基于InVEST-PLUS模型的黄河流域内蒙古段生态系统碳储量评价及预测

doi:10.13866/j.azr.2024.07.13

摘要/Abstract

摘要：

陆地生态系统碳储量对减缓全球气候变暖有重要意义，评估黄河流域内蒙古段土地利用变化对碳储量变化的影响，可以为“双碳”目标的实现提供助力。本研究运用InVEST模型对黄河流域内蒙古段过去20 a的碳储量进行评估，运用PLUS模型预测了2040年3种不同发展情景下的土地利用格局，并耦合InVEST-PLUS对黄河流域内蒙古段未来20 a的碳储量进行估算，探讨土地利用变化和碳储量之间的响应关系。结果表明：2000—2020年黄河流域内蒙古段草地是主要土地利用类型和最重要的碳库。草地面积增加是黄河流域内蒙古段碳储量上升的主要原因，碳储量累计上升4.08×10⁷ t。在生态保护情景下，最有利于2040年黄河流域内蒙古段碳储量的增加，可使碳储量累计增加4.50×10⁷ t。年均降水是解释度最高的单因子影响因素，随着社会经济的发展，社会经济因子对碳储量时空分异特征的解释度增加。双因子交互影响的解释度普遍远高于单因子对于碳储量时空分异特征的解释度。本研究以期为区域用地规划提供建议，为我国更好的实现碳中和目标提供服务。

关键词: 碳储量, 土地利用变化, InVEST模型, PLUS模型, 黄河流域内蒙古段

Abstract:

The carbon storage of terrestrial ecosystems plays a crucial role in mitigating global warming. Assessing the impact of land use changes on carbon storage in the Inner Mongolia section of the Yellow River basin can contribute to achieving “dual carbon” targets. This study applied the InVEST model to assess carbon storage in the Inner Mongolia section of the Yellow River basin over the past 20 years. The PLUS model was used to predict land use patterns in 2040 under three different development scenarios. The study then coupled the InVEST-PLUS to predict the carbon storage for the next 20 years, exploring the response relationship between land use changes and carbon storage. The results indicated that from 2000 to 2020, grasslands were the major land use type and the most significant carbon reservoir. The increase in grassland area was the primary reason for the total rise in carbon storage at 4.08×10⁷ t. Under the ecological protection scenario, it is most conducive to improving carbon storage in the basin by 2040, with a total increase of 4.50×10⁷ t. Annual precipitation was the factor with the single highest explanatory power. As socioeconomic development progresses, its explanatory power on the spatial and temporal differentiation characteristics of carbon storage becomes more apparent. The explanatory power of two-factor interactions is generally much higher than that of single factors for these characteristics. This study aims to provide recommendations for regional land planning and to help China achieve its carbon neutrality goals better.

Key words: carbon storage, land use change, InVEST model, PLUS model, Inner Mongolia section of the Yellow River Basin

李冰洁, 范志韬, 曲芷程, 姚顺予, 宿夏姝, 刘东伟, 王立新. 基于InVEST-PLUS模型的黄河流域内蒙古段生态系统碳储量评价及预测[J]. 干旱区研究, 2024, 41(7): 1217-1227.

LI Bingjie, FAN Zhitao, QU Zhicheng, YAO Shunyu, SU Xiashu, LIU Dongwei, WANG Lixin. Evaluation and prediction of ecosystem carbon storage in the Inner Mongolia section of the Yellow River Basin based on the InVEST-PLUS model[J]. Arid Zone Research, 2024, 41(7): 1217-1227.

