基于情景模拟的流域低碳土地利用格局优化研究——以汾河流域为例

doi:10.13866/j.azr.2023.02.05

Abstract

Abstract:

Carrying out the optimal allocation of land use is aimed at promoting the scientific use of regional land resources and achieving carbon emission reduction targets. In this paper, the Fenhe River Basin is taken as the research area. Based on the data on land use and resistance factors in 2015 and 2020, the FLUS-MCR model and the carbon budget coefficient method are used to verify the accuracy of the model. Five simulation scenarios, such as low-carbon development priority, economic development priority, cultivated land protection priority, ecological protection priority, and natural development in 2030, are set up to compare the layout characteristics of land use types under different scenarios in the future, and an optimized layout scheme is proposed. The results showed that: (1) In 2020, the areas of four land use functional zoning of the prohibited, restricted, key, and optimized development zones in Fenhe River Basin were 2491.76 km², 6445.99 km², 16325 km², and 14477 km², respectively. The net carbon emission of the basin is 2002.46 × 10⁴ t. The prohibited development zone is the carbon sink area of the basin, and the total carbon absorption is 0.76×10⁴ t. The remaining three areas are carbon source areas, and the total carbon emission is 2003.22 × 10⁴ t. (2) In 2030, the carbon balance of land use in each scenario from high to low is low-carbon development priority, ecological protection priority, cultivated land protection priority, natural development priority, and economic development priority. (3) In 2030, under different scenarios, in addition to the relatively reasonable land use structure of the prohibited development zone, the restricted development zone still needs to appropriately reduce the proportion of cultivated land and construction land in the area. To support the coordinated development of land use, production, living conditions, and ecological functions and to accomplish low-carbon land use goals, the key and optimal development zones should take arable grassland development into consideration.

Key words: low-carbon land use, optimize configuration, FLUS-MCR model, carbon budget coefficient, Fenhe River Basin, Shanxi

ZHANG Enyue, ZHENG Junyan, SU Yingqing, ZHANG Lei, ZHANG Pengfei, LIU Geng. Optimization of low-carbon land use pattern based on scenario simulation: A case study of Fenhe River Basin[J].Arid Zone Research, 2023, 40(2): 203-212.

