Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model
Abstract
:1. Introduction
2. Study Area and Method
2.1. Study Area
2.2. DPSIR Mode
2.3. Construction of Index System
2.4. Game Theory Portfolio Empowerment
2.5. Matter-Element Cloud Model
- (1)
- Qualitative and quantitative transformation of cloud models
- (2)
- Matter-element theory
- (3)
- Cloud correlation calculation
2.6. Comprehensive Evaluation of Water Network Construction Effect
2.7. Model Data Prediction
2.8. Overall Research Design
3. Application Examples
3.1. Data Sources and Implementation Cost
3.2. Evaluation Level Division
3.3. Index Weight Calculation
3.4. Calculation and Analysis of Evaluation Results
3.4.1. Standard Cloud Computing
3.4.2. Temporal Analysis of Correlation Degree
3.4.3. Spatial Analysis of Correlation Degree
3.5. Comparative Analysis of Prediction and Planning Data
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Standard Layer | Index Layer | Explain |
---|---|---|
Driving force | D1: Control degree of water consumption target per 10,000 RMB of GDP [46] | The ratio of water consumption per ten thousand RMB of GDP to assessment value |
D2: Development and utilization of water resources [47] | The ratio of water supply to total water resources | |
D3: Effective use coefficient of farmland irrigation water [46] | The ratio of the actual effective use of water to the total amount of water inflow in the irrigated area, excluding deep seepage and field loss | |
D4: Water quality compliance rate of water function zone [48] | The ratio of the number of water quality up-to-standard water function areas to the total number of water function areas | |
D5: Target control degree of water consumption per 10,000 RMB of industrial added value [46] | The ratio of water consumption per 10,000 RMB of industrial added value to assessment value | |
D6: Water quality compliance rate of drinking water sources [46] | The ratio of the number of drinking water sources meeting the water quality standards to the total number of drinking water sources | |
Pressure | P1: Satisfaction rate of ecological flow in control sections of important rivers and lakes [49] | The compliance rate of the ecological flow targets determined by the main control sections in important rivers and lakes |
P2: Level 1~5 embankment compliance rate [50] | The ratio of the length of dikes of grades 1 to 5 reaching the flood control standard to the total length of dikes of grades 1 to 5 | |
P3: Elimination ratio of black and odorous water bodies in urban built-up areas [51] | The ratio of the number of black and odorous water bodies eliminated in urban built-up areas to the total number of water bodies | |
P4: Ecological embankment ratio [52] | The ratio of ecological embankment to total embankment length | |
State | S1: Water shortage rate [53] | The gap between supply and demand as a percentage of water supply |
S2: Total water consumption control compliance [46] | Comparison of water allocation and total water consumption control indicators | |
S3: Agricultural irrigation water metering [54] | The proportion of agricultural irrigation water intakes using metering facilities | |
