EGU2020-11543, updated on 10 Jan 2024
https://doi.org/10.5194/egusphere-egu2020-11543
EGU General Assembly 2020
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Drought monitoring Using Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI) and Normalized-Difference Snow Index (NDSI) with observational and ERA5 dataset, within the uremia lake basin, Iran

Maral Habibi1, Wolfgang Schöner2, and Iman Babaeian3
Maral Habibi et al.
  • 1Karl-Franzens-Universität Graz, Geography, Geography and Regional Research, GRAZ, Austria (maral.habibi@uni-graz.at)
  • 2Karl-Franzens-Universität Graz, Geography, Geography and Regional Research, GRAZ, Austria(wolfgang.schoener@uni-graz.at)
  • 3Climate Research Institute, Mashhad, Iran(i.babaeian@gmail.com)

Abstract

In this study, droughts were assessed for the Uremia Lake Basin located in the North West of Iran which is facing the risk of drying over the last decades. Since long-term and spatially dense observational data are not available, in particular for the mountainous part of the Uremia lake basin, we successfully tested the performance of the ERA5 reanalysis data set for our purpose. By comparing time series plots of drought indices (SPI, SPEI), both indices were able to capture the temporal variation of droughts. SPIE identified more drought events but SPI, as it uses precipitation only as input, fails to show the increasing number of evaporation driven droughts in the Uremia Lake Basin, which were observed in particular for the most recent decade. SPEI was calculated using the monthly temperature and precipitation, the extremely dry conditions of the basin were observed in the mountainous area, it seems that based on SPEI index, the highest values of actual evapotranspiration happens near the lake and in high mountains. Moreover, in recent years, drought has become more extreme in higher elevated areas, then we focused on Snow cover which has a significant role in surface runoff and groundwater recharge in mountainous and semi-arid areas, like within the Uremia lake basin. In recent years climate change impact snow variations distribution, snow cover, and runoff in different scales. Therefore, spatial and temporal monitoring of the snow-covered surface and the impact of these changes is necessary. Consequently, the chances of snow cover (SCA) in the study area were studied using MODIS images by the NDSI index and snow cover data from the ERA5 dataset. Finally, we came to this conclusion that the temperature rise in recent decades led to a high amount of evaporation and consequently the snow surface area has decreased so that it could affect the region’s water reservoir in the future.

Key words: Drought monitoring,ERA5,MODIS,SPI,SPEI,NDSI

How to cite: Habibi, M., Schöner, W., and Babaeian, I.: Drought monitoring Using Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI) and Normalized-Difference Snow Index (NDSI) with observational and ERA5 dataset, within the uremia lake basin, Iran, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11543, https://doi.org/10.5194/egusphere-egu2020-11543, 2020.

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