Figures/Tables 12

Fig. 1

Tab. 1

Fig. 2

Tab. 2

Fig. 3

Tab. 3

Fig. 4

Fig. 5

Tab. 4

Fig. 6

Fig. 7

Fig. 8

References 33

[1]	邓旭, 谢俊, 滕飞. 何谓“碳中和”?[J]. 气候变化研究进展, 2021, 17(1): 107-113.
	[Deng Xu, Xie Jun, Teng Fei. What is carbon neutrality?[J]. Climate Change Research, 2021, 17(1): 107-113.]
[2]	项目综合报告编写组. 《中国长期低碳发展战略与转型路径研究》综合报告[J]. 中国人口·资源与环境, 2020, 30(11): 1-25.
	[The project comprehensive report compilation group. ‘Research on China’s long-term low-carbon development strategy and transformation path’ comprehensive report[J]. China Population, Resources and Environment, 2020, 30(11): 1-25.]
[3]	王灿, 张雅欣. 碳中和愿景的实现路径与政策体系[J]. 中国环境管理, 2020, 12(6): 58-64.
	[Wang Can, Zhang Yaxin. Implementation pathway and policy system of carbon neutrality vision[J]. Chinese Journal of Environmental Management, 2020, 12(6): 58-64.]
[4]	周宏春, 史作廷. 双碳导向下的绿色消费: 内涵、传导机制和对策建议[J]. 中国科学院院刊, 2022, 37(2): 188-196.
	[Zhou Hongchun, Shi Zuoting. Green consumption under carbon-orientated: Connotation, transmission mechanism and countermeasures[J]. Bulletin of Chinese Academy of Sciences, 2022, 37(2): 188-196.]
[5]	余碧莹, 赵光普, 安润颖, 等. 碳中和目标下中国碳排放路径研究[J]. 北京理工大学学报(社会科学版), 2021, 23(2): 17-24.
	[Yu Biying, Zhao Guangpu, An Runying, et al. Research on China’s CO₂ emission pathway under carbon neutral target[J]. Journal of Beijing Institute of Technology(Social Sciences Edition), 2021, 23(2): 17-24.]
[6]	杨皓然, 吴群. 不同政策方案下的南京市土地利用碳排放动态模拟[J]. 地域研究与开发, 2021, 40(3): 121-126.
	[Yang Haoran, Wu Qun. Dynamic simulation of carbon emissions from land use in Nanjing City under different policy scenarios[J]. Areal Research and Development, 2021, 40(3): 121-126.]
[7]	赵宏波, 魏甲晨, 孙东琪, 等. 基于随机森林模型的“生产-生活-生态”空间识别及时空演变分析——以郑州市为例[J]. 地理研究, 2021, 40(4): 945-957. doi: 10.11821/dlyj020200237
	[Zhao Hongbo, Wei Jiachen, Sun Dongqi, et al. Recognition and spatio-temporal evolution analysis of production-living-ecological spaces based on the random forest model: A case study of Zhengzhou City, China[J]. Geographical Research, 2021, 40(4): 945-957.] doi: 10.11821/dlyj020200237
[8]	陈万旭, 李江风, 曾杰, 等. 中国土地利用变化生态环境效应的空间分异性与形成机理[J]. 地理研究, 2019, 38(9): 2173-2187. doi: 10.11821/dlyj020180659
	[Chen Wanxu, Li Jiangfeng, Zeng Jie, et al. Spatial heterogeneity and formation mechanism of eco-environmental effect of land use change in China[J]. Geographical Research, 2019, 38(9): 2173-2187.] doi: 10.11821/dlyj020180659
[9]	袁利, 刘毅华, 邱坚坚. 经济与生态效益不同情景下的广州市土地利用优化配置[J]. 生态经济, 2021, 37(4): 103-109.
	[Yuan Li, Liu Yihua, Qiu Jianjian. An optimal allocation analysis of land use under different scenarios with economic and ecological benefits in Guangzhou[J]. Ecological Economy, 2021, 37(4): 103-109.]
[10]	涂小松, 濮励杰, 严祥, 等. 土地资源优化配置与土壤质量调控的系统动力学分析[J]. 环境科学研究, 2009, 22(2): 221-226.
	[Tu Xiaosong, Pu Lijie, Yan Xiang, et al. Analysis of optimal allocation of land resources and soil quality regulation using system dynamics[J]. Research of Environmental Sciences, 2009, 22(2): 221-226.]
[11]	魏伟, 颉耀文, 魏晓旭, 等. 基于CLUE-S模型和生态安全格局的石羊河流域土地利用优化配置[J]. 武汉大学学报(信息科学版), 2017, 42(9): 1306-1315.
	[Wei Wei, Xie Yaowen, Wei Xiaoxu, et al. Land use optimization based on CLUE-S model and ecology security scenario in Shiyang River Basin[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1306-1315.]
[12]	王帝文, 李飞雪, 陈东. 基于Pareto最优和多目标粒子群的土地利用优化配置研究[J]. 长江流域资源与环境, 2019, 28(9): 2019-2029.
	[Wang Diwen, Li Feixue, Chen Dong. Research on optimal land use allocation based on pareto optimal and multi-particle swarm algorithm[J]. Resources and Environment in the Yangtze Basin, 2019, 28(9): 2019-2029.]
[13]	彭玉玲, 徐学娴, 隗剑秋, 等. 老挝凯山丰威汉市土地资源的空间优化配置[J]. 水土保持通报, 2021, 41(5): 160-165, 373.
	[Peng Yuling, Xu Xuexian, Yu Jianqiu, et al. Spatial optimal allocation of land resources in Fengweihan City, Kaishan, Laos[J]. Bulletin of Soil and Water Conservation, 2021, 41(5): 160-165, 373.]
[14]	管成文. 基于CLUE-S模型和生态敏感性分析的江川区土地利用空间格局优化配置[D]. 昆明: 云南大学, 2018.
	[Guan Chengwen. Optimal Allocation of Land Use Spatial Pattern in Jiangchuan Area Based on CLUE-S Model and Ecological Sensitivity Analysis[D]. Kunming: Yunnan University, 2018.]
[15]	马冰滢, 黄姣, 李双成. 基于生态-经济权衡的京津冀城市群土地利用优化配置[J]. 地理科学进展, 2019, 38(1): 26-37. doi: 10.18306/dlkxjz.2019.01.003
	[Ma Bingying, Huang Jiao, Li Shuangcheng. Optimal allocation of land use types in the Beijing-Tianjin-Hebei urban agglomeration based on ecological and economic benefits trade-offs[J]. Progress in Geography, 2019, 38(1): 26-37.] doi: 10.18306/dlkxjz.2019.01.003
[16]	陈红, 史云扬, 柯新利, 等. 生态与经济协调目标下的郑州市土地利用空间优化配置[J]. 资源科学, 2019, 41(4): 717-728. doi: 10.18402/resci.2019.04.09
	[Chen Hong, Shi Yunyang, Ke Xinli, et al. Spatial optimization of land use based on the objective of coordinated ecological protection and economic development in Zhengzhou City[J]. Resources Science, 2019, 41(4): 717-728.] doi: 10.18402/resci.2019.04.09
[17]	魏伟, 石培基, 周俊菊, 等. 基于生态安全格局的干旱内陆河流域土地利用优化配置分区[J]. 农业工程学报, 2016, 32(18): 9-18.