S4: Domestic and industrial water metering rates [46] | The ratio of automatic collection sites to total collection sites | |
S5: Vertical connectivity of the river [55] | Evaluation of the number of buildings or facilities affecting river connectivity within a unit river length | |
Influence | I1: Water supply safety factor [56] | The ratio of effective water supply capacity to water supply volume |
I2: Urban water surface rate [52] | The ratio of urban water area to the total area of the region, indicating the development of urban water network area | |
I3: The degree of safety and stability of the river bank and river bed [56] | It shows that the local, temporary, and relative variation range shown by the river is generally expressed by the stability coefficient as the water and sediment conditions of the river basin change over time | |
I4: Average annual loss rate of flood disasters [57] | The ratio of the loss value of various properties or crops in the disaster-affected area to the pre-disaster value or normal value | |
I5: Storage volume siltation loss rate [57] | Total siltation loss storage capacity as a percentage of total storage capacity | |
I6: Compliance rate of waterlogging prevention and control [58] | The ratio of the area meeting the waterlogging prevention and control standard to the total area of the built-up area | |
Response | R1: Disaster prevention and emergency plan formulation rate [58] | Implementation of non-engineering measures for disaster prevention and mitigation |
R2: Coverage of important river and lake monitoring stations [59] | The proportion of important river and lake monitoring stations to total river and lake monitoring stations | |
R3: Intelligent control rate of major water conservancy projects [59] | The ratio of the number of major water conservancies projects, such as large reservoirs, dykes of level 3 and above, and major water diversion projects to achieve intelligent control in the total number of projects | |
R4: Implementation rate of the strictest water resource management [50] | Implementation of the most stringent water resource management system | |
R5: Degree of digital development [59] | Application degree of digital technology in the water network system |
Standard | Index | I (Excellent) | II (Better) | III (Pass) | IV (Bad) | V (Worse) | |
---|---|---|---|---|---|---|---|
Driving force | D1 | [95, 100] | [85, 95) | [70, 85) | [50, 70) | <50 | |
D2 | [25, 30] | [20, 25) | [10, 20) | [5, 10) | <5 | ||
D3 | [65, 100] | [60, 65) | [55, 60) | [50, 55) | <50 | ||
D4 | [95, 100] | [80, 95) | [60, 80) | [40, 60) | <40 | ||
D5 | [95, 100] | [85, 95) | [70, 85) | [50, 70) | <50 | ||
D6 | [98, 100] | [85, 98) | [75, 85) | [60, 75) | <60 | ||
Pressure | P1 | [98, 100] | [90, 98) | [80, 90) | [60, 80) | <60 | |
P2 | [95, 100] | [80, 95) | [75, 80) | [50, 75) | <50 | ||
P3 | [95, 100] | [90, 95) | [85, 90) | [70, 85) | <70 | ||
P4 | [90, 100] | [70, 90) | [50, 70) | [30, 50) | <30 | ||
State | S1 | [0, 2] | (2, 5] | (5, 10] | (10, 20] | >20 | |
S2 | Up to the standard Within 5% | Within 5% exceeding the standard | Exceeding the standard 5~10% | Exceeding the standard 10~20% | Exceeding the standard > 20% | ||
S3 | [65, 100] | [60, 65) | [55, 60) | [50, 55) | <50 | ||
