Projected Spatiotemporal Dynamics of Drought under Global Warming in Central Asia

Evaluation and Application of MSWEP in Drought Monitoring in Central Asia

Thanks to the large scope, high spatial resolution, and increasing data records, satellite-based precipitation products are playing an increasingly important role in drought monitoring. First, based on the data from ground sites, the long-term Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation product was evaluated in respect to drought monitoring. Then, based on the MSWEP product, the drought trends and the spatiotemporal characteristics of the drought events in four major basins (Amu Darya Basin, Syr Darya Basin, Chu-Talas River Basin, and Ili River Basin) in Central Asia, which have relatively dense gauge sites, were studied. The Standardized Precipitation Index (SPI) and the run theory were used to identify drought events and describe their characteristics. The results showed that MSWEP can effectively capture drought events and their basic characteristics. In the past 40 years, the study area experienced 27 drought events, among which the severest one (DS = 15.66) occurred from June 2007 to September 2008. The drought event that occurred from June 1984 to October 1984 had a drought peak value of 3.39, with the largest drought area (99.2%). Since 1881, there appeared a drying trend and a wetting trend in the Amu Darya River basin and the Ili River basin, respectively. No obvious wetting or drying trend was found in both the Chu-Talas River basin and the Syr Darya basin. Since 2016, the drought area has been on the increase.

Risk assessment of water resource shortages in the Aksu River basin of northwest China under climate change

As most of the runoff resulting from snow-ice melt is related to climate change factors in the arid region of northwest China, the risk to water resource systems threatens the socio-economic and ecological environment and is becoming increasingly prevalent. Therefore, we explored the risks of water resource shortages for different periods (2010, 2020, and 2030) in the Aksu River basin (ARB) in the northwest arid region of China by reconstructing a risk model based on the framework proposed by the Intergovernmental Panel on Climate Change (IPCC) with an improved vulnerability (V) module and a more suitable hazard probability in the cost module. The major conclusions are as follows: (1) the simulation of the Community Land Model-Distributed Time Variant Gain Model (CLM-DTVGM) and the Vegetation Interface Processes model (VIP) was suitable for the eco-hydrological processes in the ARB under climate change (i.e., R² ≥ 0.583; Nash coefficient ≥0.371; and relative mean standard ≤155.727 for CLM-DTVGM; R² = 0.798 for VIP); (2) the vulnerability of the water resource system in the ARB was medium in 2010, and dropped to a medium-low to non-vulnerable level in 2020 before increasing in 2030 under different Representative Concentration Pathways (RCP) (RCP2.6, RCP4.5, and RCP8.5); and (3) there was a medium-low risk of water resource shortages in the ARB in 2010 (i.e., 0.246), and although the risk of water resource shortages decreased in 2020 due to the increasing water supply from mountainous areas, the risk predicted to increase significantly in 2030, to a medium-high risk level. This study is critical for accurately predicting and understanding the impact of climate change on water resource systems as well as on the drought risk in arid regions.

Predicting the spatiotemporal variation in soil wind erosion across Central Asia in response to climate change in the 21st century

Wind erosion is an important environmental issue in Central Asia (CA), which includes Xinjiang, China (XJ-China), and the five CA states of the former Soviet Union (CAS5). Future climate changes could accelerate wind erosion in arid and semiarid areas and negatively impact local soil health and productivity. Based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b) climate model, we simulated the spatiotemporal dynamics of soil wind erosion from 1986 to 2099 in CA using the revised wind erosion equation (RWEQ) model. Our analysis indicated that the annual soil wind erosion modulus during the prediction period (2006-2099) increased compared with that in the reference period (1986-2005), especially in the 2030s (18.71%) and 2050s (18.85%) under RCP4.5. Spring and winter soil wind erosion will be the major contributors to increased annual wind erosion. We predicted that spring soil wind erosion will increase by 10.34% (RCP4.5) to 10.71% (RCP8.5) and that winter soil wind erosion will increase by 23.32% (RCP4.5) to 33.74% (RCP8.5) in the late 21st century. Annual soil wind erosion will increase in the northwest of CA, but decrease in the Karakum Desert, Kyzylkum Desert and Taklimakan Desert. Soil wind erosion varies under different plant functional types. By the late 21st century, the soil wind erosion modulus in grassland, irrigated cropland and rainfed cropland will increase by 62 t/km²/a (RCP4.5) to 412 t/km²/a (RCP8.5), 27 t/km²/a (RCP4.5) to 88 t/km²/a (RCP8.5) and 141 t/km²/a (RCP4.5) to 237 t/km²/a (RCP8.5), respectively. Our study indicates high risks of soil wind erosion in northwestern CA, and ecological engineering measures such as nature based solutions including ecological barriers should be developed to prevent soil loss in central and western Kazakhstan, where future warming will bring severe stress.