	[Wei Wei, Shi Peiji, Zhou Junju, et al. Configuration partition of land use optimization in arid inland river basin based on ecological security pattern[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(18): 9-18.]
[18]	Zhang X J, Wang G Q, Xue B L, et al. Dynamic landscapes and the driving forces in the Yellow River Delta wetland region in the past four decades[J]. Science of the Total Environment, 2021, 787: DOI: 10.1016/j.scitotenv.2021.147644. doi: 10.1016/j.scitotenv.2021.147644
[19]	Liu X P, Liang X, Li X, et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects[J]. Landscape & Urban Planning, 2017, 168: 94-116.
[20]	齐麟, 许东, 朱琪, 等. 基于GeoSOS-FLUS平台的东北森林屏障带生态格局优化[J]. 生态学杂志, 2021, 40(11): 3448-3462.
	[Qi Lin, Xu Dong, Zhu Qi, et al. Ecological pattern optimization of forest barrier belt in Northeast China based on GeoSOS-FLUS[J]. Chinese Journal of Ecology, 2021, 40(11): 3448-3462.]
[21]	苏迎庆, 刘庚, 赵景波, 等. 基于FLUS模型的汾河流域生态空间多情景模拟预测[J]. 干旱区研究, 2021, 38(4): 1152-1161.
	[Su Yingqing, Liu Geng, Zhao Jingbo, et al. Multi-scenario simulation prediction of ecological space in Fenhe River Basin based on FLUS model[J]. Arid Zone Research, 2021, 38(4): 1152-1161.]
[22]	景艳宾, 孙旭, 刘军, 等. 基于MCR模型的内蒙古鄂托克旗生态廊道构建[J]. 水土保持通报, 2021, 41(2): 170-177.
	[Jing Yanbin, Sun Xu, Liu Jun, et al. Construction of ecological corridorin Etuoke Banner of Inner Mongolian based on MCR model[J]. Bulletin of Soil and Water Conservation, 2021, 41(2): 170-177.]
[23]	刘海龙, 王炜桥, 王跃飞, 等. 汾河流域生态敏感性综合评价及时空演变特征[J]. 生态学报, 2021, 41(10): 3952-3964.
	[Liu Hailong, Wang Weiqiao, Wang Yuefei, et al. Comprehensive evaluation of the ecological sensitivity and the characteristics of temporal and spatial variations in Fenhe River Basin[J]. Acta Ecologica Sinica, 2021, 41(10): 3952-3964.]
[24]	陈南南, 康帅直, 赵永华, 等. 基于MSPA和MCR模型的秦岭(陕西段)山地生态网络构建[J]. 应用生态学报, 2021, 32(5): 1545-1553. doi: 10.13287/j.1001-9332.202105.012
	[Chen Nannan, Kang Shuaizhi, Zhao Yonghua, et al. Construction of ecological network in Qinling Mountains of Shaanxi, China based on MSPA and MCR model[J]. Chinese Journal of Applied Ecology, 2021, 32(5): 1545-1553.] doi: 10.13287/j.1001-9332.202105.012
[25]	钟式玉, 吴箐, 李宇, 等. 基于最小累积阻力模型的城镇土地空间重构——以广州市新塘镇为例[J]. 应用生态学报, 2012, 23(11): 3173-3179.
	[Wu Qing, Li Yu, et al. Reconstruction of urban land space based on minimum cumulative resistance model: A case study of Xintang Town, Guangzhou City[J]. Chinese Journal of Applied Ecology, 2012, 23(11): 3173-3179.]
[26]	林伊琳, 赵俊三, 陈国平, 等. 基于MCR-FLUS-Markov模型的区域国土空间格局优化[J]. 农业机械学报, 2021, 52(4): 159-170, 207.
	[Lin Yilin, Zhao Junsan, Chen Guoping, et al. Optimization of regional territory space pattern based on MCR-FLUS-Markov model[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(4): 159-170, 207.]
[27]	刘敏, 郝炜. 山西省国家A级旅游景区空间分布影响因素研究[J]. 地理学报, 2020, 75(4): 878-888. doi: 10.11821/dlxb202004015
	[Liu Min, Hao Wei. Spatial distribution and its influencing factors of national A-level tourist attractions in Shanxi Province[J]. Acta Geographica Sinica, 2020, 75(4): 878-888.] doi: 10.11821/dlxb202004015
[28]	郑洋, 郝润梅, 吴晓光, 等. 基于MCR模型的村庄“三生空间”格局优化研究[J]. 水土保持研究, 2021, 28(5): 362-367.
	[Zheng Yang, Hao Runmei, Wu Xiaoguang, et al. Research on the space pattern optimization of production-living-ecology spacesin village based on MCR model[J]. Research of Soil and Water Conservation, 2021, 28(5): 362-367.]
[29]	刘孝富, 舒俭民, 张林波. 最小累积阻力模型在城市土地生态适宜性评价中的应用——以厦门为例[J]. 生态学报, 2010, 30(2): 421-428.
	[Liu Xiaofu, Shu Jianmin, Zhang Linbo. Research on applying minimal cumulative resistance model in urban land ecological suitability assessment: As an example of Xiamen City[J]. Acta Ecologica Sinica, 2010, 30(2): 421-428.]
[30]	张杰, 陈海, 刘迪, 等. 基于县域尺度土地利用碳排放的时空分异及影响因素研究[J]. 西北大学学报(自然科学版), 2022, 52(1): 21-31.
	[Zhang Jie, Chen Hai, Liu Di, et al. The spatial and temporal variation and influencing factors of land use carbon emissions at county scale[J]. Journal of Northwest University(Natural Science Edition), 2022, 52(1): 21-31.]
[31]	朱向梅, 王子莎. 黄河流域碳水足迹评价及时空格局研究[J]. 环境科学与技术, 2020, 43(10): 200-211.
	[Zhu Xiangmei, Wang Zisha. Study on the assessment of carbon and water footprint and its spatial-temporal pattern in the Yellow River Basin[J]. Environmental Science & Technology, 2020, 43(10): 200-211.]
[32]	周嘉, 王钰萱, 刘学荣, 等. 基于土地利用变化的中国省域碳排放时空差异及碳补偿研究[J]. 地理科学, 2019, 39(12): 1955-1961. doi: 10.13249/j.cnki.sgs.2019.12.014
	[Zhou Jia, Wang Yuxuan, Liu Xuerong, et al. Spatial temporal differences of carbon emissions and carbon compensation in China based on land use change[J]. Scientia Geographica Sinica, 2019, 39(12): 1955-1961.] doi: 10.13249/j.cnki.sgs.2019.12.014
[33]	禹康康, 王延华, 孙恬, 等. 太湖流域土地利用碳排放变化及其预测[J]. 土壤, 2022, 54(2): 406-414.
	[Yu Kangkang, Wang Yanhua, Sun Tian, et al. Changes and prediction of carbon emission from different land use types in Taihu Lake Basin[J]. Soils, 2022, 54(2): 406-414.]

