Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model
Abstract
:1. Introduction
2. Study Area and Methods
2.1. Overview of the Study Area
2.2. Establishment and Grading of Evaluation Index System
2.3. Random Forest Model
2.4. Haken Model
2.5. Random Forest-Haken Model
- Step 1: Construct an evaluation index system and divide the index threshold;
- Step 2: Use the random generation method to generate the sample data of each level;
- Step 3: Standardize the positive and negative index data respectively in order to improve the accuracy of the model;
- Step 4: Use the standardized sample data as the input vector and the corresponding safety level values as the output vector to construct the random forest evaluation and prediction model, and bring in the actual data to obtain the evaluation results;
- Step 5: Apply the Haken model to identify the variables in two by two to find out slow variables of the system;
- Step 6: Use the identified slow variables as the main regulation variables, set different prediction scenarios, and input the data into the random forest model to obtain the prediction results.
3. Results and Discussion
3.1. Security Evaluation Based on Random Forest
3.1.1. Generation of Training and Test Samples
3.1.2. Data Standardization
3.1.3. Construction of Random Forest Model
3.1.4. Evaluation of the Current Situation of the Water-Energy-Food System
- Evaluation of the water resources subsystem
- 2.
- Evaluation of the Energy Subsystem
- 3.
- Evaluation of the food subsystem
3.2. Identification of Slow Variables in Systems Based on the Haken Model
3.3. Scenario Prediction
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Evaluation Index System | Attribute | ||
---|---|---|---|
Water Security | Pressure | Proportion of water used for industry and agriculture A1 | negative |
Water consumption per 10,000-yuan GDP A2 | negative | ||
Per capita water consumption A3 | negative | ||
State | Per capita water resources A4 | positive | |
Utilization rate of water resources A5 | negative | ||
Water yield per km2 A6 | positive | ||
Response | Treatment rate of urban sewage A7 | positive | |
Proportion of water-saving irrigation area A8 | positive | ||
Reuse rate of urban industrial water A9 | positive | ||
Energy Security | Pressure | Energy consumption per 10,000-yuan GDP B1 | negative |
Proportion of energy consumption in primary industry B2 | negative | ||
Per capita energy consumption B3 | negative | ||
State | Rate of energy self-sufficiency B4 | positive | |
Elasticity coefficient of energy consumption B5 | negative | ||
Proportion of electricity generated from clean energy sources B6 | positive | ||
Response | Investment intensity of resource exploration B7 | positive | |
Investment intensity of energy industry B8 | positive | ||
Comprehensive utilization rate of industrial solid waste B9 | positive | ||
Food Security | Pressure | Disaster rate of production area C1 | negative |
Fluctuation rate of grain yield C2 | negative | ||
Per capita food consumption C3 | negative | ||
State | Engel’s coefficient C4 | negative | |
Per capita grain possession C5 | positive | ||
Per capita grain sown area C6 | positive | ||
Response | Proportion of effective irrigation area C7 | positive | |
Power input per unit sown area C8 | positive | ||
Investment proportion of agriculture, forestry and water conservancy C9 | positive |
Indicator | Grading Standard of Security | ||||
---|---|---|---|---|---|
Extreme Insecurity (1st Level) | Not Security (2nd Level) | General Security (3rd Level) | Relative Security (4th Level) | Security (5th Level) | |
A1 | (90, 100] | (85, 90] | (80, 85] | (75, 80] | (65, 75] |
A2 | (280, 340] | (180, 280] | (80, 180] | (40, 80] | (0, 40] |
A3 | (700, 800] | (550, 700] | (400, 550] | (250, 400] | (150, 250] |
A4 | (0, 1000] | (1000, 2000] | (2000, 3500] | (3500, 5000] | (5000, 6500] |
A5 | (60, 650] | (40, 60] | (20, 40] | (10, 20] | (0, 10] |