S4 | [80, 100] | [70, 80) | [60, 70) | [50, 60) | <50 | ||
S5 | [0, 0.25) | [0.25, 0.5) | [0.5, 1) | [1, 1.2) | >1.2 | ||
Influence | I1 | [1.7, 2] | [1.5, 1.7) | [1.3, 1.5) | [1, 1.3) | <1 | |
I2 | North | [15, 100] | [10, 15) | [6, 10) | [4, 6) | <4 | |
South | [30, 100] | [20, 30) | [10, 20) | [6, 10) | <6 | ||
I3 | [2, 2.5] | [1.5, 2) | [1, 1.5) | [0.5, 1) | <0.5 | ||
I4 | [0, 0.15) | [0.15, 0.25) | [0.25, 0.5) | [0.5, 0.75) | >0.75 | ||
I5 | [0, 10) | [10, 15) | [15, 30) | [30, 40) | >40 | ||
I6 | [95, 100] | [90, 95) | [85, 90) | [70, 85) | <70 | ||
Response | R1 | [80, 100] | [70, 80) | [60, 70) | [50, 60) | <50 | |
R2 | [90, 100] | [80, 90) | [70, 80) | [60, 70) | <60 | ||
R3 | [90, 100] | [75, 90) | [60, 75) | [40, 60) | <40 | ||
R4 | [80, 100] | [70, 80) | [60, 70) | [50, 60) | <50 | ||
R5 | [80, 100] | [60, 80) | [30, 60) | [10, 30) | <10 |
Index Layer | Unit | Xinyang | Pingdingshan | ||||
---|---|---|---|---|---|---|---|
Objective | Subjective | Combination | Objective | Subjective | Combination | ||
D1 | % | 0.069 | 0.054 | 0.066 | 0.065 | 0.050 | 0.061 |
D2 | % | 0.016 | 0.015 | 0.016 | 0.031 | 0.049 | 0.036 |
D3 | - | 0.017 | 0.025 | 0.019 | 0.016 | 0.012 | 0.015 |
D4 | % | 0.069 | 0.068 | 0.069 | 0.050 | 0.025 | 0.042 |
D5 | % | 0.069 | 0.114 | 0.077 | 0.065 | 0.082 | 0.070 |
D6 | % | 0.069 | 0.098 | 0.074 | 0.065 | 0.053 | 0.062 |
P1 | % | 0.069 | 0.043 | 0.064 | 0.065 | 0.085 | 0.071 |
P2 | % | 0.019 | 0.007 | 0.017 | 0.015 | 0.023 | 0.017 |
P3 | % | 0.016 | 0.012 | 0.015 | 0.015 | 0.016 | 0.015 |
P4 | % | 0.017 | 0.016 | 0.017 | 0.015 | 0.028 | 0.019 |
S1 | % | 0.035 | 0.023 | 0.032 | 0.048 | 0.043 | 0.046 |
S2 | - | 0.069 | 0.046 | 0.065 | 0.065 | 0.061 | 0.064 |
S3 | % | 0.019 | 0.008 | 0.017 | 0.017 | 0.012 | 0.016 |
S4 | % | 0.019 | 0.012 | 0.017 | 0.024 | 0.021 | 0.023 |
S5 | (per 100 km) | 0.034 | 0.025 | 0.033 | 0.032 | 0.029 | 0.031 |
I1 | - | 0.021 | 0.024 | 0.021 | 0.016 | 0.016 | 0.016 |
I2 | % | 0.014 | 0.017 | 0.015 | 0.021 | 0.028 | 0.023 |
I3 | - | 0.027 | 0.030 | 0.027 | 0.043 | 0.059 | 0.048 |
I4 | % | 0.069 | 0.085 | 0.072 | 0.065 | 0.075 | 0.068 |
I5 | % | 0.037 | 0.040 | 0.038 | 0.049 | 0.060 | 0.052 |
I6 | % | 0.035 | 0.051 | 0.038 | 0.031 | 0.050 | 0.037 |
R1 | % | 0.069 | 0.059 | 0.067 | 0.065 | 0.038 | 0.057 |
R2 | % | 0.021 | 0.024 | 0.022 | 0.019 | 0.013 | 0.017 |
R3 | % | 0.069 | 0.078 | 0.070 | 0.065 | 0.048 | 0.060 |
R4 | % | 0.018 | 0.011 | 0.017 | 0.021 | 0.017 | 0.020 |
R5 | % | 0.017 | 0.015 | 0.017 | 0.016 | 0.010 | 0.014 |
Index Layer | I (Excellent) | II (Better) | III (Pass) | IV (Bad) | V (Worse) | |
---|---|---|---|---|---|---|
D1 | (97.5, 0.833, 0.008) | (90, 1.667, 0.017) | (77.5, 3.333, 0.033) | (60, 3.333, 0.033) | (25, 8.333, 0.083) | |
D2 | (27.5, 0.833, 0.008) | (22.5, 0.833, 0.008) | (15, 0.833, 0.008) | (7.5, 0.833, 0.008) | (2.5, 0.833, 0.008) | |
D3 | (82.5, 5.833, 0.011) | (62.5, 0.833, 0.008) | (57.5, 1.667, 0.017) | (55, 1.667, 0.017) | (25, 8.333, 0.083) | |
D4 | (97.5, 0.833, 0.008) | (92.5, 0.833, 0.008) | (70, 3.333, 0.033) | (50, 3.333, 0.033) | (20, 6.667, 0.067) | |
D5 | (97.5, 0.833, 0.008) | (90, 1.667, 0.017) | (77.5, 3.333, 0.033) | (60, 3.333, 0.033) | (25, 8.333, 0.083) | |