数据类型	指标	数据来源
基础数据	山西省行政边界	中国科学院资源环境科学数据中心（http://www.resdc.cn）2015年
阻力因子	土地利用/覆被	中国科学院资源环境科学数据中心（http://www.resdc.cn）2015年、2020年（Landsat 8 30 m）
	高程/m	中国科学院资源环境科学数据中心（http://www.resdc.cn） 2000年山西省DEM（SRTM 30 m）
	坡度/（°）	中国科学院资源环境科学数据中心（http://www.resdc.cn） 2000年山西省DEM（SRTM 30 m）
	土壤厚度/cm	国家地球系统科学数据中心—土壤分中心（http://soil.geodata.cn）中国高分辨率国家土壤信息格网基本属性数据集（2010—2018）1 km
	植被覆盖度/%	地理空间数据云（www.gscloud.cn） MOD13Q1数据集2020年 250 m
	年均气温/℃	WorldClim version 2.0（http://www.worldclim.org/） 2000年
	年均降水量/mm	WorldClim version 2.0（http://www.worldclim.org/） 2000年
	距道路距离/m	国家基础地理信息中心（www.ngcc.cn/ngcc/） 2015年1：1000000中国基础地理信息数据
	距水体距离/m	国家基础地理信息中心（www.ngcc.cn/ngcc/） 2015年1：1000000中国基础地理信息数据

