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长江流域江苏段碳储量的多情景模拟和空间格局优化
摘要点击 472  全文点击 18  投稿时间:2025-01-13  修订日期:2025-04-04
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中文关键词  碳储量  PLUS模型  InVEST模型  多情景模拟  贝叶斯网络模型  空间格局优化
英文关键词  carbon storage  PLUS model  InVEST model  multi-scenario simulation  Bayesian network model  spatial pattern optimization
DOI    10.13227/j.hjkx.20260220
作者单位E-mail
彭卓越 扬州大学水利科学与工程学院, 扬州 225009
扬州大学中国大运河研究院, 扬州 225009
中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100048 
pengzy@yzu.edu.cn 
李梦婷 扬州大学水利科学与工程学院, 扬州 225009  
梁煜彬 扬州大学水利科学与工程学院, 扬州 225009  
刘亚明 扬州大学水利科学与工程学院, 扬州 225009  
方红远 扬州大学水利科学与工程学院, 扬州 225009  
殷峻暹 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100048  
中文摘要
      优化碳储量的空间格局对提高区域生态系统碳汇容量和维持区域碳平衡具有重要意义. 以长江流域江苏段为例,基于土地利用/覆被变化、社会经济和气候环境数据,结合InVEST和PLUS模型预测研究区2030年自然发展、耕地保护和生态保护这3种不同情景下的生态系统碳储量和空间分布格局,并借助具有决策优化能力的贝叶斯网络模型对研究区碳储量格局进行了分区优化. 结果表明:①2000~2020年研究区碳储量呈下降趋势,共减少了4 797.63×104 t,主要原因是耕地、林地向建设用地转换. ②2030年研究区生态保护情景下的碳储量为38 528.91×104 t,呈上升趋势,其余2种情景下的碳储量均呈现下降趋势. ③通过贝叶斯网络模型,筛选出关键变量关键状态子集,将研究区划分为生态保护区、耕地保护区、水源涵养区和经济建设区这4类优化分区. 研究结果可为流域土地利用可持续发展及推进流域实现“双碳”目标提供参考.
英文摘要
      Optimizing the spatial pattern of carbon storage is of great significance for increasing the carbon sink capacity of regional ecosystems and maintaining regional carbon balance. Taking the Jiangsu section of the Yangtze River Basin as an example, combined with InVEST and PLUS models, the carbon storage and spatial distribution pattern of the ecosystem in the study area in 2030 were predicted under three different scenarios: natural development, cultivated land protection, and ecological protection. The pattern of carbon storage in the study area was optimized using a Bayesian network model with decision optimization ability. The results showed that: ① Carbon storage in the study area showed a downward trend from 2000 to 2020, with a total decrease of 4 797.63×104 t, mainly due to the conversion of cultivated land and forest land to construction land. ② In 2030, the carbon storage under the ecological protection scenario of the study area was 38 528.91×104 t, showing an increasing trend, while the carbon storage under the other two scenarios showed a decreasing trend. ③ By using the Bayesian network model, key variables and key state subsets were selected, and the study area was divided into four types of optimal zones: ecological protection area, cultivated land protection area, water conservation area, and economic construction area. This study sought to clarify the temporal and spatial evolution characteristics of carbon storage in the Jiangsu section of the Yangtze River Basin, predict its future development trend, and optimize its spatial pattern, which is conducive to the sustainable development of land use in the basin and provides reference for promoting the “dual carbon” goal of the basin.

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