基于VORS模型的黄河流域生态系统健康评估与预测

doi:10.16258/j.cnki.1674-5906.2024.10.013

生态环境学报 ›› 2024, Vol. 33 ›› Issue (10): 1612-1623.DOI: 10.16258/j.cnki.1674-5906.2024.10.013

• 研究论文【环境科学】 • 上一篇下一篇

基于VORS模型的黄河流域生态系统健康评估与预测

许静^*(), 王德仁

兰州财经大学经济学院，甘肃兰州 730101

收稿日期:2024-06-03 出版日期:2024-10-18 发布日期:2024-11-15
作者简介:*许静（1983年生），女，教授，博士，研究方向为生态经济学。E-mail: xujing@lzufe.edu.cn.
基金资助:
国家社科基金项目(23BJY198)

Assessment and Prediction of Ecosystem Health in the Yellow River Basin Based on the VORS Model

XU Jing^*(), WANG Deren

School of Economics, Lanzhou University of Finance and Economics, Lanzhou 730101, P. R. China

Received:2024-06-03 Online:2024-10-18 Published:2024-11-15

摘要/Abstract

摘要：

黄河流域水资源短缺、水土流失严重、生态本底脆弱，科学评估黄河流域生态系统健康对于防范和化解流域生态风险，保障黄河安澜，促进流域生态保护和高质量发展具有重要意义。以黄河流域为研究区，构建活力－组织力－弹力－服务（VORS）评估框架，探讨2000－2020年生态系统健康时空分异，并耦合GMOP与PLUS模型预测2030年多情景下生态系统健康动态演变。结果表明：2000、2010和2020年，黄河流域生态系统活力均值分别为0.435、0.437和0.436，整体较为稳定，呈西高东低的空间分布特征；生态系统组织力指数均值分别为0.593、0.603和0.629，呈中部向四周递减的特征；生态系统弹力指数均值分别为0.507、0.511和0.505，东部低，其余地区较高；生态系统服务指数均值分别为0.402、0.398和0.390，呈由北向南递增的趋势；生态系统健康指数分别为0.419、0.423和0.425，呈中部高、东部低的空间分布特征。2030年，各情景下活力、弹力和生态系统服务无显著差异，而生态保护（EP）和综合发展（CD）情景下组织力显著提高。2030年，各情景下生态系统健康空间分布均呈中部较高，东、西南部较低的特征，但EP和CD情景下生态系统健康水平略高于自然发展（ND）和经济发展（ED）情景，且CD情景下生态系统健康I级城市数量最多，因此CD情景可以在满足经济发展需求的前提下确保生态系统健康水平最高，为相对优选情景。该研究以VORS为基础，耦合GMOP-PLUS模型测度黄河流域生态系统健康水平，研究结果可以为流域生态系统科学管理、协同流域经济发展与生态保护提供决策依据。

关键词: 生态系统健康, 活力－组织力－弹力－服务, VORS模型, 生态系统服务, GMOP-PLUS模型, 黄河流域

Abstract:

The Yellow River Basin is characterized by a shortage of water resources, serious soil erosion, and fragile ecological fundamentals. A scientific assessment of the ecosystem health of the Yellow River Basin is of great significance for preventing and resolving ecological risks, ensuring the safety of the Yellow River, and promoting ecological protection and high-quality development in the basin. Using the Yellow River Basin as the study area, the Vigor-Organization-Resilience-Services assessment framework was constructed to discuss the spatiotemporal differentiation of ecosystem health from 2000 to 2020 and couple the GMOP and PLUS models to predict the dynamic evolution of ecosystem health under multiple scenarios in 2030. The results showed that, in 2000, 2010 and 2020, the average values of ecosystem vigor index in the Yellow River Basin were 0.435, 0.437 and 0.436 respectively, which were relatively stable overall, showing the spatial distribution pattern of high in the west and low in the east; the average value of ecosystem organization index were 0.593, 0.603 and 0.629 respectively, showing a decreasing trend from the middle to the surrounding areas; the average value of ecosystem resilience index were 0.507, 0.511 and 0.505 respectively, with lower values in the eastern region and higher values in other areas; the average value of ecosystem services index were 0.402, 0.398 and 0.390 respectively, with an increasing trend from north to south; the ecosystem health indexes were 0.419, 0.423 and 0.425 respectively, with a spatial distribution characteristic of high in the center and low in the east. In 2030, under all scenarios, there were no significant differences in vitality, resilience, and ecosystem services, whereas organizational strength significantly increased under the Ecological Protection (EP) and Comprehensive Development (CD) scenarios. In 2030, the spatial distribution of ecosystem health under all scenarios is generally higher in the central region and lower in the eastern and southwestern regions. However, under the EP and CD scenarios, the level of ecosystem health was slightly higher than that under the Natural Development (ND) and Economic Development (ED) scenarios, and under the CD scenario, the number of Grade I cities with high ecosystem health was the highest. Therefore, the CD scenario ensured the highest level of ecosystem health while meeting the needs of economic development, making it a relatively optimal scenario. In this study, the ecosystem health level of the Yellow River Basin was measured using the coupled GMOP-PLUS model based on VORS, which can provide a decision-making basis for the scientific management of the basin ecosystem as well as the synergy between the economic development and ecological protection of the basin.

