Digital Twin of Climate Responsive Smart Cities and the Application of Meteorological Data in Sustainable Urban Design

To achieve the design and construction of climate responsive smart cities, this study proposes a sustainable urban flood control scheduling optimization system based on digital twins and meteorological data. The new system can use urban climate data and digital twin technology to achieve flood warning and flood evolution in cities, providing better guidance for urban development and design. The results indicated that the scheduling model used had better flood control scheduling effect, with a water level reduction of 7 m and 5 m compared to the simulated annealing model. The water flow rate was reduced by 803 m ³ /s and 1243 m ³ /s compared to the simulated annealing algorithm. The water level of the reservoir has decreased by 6 m and 5 m compared to the genetic algorithm model. The scheduling peak optimization effect of the new model used in this study was the best, with the highest value reaching 92.5%. Therefore, by using the new system model, optimization analysis of sustainable urban flood control scheduling can be achieved. This has good reference value for the development of sustainable urban design.