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数据类型	数据名称	分辨率	数据来源
土地利用	2000年、2010年、2020年土地利用数据	30 m×30 m	Global Land 30（http://www.globeland30.org）
气候环境	年平均气温	1 km×1 km	资源环境科学与数据中心（https://www.resdc.cn）
	年平均降水	1 km×1 km	资源环境科学与数据中心（https://www.resdc.cn）
	高程	30 m×30 m	地理空间数据云（https://www.gscloud.cn）
	坡度	30 m×30 m
	坡向	30 m×30 m
	NDVI	1 km×1 km	国家青藏高原科学数据中心（https://data.tpdc.ac.cn）
	到水系距离	1 km×1 km	OSM，采用欧式距离进行计算（https://www.openstreetmap.org/）
社会经济	GDP	1 km×1 km	中国科学院地理科学与资源研究所（http://www.igsnrr.cas.cn/skjs）
	人口	1 km×1 km	美国能源部橡树岭国家实验室（ORNL）（https://www.ornl.gov）
	夜间灯光	1 km×1 km	地球资源云（http://gis5g.com）
	到县政府距离	1 km×1 km	全国地理信息资源目录服务系统（https://www.webmap.cn/main.do）
	到一级道路距离	1 km×1 km	OSM，采用欧式距离进行计算（https://www.openstreetmap.org/）
	到二级道路距离	1 km×1 km
	到三级道路距离	1 km×1 km

土地利用类型	地上碳密度	地下碳密度	土壤碳密度
耕地	2.58	3.57	80.39
林地	35.83	18.53	114.18
草地	0.83	5.05	86.05
灌木地	5.71	3.75	73.92
湿地	2.27	1.82	231.20
水体	0.00	0.00	0.00
建设用地	0.00	0.00	35.18
未利用地	0.45	0.87	38.55

土地利用类型	2000年		2010年		2020年		2000—2020年
土地利用类型	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%	面积变化/km²
耕地	49756.5	19.60	48045.9	18.93	50209	19.78	452.50
林地	2308.29	0.91	3000.68	1.18	2854.13	1.12	545.84
草地	133638	52.64	139341	54.89	139705	55.03	6067.00
灌木地	3102.76	1.22	6860.91	2.70	6324.86	2.49	3222.10
湿地	1310.33	0.52	883.95	0.35	698.353	0.28	-611.98
水体	1166.84	0.46	1050.04	0.41	1285.05	0.51	118.21
建设用地	2971.14	1.17	3665.14	1.44	6197.08	2.44	3225.94
未利用地	59610.00	23.48	51007.90	20.09	46603.3	18.36	-13006.70

土地利用类型	2000年		2010年		2020年
土地利用类型	碳储量/10⁴ t	占比/%	碳储量/10⁴ t	占比/%	碳储量/10⁴ t	占比/%
耕地	43061.80	21.50	41581.34	20.37	43453.36	21.26
林地	3890.28	1.94	5057.20	2.48	4810.20	2.35
草地	122836.31	61.34	128079.17	62.74	128413.70	62.84
灌木地	2587.18	1.29	5720.85	2.80	5273.88	2.58
湿地	3082.94	1.54	2079.76	1.02	1643.09	0.80
水体	0.00	0.00	0.00	0.00	0	0.00
人造地表	1045.25	0.52	1289.40	0.63	2180.13	1.07
未利用地	23766.50	11.87	20336.85	9.96	18580.72	9.09
合计	200270.24	100.00	204144.57	100.00	204355.09	100.00

土地利用类型	自然发展情景		城镇发展情景		生态保护情景
土地利用类型	面积/km²	碳储量/10⁴ t	面积/km²	碳储量/10⁴ t	面积/km²	碳储量/10⁴ t
耕地	50136.80	43390.85	49966.10	44108.61	50203.40	43448.57
林地	2560.68	4315.64	2222.55	3745.77	3539.61	5965.48
草地	143516	131916.64	142836.00	131291.64	147541.00	135615.80
灌木地	7726.77	6442.84	7689.24	6411.54	6404.40	5340.20
湿地	490.77	1154.68	488.61	1149.60	491.76	1157.01
水体	1325.79	0.00	1318.05	0.00	1326.60	0.00
建设用地	8548.02	3007.19	8602.23	2604.10	7313.22	2572.79
未利用地	39513.20	15753.93	40695.20	16304.91	36998.60	14751.32