Key words: ecosystem health, vigor-organization-resilience-services, VORS model, GMOP-PLUS model, ecosystem services, the Yellow River Basin

中图分类号:

X821

许静, 王德仁. 基于VORS模型的黄河流域生态系统健康评估与预测[J]. 生态环境学报, 2024, 33(10): 1612-1623.

XU Jing, WANG Deren. Assessment and Prediction of Ecosystem Health in the Yellow River Basin Based on the VORS Model[J]. Ecology and Environment, 2024, 33(10): 1612-1623.

图/表 13

图1 研究区区位底图采用自然资源部标准地图制作，审图号为GS（2022）4318号，对底图边界无修改，下同

Figure 1 Location of the study area

表1 各土地利用类型的恢复力和抵抗力系数

Table 1 Resilience and resistance coefficients for each land-use type

土地利用类型	耕地	林地	草地	水体	建设用地	未利用地
恢复力系数	0.5	1	0.7	0.8	0.3	0.2
抵抗力系数	0.3	0.6	0.8	0.7	0.2	0.1

表2 生态系统服务评估方法

Table 2 Methods for assessing ecosystem services

生态系统服务类型	生态系统服务	计算方法
供给服务	食物供给	$G i = I NDV, i I NDV, sum × G sum$ 式中：G_i为栅格i的食物产量；I_NDV,_i为栅格i的NDVI值；I_{NDV, sum}为草地、耕地的NDVI总值；G_sum为食物总产量，包括粮食、肉类和和奶类
调节服务	产水量	$Y i = 1 − A ET, i P i P i$ 式中：A_ET,_i为栅格i的实际蒸散量，P_i为栅格i的年均降水量
	水质净化	X_exporti=l_surf,_i×N_surf,_i +l_subs,_i×N_subs,_i 式中：X_exporti为营养物质输送量；l_surf,_i与l_subs,_i分别为栅格i的地表与地下营养物质负荷量；N_surf,_i和N_subs,_i分别为栅格i的地表与地下营养物质输送速率
	碳储存	C_total=C_above+C_below+C_soil+C_dead 式中：C_total为总碳储量；C_above为地表碳储量；C_below为地下碳储量；C_soil为土壤碳储量；C_dead为死亡有机物碳储量
支持服务	土壤保持	U_i =R_i∙K_i∙F_ls,_i∙(1−C_iP_i) 式中：U_i为栅格i的土壤保持量；R_i为降雨侵蚀因子；K_i为土壤可蚀性因子；F_ls,_i为坡长和坡度因子；C_i和P_i分别为植被覆盖管理因子与土壤保持管理因子

表2 生态系统服务评估方法

Table 2 Methods for assessing ecosystem services

生态系统服务类型	生态系统服务	计算方法
供给服务	食物供给	$G i = I NDV, i I NDV, sum × G sum$ 式中：G_i为栅格i的食物产量；I_NDV,_i为栅格i的NDVI值；I_{NDV, sum}为草地、耕地的NDVI总值；G_sum为食物总产量，包括粮食、肉类和和奶类
调节服务	产水量	$Y i = 1 − A ET, i P i P i$ 式中：A_ET,_i为栅格i的实际蒸散量，P_i为栅格i的年均降水量
	水质净化	X_exporti=l_surf,_i×N_surf,_i +l_subs,_i×N_subs,_i 式中：X_exporti为营养物质输送量；l_surf,_i与l_subs,_i分别为栅格i的地表与地下营养物质负荷量；N_surf,_i和N_subs,_i分别为栅格i的地表与地下营养物质输送速率
	碳储存	C_total=C_above+C_below+C_soil+C_dead 式中：C_total为总碳储量；C_above为地表碳储量；C_below为地下碳储量；C_soil为土壤碳储量；C_dead为死亡有机物碳储量
支持服务	土壤保持	U_i =R_i∙K_i∙F_ls,_i∙(1−C_iP_i) 式中：U_i为栅格i的土壤保持量；R_i为降雨侵蚀因子；K_i为土壤可蚀性因子；F_ls,_i为坡长和坡度因子；C_i和P_i分别为植被覆盖管理因子与土壤保持管理因子

