Zhang Tianpeng, Yan Tiezhu, Li Hao, An Miaoying, Du Xinzhong, Lei Qiuliang, Liu Hongbin
Key Laboratory of Non-point Source Pollution Control, Ministry of Agriculture and Rural Affairs/ Changping Soil Quality National Observation and Research Station /State Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Technical Center for Soil, Agricultural and Rural Ecology and Environment, Ministry of Ecology and Environment of the People's Republic China, Beijing 100012, China.
Water Res. 2025 Jul 5;286:124161. doi: 10.1016/j.watres.2025.124161.
Carbon dioxide (CO) emissions are a critical indicator influencing climate change and have significant impacts on the health of riverine ecosystems. The effects of CO emissions on streamflow and stream temperature have not been explicitly considered in process-based models, which limits the models' capability to simulate streamflow and stream temperature under varying CO concentration scenarios. This study modified an equilibrium temperature model and a CO effect model to overcome this limitation, which were subsequently coupled with the Soil and Water Assessment Tool (SWAT) model. The coupled model was tested and applied in the Chaohe River basin in China from 2021 to 2080, and daily streamflow and stream temperature were simulated under the RCP8.5 and RCP4.5 scenarios based on the ACCESS and HadGEM climate models. The study showed that the coupled model performs well in simulating streamflow and stream temperature, with the PBIAS of less than ±10 %, and both the NSE and R exceeding 0.85. Under both the ACCESS and HadGEM climate models, the simulations of streamflow and stream temperature exhibit a consistent pattern: increased CO concentration leads to higher air temperatures, which in turn elevates stream temperatures and changes streamflow mainly through evapotranspiration process. However, the lower CO concentrations or where snowmelt is significant in regions, streamflow and stream temperature exhibit greater variability. When CO levels are high to induce stomatal closure in plants, decreased evapotranspiration can lead to increased streamflow. In addition, headwater tributaries, primarily fed by rainfall, snowmelt, and groundwater, are located in high-altitude areas influenced by natural factors, while the main stem, mainly supplied by tributary inflows and precipitation, is situated in low-altitude areas affected by both natural and anthropogenic factors. This difference in water sources and influencing factors leads to distinct patterns in streamflow and stream temperature. Therefore, it is essential to develop algorithms that explicitly account for the impacts of CO concentration on hydrological processes and stream temperature dynamics, to accurately simulate the effects of climate change on streamflow and stream temperature, enabling the prediction of future climate change impacts on the thermal regime of river basins. The coupled model developed in this study provides a valuable tool for simulating the effects of CO on streamflow and stream temperature, offering insights into the complex interactions between climate change and hydrological processes.
二氧化碳（CO₂）排放是影响气候变化的关键指标，对河流生态系统健康有重大影响。基于过程的模型尚未明确考虑CO₂排放对径流和河流温度的影响，这限制了模型在不同CO₂浓度情景下模拟径流和河流温度的能力。本研究对平衡温度模型和CO₂效应模型进行了改进以克服这一限制，随后将其与土壤和水资源评估工具（SWAT）模型耦合。耦合模型于2021年至2080年在中国潮河流域进行测试和应用，并基于ACCESS和HadGEM气候模型在RCP8.5和RCP4.5情景下模拟了日径流和河流温度。研究表明，耦合模型在模拟径流和河流温度方面表现良好，PBIAS小于±10%，NSE和R均超过0.85。在ACCESS和HadGEM气候模型下，径流和河流温度的模拟呈现出一致的模式：CO₂浓度升高导致气温升高，进而使河流温度升高，并主要通过蒸散过程改变径流。然而，在CO₂浓度较低或融雪显著的地区，径流和河流温度表现出更大的变异性。当CO₂水平较高导致植物气孔关闭时，蒸散减少会导致径流增加。此外，源头支流主要由降雨、融雪和地下水补给，位于受自然因素影响的高海拔地区，而干流主要由支流汇入和降水补给，位于受自然和人为因素影响的低海拔地区。这种水源和影响因素的差异导致径流和河流温度呈现出不同的模式。因此，开发明确考虑CO₂浓度对水文过程和河流温度动态影响的算法至关重要，以便准确模拟气候变化对径流和河流温度的影响，从而预测未来气候变化对流域热状况的影响。本研究开发的耦合模型为模拟CO₂对径流和河流温度的影响提供了有价值的工具，有助于深入了解气候变化与水文过程之间的复杂相互作用。
