Author(s): Yuanyuan Wang; Borui Wang; Xiaolong He

Linked Author(s):

Keywords: Cascade dams; Carbon emissions; Greenhouse gases; Remote sensing technology; Hydrological changes

Abstract: The operation of cascade dams exerts a profound influence on riverine carbon dynamics, substantially altering greenhouse gas (GHG) fluxes at the water–air interface. This study focuses on the Yalong River, one of the eight major tributaries of the Yangtze River, and a significant hydropower base in southwestern China. Utilizing satellite remote sensing data, hydrological observation records, and model inversion techniques, this research systematically evaluates the impact of dam operations on regional carbon cycling. Specifically, atmospheric CO2 dry air column mean mole fraction (XCO2) data from the OCO-2 and OCO-3 satellites are employed to reconstruct the daily spatiotemporal distribution of XCO2 at a 1 km resolution across the Yalong River Basin from 2015 to 2020. By analyzing the spatiotemporal variations in XCO2 and examining their correlation with hydrological changes, such as impoundment and water release phases, this study reveals the dynamic characteristics of XCO2 in both reservoir and downstream river segments during different operational stages. The results indicate that, due to the accumulation of organic matter and prolonged water retention time, the mean annual XCO2 in the reservoir area reaches 407.02 ppm, which is significantly higher than that in the downstream dewatered river segments (406.84 ppm), thus highlighting a clear CO2 emission hotspot. Moreover, the seasonal variation analysis indicates that, during the dry season, the reduced flow of the river results in a peak in XCO2, with the seasonal difference between the dry season and the wet season reaching 1.54 ppm. This study demonstrates the effectiveness of integrating remote sensing technologies with hydrological models for large-scale assessments of CO2 emission dynamics, thereby providing essential scientific support for optimizing hydropower operations and advancing regional carbon cycle research.

DOI: https://doi.org/10.64697/978-90-835589-7-4_41WC-P2099-cd

Year: 2025