表3 2030年黄河流域各土地利用类型价值系数

Table 3 Value coefficients of different land use types in the Yellow River Basin in 2030 106 yuan?km?2

土地利用类型	耕地	林地	草地	水体	建设用地	未利用地
生态价值系数	0.72	4.14	3.55	22.6	0	0.19
经济价值系数	0.86	0.04	0.34	0.09	15.1	0

表4 情景预测的约束条件

Table 4 Constraints on Scenario Prediction

约束条件	约束表达式	约束条件表示
生态价值	$∑ k = 1 6 x k B k ≥ ∑ k = 1 6 w k B k$	各优化情景下流域生态价值高于ND情景
经济价值	$∑ k = 1 6 x k A k ≥ ∑ k = 1 6 w k A k$	各优化情景下流域经济价值高于ND情景
研究区总面积	$∑ k = 1 6 x k = 1 168027$	各情景下土地利用总面积等于研究区面积
耕地面积	x₁>w₁	耕地面积保持动态平衡, 且不低于现状面积
建设用地	x₅<70\|107	建设用地面积不超过《城镇开发边界划定指南(试行)》的规划值
植被覆盖	0.46x₁+x₂+0.49x₃≥0.46w₁+w₂+0.49w₃	各优化情景下的植被覆盖度不低于ND情景
景观多样性	x₂+x₃+x₄≥w₂+w₃+w₄	各优化情景下林地、草地、水域的总面积不低于自然发展情景
模型精度	0.8w_k£x_k£1.2w_k	优化情景下各类用地面积以ND情景为基准, 浮动范围20%

表4 情景预测的约束条件

Table 4 Constraints on Scenario Prediction

约束条件	约束表达式	约束条件表示
生态价值	$∑ k = 1 6 x k B k ≥ ∑ k = 1 6 w k B k$	各优化情景下流域生态价值高于ND情景
经济价值	$∑ k = 1 6 x k A k ≥ ∑ k = 1 6 w k A k$	各优化情景下流域经济价值高于ND情景
研究区总面积	$∑ k = 1 6 x k = 1 168027$	各情景下土地利用总面积等于研究区面积
耕地面积	x₁>w₁	耕地面积保持动态平衡, 且不低于现状面积
建设用地	x₅<70\|107	建设用地面积不超过《城镇开发边界划定指南(试行)》的规划值
植被覆盖	0.46x₁+x₂+0.49x₃≥0.46w₁+w₂+0.49w₃	各优化情景下的植被覆盖度不低于ND情景
景观多样性	x₂+x₃+x₄≥w₂+w₃+w₄	各优化情景下林地、草地、水域的总面积不低于自然发展情景
模型精度	0.8w_k£x_k£1.2w_k	优化情景下各类用地面积以ND情景为基准, 浮动范围20%

图2 2000－2020年黄河流域土地利用类型分布

Figure 2 Distribution of land use types in the Yellow River Basin from 2000 to 2020

表5 2000－2020年各土地利用类型面积变化

Table 5 Changes in area of various land use types from 2000 to 2020 104 km2

土地利用类型	2000年面积	2000‒2010年变化面积	2010‒2020年变化面积
耕地	26.6	−0.593	−0.707
林地	11.1	0.888	0.192
草地	32.4	−0.309	−0.987
水体	1.29	0.163	0.127
建设用地	1.87	0.345	1.455
未利用地	6.22	−0.493	−0.079

图3 2000－2020年黄河流域土地利用类型转移

Figure 3 Transfer of land use types in the Yellow River Basin from 2000 to 2020

图4 2030年不同发展情景下黄河流域土地利用预测

Figure 4 Projections of land use in the Yellow River Basin under different scenarios in 2030

图5 2000－2020年黄河流域VORS水平分布

Figure 5 Distribution of VORS levels in the Yellow River Basin from 2000 to 2020

图6 2000－2020年黄河流域生态系统健康等级分布

Figure 6 Distribution of ecosystem health level in the Yellow River Basin from 2000 to 2020

图7 不同发展情景下黄河流域生态系统健康VORS水平分布

Figure 7 Distribution of VORS levels in the Yellow River Basin under different development scenarios

图8 2030年各发展情景下黄河流域生态系统健康预测

Figure 8 Projections of ecosystem health in the Yellow River Basin under different scenarios in 2030

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基于VORS模型的黄河流域生态系统健康评估与预测

Assessment and Prediction of Ecosystem Health in the Yellow River Basin Based on the VORS Model

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