Identification of Ecological Compensation Zones and Compensation Amounts: A Case Study of the Yellow River Delta
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area Overview
2.2. Data Preparation and Processing
2.2.1. Data Preparation
2.2.2. Land Use Type Interpretation
2.3. Selection of ESV Indicators
2.4. Methods
2.4.1. Methods for ESV Accounting
2.4.2. Methods for Ecological Compensation
- (1)
- EPRPS Model
- (2)
- ECA Accounting
3. Results
3.1. Yellow River Delta ESV Change Characteristics
3.2. EC Results for the Yellow River Delta
3.2.1. Identification of EC Zone
3.2.2. Identification of Priority Zones for EC
3.2.3. Accounting of ECA
4. Discussion
4.1. Analysis of the Key Stakeholders in EC
4.2. Exploring EC Scheme for the Yellow River Delta
4.3. Comparative Analysis of Different ECA Accounting Methods
4.4. Limitations and Future Work of the Study
5. Conclusions
- (1)
- From 2015 to 2020, the ESV of the Yellow River Delta showed a declining trend, with coastal mudflats representing the highest ESV in 2020, accounting for 19% of the total service value. Among the different ecosystem service categories, cultural services had the highest value at 42.5 billion RMB. Spatially, the uneven distribution of ecological value intensified, with low-value areas expanding and high-value areas shifting eastward, indicating an urgent need to strengthen ecological protection.
- (2)
- The ESV and economic development levels showed positive and negative correlations with the EC priority, respectively. Coastal mudflats, the Yellow River, and water bodies were identified as the highest priority for EC due to their high ecological value and lower levels of economic development. These areas should be compensated first. Conversely, industrial land and farmland, which were identified as the highest priority for ecological payment, should bear the responsibility for funding EC to ensure the rational undertaking of ecological responsibilities. In 2020, the total ECA for the Yellow River Delta was 3.848 billion RMB, with 4.032 billion RMB allocated for beneficiaries and 1.84 billion RMB for payers. Industrial land was the primary payer, while coastal mudflats were the primary beneficiaries.
- (3)
- The Yellow River Delta should establish a horizontal fiscal transfer payment system where regions provide financial support to beneficiaries under the guidance of a coordinated management institution. Through adequate consultation, funds should be collected from ecological payers and distributed to ecological beneficiaries to ensure the efficient operation of the EC mechanism, thereby promoting sustainable ecological development in the Yellow River Delta.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data | Data Source | Resolution (m) | |
---|---|---|---|
Meteorological Data | Annual Average Rainfall | NASA (https://www.nasa.gov/) (accessed on 27 June 2023) | 30 |
Potential Evapotranspiration | Based on meteorological station data, calculated using equation [34] | 30 | |
Erosion Factor (R) | 30 | ||
Soil Erosion Factor (K) | Based on rainfall data | 30 | |
Satellite Remote Sensing Data | DEM | Geospatial Data Cloud (https://www.gscloud.cn/) (accessed on 10 July 2023) | 30 |
Slope Erosion Factor (LS) | Based on DEM calculation | 30 | |
Landsat 5 | GEE (2000-09-27) | 30 | |
Landsat 8 | GEE (2020-09-21) | 30 | |
LUCC | Based on SVM interpretation | 30 | |
NDVI | GEE | 30 | |
Root Depth | Referencing the InVEST model’s root depth table, creating raster data using LUCC data | 30 | |
GDP | Based on multi-factor weight distribution method | 1000 | |
Available Water | Referencing the InVEST model’s water availability table, creating raster data using LUCC data | 30 | |
Simpson’s Diversity Index | Calculated using FRAGSTATS4.2 | 30 | |
Socioeconomic Data | Aquaculture Production | 2015 and 2020 statistical yearbooks of Dongying and Binzhou | - |
Crop Production | |||
Tourism Income | |||
GDP |
Primary Indicator | Secondary Indicator | Accounting Content | Indicator Description |
---|---|---|---|
Supply service | Crop production | Supply of crop crops and aquatic products. | The Yellow River Delta, as a major grain production base, significantly contributes to the local economy with its abundant fishery resources and thriving marine aquaculture |
Marine aquaculture | |||
Regulation service | Carbon storage | Amount of carbon stored | Wetland vegetation plays an important role in carbon storage |
Water conservation | Amount of water conserved | The wetland ecosystem plays a key role in maintaining water balance | |
Soil retention | Amount of soil retained | The root network of wetland vegetation contributes to preventing soil erosion | |
Water purification | Amount of pollutants removed (nitrogen, phosphorus) | The ability of wetlands to absorb and degrade water pollutants | |
Cultural service | Leisure | Tourism income | Natural landscapes like the Yellow River Estuary National Park provide recreational spaces |
Indicators | Material | Emergy | Value | Relevant Parameters |
---|---|---|---|---|
Crop Production | represents the material of crop production; is the total crop production of the j-th LULC type in the nth county; stands for the cumulative NDVI value of the j-th LULC type in the n-th county; EmCP represents the emergy of crop production service; TCP represents the emergy transformity rate of crop production; VCP represents the value of the crop production service. | |||
