A comprehensive drought index based on remote sensing data and nested copulas for monitoring meteorological and agroecological droughts: A case study on the Qinghai-Tibet Plateau

This study proposes a new comprehensive remote sensing drought index (CRSDI) based on the nested copulas of remotely sensed precipitation, vegetation index, and land surface temperature that represent water availability, vegetation health, and disturbance impact, respectively, for monitoring meteorological and agroecological droughts. The Qinghai-Tibet Plateau (QTP) is chosen as a case study to test the CRSDI and investigate drought changes and their impacts on vegetation. The results show that CRSDI can effectively monitor the propagation processes and characteristics of meteorological and agroecological droughts. Drought conditions on the QTP are overall relieved from 2000 to 2020, while these changes show an apparent spatial variability, with a general drying (wetting) trend in the north (south). Moreover, vegetation response to drought is different among different vegetation types, with shrubland having a stronger response, followed by cropland, grassland, and forestland. Clearly, CRSDI is valuable for large-scale drought monitoring and assessment.

Automated summary

This study proposes a new comprehensive remote sensing drought index (CRSDI) based on the nested copulas of remotely sensed precipitation, vegetation index, and land surface temperature that represent water availability, vegetation health, and disturbance impact, respectively, for monitoring meteorological and agroecological droughts. The Qinghai-Tibet Plateau (QTP) is chosen as a case study to test the CRSDI and investigate drought changes and their impacts on vegetation. The results show that CRSDI can effectively monitor the propagation processes and characteristics of meteorological and agroecological droughts. Drought conditions on the QTP are overall relieved from 2000 to 2020, while these changes show an apparent spatial variability, with a general drying (wetting) trend in the north (south). Moreover, vegetation response to drought is different among different vegetation types, with shrubland having a stronger response, followed by cropland, grassland, and forestland. Clearly, CRSDI is valuable for large-scale drought monitoring and assessment.