Abstract

As a key service for regulating ecosystems, soil conservation (SC) plays a critical role in preventing regional land degradation. However, there are few studies on SC services in Central Asia, and there is a lack of quantitative assessments of long-term time series. Meanwhile, future climate change is also expected to exacerbate the uncertainty in SC assessments in Central Asia. Based on this, we modified the revised universal soil loss equation (RUSLE) model applicable to the Central Asia region through the localizing parameters. This study represents the first comprehensive assessment to investigate the SC in the four major basins (FMB) in Central Asia (Amu Darya Basin, ADB; Syr Darya Basin, SDB; Ili River Basin, IRB; and Tarim River Basin, TRB) in the current period (1996–2015) and in the future (with global warming of 1.5 °C (GW_1.5 °C) and 2.0 °C (GW_2.0 °C)). The results indicate that the current and future SC in Central Asia generally show increasing trends, but these trends slow with increasing temperature. Compared with the current value, the future SC in Central Asia is 4.7% and 7.9% lower under GW_1.5 °C and GW_2.0 °C, respectively. The future SC in the FMB decreases under global warming of 2.0 °C (GW_2.0 °C), with the decreases in the basins exhibiting the following order: TRB (-15.1%) > SDB (-8.6%) > ADB (-4.6%) > IRB (-3.3%). With increasing elevation, the SC in Central Asia increases and then decreases. Moreover, under GW_1.5 °C and GW_2.0 °C, the areas with the most concentrated SC extend from the areas at elevations of 1500–3500 m to areas at higher elevations. Temperature and precipitation had a synergistic effect on SC in Central Asia. Among the FMB, the TRB is most sensitive to climate variability. As the temperature increases by 16.9% and the precipitation increases by 30.0%, the SC in the TRB decreases by 7.0% (20.3 t km−2). The SC in the TRB should be prioritized in the FMB in Central Asia under GW_1.5 °C and GW_2.0 °C. The present study fills the gaps in the study of SC services in Central Asia and improves the simulation and risk assessment of SC in arid regions.

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