[M-IS01] Environmental, socio-economic, and climatic changes in Northern Eurasia

[MIS01-P04] Development of a New Drought Index Using SMOS Satellite Soil Moisture Products: Case Study in Southwestern Mongolia

*Oyudari Vova¹, Martin Kappas¹, Pavel Groisman², Tsolmon Renchin³, Steven Fassnacht^1,4,5,6 (1.University of Göttingen, Göttingen, Germany, 2.NC State University Research Scholar at National Centers for Environment Information, Asheville, USA, 3.Department of Physics, National University of Mongolia, Ulaanbaatar, Mongolia, 4.Department of Ecosystem Science and Sustainability – Watershed Science, Colorado State University, Fort Collins, United States, 5.Cooperative Institute for Research in the Atmosphere, CSU, Fort Collins, USA, 6.Natural Resources Ecology Lab, Colorado State University, Fort Collins, USA)

Keywords:drought, SMOS L2, MODIS products, in-situ soil moisture (SM), multiple regression

A new drought index for meteorological and hydrological drought monitoring is presented, based on the integration of different remote sensing products and in situ observations. This research was conducted in the Bayankhongor Province. The Province is located in the southwest of Mongolia and covers an area of 116,000 square kilometers. It includes the southern region of the Khangai Mountain Range, the eastern ridges of the Altai Mountains, and the unique Gobi Desert to the south (Figure 1). The research area suffers from a scarcity of water and has an average annual precipitation of 80 --160 mm (Vova et al. 2020).

Multiple linear regression method was used for estimation of GDI drought index. The former includes the surface soil moisture from the Soil Moisture and Ocean Salinity (SMOS) mission, the Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface temperature (LST), normalized difference vegetation index (NDVI), and potential evapotranspiration (PET). The validation of the approach is based on the relationship between SPI and in-situ soil moisture (SM) observations, and their comparison to remote sensing -- derived indices. The GDI drought index combines the soil moisture and temperature conditions while including the sensitive response of arid and semi-arid vegetation. The GDI benefits are: (a) few data are required for its computation; (b) it is mostly a remote sensing product; (c) it is easily transferable and scalable over the entire globe; (d) it is a useful model in areas with scarce gauge coverage; and (e) it is an affordable tool since it can identify agrometeorological and hydrological droughts. The established new GDI index was retrieved at the 1 km spatial resolution for Southwest Mongolia from 2000 to 2018, and their two summer months (July, August) were used for monitoring drought and vegetation response to the varying soil/climatic conditions. Based on the assessment of drought severity, the new drought index allowed us to assess a large-scale spatial coherence of droughts across the Southwestern part of Mongolia.

FIGURE 1 CAPTION. Geographical location and vegetation zone maps of Bayankhongor Province. (a) Meteorological station distribution and vegetation zones, data sourced from the Information and Research Institute of Meteorology, Hydrology, and Environment (IRIMHE) of Mongolia.

REFERENCE:

Vova, Oyudari, Martin Kappas, Tsolmon Renchin, and Steven Fassnacht. 2020: Extreme Climate Event and Its Impact on Landscape Resilience in Gobi Region of Mongolia. Remote Sensing 12 (18): 2881. https://doi.org/10.3390/rs12182881.