Climate warming is changing streamflow regimes and groundwater storage in cold alpine regions. In this study, the Yangbajain headwater catchment in the Lhasa River basin is adopted as the study area to assess streamflow changes and active groundwater storage in response to climate warming. The results show that both annual streamflow and the mean air temperature increase significantly at respective rates of about 12.30 mm per decade and 0.28 ∘C per decade from 1979 to 2013 in the study area. The results of gray relational analysis indicate that the air temperature acts as a primary factor for the increased streamflow. Due to climate warming, the total glacier volume has retreated by over 25 % during the past 50 years, and the areal extent of permafrost has degraded by 15.3 % over the last 20 years. Parallel comparisons with other subbasins in the Lhasa River basin indirectly reveal that the increased streamflow at the Yangbajain Station is mainly fed by the accelerated glacier retreat. Using baseflow recession analysis, we also find that the estimated groundwater storage that is comparable with the GRACE data increases significantly at rates of about 19.32 mm per decade during the abovementioned period. That is to say, as permafrost thaws, more spaces have been made available to accommodate the increasing meltwater. Finally, a large water imbalance (of more than 5.79×107 m3 a−1) between the melt-derived runoff and the actual increase in runoff as well as the groundwater storage is also observed. The results from this study suggest that the impacts of glacial retreat and permafrost degradation show compound behaviors on the storage–discharge mechanism due to climate warming, and that this fundamentally affects the water supply and the mechanisms of streamflow generation and change.

The redistribution of hillslope soil water during and after rainstorms is affected by soil properties and topography. Therefore, understanding how soil‐terrain attributes affect the soil volumetric water content (VWC) distribution under various catchment storages is a prerequisite for accurate hydrological modeling. Herein, the relationships between soil‐terrain attributes and soil VWC were examined in a steep (average slope = 60%), forested, zero‐order catchment. Detailed topography, soil properties, and runoff, and high frequency (6‐min) soil moisture data observed from July 2016 to November 2017 were employed along with resampled VWC data in three time‐steps (daily, hourly, and 6‐min intervals) for correlation analysis between soil‐terrain attributes and measured VWC. The results showed that daily aggregated data overlooked the highly heterogeneous flow conditions under dry‐wet transitions, leading to a constantly high correlation between VWC and the topographic wetness index (TWI). In comparison, the 6‐min data captured short‐lived flow processes, highlighting that, in reality, VWC‐TWI correlations fluctuated frequently as a function of catchment storages and precipitation characteristics, with four wetting patterns identified. Under wet‐dry transitions, the VWC‐TWI correlations increased significantly (from 0.3 to 0.6) as the hillslope gradually drained of lateral subsurface water. Soil water behavior consists of diurnal oscillations superimposed on a declining trend, which demonstrates the existence of unsaturated flow and which contributed to the increase in the strength of the correlations. Finally, through correlation analysis of all drying (n = 4) and wetting (n = 45) periods, we found that soil‐terrain attributes and VWC correlations can be used to identify the dominant soil water processes in various catchment storages.

Solar farms play an integral role in the global energy transition and climate change mitigation. However, criticism has emerged, arguing that mitigating climate change cannot come at the expense of ecosystem degradation due to an ambiguous understanding of solar farms’ environmental impacts. Here we developed a harmonic regression model to conduct a nuanced global analysis of solar farms’ influences on vegetation. Results show that 52% of solar farms exhibited beneficial effects on vegetation coverage, with the highest enhancement (136.72%) found in regions where the aridity index is 0.39. However, changes in coverage are not triggered solely by solar farms; rather, there is a counterbalance between the contributions from climate change and from solar farms, implying that observed coverage changes could be stalled or even reversed in the future. Furthermore, plant functional type transition is an additional potential driver. Our findings could improve solar farm site selection and policies.