Altitudinal variation in impacts of snow cover, reservoirs and precipitation seasonality on monthly runoff in Tibetan Plateau catchments

融雪 地表径流 环境科学 季节性 水力发电 降水 水文学(农业) 高原(数学) 水资源 气候变化 水循环 蓄水 积雪 出院手续 水流 空间变异性 流域 自然地理学 沉积(地质) 大气科学
作者
Nan Wu,Ke Zhang,Seyed Amir Naghibi,Hossein Hashemi,Zhongrui Ning,Jerker Jarsjö
出处
期刊:Hydrology and Earth System Sciences [Copernicus Publications]
卷期号:29 (21): 5913-5930 被引量:1
标识
DOI:10.5194/hess-29-5913-2025
摘要

Abstract. Understanding monthly runoff variability, its spatio–temporal characteristics, and key drivers under climate change and human impacts is crucial for long-term water resource management. However, current knowledge remains limited, especially in high-elevation, seasonally cold regions. Focusing on 10 sub-basins along an elevation gradient (1000 to 5900 ma.s.l.) in the hydrologically complex Yalong River basin, China, this study developed an extended Budyko framework based on monthly water balances (2002–2016), explicitly separating snow storage dynamics (ΔSsnow) from other terrestrial water storage changes (ΔS′), including those related to hydropower reservoir construction. Results showed that snow accumulation and snowmelt are main drivers of runoff seasonality in the upper sub-catchments, and their effects propagate to the lower-elevation snow-free sub-catchments, which are also subject to additional influence from hydropower reservoirs. This created pronounced altitudinal heterogeneity in drivers of monthly runoff, a phenomenon suggested but rarely quantified at high spatio–temporal resolution in other global regions. Furthermore, a decrease in runoff seasonality in the Yalong River at its Yangtze River outlet (that receives water from all 10 investigated sub-basins) was observed, this change appeared unrelated to snow storage changes and was more likely driven by trends in unfrozen precipitation seasonality and/or flow-modulating impacts of reservoirs, natural lakes and groundwater. Future snow thinning may exacerbate these trends. Implementing the variance decomposition method within the extended Budyko framework, the intra-annual runoff variability (σR2) was captured by calculating the variance and covariance of influencing factors, achieving R2 values above 0.9 in most sub-basins, and the rainfall (Pr) and ΔS′variances were identified as the main contributors. Methodologically, we have verified the substantial contribution of hydropower reservoir storage changes on total storage changes by independent analysis of reservoir storage data. These findings supported the applicability of the extended monthly Budyko framework for identifying dominant processes in the context of runoff generation and the rapid environmental changes that the Yalong River basin and other cold regions (not least of the Tibetan plateau) are currently experiencing.
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