Study on the dissolved inorganic carbon cycling and carbon emission during the wet season across cascade hydropower stations on the Jinsha River, southwestern China

Abstract

The Jinsha River Basin, situated in the arid and warm upper reaches of the Yangtze River in China, presents distinctive challenges for investigating dissolved inorganic carbon (DIC) due to its regional geography and climate. This study explored the spatial distribution and cycling of DIC during the wet season at four cascade power stations: Wudongde (WDD), Baihetan (BHT), Xiluodu (XLD), and Xiangjiaba (XJB). The results indicate that the primary sources of DIC at these stations are the result of carbonate rocks weathering by carbonic acid and sulfuric/nitric acids. Specifically, DIC production from weathering at WDD significantly surpasses that at the other stations (BHT, XLD, XJB) under the sulfuric/nitric acid weathering conditions (p < 0.05). In the cascade reservoirs of the Jinsha River, biochemical processes predominantly facilitate the precipitation of calcium carbonate. Among these reservoirs, XLD exhibits the highest efficiency in converting DIC into calcite, with a transformation rate of ΔDIC_trans reaching 2.62 Tg/year. During the wet season, the combined effects of air temperature, wind speed, and partial pressure result in higher average CO₂ emissions from the cascade power stations in the Jinsha River and Yellow River basins compared to other cascade power stations, comparable to emissions from the Three Gorges Reservoir. Specifically, XLD exhibits the highest CO₂ emission rate (FCO₂ = 102.38 ± 94.71 mmol/m2/d). Nevertheless, these levels are lower than those observed in most natural rivers globally. Buffer factor analysis indicates that the carbonate buffering capacity of the Jinsha River cascade reservoirs is relatively weak, with an average Revelle coefficient of approximately 41.4. These results enhance our understanding of carbon cycling in the Jinsha River’s cascade power stations and provide crucial insights.

for preserving the long-term stability of river ecosystems.