基于RWEQ模型的疏勒河流域防风固沙功能价值评估

doi:10.12118/j.issn.1000－6060.2023.333

干旱区地理 ›› 2024, Vol. 47 ›› Issue (1): 58-67.doi: 10.12118/j.issn.1000－6060.2023.333

基于RWEQ模型的疏勒河流域防风固沙功能价值评估

蔺阿荣¹(),周冬梅²,马静²,朱小燕²,江晶¹,张军^2,³()

1.甘肃农业大学管理学院，甘肃兰州 730070
2.甘肃农业大学资源与环境学院，甘肃兰州 730070
3.甘肃省节水农业工程技术研究中心，甘肃兰州 730070

收稿日期:2023-07-02 修回日期:2023-09-13 出版日期:2024-01-25 发布日期:2024-01-26
通讯作者: 张军（1977-），男，博士，教授，主要从事生态系统服务和土地资源管理等方面的研究. E-mail: zhangjun@gsau.edu.cn
作者简介:蔺阿荣（1999-），女，硕士研究生，主要从事生态系统服务方面的研究. E-mail: linarong2023@163.com
基金资助:
甘肃省科技厅重点研发计划-农业领域(23YFNA0036);甘肃省自然科学基金项目(21JR7RA811);甘肃省林业和草原科技创新计划(LCKJCX202205);国家重点研发项目课题(2022YFD1900203)

Evaluation of wind prevention and sand fixation function in Shule River Basin based on RWEQ model

LIN Arong¹(),ZHOU Dongmei²,MA Jing²,ZHU Xiaoyan²,JIANG Jing¹,ZHANG Jun^2,³()

1. College of Management, Gansu Agricultural University, Lanzhou 730070, Gansu, China
2. College of Resources and Environmental Science, Gansu Agricultural University, Lanzhou 730070, Gansu, China
3. Research Center for Water Saving Agriculture in Gansu Province, Lanzhou 730070, Gansu, China

Received:2023-07-02 Revised:2023-09-13 Online:2024-01-25 Published:2024-01-26

摘要/Abstract

摘要：

疏勒河流域地处西北内陆，是“一带一路”的关键节点。近年来随着全球变化与经济社会活动强度增加，导致建设用地快速扩张、土地沙化等问题，影响区域生态与经济社会的可持续发展。疏勒河流域处于北方防沙带中心，开展其防风固沙价值评估对于构建区域生态安全格局和保障流域可持续发展具有重要生态意义。基于修正风蚀方程模型（RWEQ）对2008—2018年疏勒河流域防风固沙功能及其价值进行评估。结果表明：（1） 2008—2018年疏勒河流域防风固沙总量为43.927×10⁴~129.530×10⁴ t·km^-2，防风固沙量呈上升趋势。（2） 2008—2018年疏勒河流域防风固沙价值快速增加，其多年平均价值占比由高到低依次为减少土地损失价值（99.46%）、保持土壤肥力价值（0.47%）、保持土壤有机质价值（0.04%）、减少交通运输经济损失价值（0.03%）。（3）流域防风固沙功能与土地利用密切相关，防风固沙能力较强的区域主要分布在草地、耕地等植被覆盖率较高区域；低值区主要分布在流域土地利用类型为未利用地区域。（4）相较社会因素，自然指标因子对流域防风固沙功能价值影响更大。研究结果可为确定流域生态补偿主客体及补偿标准提供依据。

关键词: 防风固沙服务, 修正的土壤风蚀方程（RWEQ）, 价值评估, 疏勒河流域

Abstract:

The Shule River Basin is located in the northwest inland region of China and is a key node of the Belt and Road Initiative. In recent years, with the increasing intensity of global changes and economic and social activities, problems, such as the rapid expansion of construction land and desertification have affected the sustainable development of regional ecology and economic society. The Shule River Basin is located at the center of the northern sand prevention belt of China, and an evaluation of its wind prevention and sand fixation value is of great ecological significance for building a regional ecological security pattern and ensuring sustainable development of the basin. On the basis of the revised wind erosion equation model, the value of wind prevention and sand fixation in the Shule River Basin from 2008 to 2018 was evaluated. The results are as follows: (1) The total amount of wind prevention and sand fixation in the Shule River Basin from 2008 to 2018 was 43.927×10⁴ to 129.530×10⁴ t·km⁻², with an increasing trend in wind prevention and sand fixation capacity. (2) The value of wind prevention and sand fixation in the Shule River Basin rapidly increased from 2008 to 2018, with an annual average value ranging from high to low to reduce the value of land loss (99.46%), maintain the value of soil fertility (0.47%), maintain the value of soil organic matter (0.04%), and reduce the value of economic loss of transportation (0.03%). (3) The function of wind prevention and sand fixation in river basins is closely related to land use. Among them, the areas with stronger windproof and sand-fixing capability are primarily distributed in grassland, cropland, and other areas with higher vegetation cover; the low-value areas are primarily distributed in unused land of the land use type of the river basin. (4) Natural indicator factors have a greater impact on the value of wind and sand fixation functions in river basins than social factors. These findings can provide a basis for determining the subject and object of ecological compensation and compensation standards in the Shule River Basin.