D6 | (99, 0.333, 0.003) | (91.5, 2.167, 0.022) | (80, 2.500, 0.025) | (67.5, 2.500, 0.025) | (30, 10.000, 0.100) | |
P1 | (99, 0.333, 0.003) | (94, 1.333, 0.013) | (85, 3.333, 0.033) | (70, 3.333, 0.033) | (30, 10.000, 0.100) | |
P2 | (97.5, 0.833, 0.008) | (87.5, 2.500, 0.025) | (77.5, 4.167, 0.042) | (62.5, 4.167, 0.042) | (25, 8.333, 0.083) | |
P3 | (97.5, 0.833, 0.008) | (92.5, 0.833, 0.008) | (87.5, 2.500, 0.025) | (77.5, 2.500, 0.025) | (35, 11.667, 0.117) | |
P4 | (95, 1.667, 0.017) | (80, 3.333, 0.033) | (60, 3.333, 0.033) | (40, 3.333, 0.033) | (15, 5.000, 0.050) | |
S1 | (1, 0.333, 0.003) | (3.5, 90.500, 0.005) | (7.5, 1.667, 0.017) | (15, 1.667, 0.017) | (60, 13.333, 0.133) | |
S2 | (0.5, 0.167, 0.002) | (3.0, 0.667, 0.007) | (7.5, 0.833, 0.008) | (15.0, 1.667, 0.017) | (60.0, 13.333, 0.13) | |
S3 | (82.5, 5.833, 0.058) | (62.5, 0.833, 0.008) | (57.5, 0.833, 0.008) | (52.5, 0.833, 0.008) | (25, 8.333, 0.083) | |
S4 | (90, 3.333, 0.033) | (75, 1.667, 0.017) | (65, 1.667, 0.017) | (55, 1.667, 0.017) | (25, 8.333, 0.083) | |
S5 | (0.25, 0.083, 0.001) | (0.375, 0.042, 0.00) | (0.75, 0.033, 0.000) | (1.1, 0.033, 0.000) | (1.6, 0.133, 0.001) | |
I1 | (1.85, 0.05, 0.001) | (1.6, 0.033, 0.000) | (1.4, 0.050, 0.001) | (1.15, 0.050, 0.001) | (0.5, 0.167, 0.002) | |
I2 | N | (57.5, 14.167, 0.02) | (12.5, 0.833, 0.008) | (8, 0.333, 0.003) | (5, 0.333, 0.003) | (2, 0.667, 0.007) |
S | (65, 11.667, 0.117) | (25, 1.667, 0.017) | (15, 0.667, 0.007) | (8, 0.667, 0.007) | (3, 1.000, 0.010) | |
I3 | (2.25, 0.083, 0.001) | (1.75, 0.083, 0.001) | (1.25, 0.083, 0.001) | (0.75, 0.083, 0.001) | (0.25, 0.083, 0.001) | |
I4 | (0.075, 0.025, 0.00) | (0.2, 0.017, 0.000) | (0.375, 0.042, 0.00) | (0.625, 0.042, 0.00) | (0.375, 0.13, 0.001) | |
I5 | (5, 1.667, 0.017) | (12.5, 0.833, 0.008) | (22.5, 1.667, 0.017) | (35, 1.667, 0.017) | (70, 10.000, 0.100) | |
I6 | (97.5, 0.833, 0.008) | (92.5, 0.833, 0.008) | (87.5, 2.500, 0.025) | (77.5, 2.500, 0.025) | (35, 11.667, 0.117) | |
R1 | (90, 3.333, 0.033) | (75, 1.667, 0.017) | (65, 1.667, 0.017) | (55, 1.667, 0.017) | (25, 8.333, 0.083) | |
R2 | (95, 1.667, 0.017) | (85, 1.667, 0.017) | (75, 1.667, 0.017) | (65, 1.667, 0.017) | (30, 10.000, 0.100) | |
R3 | (95, 1.667, 0.017) | (82.5, 2.500, 0.025) | (67.5, 3.333, 0.033) | (50, 3.333, 0.033) | (20, 6.667, 0.067) | |
R4 | (90, 3.333, 0.033) | (75, 1.667, 0.017) | (65, 1.667, 0.017) | (55, 1.667, 0.017) | (25, 8.333, 0.083) | |
R5 | (90, 3.333, 0.033) | (70, 3.333, 0.033) | (45, 3.333, 0.033) | (20, 3.333, 0.033) | (5, 1.667, 0.017) |
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Li, F.; Zhang, P.; Huang, X.; Li, H.; Du, X.; Fei, X. Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model. Water 2023, 15, 2507. https://doi.org/10.3390/w15142507
Li F, Zhang P, Huang X, Li H, Du X, Fei X. Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model. Water. 2023; 15(14):2507. https://doi.org/10.3390/w15142507
Chicago/Turabian StyleLi, Feng, Pengchao Zhang, Xin Huang, Huimin Li, Xuewan Du, and Xiaoxia Fei. 2023. "Evaluation of Water Network Construction Effect Based on Game-Weighting Matter-Element Cloud Model" Water 15, no. 14: 2507. https://doi.org/10.3390/w15142507