Coordination of Flood Control under Urbanization on the Taihu Plain: Basin, City and Region Perspectives
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methods
2.2.1. Hydrodynamic Model
2.2.2. Flood Indicators
2.2.3. TOPSIS Coordination Evaluation Model
2.3. Data Description
3. Results
3.1. Modeling the Hydrological Process Based on a MIKE Model
3.1.1. Model Construction
3.1.2. Model Calibration and Validation
3.2. Simulation of Flood Characteristics under Different Scheduling Rules
3.2.1. Scheduling Scheme Scenarios
- (1)
- Scheme S0 refers to the present scheduling scheme.
- (2)
- Scheme S1 and Scheme S2 were urban optimal scheduling schemes, mainly examining the impact of controlled water level changes in the LEFCPs on the coordination of flood control.
- (3)
- Scheme S3 and Scheme S4 were the optimal scheduling schemes of the basin (water conservancy region), mainly examining the impact of controlled water level changes in sluices along the Yangtze River on the coordination of flood control.
- (4)
- Scheme S5, Scheme S6, Scheme S7, and Scheme S8 were the simultaneous optimal scheduling schemes of the city and basin, mainly examining the effect of combined optimal scheduling of the city and basin.
3.2.2. Flood Characteristics under Different Scheduling Rules
3.3. Coordination of Flood Control under Urbanization
3.3.1. Flood Control Coordination Assessment Index System and Weights
3.3.2. Flood Control Coordination between Basin and Regions
3.3.3. Flood Control Coordination between Basin and Cities
3.3.4. Flood Control Coordination between Regions and Cities
4. Discussion
4.1. Method Design
4.2. Limitations
4.3. Implication
5. Conclusions
- (1)
- Variations in Flood Characteristics under Different Flood Control Coordination Schemes: Schemes S2, S7, and S8 stand out by significantly reducing both the mean and maximum water level differences between the inner and outer urban areas. The flood characteristics of the flood processes under different scheduling rules varied slightly, especially the FI. With the exception of S4, the RCS means for the other models are higher than S0, and the highest RCS mean is for S5 at 1.022. The SFDC means for most scenarios are lower than S0, and the highest SFDC mean is for S5 at 0.305.
- (2)
- Effect of Different Scheduling Optimization Schemes on Flood Control Coordination at Various Levels: At the basin–region level, Scheme S8 significantly improved flood coordination, achieving a coordination coefficient of 0.68, compared to Scheme S0, which only scored 0.12. Moving to the basin–city level, Scheme S7 demonstrated notable progress with a coordination coefficient of 0.67, signifying a 0.37 improvement over Scheme S0, which scored 0.30. Finally, at the region-city level, Scheme S5 emerged as the most effective, attaining a coordination coefficient of 0.68, indicating a 0.22 improvement over Scheme S0, which scored 0.46. Overall, the optimal scheduling of cities and basins simultaneously had the most significant effect on enhancing coordination, followed by urban optimization schemes, while the effect of basin optimization schemes was relatively weaker.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Indicator | Formula | Meaning | |
---|---|---|---|
SFDC | (5) | SFDC represents the flood process’s responsiveness to rainfall. Higher SFDC values indicate a more rapid response of the flooding process to rainfall. | |
where w33% and w66% are the water level value at the 33rd and 66th percentile, respectively. | |||
RCS | (6) | RCS quantifies the change in water level during the flood process. Larger RCS values imply a faster rate of water level rise, potentially leading to increased flood control pressure. | |
where wp is the peak water level, w0 is the initial water level, and Δt is the interval from the initial water level to the peak water level. | |||
FI | (7) | FI measures the degree of fluctuation in the flood process over time. Higher FI values indicate a greater degree of fluctuation in the flood process. | |
where wi is the water level at the ith moment. |
