Changes in key ecosystem service parameters (Water balance residual (eWBR), Carbon storage (CS) and carbon sequestration (C.Seq)),and their response to land cover conversions and climate variability as an index of ecosystem restoration and degradation, in arid and semi-arid endorheic inland basins, vis-à-vis the Sustainable Development Goals (SDGs) remained underexplored. Thus, this study used the multi-layer perceptron model to simulate and predict land cover changes (LCC), the CASA-GRAMI, the InVEST, and Hargreaves-Sumani models estimated the ecosystem services. Whereas, the Ordinary Least Square Regression predicted changes in ecosystem services from anthropo-climatic factors while the Theil-Sen slopes, pixel correlations, and the advanced geostatistical methods examined the trends and responses of ecosystem services to land conversions and climate extremes. The results revealed degraded baseline condition in C.Seq and CS coefficients for LCB and ASB (1.858 and -0.025 and -0.002). In LCB, temperature and NDVI predicted a decreased eWBR, while, precipitation and LCC predicted a decreased CS. Also, the depletion of shrublands occasioned by its conversion to cropland degraded CS and C.Seq, opposing the SDGS. Furthermore, increased precipitation restored CS and C.Seq and vice versa. Contrastingly, in ASB, the temperature and precipitation predicted an increase eWBR, while the temperature predicted a decrease in CS. Furthermore, the conversion of bareland and grassland to cropland restored CS and C.Seq, as well as, reduced precipitation restored CS due to snowmelt and temperature increase. Temperature increases in LCB degrades CS and eWBR, while in ASB, it restores CS and carbon sink. The findings underscore the importance of adaptive and sustainable land and water management, climate strategies, and continuous monitoring of land cover changes to enhance ecosystem services and health to meet the SDGs through Inter-regional cooperation and knowledge sharing.

Mountain snow is a fundamental freshwater supply in the arid regions. Climate warming alters the timing of snowmelt and shortens the snow cover duration, which profoundly influences the regional climate and water management. However, a reliable estimation of snow mass in the Tianshan Mountains (TS) is still unclear due to the scarcity of extensive continuous surface observations and a complex spatial heterogeneity. Therefore, a long-time series of snow simulation was performed in the WRF/Noah-MP from 1982 until 2018 to quantify the snow mass in the TS, forced by the ERA5 reanalysis data and real-time updated leaf area index and green vegetation fraction. Meanwhile, March snow mass (close to the annual peak snow mass), snow cover fraction (SCF), and trends were investigated in the TS. The results indicated a good accuracy of the estimated snow water equivalent (root mean square error (RMSE): 7.82 mm/day) with a slight overestimation (2.84 mm/day). Compared with the ERA5 dataset, the RMSE and mean bias (MB) of the daily snow depth from the WRF/Noah-MP were significantly reduced by 95.74% and 93.02%, respectively. The climatological March snow mass measured 97.85 (±16.60) gigatonnes in the TS and exhibited a negligible tendency. The total precipitation during the cold season controlled the variations of the March snow mass. The increased precipitation in the high-altitude regions contributed to an extensive snow mass, which could offset the loss in the TS lowland. In contrast, rapidly rising air temperature caused a significant reduction of the March SCF, particularly in the Southern TS.

Understanding the response of extreme precipitation (EP) at a city scale to global warming is critical to protect a city from the risks of urban flooding under climate change. Yet, current knowledge on this issue is limited. Here, focusing on an urban agglomeration in the tropics, Singapore, we reveal that future global warming enhances both frequency and intensity of EP, based on simulations with a state-of-the-art convection-permitting regional climate model. EP intensification can reach maximum “super” Clausius-Clapeyron ( +7% per K warming) rate, consistently for both Representative Concentration Pathways (RCPs) 8.5 and 4.5. The intensification is lower for moderate and light precipitation, implying a situation of “wet gets wetter and dry remains dry”. EP enhancement is attributed to the increased atmospheric moisture and, more importantly, the enhanced lifting force, which directly strengthens the precipitation-making processes.