情景类型	转换原则
低碳发展优先	结合《中国能源统计年鉴》、中国碳核算数据库（https://www.ceads.net.cn/data/）、《山西省统计年鉴》等省市统计年鉴历年研究区能源排放量变化趋势，并参照《山西省国民经济和社会发展第十四个五年规划和2035年远景目标纲要》，以最低增长量为目标，优先转换碳汇用地类型林地、水域、草地等
生态保护优先	基于《汾河流域生态修复规划（2015—2030年）》、《汾河流域生态景观规划（2020—2035）》等相关省市国土空间规划基础，纳入生态保护红线区域限制转换，按用地类型生态效益等级依次转换林地、水域、草地、其他
耕地保护优先	通过加入永久基本农田保护区为限制转化区，控制耕地向建设用地转移，除建设用地，加大其他用地类型转换为耕地的概率
自然发展	以2015—2020年土地利用变化速率及基准年驱动因子为源，不考虑政策规划限制，预测各地类未来规模
经济发展优先	基于《山西省国民经济和社会发展第十四个五年规划和2035年远景目标纲要》及历年建设用地等变化趋势，以最大增长量为目标，按低到高等级用地单向转换原则排序：建设用地、耕地、林地、草地、水域等，优先安排建设用地转换

阻力因子	阻力因子分级（生态/城镇源地）					权重
阻力因子	低阻力/ 高阻力	较低阻力/ 较高阻力	中等阻力/ 中等阻力	较高阻力/ 较低阻力	高阻力/ 低阻力	权重
高程/m	>1600	1200~1600	1000~1200	800~1000	<800	0.1412
坡度/（°）	>60	45~60	30~45	13~30	<13	0.1313
土地利用类型	林地、水域	草地	耕地	未利用地	建设用地	0.1540
土壤厚度/cm	>150	100~150	60~100	40~60	<40	0.0783
植被覆盖度/%	>80	60~80	40~60	20~40	0~20	0.1358
年均气温/℃	<4	4~7	7~9	9~11	>11	0.0632
年均降水量/mm	>548	515~548	483~515	447~483	0~447	0.0674
距道路距离/m	>138	88~138	51~88	17~51	0~17	0.1072
距水体距离/m	0~54	54~114	114~182	182~284	>284	0.1216

用地类型	碳收支系数	碳效应
耕地	0.37	碳源
林地	-0.49	碳汇
草地	-0.02	碳汇
水域	-0.46	碳汇
建设用地	65.30	碳源

Optimization of low-carbon land use pattern based on scenario simulation: A case study of Fenhe River Basin