Marine Aquaculture | represents the material of marine aquaculture; stands for total aquatic product yield of the j-th land use/cover type in the m-th district; TMA represents the emergy transformity rate of marine aquaculture; K is dry weight proportion coefficient, 1 kcal = 4186 J; μ is standard animal heat value, EmMA represents the emergy of marine aquaculture service; VMA represents the value of the marine aquaculture service. | |||
Water Conservation | is the material of water conservation; represents the annual water conservation of grid x in the j-th type of ecosystem; and denote the annual actual evapotranspiration and surface runoff of grid x in the j-th type of ecosystem, respectively. represents the annual precipitation of grid x. C represents the surface runoff coefficient; Emwc represents the emergy of water conservation service; ρ represents the density of water (1.0 × 106 g/m3); G represents the Gibbs free energy (4.94 J/g); Twc represents the emergy transformity rate of water conservation; VWC stands for the value of the water conservation service. | |||
Carbon Storage | represents the material of carbon storage service; represents the area of the i-th land use type; n represents the total number of LULC types in the study area; ,,,, represent the carbon density of the i-th land use type, aboveground biochar, underground biochar, soil organic carbon, and dead organic carbon, respectively. EmCS represents the emergy of carbon storage services; TCS is the emergy transformity rate of carbon storage; VCS stands for the value of the carbon storage service. | |||
Soil Retention | represents the material of soil retention; represents the potential soil erosion quantity; represents the actual soil erosion quantity; R is the rainfall erosivity factor; K is the soil erodibility factor; LS denotes the slope length and steepness factor; C accounts for the vegetation cover and management factor; P signifies the soil retention practice factor; EmSR represents the emergy of soil retention service; is the emergy conversion ratio for the topsoil layer (6.78 × 102 J); TSR represents the emergy transformity rate of soil retention; VSR represents the value of the soil retention service. | |||
Water Purification | represents the material of water purification; represents nitrogen load of the i-th grid; is nitrogen output of the i-th grid; EmNDR represents the emergy of water purification service; TNDR represents the emergy transformity rate of water purification; VNDR represents the value of the water purification service. | |||
Leisure | represents the material of leisure; Si is tourism income of the i-th grid; SLi is slope of grid i; SLmax and SLmin represent the maximum and minimum slopes among all grids in the study area, respectively. Slope data generated from DEM; stands for Simpson’s Diversity Index of grid I; EmRC represents the emergy of leisure service; TRC represents the emergy transformity rate of leisure; VRC represents the value of the leisure service |
Indicatos | Emergy Conversion Rate | References |
---|---|---|
Crop production | 1.51 × 1015 sej/t | [38] |
Marine aquaculture | 2.00 × 106 sej/g | [39] |
Water conservation | 4.09 × 104 sej/J | [40] |
Carbon storage | 3.78 × 107 sej/g | [39] |
Water purification | 2.80 × 109 sej/g | [40] |
Soil retention | 7.40 × 104 sej/J | [39] |
Leisure | 0.74 × 1012 sej/RMB | [39] |
Service Value Classification | ESV (RMB) | ||||
---|---|---|---|---|---|
Primary Type | Secondary Type | 2015 | 2020 | Rate of Change | |
Market value | Supply service | Crop production | 8.71 × 109 | 5.49 × 109 | −36.94% |
Marine aquaculture | 6.97 × 109 | 6.05 × 109 | −13.17% | ||
Non-market value | Regulation service | Water conservation | 1.09 × 109 | 2.19 × 109 | 100.23% |
Soil retention | 2.17 × 109 | 2.00 × 109 | −7.73% | ||
Water purification | 2.28 × 109 | 1.84 × 109 | −19.22% | ||
Carbon storage | 3.60 × 109 | 2.66 × 109 | −26.22% | ||
Cultural service | Leisure | 4.56 × 1010 | 4.25 × 1010 | −6.85% | |
Total | 7.04 × 1010 | 6.27 × 1010 | −10.96% |
Land Use Type | ESV (RMB) | Proportion | ||
---|---|---|---|---|
2015 | 2020 | 2015 | 2020 | |
Cropland | 1.25 × 1010 | 8.38 × 109 | 0.18 | 0.13 |
Forest | 9.32 × 109 | 9.47 × 109 | 0.13 | 0.15 |
Grassland | 1.13 × 1010 | 1.01 × 1010 | 0.16 | 0.16 |
Tideland | 1.16 × 1010 | 1.18 × 1010 | 0.16 | 0.19 |
Yellow River | 5.64 × 109 | 5.25 × 109 | 0.08 | 0.08 |
Water | 5.68 × 109 | 5.34 × 109 | 0.08 | 0.09 |
Settlement | 2.87 × 108 | 3.49 × 108 | 0.00 | 0.01 |
Saline | 3.98 × 109 | 3.52 × 109 | 0.06 | 0.06 |
Industrial land | 2.11 × 109 | 1.21 × 109 | 0.03 | 0.02 |
Salt pans | 1.34 × 108 | 7.47 × 108 | 0.00 | 0.01 |
Venture | 7.70 × 109 | 6.48 × 109 | 0.11 | 0.10 |
Port | 9.74 × 107 | 8.03 × 107 | 0.00 | 0.00 |
Total | 7.04 × 1010 | 6.27 × 1010 | 1 | 1 |
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Guan, Q.; Li, H.; Guan, C.; Chen, J.; Fan, Y. Identification of Ecological Compensation Zones and Compensation Amounts: A Case Study of the Yellow River Delta. Land 2024, 13, 1582. https://doi.org/10.3390/land13101582
Guan Q, Li H, Guan C, Chen J, Fan Y. Identification of Ecological Compensation Zones and Compensation Amounts: A Case Study of the Yellow River Delta. Land. 2024; 13(10):1582. https://doi.org/10.3390/land13101582
Chicago/Turabian StyleGuan, Qingchun, Hui Li, Chengyang Guan, Junwen Chen, and Yanguo Fan. 2024. "Identification of Ecological Compensation Zones and Compensation Amounts: A Case Study of the Yellow River Delta" Land 13, no. 10: 1582. https://doi.org/10.3390/land13101582
APA StyleGuan, Q., Li, H., Guan, C., Chen, J., & Fan, Y. (2024). Identification of Ecological Compensation Zones and Compensation Amounts: A Case Study of the Yellow River Delta. Land, 13(10), 1582. https://doi.org/10.3390/land13101582