Use of A MODIS Satellite-Based Aridity Index to Monitor Drought Conditions in Mongolia from 2001 to 2013

The 4D disasters (desertification, drought, dust, and dzud, a Mongolian term for severe winter weather) have recently been increasing in Mongolia, and their impacts on the livelihoods of humans has likewise increased. The combination of drought and dzud has caused the loss of livestock on which nomadic herdsmen depend for their well-being. Understanding the spatiotemporal patterns of drought and predicting drought conditions are important goals of scientific research in Mongolia. This study involved examining the trends of the normalized difference vegetation index (NDVI) and satellite-based aridity index (SbAI) to determine why the land surface of Mongolia has recently (2001-2013) become drier across a range of aridity indices (AIs). The main reasons were that the maximum NDVI (NDVImax) was lower than the NDVImax typically found in other arid regions of the world, and the SbAI throughout the year was large (dry), although the SbAI in summer was comparatively small (wet). Under the current conditions, the capacity of the land surface to retain water throughout the year caused a large SbAI because rainfall in Mongolia is concentrated in the summer, and the conditions of grasslands reflect summer rainfall in addition to grazing pressure. We then proposed a method to monitor the land-surface dryness or drought using only satellite data. The correct identification of drought was higher for the SbAI. Drought is more strongly correlated with soil moisture anomalies, and thus the annual averaged SbAI might be appropriate for monitoring drought during seasons. Degraded land area, defined as annual NDVImax < 0.2 and annual averaged SbAI > 0.025, has decreased. Degraded land area was large in the major drought years of Mongolia.

Automated summary

The 4D disasters in Mongolia, consisting of desertification, drought, dust, and dzud, have been on the rise and have negatively impacted human livelihoods. The study focused on analyzing trends in NDVI and SbAI to understand the increasing dryness of the Mongolian land surface, which is attributed to lower NDVI levels and relatively high aridity indices. The research also proposed a method using satellite data to monitor land-surface dryness and drought, with a focus on the strong correlation between drought and soil moisture anomalies.