中国大中型水库二氧化碳排放预测研究

张益; 徐俏; 尹心安; 杨柏蘅; 孙悦; 关欣然; 吴子敬; 孙楚淇

doi:10.13205/j.hjgc.202605009

中国大中型水库二氧化碳排放预测研究

doi: 10.13205/j.hjgc.202605009

北京师范大学环境学院区域环境安全全国重点实验室, 北京 100875

基金项目:

内蒙古自治区科技创新重大示范项目“内蒙古黄河流域水生态环境智慧模拟与应用示范”（2025ZDSF0011）；北京市科技新星交叉合作课题（20240484647）

详细信息

作者简介:
张益,女,研究生,主要研究方向为水生态系统保护。202421180030@mail.bnu.edu.cn

通讯作者:
尹心安,男,教授,主要研究方向为生态水利和水生态系统保护与修复研究。yinxinan@bnu.edu.cn

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出版历程
- 收稿日期: 2026-01-09
- 网络出版日期: 2026-06-06

Carbon dioxide emission forecasting for medium and large reservoirs in China

State Key Laboratory of Regional Environment and Sustainability, School of Environment, Beijing Normal University, Beijing 100875, China

摘要

摘要: 水库CO₂排放预测是全球碳循环的关键环节。现有预测研究多基于机器学习模型，且将大、中、小库容水库的数据一起用于模型率定，未根据库容等级分别率定模型和预测排放量，忽略了水库规模差异对碳循环机制的影响。针对该问题，研究摒弃传统的全口径混合建模策略，构建专门针对大中型水库的训练数据集。基于中国大中型水库数据，研究建立了CO₂排放预测模型，深入探究了不同流域水库CO₂通量的时空演变规律，并定量识别了其主导驱动因子。研究表明：中国水库CO₂通量呈现显著的纬度地带性，南方低纬度地区显著高于北方高纬度地区；CO₂通量与水库库龄、纬度及总磷含量呈显著相关，其中总磷含量是相关性最强的驱动因子，二者呈指数正相关；而水库面积、蓄水前淹没比及平均水深等物理参数在全国尺度上与CO₂通量无显著相关性，且不同流域的主导影响因素存在异质性。研究结果可为明晰中国大中型水库碳排放特征提供理论依据，并为水库碳汇管理提供科学支撑。
- 中国大中型水库 /
- 二氧化碳通量 /
- 影响因素 /
- 空间分布 /
- 神经网络
Abstract: Reservoir carbon dioxide （CO₂） emission forecasting is a key component of the global carbon cycle. Most existing prediction studies are based on machine learning models， where data from large-， medium-， and small-sized reservoirs are used together for model calibration. Neither the model calibration nor the emission forecasting is stratified by reservoir capacity level， thereby ignoring the impact of reservoir size on the carbon cycle mechanism. To address this problem， this study abandoned the traditional full-scale hybrid modeling strategy and constructed a training dataset specifically for large- and medium-sized reservoirs. Using data from large- and medium-sized reservoirs in China， this study established a CO₂ emission forecasting model， thoroughly explored the spatiotemporal evolution of CO₂ flux across different river basins， and quantitatively identified the leading driving factors. The results showed that CO₂ flux of reservoirs in China exhibited significant latitudinal zonation， with values in low-latitude areas in the south significantly higher than those in high-latitude areas in the north. CO₂ flux was significantly correlated with reservoir age， latitude， and total phosphorus content. Among these， total phosphorus content was the most strongly correlated driving factor， showing a positive exponential correlation with CO₂ flux. However， physical parameters such as reservoir area， pre-impoundment submersion ratio， and average water depth showed no significant correlation with CO₂ flux at the national scale， and the dominant influencing factors varied heterogeneously across different basins. The findings of this study provide a theoretical basis for clarifying the carbon emission characteristics of large- and medium-sized reservoirs in China offer scientific support for the management of carbon sinks in reservoirs.
- large-and medium-sized reservoirs in China /
- CO₂ flux /
- influencing factors /
- spatial distribution /
- neural network

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