioeconomic activities globally, posing serious challenges to water resources, agriculture, and ecosystems. Drought as a complicated natural occurrence is difficult to monitor and anticipate. However, to address the detrimental issues of drought, this study examined the innovative Trivariate Multiscalar–Standardized Drought Index (TMSDI). The climatic factors of precipitation, temperature, and Normalized Difference Vegetation Index (NDVI) are components in the development of TMSDI. To check the association of the innovative index with the another drought indices, this study evaluated correlations between the proposed index (TMSDI) and traditional drought indices, i.e., the Standardized Precipitation Index (SPI) and the Standardized Precipitation Temperature Index (SPTI) at 1-, 3-, 6-, 9-, 12-, 24-, and 48-month time scales. The outcomes demonstrate that there is a consistent relationship between the TMSDI and SPI due to higher values of correlation. The lower correlation between TMSDI and SPTI shows that there is a substantial and consistent relationship between TMSDI and SPI than TMSDI and SPTI. Moreover, the long-term behavior of different drought conditions indicates that extreme drought is more likely than extreme wet across the Markov chain’s Steady States Probabilities (SSPs). Consequently, the proposed index (TMSDI) is recommended as an effective tool to precisely and accurately monitor drought conditions over different time scales within different climate factors.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 3","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10661-025-13742-y.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Monitoring and Assessment","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10661-025-13742-y","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Drought is an extensive natural hazard influenced by human activities. Drought has a substantial impact on environmental systems and socioeconomic activities globally, posing serious challenges to water resources, agriculture, and ecosystems. Drought as a complicated natural occurrence is difficult to monitor and anticipate. However, to address the detrimental issues of drought, this study examined the innovative Trivariate Multiscalar–Standardized Drought Index (TMSDI). The climatic factors of precipitation, temperature, and Normalized Difference Vegetation Index (NDVI) are components in the development of TMSDI. To check the association of the innovative index with the another drought indices, this study evaluated correlations between the proposed index (TMSDI) and traditional drought indices, i.e., the Standardized Precipitation Index (SPI) and the Standardized Precipitation Temperature Index (SPTI) at 1-, 3-, 6-, 9-, 12-, 24-, and 48-month time scales. The outcomes demonstrate that there is a consistent relationship between the TMSDI and SPI due to higher values of correlation. The lower correlation between TMSDI and SPTI shows that there is a substantial and consistent relationship between TMSDI and SPI than TMSDI and SPTI. Moreover, the long-term behavior of different drought conditions indicates that extreme drought is more likely than extreme wet across the Markov chain’s Steady States Probabilities (SSPs). Consequently, the proposed index (TMSDI) is recommended as an effective tool to precisely and accurately monitor drought conditions over different time scales within different climate factors.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.