Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine

authored by
Soroosh Mehravar, Meisam Amani, Armin Moghimi, Farzaneh Dadrass Javan, Farhad Samadzadegan, Arsalan Ghorbanian, Alfred Stein, Ali Mohammadzadeh, S. Mohammad Mirmazloumi
Abstract

Remote Sensing (RS) offers efficient tools for drought monitoring, especially in countries with a lack of reliable and consistent in-situ multi-temporal datasets. In this study, a novel RS-based Drought Index (RSDI) named Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI) was proposed. To the best of our knowledge, TVMPDI is the first RSDI using four different drought indicators in its formulation. TVMPDI was then validated and compared with six conventional RSDIs including VCI, TCI, VHI, TVDI, MPDI and TVMDI. To this end, precipitation and soil temperature in-situ data have been used. Different time scales of meteorological Standardized Precipitation Index (SPI) index have also been used for the validation of the RSDIs. TVMPDI was highly correlated with the monthly precipitation and soil temperature in-situ data at 0.76 and 0.81 values respectively. The correlation coefficients between the RSDIs and 3-month SPI ranged from 0.07 to 0.28, identifying the TVMPDI as the most suitable index for subsequent analyses. Since the proposed TVMPDI could considerably outperform the other selected RSDIs, all spatiotemporal drought monitoring analyses in Iran were conducted by TVMPDI over the past 21 years. In this study, different products of the Moderate Resolution Imaging Spectrometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), and Global Precipitation Measurement (GPM) datasets containing 15,206 images were used on the Google Earth Engine (GEE) cloud computing platform. According to the results, Iran experienced the most severe drought in 2000 with a 0.715 TVMPDI value lasting for almost two years. Conversely, the TVMPDI showed a minimum value equal to 0.6781 in 2019 as the lowest annual drought level. The drought severity and trend in the 31 provinces of Iran have also been mapped. Consequently, various levels of decrease over the 21 years were found for different provinces, while Isfahan and Gilan were the only provinces showing an ascending drought trend (with a 0.004% and 0.002% trendline slope respectively). Khuzestan also faced a worrying drought prevalence that occurred in several years. In summary, this study provides updated information about drought trends in Iran using an advanced and efficient RSDI implemented in the cloud computing GEE platform. These results are beneficial for decision-makers and officials responsible for environmental sustainability, agriculture and the effects of climate change.

External Organisation(s)
University of Tehran
K.N. Toosi University of Technology
Wood Environment & Infrastructure Solutions
International Institute for Geo-Information Science and Earth Observation - ITC
CTTC - Catalan Telecommunications Technology Centre
Type
Article
Journal
Advances in space research
Volume
68
Pages
4573-4593
No. of pages
21
ISSN
0273-1177
Publication date
01.12.2021
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
Aerospace Engineering, Astronomy and Astrophysics, Geophysics, Atmospheric Science, Space and Planetary Science, General Earth and Planetary Sciences
Sustainable Development Goals
SDG 13 - Climate Action
Electronic version(s)
https://doi.org/10.1016/j.asr.2021.08.041 (Access: Unknown)