Jing-tao Shi; Ge Gao; Jun-jian Liu; Yu-ge Jiang; Bo Li; Xiao-yan Hao; Jun-chao Zhang; Zhao-yi Li; Huan Sun

doi:10.26599/JGSE.2025.9280050

doi: 10.26599/JGSE.2025.9280050

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出版历程
- 收稿日期: 2024-10-16
- 录用日期: 2025-04-12
- 网络出版日期: 2025-06-27
- 刊出日期: 2025-08-08

Ecological vulnerability assessment and driving force analysis of small watersheds in Hilly Regions using sensitivity-resilience-pressure modeling

1.
Langfang Natural Resources Comprehensive Survey Center, China Geological Survey, Langfang 065000, Hebei Province, China
2.
Pingquan City Department of Natural Resources and Planning, Pingquan 067500, Hebei Province, China
3.
Pingquan soil and water Conservation Construction Service Center, Pingquan 067500, Hebei Province, China
4.
Chinese Academy of Geological Sciences, Beijing 100037, China

More Information

Corresponding author: liujunjian@mail.cgs.gov.cn

摘要

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Abstract: Pingquan City, the origin of five rivers, serves as the core water conservation zone for the Beijing-Tianjin-Hebei region and exemplifies the characteristics of small watersheds in hilly areas. In recent years, excessive mining and intensified human activities have severely disrupted the local ecosystem, creating an urgent need for ecological vulnerability assessment to enhance water conservation functions. This study employed the sensitivity-resilience-pressure model, integrating various data sources, including regional background, hydro-meteorological data, field investigations, remote sensing analysis, and socio-economic data. The weights of the model indices were determined using an entropy weighting model that combines principal component analysis and the analytic hierarchy process. Using the ArcGIS platform, the spatial distribution and driving forces of ecological vulnerability in 2020 were analyzed, providing valuable insights for regional ecological restoration. The results indicated that the overall Ecological Vulnerability Index (EVI) was 0.389, signifying moderate ecological vulnerability, with significant variation between watersheds. The Daling River Basin had a high EVI, with ecological vulnerability primarily in levels IV and V, indicating high ecological pressure, whereas the Laoniu River Basin had a low EVI, reflecting minimal ecological pressure. Soil type was identified as the primary driving factor, followed by elevation, temperature, and soil erosion as secondary factors. It is recommended to focus on key regions and critical factors while conducting comprehensive monitoring and assessment to ensure the long-term success of ecological management efforts.
- Beijing-Tianjin-Hebei water conservation zone /
- Spatital analysis /
- SRP model /
- GIS /
- Watershed variation

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Figure 1. Location and geologic map of the study area (B1: Cascade River Basin; B2: Laoha River Basin; B3: Daling River Basin; B4: Qinglong River Basin; B5: Laoniu River Basin)

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Figure 2. Single-indicator evaluation map of ecological-geological vulnerability in Pingquan City

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Figure 3. Ecological vulnerability assessment of Pingquan City (a: Ecological sensitivity assessment; b: Ecological resilience assessment; c: Ecological pressure assessment; d: Ecological Vulnerability Assessment)

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Figure 4. Mean EVI values (a) and area ratios of EVI to each element (b) for different watershed districts in the Pingquan area

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Figure 5. Interaction detector results for the Pingquan area

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Table 1. Evaluation index system of SRP model for ecological vulnerability in Pingquan area

Target level	Factor layer	Indicator layer	Relationship type
Ecological vulnerability	Ecological sensitivity	Geo-construction (X1)	Proactively
		Elevation (X2)	Proactively
		Altitude (X3)	Proactively
		Annual rainfall (X4)	Pessimistic
		Average annual temperature (X5)	Pessimistic
		Dryness index (X6)	Pessimistic
		Vegetation cover (X7)	Pessimistic
		Soil erosion factor (X8)	Proactively
		Landscape fragmentation (X9)	Proactively
	Ecological resilience	Vegetation NPP (X10)	Pessimistic
		Soil type (X11)	Proactively
		Soil nutrient synthesis (X12)	Pessimistic
		Ecological richness (X13)	Pessimistic
	Ecological pressure	Population density (X14)	Proactively
		GDP (X15)	Proactively
		Food crop production (X16)	Proactively
		Gross output value of agriculture, forestry, livestock and fisheries (X17)	Proactively

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Table 2. Soil N, P, K composite nutrient index division

Indicator	K_i	100	90	70	50	30
N	(g/kg)	＞2	＞1.5–2	＞1–1.5	＞0.75–1	≤0.75
P		＞1	＞0.8–1	＞0.6–0.8	＞0.4–0.6	≤0.4
K		＞25	＞20–25	＞15–20	＞10–15	≤10

