Study on the Evolution of Ecological Sensitivity and Zoning Management for Sustainable Development in the Kuye River Basin
Abstract
:1. Introduction
2. Overview of the Study Area and Data Sources
2.1. Overview of the Study Area
2.2. Data Sources and Processing
3. Research Methodology
3.1. Basis for Selection of Indicators
3.2. Indicator Factor Standardization Processing
3.3. Calculation of Single Ecological Sensitivity Index
3.4. Comprehensive Ecological Sensitivity Calculation Method
3.5. Grid Coding Analysis
3.6. Geographical Detector
3.7. Sensitive Control Zone
4. Result Analysis
4.1. Temporal and Spatial Variation Characteristics of Ecological Sensitivity
4.2. Ecological Sensitivity Fluctuations and Trend Characteristics
4.3. Comprehensive Analysis of Ecological Sensitivity Driving Factors
4.4. Ecological Sensitivity Zoning
5. Discussion
6. Conclusions
- (1)
- The ecological sensitivity of the Kuye River Basin shows significant spatial differentiation in different periods. Specifically, in 2005, the sensitivity was lower in the northwest and higher in the central and southwestern parts. By 2020, the spatial distribution of ecological sensitivity was characterized by lower values at both the northern and southern ends and higher values in the central part. From 2005 to 2020, the average ecological sensitivity of the Kuye River Basin decreased by 1.11, indicating that the ecological environment quality within the basin has been effectively improved, while greatly enhancing the possibility of its sustainable development.
- (2)
- Most areas of the Kuye River Basin are in the ecological sensitivity fluctuation zone, with low fluctuation and high fluctuation areas accounting for 29.09% and 59.79%, respectively. However, the majority of fluctuations are downward fluctuations, with only 9.48% of the area experiencing upward fluctuations. The area of perennial stable zones accounts for 11.12%, but due to differences in the ecological environment, the ecological sensitivity of the stable zones still varies significantly.
- (3)
- From the results of Geodetector, biodiversity is the main influencing factor of spatial differences and sustainable development in the Kuye River Basin. In the future ecological protection and management of the Kuye River Basin, attention should be paid to the coverage of vegetation growth and the variety of species, but at the same time, soil erosion and water resource conditions should not be neglected.
- (4)
- The Kuye River Basin ecological environment protection area, ecological environment optimization area, ecological environment control area, and ecological environment management area account for 8.95%, 52.75%, 31.02%, and 7.28% of the area, respectively. Different regions have distinct ecological and environmental issues, leading to various zoning characteristics. To achieve sustainable development in the area, targeted ecological governance strategies should be implemented in subsequent management.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Data | Time | Source | Purpose |
---|---|---|---|
Digital Elevation Model (DEM) with a resolution of 30 m. | 2005, 2010, 2015, 2020 | Geospatial Data Cloud platform (https://www.gscloud.cn) (visited on 24 October 2024) | Calculate the slope and the distance to the water source. |
Precipitation data with a resolution of 1000 m. | 2005, 2010, 2015, 2020 | Geographic Data Sharing Infrastructure, global resources data cloud (http://gis5g.com/home) (visited on 24 October 2024) | For the calculation of soil erosion sensitivity and water resource sensitivity. |
Soil erodibility factor k data with a resolution of 90 m. | 2005, 2010, 2015, 2020 | Geographic Data Sharing Infrastructure, global resources data cloud (http://gis5g.com/home) (visited on 24 October 2024) | For the calculation of soil erosion sensitivity. |
NDVI data with a resolution of 30 m. | 2005, 2010, 2015, 2020 | National Science and Technology Infrastructure Platform—National Ecological Science Data Center (http://www.nesdc.org.cn) (visited on 24 October 2024) | Calculate its vegetation coverage using the pixel dichotomy method. |