Schemes | Operation Rules of Sluices along the Yangtze River | Operation Rules of the LEFCPs |
---|---|---|
S0 | Changzhou > 4.0 m | Sanbaojie > 4.3 m |
Wuxi > 3.6 m | ||
Qingyang > 3.7 m | Nanmen > 3.8 m | |
S1 | Changzhou > 4.0 m | Sanbaojie > 4.43 m |
Wuxi > 3.6 m | ||
Qingyang > 3.7 m | Nanmen > 4.0 m | |
S2 | Changzhou > 4.00 m | Sanbaojie > 4.57 m |
Wuxi > 3.6 m | ||
Qingyang >3.7 m | Nanmen > 4.2 m | |
S3 | Changzhou > 3.87 m | Sanbaojie > 4.3 m |
Wuxi > 3.4 m | ||
Qingyang > 3.53 m | Nanmen > 3.8 m | |
S4 | Changzhou >3.73 m | Sanbaojie > 4.3 m |
Wuxi > 3.2 m | ||
Qingyang > 3.35 m | Nanmen > 3.8 m | |
S5 | Changzhou > 3.87 m | Sanbaojie > 4.43 m |
Wuxi > 3.4 m | ||
Qingyang > 3.53 m | Nanmen > 4.0 m | |
S6 | Changzhou >3.73 m | Sanbaojie > 4.43 m |
Wuxi > 3.2 m | ||
Qingyang > 3.35 m | Nanmen > 4.0 m | |
S7 | Changzhou > 3.87 m | Sanbaojie > 4.57 m |
Wuxi (da) > 3.4 m | ||
Qingyang > 3.53 m | Nanmen > 4.2 m | |
S8 | Changzhou >3.73 m | Sanbaojie > 4.57 m |
Wuxi > 3.2 m | ||
Qingyang > 3.35 m | Nanmen > 4.2 m |
Indicators | Level | Weights | Direction | Normalized Value of Each Indicator | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
S0 | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | ||||
FI | Basin | 0.187 | Negative | 0.333 | 0.331 | 0.335 | 0.334 | 0.330 | 0.335 | 0.333 | 0.335 | 0.334 |
Region | 0.255 | Negative | 0.295 | 0.297 | 0.353 | 0.355 | 0.299 | 0.342 | 0.347 | 0.345 | 0.357 | |
RCS | Basin | 0.195 | Negative | 0.309 | 0.333 | 0.306 | 0.330 | 0.358 | 0.308 | 0.358 | 0.333 | 0.359 |
Region | 0.146 | Negative | 0.338 | 0.331 | 0.337 | 0.332 | 0.327 | 0.337 | 0.329 | 0.334 | 0.335 | |
SFDC | Basin | 0.062 | Negative | 0.333 | 0.336 | 0.315 | 0.319 | 0.341 | 0.405 | 0.310 | 0.306 | 0.324 |
Region | 0.155 | Negative | 0.320 | 0.332 | 0.315 | 0.334 | 0.346 | 0.320 | 0.347 | 0.334 | 0.350 |
Indicators | Level | Weights | Direction | Normalized Value of Each Indicator | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
S0 | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | ||||
FI | Basin | 0.173 | Negative | 0.333 | 0.331 | 0.335 | 0.334 | 0.330 | 0.335 | 0.333 | 0.335 | 0.334 |
City | 0.236 | Negative | 0.295 | 0.297 | 0.353 | 0.355 | 0.299 | 0.342 | 0.347 | 0.345 | 0.357 | |
RCS | Basin | 0.180 | Negative | 0.309 | 0.333 | 0.306 | 0.330 | 0.358 | 0.308 | 0.358 | 0.333 | 0.359 |
City | 0.114 | Negative | 0.327 | 0.330 | 0.330 | 0.334 | 0.332 | 0.330 | 0.335 | 0.341 | 0.341 | |
SFDC | Basin | 0.096 | Negative | 0.302 | 0.306 | 0.314 | 0.345 | 0.308 | 0.356 | 0.360 | 0.380 | 0.319 |
City | 0.201 | Positive | 0.354 | 0.329 | 0.355 | 0.329 | 0.314 | 0.352 | 0.315 | 0.332 | 0.316 |
Indicators | Level | Weights | Direction | Normalized Value of Each Indicator | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
S0 | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | ||||
FI | Region | 0.180 | Negative | 0.338 | 0.331 | 0.337 | 0.332 | 0.327 | 0.337 | 0.329 | 0.334 | 0.335 |
City | 0.077 | Negative | 0.333 | 0.336 | 0.315 | 0.319 | 0.341 | 0.405 | 0.310 | 0.306 | 0.324 | |
RCS | Region | 0.192 | Negative | 0.320 | 0.332 | 0.315 | 0.334 | 0.346 | 0.320 | 0.347 | 0.334 | 0.350 |
City | 0.153 | Negative | 0.327 | 0.330 | 0.330 | 0.334 | 0.332 | 0.330 | 0.335 | 0.341 | 0.341 | |
SFDC | Region | 0.128 | Negative | 0.302 | 0.306 | 0.314 | 0.345 | 0.308 | 0.356 | 0.360 | 0.380 | 0.319 |
City | 0.270 | Positive | 0.354 | 0.329 | 0.355 | 0.329 | 0.314 | 0.352 | 0.315 | 0.332 | 0.316 |
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Lu, M.; Kang, C.; Yu, Z.; Zhang, X. Coordination of Flood Control under Urbanization on the Taihu Plain: Basin, City and Region Perspectives. Water 2023, 15, 3723. https://doi.org/10.3390/w15213723
Lu M, Kang C, Yu Z, Zhang X. Coordination of Flood Control under Urbanization on the Taihu Plain: Basin, City and Region Perspectives. Water. 2023; 15(21):3723. https://doi.org/10.3390/w15213723
Chicago/Turabian StyleLu, Miao, Congxuan Kang, Zhihui Yu, and Xiuhong Zhang. 2023. "Coordination of Flood Control under Urbanization on the Taihu Plain: Basin, City and Region Perspectives" Water 15, no. 21: 3723. https://doi.org/10.3390/w15213723