Spatio-temporal Variations in Soil Erosion and Its Economic Value of Soil Conservation in Henan Province

doi:10.16258/j.cnki.1674-5906.2024.05.007

Ecology and Environment ›› 2024, Vol. 33 ›› Issue (5): 730-744.DOI: 10.16258/j.cnki.1674-5906.2024.05.007

• Research Article [Ecology] • Previous Articles Next Articles

Spatio-temporal Variations in Soil Erosion and Its Economic Value of Soil Conservation in Henan Province

WANG Meinai¹^,²(), FAN Shunxiang³, SHU Hanjun⁴, ZHANG Jianjie¹, CHU Liqi¹, FA Yuqi¹^,^*()

1. School of Engineering Management and Real Estate/School of Agriculture and Rural Development, Henan University of Economics and Law, Zhengzhou 450046, P. R. China
2. Geophysical Zone Postdoctoral research station, Henan University, Kaifeng 475004, P. R. China
3. College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, P. R. China
4. Shanghai Land Consolidation and Rehabilitation Center, Shanghai 200003, P. R. China

Received:2023-12-12 Online:2024-05-18 Published:2024-06-27

河南省土壤侵蚀时空分异特征及土壤保持经济价值

王美娜¹^,²(), 范顺祥³, 舒翰俊⁴, 张建杰¹, 褚力其¹, 法玉琦¹^,^*()

1.河南财经政法大学工程管理与房地产学院/农业农村发展学院，河南郑州 450046
2.河南大学地理学博士后科研流动站，河南开封 475004
3.中国农业大学资源与环境学院，北京 100193
4.上海市建设用地和土地整理事务中心，上海 200003

通讯作者: * 法玉琦。E-mail: hncdfyq@huel.edu.cn
作者简介:王美娜（1992年生），女，讲师，博士，主要从事景观生态和土地利用等研究。E-mail: mnwang_eco@163.com
基金资助:
国家社会科学基金项目(21BJY186);教育部人文社会科学青年项目(23YJC790014);河南省软科学研究计划项目(222400410167);河南省高校人文社会科学研究资助性计划项目(2022-ZZJH-022)

Abstract

Abstract:

Mastering the spatio-temporal variations in soil erosion and its economic value is of great significance for the comprehensive management of river basins and the stable performance of soil conservation functions. Most existing studies tend to use the superposition of multi temporal soil erosion spatial distribution maps and equivalence method to explore the spatio-temporal pattern and economic value of soil erosion, but the spatial differentiation and dynamics of soil erosion were often overlooked. Taking Henan Province as an example, based on the RUSLE model, the parameter factors in the model were determined through data such as rainfall, soil particle composition, land use type, digital elevation, and remote sensing images to quantitatively analyze the spatio-temporal distribution characteristics of soil erosion in the region from 2000 to 2020. Exploratory Spatial Data Analysis (ESDA) and the geographical detector method were employed to explore hotspot areas of soil erosion and their driving factors. The economic value of soil conservation was assessed using the replacement cost method. The results show that: 1) the overall erosion area of moderate to mild and above in Henan Province showed a decreasing trend, reaching its lowest point in 2015. 2) The spatial distribution and evolution of soil erosion in Henan Province displayed an obvious spatial aggregation effect, with soil erosion intensity showing a positive spatial correlation (the global Moran’s I index ranged from 0.450 to 0.705). The area of the “high-high” aggregation zones has significantly decreased, and the aggregation trend has shown an overall weakening with slight expansion. The hotspots of soil erosion were primarily distributed in Anyang, Hebi, Jiyuan and Sanmenxia cities. 3) Rainfall and slope were primary environmental drivers affecting soil erosion, with single-factor q values ranging from 77.7% to 79.1% for rainfall and from 43.7% to 82.2% for slope, respectively. Areas with rainfall of 3.28×10²‒6.43×10² mm and steep slopes greater than 29.0° were high-risk areas for soil erosion. Vegetation coverage was found to have a significant inhibitory effect on the soil erosion process, with single-factor q values ranging from 16.1% to 19.4%, and the q values for the interaction of any two factors ranging from 40.0% to 83.9%. 4) The economic values of soil conservation were notably fluctuating, with values of 8.36×10⁹, 8.21×10⁹, 9.26×10⁹, 3.52×10⁹ and 7.17×10⁹ yuan from 2000 to 2020, respectively. The research results can provide theoretical reference and decision-making basis for improving soil conservation function and economic value by clarifying the current situation and driving factors of regional soil erosion.