A6 | (15, 40] | (40, 65] | (65, 90] | (90, 120] | (120, 145] |
A7 | (0, 40] | (40, 60] | (60, 80] | (80, 90] | (90, 100] |
A8 | (0, 40] | (40, 60] | (60, 75] | (75, 85] | (85, 100] |
A9 | (0, 40] | (40, 60] | (60, 80] | (80, 90] | (90, 100] |
B1 | (1.39, 2.24] | (1.07, 1.39] | (0.75, 1.07] | (0.43, 0.75] | (0, 0.43] |
B2 | (4.53, 5.96] | (3.33, 4.53] | (2.13, 3.33] | (0.93, 2.13] | (0, 0.93] |
B3 | (4.2, 5] | (3.4, 4.2] | (2.6, 3.4] | (1.8, 2.6] | (1, 1.8] |
B4 | (0, 40] | (40, 60] | (60, 80] | (80, 100] | (100, 160] |
B5 | (1, 1.5] | (0.5, 1] | (0, 0.5] | (−0.5, 0] | (−1.5, −0.5] |
B6 | (0, 30] | (30, 60] | (60, 70] | (70, 80] | (80, 100] |
B7 | (0, 0.5] | (0.5, 1] | (1, 1.5] | (1.5, 2] | (2, 2.5] |
B8 | (0, 2] | (2, 4] | (4, 7] | (7, 10] | (10, 13] |
B9 | (0, 40] | (40, 60] | (60, 80] | (80, 90] | (90, 100] |
C1 | (32, 40] | (24, 32] | (16, 24] | (8, 16] | (0, 8] |
C2 | (11, 20] | (7, 11] | (4, 7] | (1, 4] | (0, 1] |
C3 | (190, 220] | (165, 190] | (140, 165] | (120, 140] | (90, 120] |
C4 | (60, 100] | (50, 60] | (40, 50] | (20, 40] | (0, 20] |
C5 | (0, 260] | (260, 400] | (400, 540] | (540, 680] | (680, 800] |
C6 | (0, 0.04] | (0.04, 0.07] | (0.07, 0.1] | (0.1, 0.13] | (0.13, 0.16] |
C7 | (0, 20] | (20, 40] | (40, 55] | (55, 75] | (75, 100] |
C8 | (0, 3] | (3, 5] | (5, 7] | (7, 9] | (9, 11] |
C9 | (0, 1] | (1, 2] | (2, 3] | (3, 4] | (4, 5] |
Security Level | Classification Results | |||
---|---|---|---|---|
Water-Energy-Food SYSTEM | Water Subsystem | Energy Subsystem | Food Subsystem | |
1 | ≤1.615 | ≤1.640 | ≤1.623 | ≤1.596 |
2 | (1.615, 2.507] | (1.640, 2.504] | (1.623, 2.508] | (1.596, 2.524] |
3 | (2.507, 3.497] | (2.504, 3.556] | (2.508, 3.474] | (2.524, 3.436] |
4 | (3.497, 4.542] | (3.556, 4.534] | (3.474, 4.444] | (3.436, 4.573] |
5 | >4.542 | >4.534 | >4.444 | >4.573 |
Slow Variable | a | Fast Variable | b | ||
---|---|---|---|---|---|
A8 | −0.036 | 0.037 | B7 | 0.144 | 0.074 |
−0.0035 | −0.048 | B3 | 0.0333 | −0.009 | |
A3 | 0.025 | −0.058 | A1 | 0.0615 | 0.07 |
B1 | −0.003 | −0.037 | A5 | 0.024 | 0.0311 |
−0.056 | 0.0278 | A9 | 0.088 | 0.1054 | |
−0.0813 | 0.0908 | C4 | 0.267 | 0.2518 | |
C5 | 0.001 | −0.0396 | C8 | 0.01 | 0.044 |
0.018 | −0.04 | A9 | 0.05 | 0.118 | |
C6 | −0.009 | 0.0156 | C9 | 0.023 | 0.085 |
0.0153 | −0.0247 | B3 | 0.061 | 0.0368 | |
C7 | −0.0069 | −0.0323 | B4 | 0.01 | −0.0096 |
Province | A3 | A8 | B1 | C5 | C6 | C7 |
---|---|---|---|---|---|---|
Jiangsu | 550 | 80 | 0.2 | 500 | 0.07 | 95 |
Hubei | 450 | 60 | 0.3 | 580 | 0.1 | 65 |
Security Value | Level | ||||||||
---|---|---|---|---|---|---|---|---|---|
W-E-F | Water | Energy | Food | W-E-F | Water | Energy | Food | ||
Jiangsu | Scenario 1 | 3.481 | 3.208 | 3.155 | 3.969 | 3 | 3 | 3 | 4 |
Scenario 2 | 3.765 | 3.387 | 3.703 | 4.102 | 4 | 3 | 4 | 4 | |
Scenario 3 | 3.955 | 3.615 | 3.947 | 4.191 | 4 | 4 | 4 | 4 | |
Hubei | Scenario 1 | 3.406 | 3.353 | 3.165 | 3.761 | 3 | 3 | 3 | 4 |
Scenario 2 | 3.633 | 3.426 | 3.458 | 4.025 | 4 | 3 | 3 | 4 | |
Scenario 3 | 3.937 | 3.587 | 3.973 | 4.230 | 4 | 4 | 4 | 4 |
Jiangsu | Hubei | |||||||
---|---|---|---|---|---|---|---|---|
W-E-F | Water | Energy | Food | W-E-F | Water | Energy | Food | |
Scenario 1 | 12.20% | 17.41% | 14.04% | 9.65% | 12.36% | 6.29% | 22.67% | 11.97% |
Scenario 2 | 21.36% | 23.94% | 33.85% | 13.33% | 19.83% | 8.69% | 34.05% | 19.84% |
Scenario 3 | 27.48% | 32.31% | 42.65% | 15.79% | 29.87% | 13.86% | 54.00% | 25.93% |
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Chen, Y.; Xu, L. Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model. Water 2021, 13, 695. https://doi.org/10.3390/w13050695
Chen Y, Xu L. Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model. Water. 2021; 13(5):695. https://doi.org/10.3390/w13050695
Chicago/Turabian StyleChen, Yan, and Lifan Xu. 2021. "Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model" Water 13, no. 5: 695. https://doi.org/10.3390/w13050695