Key words: wind prevention and sand fixation services, revised wind erosion equation (RWEQ), value evaluation, Shule River Basin

蔺阿荣, 周冬梅, 马静, 朱小燕, 江晶, 张军. 基于RWEQ模型的疏勒河流域防风固沙功能价值评估[J]. 干旱区地理, 2024, 47(1): 58-67.

LIN Arong, ZHOU Dongmei, MA Jing, ZHU Xiaoyan, JIANG Jing, ZHANG Jun. Evaluation of wind prevention and sand fixation function in Shule River Basin based on RWEQ model[J]. Arid Land Geography, 2024, 47(1): 58-67.

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分类	指标	编号
自然因素	植被指数/%	X1
	年降水/mm	X2
	年均温度/℃	X3
	土壤湿度/%	X4
社会经济因素	人均GDP/元	X5
社会经济因素	人口密度/人·km^-2	X6

土地利用类型	2008年		2013年		2018年		2008—2018年
土地利用类型	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%	增减量/km²
耕地	1405.94	1.21	1744.23	1.50	1788.95	1.54	383.01
林地	2.54	0.00	2.56	0.00	2.66	0.00	0.12
草地	13600.37	11.70	15125.72	13.01	15088.86	12.98	1488.49
水域	573.78	0.49	481.83	0.41	423.28	0.36	-150.50
建设用地	7.63	0.01	8.27	0.01	9.23	0.01	1.60
未利用地	100637.66	86.59	98865.29	85.06	98914.89	85.10	-1722.77
湿地	0.03	0.00	0.04	0.00	0.08	0.00	0.05

年份	土地利用类型	面积/km²	防风固沙量/10⁴ t·km^-2	单位面积潜在防风固沙量/10⁴ t·km^-2	单位面积实际防风固沙量/10⁴ t·km^-2	单位面积防风固沙量/t·km^-2
2008	耕地	1405.94	1.84	0.18	0.18	13.08
	林地	2.54	0.02	0.44	0.43	68.90
	草地	13600.37	41.39	0.16	0.16	30.43
	湿地	0.03	0.00	0.05	0.05	4.74
	水域	573.78	0.68	0.13	0.13	11.85
	总计	15582.66	43.93	0.96	0.95	129.00
2013	耕地	1744.23	34.13	0.56	0.54	195.70
	林地	2.56	0.02	0.41	0.41	69.21
	草地	15125.72	68.29	0.23	0.22	45.15
	湿地	0.04	0.00	0.07	0.06	15.07
	水域	481.83	1.32	0.31	0.31	27.36
	总计	17354.38	103.76	1.58	1.54	352.49
2018	耕地	1788.95	33.13	0.54	0.52	185.22
	林地	2.66	0.02	0.42	0.42	77.25
	草地	15088.86	94.97	0.27	0.27	62.94
	湿地	0.08	0.00	0.07	0.07	12.73
	水域	423.28	1.41	0.37	0.37	33.21
	总计	17303.83	129.53	1.67	1.65	371.35

年份	减少土地损失价值	保持土壤肥力价值	保持土壤有机质价值	减少交通运输经济损失的价值	总价值
2008	737.538	3.520	0.293	0.208	741.559
2013	1747.065	8.339	0.693	0.493	1756.590
2018	2185.012	10.429	0.867	0.617	2196.925

成分	初始特征值			提取载荷平方和
成分	总计	方差百分比/%	累计贡献率/%	总计	方差百分比/%	累计贡献率/%
1	4.559	75.977	75.977	4.559	75.977	75.977
2	1.038	12.471	88.448	1.038	12.471	88.448
3	0.325	6.616	95.064
4	0.115	3.109	98.172
5	0.009	1.356	99.529
6	-0.045	0.471	100.000

基于RWEQ模型的疏勒河流域防风固沙功能价值评估

Evaluation of wind prevention and sand fixation function in Shule River Basin based on RWEQ model

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图/表 11

参考文献 40

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变量	主成分1	主成分2
X1	0.927	0.086
X2	0.855	-0.198
X3	0.766	0.582
X4	0.891	0.318
X5	0.849	-0.386
X6	0.931	-0.336

年份	F1	F2	F	排序
2008	-4.14	0.64	-3.07	11
2009	-3.01	0.89	-2.18	10
2010	-1.11	-0.63	-0.92	9
2011	-0.35	-0.75	-0.36	7
2012	-0.80	-1.29	-0.77	8
2013	0.62	-0.65	0.39	6
2014	0.78	-0.22	0.56	5
2015	1.57	0.73	1.29	4
2016	2.35	0.47	1.84	1
2017	1.99	0.47	1.57	3
2018	2.10	0.35	1.64	2

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