Key words: soil and water loss, the middle and lower reaches of the Yellow River, erosion hotspots, environmental driving factors, geographical detector

摘要：

掌握土壤侵蚀时空变化特征及其经济价值对流域综合治理和土壤保持功能的稳定发挥具有重要意义。现有研究通常采用多时相土壤侵蚀空间分布图的叠加和当量法来探讨土壤侵蚀的时空格局及其经济价值，往往忽视了土壤侵蚀的空间分异性和动态性。以河南省为例，基于RUSLE模型，通过降雨、土壤颗粒组成、土地利用类型、数字高程和遥感影像等数据确定模型中的参数因子定量分析2000－2020年区域内的土壤侵蚀时空分布特征，同时结合探索性空间数据分析ESDA和地理探测器方法探讨土壤侵蚀热点区域及其驱动因素，并采用替代成本法评估土壤保持功能及其经济价值。结果表明：1）河南省中轻度及以上的侵蚀面积整体呈减少趋势，在2015年达到最低；2）土壤侵蚀的空间分布与演化具有明显聚集效应，土壤侵蚀强度在空间上呈正相关分布（全局Moran’s I指数介于0.450－0.705），“高-高”聚集区面积显著减小，聚集趋势表现为总体减弱且小幅扩散，土壤侵蚀热点区主要分布在安阳、鹤壁、济源和三门峡4个市域；3）降雨和坡度是主要影响土壤侵蚀的环境因素（单因素解释力q值：77.7%－79.1%和43.7%－82.2%），3.28×10²－6.43×10² mm的降雨量和大于29.0°的陡坡均是土壤侵蚀的高风险区域，而植被覆盖度对土壤侵蚀过程有较强的抑制效果（单因素解释力q值：16.1%－19.4%；交互作用解释力q值：40.0%－83.9%）；4）土壤保持经济价值波动明显，2000－2020年分别为8.36×10⁹、8.21×10⁹、9.26×10⁹、3.52×10⁹和7.17×10⁹元。研究结果通过明晰区域土壤侵蚀现状及其驱动因素，可为提高土壤保持功能及其经济价值提供理论参考和决策依据。

关键词: 水土流失, 黄河中下游, 侵蚀热点区, 环境驱动因素, 地理探测器

CLC Number:

WANG Meinai, FAN Shunxiang, SHU Hanjun, ZHANG Jianjie, CHU Liqi, FA Yuqi. Spatio-temporal Variations in Soil Erosion and Its Economic Value of Soil Conservation in Henan Province[J]. Ecology and Environment, 2024, 33(5): 730-744.

王美娜, 范顺祥, 舒翰俊, 张建杰, 褚力其, 法玉琦. 河南省土壤侵蚀时空分异特征及土壤保持经济价值[J]. 生态环境学报, 2024, 33(5): 730-744.

Figures/Tables 17

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数据	来源
河南省矢量边界	国家基础地理信息中心 (https://www.webmap.cn)
DEM (空间分辨率30 m)	地理空间数据云平台 (http://www.gscloud.cn)
降水数据 (2000、2005、2010、2015和2020年)	Climate AP模型中的年均降水数据
土壤颗粒组成 (空间分辨率30弧秒)	世界土壤数据库 (HWSD, Harmonized World Soil Database)
土地利用类型 (空间分辨率30 m)	CLCD数据集 (1990－2020年的长时间序列中国土地利用数据集)
归一化植被指数 (Normalized Difference Vegetation Index, NDVI) 数据 (2000、2005、2010、2015和2020年) (空间分辨率30 m)	国家生态数据中心资源共享服务平台 (http://www.nesdc.org.cn)

数据	来源
河南省矢量边界	国家基础地理信息中心 (https://www.webmap.cn)
DEM (空间分辨率30 m)	地理空间数据云平台 (http://www.gscloud.cn)
降水数据 (2000、2005、2010、2015和2020年)	Climate AP模型中的年均降水数据
土壤颗粒组成 (空间分辨率30弧秒)	世界土壤数据库 (HWSD, Harmonized World Soil Database)
土地利用类型 (空间分辨率30 m)	CLCD数据集 (1990－2020年的长时间序列中国土地利用数据集)
归一化植被指数 (Normalized Difference Vegetation Index, NDVI) 数据 (2000、2005、2010、2015和2020年) (空间分辨率30 m)	国家生态数据中心资源共享服务平台 (http://www.nesdc.org.cn)

土地利用类型	坡度/(°)	p值
耕地	0‒5	0.100
	5‒10	0.221
	10‒15	0.305
	15‒20	0.575
	20‒25	0.705
	>25	0.800
林地		1
草地		1
水域		0
建设用地		0
未利用地		1

土地利用类型	坡度/(°)	p值
耕地	0‒5	0.100
	5‒10	0.221
	10‒15	0.305
	15‒20	0.575
	20‒25	0.705
	>25	0.800
林地		1
草地		1
水域		0
建设用地		0
未利用地		1

地形类型	坡度
平原	<5°
缓坡	5°‒15°
斜坡	15°‒25°
陡坡	>25°

Spatio-temporal Variations in Soil Erosion and Its Economic Value of Soil Conservation in Henan Province

