Compared with arctic and subarctic catchments, our knowledge about the hydrological functions of glaciers and porous aquifers is still limited for the partly glacierized alpine‐gorge headwaters in the Qinghai‐Tibet Plateau. Here we examine the impact of glacial and groundwater storage on the variability of warm‐season (June to September) discharge from the Hulugou catchment, an alpine‐gorge headwater with 3% glacial coverage, by quantifying the timing and magnitude of contributions of glacier‐snow meltwater, baseflow, and rainwater to streamflow using a three‐component hydrograph separation model. It is found that baseflow was the largest component (55 ± 2%) of warm‐season streamflow while glacier‐snow meltwater also contributed significantly (30 ± 10%) despite of the very low glacial coverage. We suggest that the water flowing out of glaciers was mainly supplied by the melting short‐ and intermediate‐term storages (i.e., snow over glaciers), which led to the high meltwater contribution to streams during the warm season and the high peaks of meltwater discharge following heavy precipitation events. The porous aquifers in piedmont plain may serve as major reservoirs that store a growing body of groundwater during the warm season, which explains the general increasing trend of baseflow contribution during this period. The moraine and talus deposits in high mountains, by contrast, allow groundwater to pass through them quickly and therefore being responsible for the obvious responses of baseflow contribution amount to heavy rainfall events. Our findings suggest that small mountain glaciers and porous aquifers may play a greater role than expected in hydrological regulation in the alpine‐gorge catchments of northeastern Qinghai‐Tibet Plateau.

While the individual effects of permafrost and seasonal frost on the interactions between groundwater and surface water have received much attention, few attempts have been made to investigate the effects of permafrost and seasonal frost together on groundwater flow and its interactions with surface water. In this study, hydraulic, chemical, and isotopic data as well as a Bayesian mixing model were employed to investigate the interactions between streams and groundwater, the contributions of groundwater to the mainstream, and their relationships to the distribution of permafrost and seasonal frost in a representative subcatchment in the headwater region of the Heihe River Basin on the northeastern Qinghai‐Tibet Plateau in China. Our results showed that due to the freezing and thawing of recharge water sources and soils, the groundwater flow and stream flux from the permafrost zone to the seasonal frost zone increased during the thawing period, with maximum values in thawed period, and decreased during the frozen period. These variations affected groundwater recharge in the seasonal frost zone, resulting in dynamic changes in the groundwater table and the hydraulic gradient between the recharge and discharge points in the seasonal frost zone during the different freeze‐thaw periods. Correspondingly, the contribution of groundwater to the mainstream discharge decreased from 95% during the frozen period to 80%–90% during the thawing period. It then decreased to ∼40%–60% of the mainstream discharge during the thawed period and increased to ∼70%–90% during the refreezing period. From the permafrost zone to the seasonal frost zone and the catchment outlet, the aquifers in the piedmont plain of the seasonal frost zone play an important role in maintaining streamflows by switching their hydrological functions, that is, slowly releasing groundwater to maintain the streamflow during the frozen period and rapidly transferring the groundwater to mainstream during the thawed period.

《地球科学》(ISSN 1000-2383;CN42-1874/P) (原刊名《地球科学——中国地质大学学报》ISSN 1000-2383;CN42-1233/P)，创刊于1957年，是由教育部主管、中国地质大学主办的综合性地学学术理论期刊，月刊，2015年改名为《地球科学》,她以反映中国地质大学教学与科研最新的、高水平的基础地质、应用地质、资源与环境地质及地学工程技术研究成果为主要任务。

Rapid algal proliferation in human-impacted freshwater ecosystems necessitates advanced predictive tools for effective management. This study aims to capture the stochastic dynamics of algal blooms in the Fuxi River, China, using high-frequency monitoring and interpretable machine learning. A 2 h interval dataset was utilized to construct Random Forest models in Python for predicting Chlorophyll-a (Chl-a) and algal density, both measured via in situ multi-wavelength fluorescence. Model interpretability was achieved through SHAP (SHapley Additive exPlanations) analysis to identify non-linear environmental drivers and ecological thresholds. The models demonstrated high predictive accuracy. SHAP analysis revealed that dissolved oxygen (>10 mg/L) is the primary diagnostic indicator for peak Chl-a, with an optimal thermal window of 15–20 °C identified for proliferation. For algal density, chemical oxygen demand (COD_Cr > 25 mg/L) and conductivity (>1000 μS/cm) were identified as critical tipping points, showing pronounced synergistic effects between organic enrichment and nutrient levels. This study underscores that managing organic loading and monitoring specific thermal–hydrochemical windows are vital for mitigating extreme algal events, providing a robust, interpretable framework for real-time water quality early warning.