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• Declining water storage trends in the GRACE and GHMs were observed over Central Asia. • TWSA can be well simulated and predicted by climate variables. • Potential strategies are provided to address the SDGs of water resource over Central Asia. Arid regions of Central Asia have sensitive ecosystems that rely heavily on terrestrial water storage which is composed of surface water storage, soil moisture storage and groundwater storage. Therefore, we employed three Gravity Recovery and Climate Experiment (GRACE) satellite datasets and five global hydrological models (GHMs) to explore the terrestrial water storage (TWS) changes over arid regions of Central Asia from 2003 to 2014. We observed significantly decreasing water storage trends in the GRACE data, which were underestimated by the GHMs. After averaging the three GRACE satellite datasets, we found that the water storage was decreasing at a rate of −4.74 mm/year. Contrary to the prevailing declining water storage trends, northeastern Kazakhstan (KAZ), and southern Xinjiang increased their water storage over the same period. The GRACE data showed that Turkmenistan (TKM), Uzbekistan (UZB) and KAZ experienced the most severe water depletions, while Tajikistan (TJK) and northwest China (NW) experienced the least significant depletions. With respect to the major river and lake basins, the Aral Sea Basin exhibited the most serious water loss (-0.60 mm/month to −0.38 mm/month). The water storage positively correlates with the precipitation; and negatively correlates, with a three-month lag, with temperature and potential evapotranspiration (PET). Partial least square regression (PLSR) had the high capability in simulating and predicting the TWS. These results provide scientific evidence and guidance for local policy makers working toward sustainable water resource management, and the resolution of international water resource disputes among Central Asian countries. [ABSTRACT FROM AUTHOR]

[Display omitted] • Proposed: DISO-based CESAI for comprehensive ESs assessment in arid regions. • Wind erosion's significant impact mandates its inclusion in arid ESs assessments. • From 1992 to 2020, Uzbekistan's ESs declined due to drops in HQ and SF functionality. • Natural factors affect WY, and SR, while human activities impact SF, CS, and HQ. Wind erosion, a crucial disruptor of ecosystem health and stability, especially in arid regions, remains unincorporated in extensively utilized ecosystem services (ESs) quantification models such as InVEST. This neglect results in a gap: the profound influence of wind erosion on ESs remains largely underexplored and unquantified. Moreover, current models predominantly concentrate on individual ESs, thus bypassing the necessary comprehensive evaluation of various ESs' developmental status. To address this gap, we propose a systematic framework based on the Distance between Indices of Simulation and Observation (DISO), which integrates the Revised Wind Erosion Equation (RWEQ) and key modules of the InVEST model to derive a Comprehensive Ecosystem Services Assessment Index (CESAI) for arid regions. We evaluated five ESs, including water yield, soil retention, sand fixation (measured by wind erosion), carbon storage, and habitat quality. To further investigate the influence of each ES on the comprehensive assessment, we employed a suite of statistical methods, including independent samples t-tests and a generalized additive model (GAM), to elucidate the complex relationships and significant effects of wind erosion on the CESAI. The results of the t-tests and GAM highlighted the significant influence of wind erosion, which demonstrated the highest edf-value (2.000) and the highest F-value (1039.6, p < 0.001). Spatiotemporal dynamics show that ES functionality in Uzbekistan has deteriorated from 1992 to 2020, a trend starkly exemplified by the severe harm inflicted by the Aral Sea crisis. Drawing upon the DISO concept, we have innovatively designed a framework that steers the CESAI index, a comprehensive instrument for evaluating ESs. Beyond providing a holistic perspective on ESs assessments, this framework also deciphers the multifaceted interplay within ecosystems through statistical dissection of each service's influence. Collectively, our findings deepen the understanding of ESs dynamics, shedding light on the crucial role of wind erosion within arid ecosystem service assessments. [ABSTRACT FROM AUTHOR]