河南省土壤侵蚀时空分异特征及土壤保持经济价值

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土地利用一级分类	土地利用二级分类
耕地	平原耕地
	缓坡耕地
	斜坡耕地
	陡坡耕地
林地	平原林地
	缓坡林地
	斜坡林地
	陡坡林地
草地	平原草地
	缓坡草地
	斜坡草地
	陡坡草地
水域
未利用地
建筑用地

侵蚀等级	平均侵蚀模数/ (t·km⁻²·a⁻¹)	2000年		2005年		2010年		2015年		2020年
侵蚀等级	平均侵蚀模数/ (t·km⁻²·a⁻¹)	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%
微度侵蚀	<500	1.58×10⁵	96.6	1.63×10⁵	99.9	1.63×10⁵	99.6	1.63×10⁵	99.9	1.61×10⁵	98.8
轻度侵蚀	500‒2500	5.13×10³	3.14	1.42×10²	0.09	5.89×10²	0.36	49.0	0.03	1.57×10³	0.96
中度及以上侵蚀	>2500	4.24×10²	0.26	1.81	0.00	1.78×10¹	0.01	0.350	0.00	3.21×10²	0.02

年份	坡度/(°)	海拔/(10³m)	降雨量/mm
2000	29.0‒72.2	1.30‒2.38	464‒642
2005	29.0‒72.2	1.30‒2.38	464‒642
2010	29.0‒72.2	1.30‒2.38	369‒521
2015	29.0‒65.7	1.30‒2.38	328‒464
2020	29.0‒72.2	1.30‒2.38	387‒604

土地利用类型	2000年		2005年		2010年		2015年		2020年
土地利用类型	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%	侵蚀面积/km²	比例/%
平原耕地	1.07×10⁵	65.0	1.05×10⁵	64.0	1.05×10⁵	63.0	1.01×10⁵	61.4	9.93×10⁴	60.4
缓坡耕地	1.08×10⁴	6.59	1.05×10⁴	6.39	1.01×10⁴	6.13	9.76×10³	5.93	9.77×10³	5.94
斜坡耕地	2.25×10³	1.37	2.11×10³	1.29	2.03×10³	1.23	1.99×10³	1.21	2.09×10³	1.27
陡坡耕地	3.83×10²	0.230	3.75×10²	0.230	3.57×10²	0.220	3.57×10²	0.220	3.89×10²	0.240
耕地	1.20×10⁵	73.1	1.18×10⁵	71.9	1.16×10⁵	70.5	1.13×10⁵	68.8	1.11×10⁵	67.8
平原林地	3.06×10³	1.86	3.36×10³	2.04	3.45×10³	2.10	3.78×10³	2.30	3.78×10³	2.30
缓坡林地	1.04×10⁴	6.33	1.09×10⁴	6.64	1.11×10⁴	6.79	1.14×10⁴	6.96	1.17×10⁴	7.10
斜坡林地	9.52×10³	5.79	9.73×10³	5.92	9.75×10³	5.93	9.82×10³	5.97	9.94×10³	6.04
陡坡林地	3.97×10³	2.41	3.99×10³	2.42	3.98×10³	2.42	4.00×10³	2.44	4.03×10³	2.45
林地	2.70×10⁴	16.4	2.80×10⁴	17.0	2.84×10⁴	17.2	2.91×10⁴	17.7	2.94×10⁴	17.9
平原草地	7.31×10²	0.440	6.20×10²	0.380	5.77×10²	0.350	4.95×10²	0.300	4.15×10²	0.250
缓坡草地	1.45×10³	0.880	1.24×10³	0.750	1.30×10³	0.790	1.26×10³	0.760	9.28×10²	0.560
斜坡草地	8.08×10²	0.490	7.14×10²	0.430	7.53×10²	0.460	7.13×10²	0.430	4.85×10²	0.300
陡坡草地	2.10×10²	0.130	1.95×10²	0.120	2.08×10²	0.130	1.82×10²	0.110	1.29×10²	0.08
草地	3.20×10³	1.95	2.77×10³	1.68	2.84×10³	1.73	2.65	1.61	1.96×10³	1.19
水域	1.42×10³	0.870	1.72×10³	1.05	1.76×10³	1.07	1.78×10³	1.08	1.90×10³	1.15
未利用地	4.33	0.00	2.00	0.00	2.00	0.00	1.00	0.00	1.00	0.00
建筑用地	1.26×10⁴	7.65	1.38×10⁴	8.40	1.55×10⁴	9.43	1.79×10⁴	10.9	1.96×10⁴	11.9

年份	指标核算/(10⁹元)
年份	V_s	V_n	V_p	V_np	V_sc
2000	3.45	2.54	2.37	4.91	8.36
2005	3.38	2.50	2.33	4.83	8.21
2010	3.82	2.82	2.63	5.44	9.26
2015	1.45	1.07	1.00	2.07	3.52
2020	2.96	2.18	2.04	4.22	7.17

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