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Table 3. Grading criteria for ecological vulnerability assessment in Pingquan City

Factor	Indicator	Very low vulnerability	Low vulnerability	Moderate vulnerability	High vulnerability	Very high vulnerability	Grading standard
Ecological sensitivity	X1	Quaternary terrestrial loose accumulation formation	Jurassic-Cretaceous medium-acidic ejecta formation; Precambrian medium-acidic rock formation	Precambrian basement rock formation; Precambrian regional metamorphic rock formation; Precambrian contact metamorphic rock formation	Triassic-Cretaceous terrestrial clastic formation; Jurassic-Cretaceous volcanic clastic formation; Sinian-Permian sandy clastic formation; Sinian-Carboniferous argillaceous clastic formation	Sinian-Permian marine carbonate rock formation	Field survey validation
	X2 (°)	＜2	[2,6)	[6,15)	[15,25)	≥25	TD/T1055-2019
	X3 (m)	＜595	[595,741)	[741,909)	[909,1152)	≥1152	Natural breakpoint method
	X4 (mm)	＞582	(528,582]	(478,528]	(432,478]	≤432	Natural breakpoint method
	X5 (°C)	＞9.2	(8.6,9.2]	(7.8,8.6]	(6.5,7.8]	≤6.5	Natural breakpoint method
	X6	＞30.7	(28.2,30.7]	(26.1,28.2]	(23.3,26.1]	≤23.3	Natural breakpoint method
	X7	＞0.91	(0.72,0.91]	(0.49,0.72]	(0.18,0.49]	≤0.18	Natural breakpoint method
	X8	＜0.03052	[0.03052,0.03068)	[0.03068,0.03085)	[0.03085,0.03110)	≥0.03110	Natural breakpoint method
	X9	＜23.28	[23.28,48.46)	[48.46,82.89)	[82.89,164.67)	≥164.67	Natural breakpoint method
Ecological resilience	X10	＞557.6	(486.8,557.6]	(430.4,486.8]	(214.2,430.4]	≤214.2	Natural breakpoint method
	X11		Brown soil	Cinnamon soil	Damp soil	Coarse aggregate soil	Field survey validation
	X12	(96.6,100]	(91.8,96.6]	(87.3,91.8]	[80,87.3]	＜80	Natural breakpoint method
	X13	＞86.55	(76.66,86.55]	(68.63,76.66]	(53.13,68.63]	≤53.13	Natural breakpoint method
Ecological pressure	X14 (persons/km²)	＜83	[83,124)	[124,141)	[141,169)	≥169	Natural breakpoint method
	X15 (million/km²)	＜336	[336,374)	[374,444)	[444,727)	≥727	Natural breakpoint method
	X16/t	＜1283	[1283,8022)	[8022,12963)	[12963,19230)	≥19230	Natural breakpoint method
	X17/million	＜9326	[9326,19168)	[19168,28566)	[28566,38376)	≥38376	Natural breakpoint method

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Table 4. The load of each index factor in the study area

Typology	F1	F2	F3	Typology	F1	F2	F3	Typology	F1	F2	F3
Sensitivity	−0.070	−0.027	0.997	Resilience	0.926	0.369	0.075	Pressure	−0.370	0.929	−0.001
X1	0.846	−0.453	−0.014	X10	0.045	−0.011	−0.043	X14	−0.024	0.983	−0.167
X2	0.111	−0.093	−0.213	X11	0.988	−0.147	0.009	X15	0.015	0.089	0.071
X3	−0.081	−0.174	−0.459	X12	−0.007	−0.002	0.999	X16	0.653	0.136	0.741
X4	0.406	0.637	0.028	X13	0.147	0.989	0.002	X17	0.757	−0.088	−0.646
X5	0.121	0.155	0.455
X6	0.278	0.455	−0.214
X7	0.065	−0.050	−0.136
X8	0.039	−0.296	0.570
X9	0.057	−0.169	−0.383
Eigenvalue	0.073	0.046	0.035	Eigenvalue	0.118	0.036	0.012	Eigenvalue	0.064	0.031	0.006
Variance/%	36.13	22.663	17.52	Variance/%	69.45	21.169	7.027	Variance/%	61.343	30.180	5.790

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Table 5. Judgement matrix for evaluation of ecological sensitivity indicators in Pingquan City