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 33

Related Articles 15

Metrics

Comments

Recommended 0

[1]	LI Kexuan, ZHANG Lei, LI Hao, ZHANG Enyue, LI Yuzhen, SONG Caiyun, LIU Geng. Identification of the key regions of spatial ecological restoration in the Northwest Shanxi based on the MSPA model and circuit theory [J]. Arid Zone Research, 2024, 41(9): 1593-1604.
[2]	WU Zhaoqiao, LIN Fei, NIU Junjie, GENG Tianwei. Response of ecosystem service to land use pattern change in the Shanxi central urban agglomeration [J]. Arid Zone Research, 2024, 41(7): 1153-1166.
[3]	XU Mingjing, FENG Qiang, LYU Meng. Tradeoffs of ecosystem services and their influencing factors: A case study of the Shanxi Section of the Yellow River Basin [J]. Arid Zone Research, 2024, 41(3): 467-479.
[4]	WANG Bo, ZHANG Jianjun, LAI Zongrui, ZHAO Jiongchang, HU Yawei, YANG Zhou, LI Yang, WEI Zhaoyang. Effect of soil moisture content on the accuracy of root configuration detection by ground penetrating radar [J]. Arid Zone Research, 2024, 41(3): 456-466.
[5]	ZHOU Yi, SUO Wenjiao. Spatialtemporal variation characteristics of drought in the Fenhe River Basin based on CWSI [J]. Arid Zone Research, 2024, 41(2): 191-199.
[6]	WANG Siqi, ZHANG Jianjun, ZHANG Yanqin, ZHAO Jiongchang, HU Yawei, LI Yang, TANG Peng, WEI Zhaoyang. Understory plant community diversity of Robinia pseudoacacia plantation with different densities in the loess plateau of western Shanxi Province [J]. Arid Zone Research, 2023, 40(7): 1141-1151.
[7]	XU Liting,LIU Haihong,HUANG Lijie,WANG Yufan. Spatial and temporal changes of ecological environment and water conservation in Fenhe River Basin from 2000 to 2020 [J]. Arid Zone Research, 2023, 40(2): 313-325.
[8]	ZHANG Jianhua, ZHANG Kun, LIU Yong, ZHANG Hong, ZHANG Kaiquan, ZHOU Xiaoyang, XU Longchao. Study on water-holding capacity of litters from typical artificial forests in reclaimed regions of the opencast coal mine in Shanxi Province [J]. Arid Zone Research, 2023, 40(12): 2043-2052.
[9]	JI Qianqian, PAN Huanhuan, WU Shurong, WU Zhitao, DU Ziqiang. Effect of spatial reconstruction of “production-living-ecology” space and precipitation changes on water yield services in the Yellow River Basin in Shanxi Province [J]. Arid Zone Research, 2023, 40(1): 132-142.
[10]	LIU Hailong,TANG Fei,DING Ya’nan,ZHANG Yu,GUO Xiaojia,TAN Jingbai,CHENG Yue. Temporal and spatial evolution characteristics of the coupling between county high-quality development and ecosystem services in Shanxi Province [J]. Arid Zone Research, 2022, 39(4): 1234-1245.
[11]	SU Yingqing,ZHANG Enyue,LIU Yuan,LIU Geng,LIN Fei. Land-use change and ecological environment effects on Fenhe River Basin [J]. Arid Zone Research, 2022, 39(3): 968-977.
[12]	HU Yawei,SUN Ruoxiu,SHEN Mingshuang,SHI Zhengle,LIU Chang,XU Qintao,LIU Junting,ZHANG Jianjun. Effects of land use types on the stoichiometric characteristics of soil C:N:P and the physical and chemical properties of soil in western Shanxi loess region [J]. Arid Zone Research, 2021, 38(4): 990-999.
[13]	SU Yingqing,LIU Geng,ZHAO Jingbo,NIU Junjie,ZHANG Enyue,GUO Ligang,LIN Fei. Multi-scenario simulation prediction of ecological space in the Fenhe River Basin using the FLUS model [J]. Arid Zone Research, 2021, 38(4): 1152-1161.
[14]	XU Zhiping,SHAO Tianjie,ZHANG Liankai,SHAO Mingyu,NIU Junjie. Study on the change of surface CO₂ flux in sandy loamy soil under different land use types: An example from the Qingliangsi ditch watershed [J]. Arid Zone Research, 2021, 38(4): 1000-1009.
[15]	WANG Shang-Yi, NIU Jun-Jie, ZHU Wei-Xin, ZHANG Xiu-Wei. Change of Soil Moisture Content under Different Plant Species in Mining and Non-mining Areas in Northwest Shanxi Province [J]. , 2013, 30(6): 986-991.