Land use type data with a resolution of 30 m. | 2005, 2010, 2015, 2020 | Resource and Environmental Science Data Platform (https://www.resdc.cn) (visited on 24 October 2024) | Calculate water pollution risk levels and biological richness index based on land use data. |
Monthly potential evapotranspiration data with a resolution of 1000 m. | 2005, 2010, 2015, 2020 | National Earth System Science Data (https://www.geodata.cn) (visited on 24 October 2024) | Convert it into annual-scale data using the iterative model. |
Population density data with a resolution of 1000 m. | 2020 | Resource and Environmental Science Data Platform (https://www.resdc.cn) (visited on 24 October 2024) | To calculate the relationship between human activities and sensitivity. |
GDP data with a resolution of 1000 m. | 2020 | Resource and Environmental Science Data Platform (https://www.resdc.cn) (visited on 24 October 2024) | To calculate the relationship between human activities and sensitivity. |
Indicator | Indicator Factor Standardization | Standardization and Grading Assignment of Indicator Factors | ||||
---|---|---|---|---|---|---|
Non Sensitivity /1 | Low Sensitivity /3 | Medium Sensitivity /5 | High Sensitivity /7 | Extremely High Sensitivity/9 | ||
Soil erosion sensitivity | Precipitation (+) | (0–0.18) | (0.18–0.33) | (0.33–0.52) | (0.52–0.75) | (0.75–1) |
Slope (+) | (0–0.08) | (0.08–0.15) | (0.15–0.24) | (0.24–0.36) | (0.36–1) | |
Soil erodibility factor (+) | (0–0.21) | (0.21–0.36) | (0.36–0.55) | (0.55–0.68) | (0.68–1) | |
Vegetation coverage (−) | (1–0.6) | (0.6–0.5) | (0.5–0.4) | (0.4–0.3) | (0.3–0) | |
Water resource sensitivity | Distance from the water source (+) | (0–0.12) | (0.12–0.24) | (0.24–0.37) | (0.37–0.53) | (0.53–1) |
Precipitation (−) | (1–0.75) | (0.75–0.52) | (0.52–0.33) | (0.33–0.18) | (0.18–0) | |
Water pollution risk (+) | (0–0.21) | (0.21–0.43) | (0.43–0.64) | (0.64–0.86) | (0.86–1) | |
Annual potential evapotranspiration (+) | (0–0.27) | (0.27–0.41) | (0.41–0.56) | (0.56–0.72) | (0.72–1) | |
Biodiversity sensitivity | Vegetation coverage (−) | (1–0.6) | (0.6–0.5) | (0.5–0.4) | (0.4–0.3) | (0.3–0) |
Biological richness index (−) | (1–0.67) | (0.67–0.5) | (0.5–0.37) | (0.37–0.24) | (0.24–0) |
Biodiversity | Soil Erosion | Water Resources | Human Activities | |
---|---|---|---|---|
q | 0.48 | 0.30 | 0.25 | 0.03 |
p | 0 | 0 | 0 | 0 |
Population Density | GDP | Biological Richness Index | Water Pollution Risk | Vegetation Coverage | Distance from the Water Source | Soil Erodibility Factor | Slope | Precipitation | Annual Potential Evapotranspiration | |
---|---|---|---|---|---|---|---|---|---|---|
q | 0.02 | 0.04 | 0.37 | 0.29 | 0.32 | 0.12 | 0.20 | 0.06 | 0.28 | 0.07 |
p | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Ranking | 10 | 9 | 1 | 3 | 2 | 6 | 5 | 8 | 4 | 7 |
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Wang, Y.; Qin, F.; Dong, X.; Yuan, Y.; Wu, Y. Study on the Evolution of Ecological Sensitivity and Zoning Management for Sustainable Development in the Kuye River Basin. Sustainability 2025, 17, 2835. https://doi.org/10.3390/su17072835
Wang Y, Qin F, Dong X, Yuan Y, Wu Y. Study on the Evolution of Ecological Sensitivity and Zoning Management for Sustainable Development in the Kuye River Basin. Sustainability. 2025; 17(7):2835. https://doi.org/10.3390/su17072835
Chicago/Turabian StyleWang, Yang, Fucang Qin, Xiaoyu Dong, Yuan Yuan, and Yihan Wu. 2025. "Study on the Evolution of Ecological Sensitivity and Zoning Management for Sustainable Development in the Kuye River Basin" Sustainability 17, no. 7: 2835. https://doi.org/10.3390/su17072835
APA StyleWang, Y., Qin, F., Dong, X., Yuan, Y., & Wu, Y. (2025). Study on the Evolution of Ecological Sensitivity and Zoning Management for Sustainable Development in the Kuye River Basin. Sustainability, 17(7), 2835. https://doi.org/10.3390/su17072835