Typology	X1	X2	X3	X4	X5	X6	X7	X8	X9
X1	1
X2	1/8	1
X3	1/8	1	1
X4	1/8	1/4	1/4	1
X5	1/8	1/2	1/2	1/2	1
X6	1/9	1/2	1/3	1	1	1
X7	1/2	1	1/2	1/2	1/4	1/3	1
X8	1	1/6	1/6	1/6	1/6	1/6	1/6	1
X9	1/2	1/2	1/6	1/8	1/8	1/6	1/4	1/8	1

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Table 6. Judgement matrix for evaluation of ecological resilience indicators in Pingquan City

Typology	X10	X11	X12	X13
X10	1
X11	1/4	1
X12	1/2	1/2	1
X13	1	1/4	1/2	1

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Table 7. Judgement matrix for evaluation of ecological pressure indicators in Pingquan City

Typology	X14	X15	X16	X17
X14	1
X15	1	1
X16	1/4	1/2	1
X17	1/4	1/2	1/6	1

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Table 8. Weights of ecological vulnerability evaluation indicators in Pingquan City (w_j is the comprehensive weight; w_1j is the weight calculated by PCA; w_2j is the weight obtained by AHP)

Typology	W_1j	W_2j	W_j	Typology	W_1j	W_2j	W_j
Ecological sensitivity	0.197	0.655	0.416	Ecological resilience	0.690	0.211	0.442
Geo-construction (X1)	0.1	0.349	0.216	Vegetation NPP (X10)	0.098	0.387	0.21
Elevation (X2)	0.051	0.101	0.083	Soil type (X11)	0.425	0.282	0.373
Altitude (X3)	0.001	0.125	0.013	Soil nutrient synthesis (X12)	0.15	0.175	0.174
Annual rainfall (X4)	0.215	0.086	0.157	Ecological richness (X13)	0.327	0.156	0.243
Average annual temperature (X5)	0.152	0.095	0.139	Ecological pressure	0.113	0.134	0.142
Dryness index (X6)	0.157	0.085	0.134	Population density (X14)	0.252	0.4	0.335
Vegetation cover (X7)	0.08	0.07	0.087	GDP (X15)	0.13	0.291	0.205
Soil erosion factor (X8)	0.163	0.061	0.115	Food crop production (X16)	0.405	0.217	0.313
Landscape fragmentation (X9)	0.081	0.028	0.055	Gross output value of agriculture, forestry, livestock and fisheries (X17)	0.213	0.092	0.148

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Table 9. Area ratio of different vulnerability classes of EVI in Pingquan City

Typology	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ
Area (km²)	500.91	783.60	680.92	755.50	433.36
Area ratio (%)	16	25	21	24	14

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Table 10. Ratio of EVI to area of each element in different watersheds in Pingquan region

Basin	Ecological Vulnerability (%)					Ecological sensitivity (%)
Basin	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ
B1	20.29	34.34	23.10	11.55	10.72	23.80	22.42	38.41	15.26	0.11
B2	5.80	22.60	17.68	39.38	14.53	0.01	24.40	43.94	26.58	5.08
B3	0.00	10.71	29.81	29.85	29.63	0.00	0.21	18.34	34.16	47.29
B4	11.80	31.85	26.96	17.04	12.36	16.41	32.46	21.68	28.93	0.53
B5	56.60	3.87	8.21	31.27	0.06	6.80	14.71	53.01	25.49	0.00
Basin	Ecological resilience (%)					Ecological pressure (%)
Basin	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ
B1	7.88	36.41	21.43	13.16	21.12	9.64	27.30	21.91	39.40	1.75
B2	3.05	18.79	16.65	21.26	40.26	35.18	41.42	22.70	0.62	0.09
B3	0.97	57.91	4.43	2.46	34.22	0.00	0.18	39.82	0.08	59.92
B4	0.00	38.62	33.13	0.22	28.03	0.00	50.50	25.40	24.10	0.00
B5	54.15	5.29	0.06	40.43	0.07	0.45	99.10	0.19	0.26	0.00

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Table 11. Detection results of factors in Pingquan area

Indicator	q value	Indicator	q Value	Indicator	q Value
Geo-construction (X1)	0.123	Vegetation cover (X7)	0.014	Ecological richness (X13)	0.120
Elevation (X2)	0.083	Soil erosion factor (X8)	0.188	Population density (X14)	0.027
Altitude (X3)	0.248	Landscape fragmentation (X9)	0.084	GDP (X15)	0.051
Annual rainfall (X4)	0.105	Vegetation NPP (X10)	0.025	Food crop production (X16)	0.084
Average annual temperature (X5)	0.220	Soil type (X11)	0.543	Gross output value of agriculture, forestry, livestock and fisheries (X17)	0.070
Dryness index (X6)	0.040	Soil nutrient synthesis (X12)	0.035

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