Spatial and Temporal Variability of Carbon Stocks in Different Land-use Types in the Yiluo River Basin in the Middle Section of the Yellow River from 1990 to 2050

doi:10.19657/j.geoscience.1000-8527.2024.035

Abstract

Abstract:

The change of land-use type is the key influence factor of regional carbon stocks, which significantly affects the whole terrestrial ecosystem. Taking the Yiluo River Basin in the middle section of the Yellow River as an study case, we assessed the spatial and temporal variations and influence factors of carbon stocks based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model during 1990—2020. We predicted the land-use types and carbon stock using the coupled PLUS model for the period of 2025-2050. A geoprobe was used to explore the regional carbon stock driving factor. The results show that (1) the land-use types in the Yiluo River Basin shifted to transferring-out with cropland and grassland, and transferring-in with forest land, water-body, and construction land. The regional carbon stock increased by 1.0×10⁷ t from 1990 to 2020, with a continuous drop of carbon stock in the east and a continuous increase in the central and western areas. (2) The predicted overall regional carbon sequestration capacity decreases from 2025 to 2050. Comparing with the historical period, the carbon sequestration capacity in the east continues to decline and the carbon sequestration capacity in the central and western areas changes from a continuous increasing to a trend of overall increasing. the environmental restoration scenario is the most favorable to regional carbon sequestration, while the cultivated land protection scenario is the most unfavorable. (3) The geoprobe results indicate that the q-value (explanatory power) of Normalized Vegetation Index (NDVI) in the one-way analysis is 0.561, which has the strongest explanatory power. The q-value of Digital Elevation Model interacting with NDVI in the analysis is 0.592, showing a stronger explanatory power. It is recommended that the economic and agricultural development in the regions with a better economy and flat region (IV12-1) should emphasize the protection of nature. The regions with a better ecology and high altitude (VI22-1 and VI22-3) is recommended to mainly implement the ecological restoration strategy.

Key words: InVEST model, PLUS model, carbon stock, GeoDetector, Mann-Kendall’s test

CLC Number:

P962

YUAN Jianglong, LIU Xiaohuang, LI Hongyu, XING Liyuan, LUO Xinping, WANG Ran, WANG Chao, ZHAO Honghui. Spatial and Temporal Variability of Carbon Stocks in Different Land-use Types in the Yiluo River Basin in the Middle Section of the Yellow River from 1990 to 2050[J]. Geoscience, 2024, 38(03): 559-573.

Figures/Tables 19

References 67

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数据名称	数据描述	数据来源
DEM	ASTER GDEM 30M分辨率数字高程模型	地理空间数据云(https://www.gscloud.cn/)
土地利用数据	武汉大学 CLCD 30M分辨率数据	Zenodo网站(https://zenodo.org/record/5816591)
土壤属性数据	HWSD世界土壤数据库	粮农组织土壤门户网站(FAO SOILS PORTAL)
NDVI(MYD13Q1) GPP(MYD17A2H) NPP(MOD173AH)	MoDIS 500M分辨率产品	NASA地球数据(EARTHDATA)
降水(Rain) 温度(Tmp) 蒸散量(ET)	ERA5 500M分辨率数据	GEE数据网站(https://developers.google.com/earth-engine/datasets)
未来气温和降水数据	CMIP6数据集	WCRP CMIP6(https://esgf.nci.org.au/projects/cmip6-nci/)
经济(GDP)、人口数据 (POP)	1km 分辨率栅格数据	资源环境科学与数据中心(https://www.resdc.cn/)
路网等矢量数据(铁路、 GS和XY)	矢量数据	全国地理信息资源目录服务系统(https://www.webmap.cn/main.do?method=index)

数据名称	数据描述	数据来源
DEM	ASTER GDEM 30M分辨率数字高程模型	地理空间数据云(https://www.gscloud.cn/)
土地利用数据	武汉大学 CLCD 30M分辨率数据	Zenodo网站(https://zenodo.org/record/5816591)
土壤属性数据	HWSD世界土壤数据库	粮农组织土壤门户网站(FAO SOILS PORTAL)
NDVI(MYD13Q1) GPP(MYD17A2H) NPP(MOD173AH)	MoDIS 500M分辨率产品	NASA地球数据(EARTHDATA)
降水(Rain) 温度(Tmp) 蒸散量(ET)	ERA5 500M分辨率数据	GEE数据网站(https://developers.google.com/earth-engine/datasets)
未来气温和降水数据	CMIP6数据集	WCRP CMIP6(https://esgf.nci.org.au/projects/cmip6-nci/)
经济(GDP)、人口数据 (POP)	1km 分辨率栅格数据	资源环境科学与数据中心(https://www.resdc.cn/)
路网等矢量数据(铁路、 GS和XY)	矢量数据	全国地理信息资源目录服务系统(https://www.webmap.cn/main.do?method=index)

土地利用类型	碳密度 (t/hm²)
土地利用类型	C_above	C_below	C_soil	C_dead
耕地	16.15	3.20	82.50	0
林地	67.45	30.25	120.98	13
草地	2.83	23.52	121.83	2
水体	3.20	0.64	71.77	0
荒地	0.96	0.99	60.00	0
建设用地	1.20	0	0	0

土地利用类型	碳密度 (t/hm²)
土地利用类型	C_above	C_below	C_soil	C_dead
耕地	16.15	3.20	82.50	0
林地	67.45	30.25	120.98	13
草地	2.83	23.52	121.83	2
水体	3.20	0.64	71.77	0
荒地	0.96	0.99	60.00	0
建设用地	1.20	0	0	0

年份	不同土地利用类型面积(km²)
年份	耕地	林地	草地	水体	荒地	建设用地
1990	9118.46	7722.35	1468.90	68.86	0.15	502.27
1995	9118.43	7722.34	1468.90	68.86	0.15	502.27
2000	9230.22	7651.91	1306.08	61.68	0.09	631.00
2005	8899.65	7885.56	1229.26	66.94	0.08	799.52
2010	8831.66	8025.89	1037.01	84.99	0.06	901.36
2015	8474.11	8056.20	1185.06	91.22	0.06	1074.33
2020	8150.06	8314.50	1044.95	98.58	0.16	1272.74
变化幅度 (%)	-10.62	7.67	-28.86	43.16	2.40	153.40