A new drought monitoring approach using three-dimensional drought properties based on a dynamic drought detection technique algorithm

Abstract

Study region: Central Asia. Study focus: In Central Asia, there is a lack of drought information to help understand the spatiotemporal variability and evolutionary characteristics of droughts. In this study, drought analysis data (i.e., high-resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset) was utilized in consideration of the meteorological and topographical characteristics of Central Asia and a dynamic drought detection technique (DDDT) algorithm was proposed for extracting three-dimensional(3D) drought events. As a result, it was possible to analyze the spatiotemporal distribution patterns and characteristics of droughts, which are intertwined with spatiotemporal dimensions. The drought events in Central Asia during the period of 1981–2018 were identified and their spatiotemporal distribution patterns and variabilities were characterized using various drought characteristic indicators (drought duration, severity, affected area, intensity, location (latitude and longitude), and the distance and direction of the drought trajectory). Finally, a new approach to monitoring conditional drought in Central Asia was proposed based on a dynamic drought map that includes all 3D-drought properties. New hydrological insights for the region: Our major findings include (i) high-resolution data sets are suitable to interpret the development process and evolutionary characteristics of drought in consideration of the climatic and various topographical characteristics of Central Asia, (ii) most droughts of large and small scale in Central Asia can be quantified by identifying drought events in a three-dimensional concept using a DDDT algorithm, (iii) the direction of the drought trajectory that occurred in the study area during the period of 1981–2018 was often lateral, i.e., east and west, and (iv) in Central Asia at the beginning of 2008, severe drought continued in 2008, although the number of new monthly droughts tended to decrease. As a result of identifying the cause using the dynamic drought map, the number of new droughts that occurred every month in the second half of 2007 tended to increase, which led to the long-term drought in 2008.

Keywords

• 3D-drought event
• Central Asia
• Dynamic drought map
• Drought monitoring
• Drought trajectory
• Spatiotemporal analysis