Over the past several decades, urban flooding and other water-related disasters have become increasingly prominent and serious. Although the urban rain flood model’s benefits for urban flood simulation have been extensively documented, the impact of rainfall input to model simulation accuracy remains unclear. This systematic review aims to provide structured research on how rain inputs impact urban rain flood model’s simulation accuracy. The selected 48 peer-reviewed journal articles published between 2015 and 2019 on the Web of Science™ database were analyzed by key factors, including rainfall input type, calibration times and verification times. The results from meta-analysis reveal that when a traditional rain measurement was used as the rainfall input, model simulation accuracy was higher, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) of traditional technology for rain measurement was higher than the 0.18 for the new technology rain measurement with respect to flow simulation. In addition, the single-field sub-flood calibration model was better than the multi-field sub-flood calibration model. NSE was higher than 0.14. The precision was better for the verification period; NSE of the calibration value showed a 0.07 higher verification value on average in flow simulation. These findings have certain significance for the development of future urban rain flood models and propose the development direction of the future urban rain flood model. Finally, in view of the rainfall input problem of the urban storm flood model, we propose the future development direction of the urban storm flood model.

Climate change and rapid urbanization have increased pressure on drainage systems, posing new challenges to preventing and controlling urban waterlogging. In 2013, China proposed the Sponge City, a strategic measure for urban waterlogging control. This study quantifies the effects of stormwater management measures in runoff reduction for different levels of rainfall and conducts a one-dimensional visual analysis of urban waterlogging risks. At the same time, the best cost-effective scheme is determined based on life-cycle cost, analytic hierarchy process, and regret decision theory. The results showed stormwater management measures could realize the function of runoff control and waterlogging prevention, especially under low precipitation. However, these measures were still not enough to eliminate waterlogging risk. Combined measures have stronger runoff control capabilities than single measures. Considering economic, environmental, and operational impacts comprehensively, the combined measures of bio-retention (BR), permeable pavement (PP), and green roof (GR) were determined as the best cost-effective scheme because of the lowest regret value. The proposed method is helpful to provide reference and decision-making basis for the construction of sponge cities in the future.

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To address the two problems of unclear delineation of sub-catchment and complicated and cumbersome parameter rate determination in the Storm Water Management Model (SWMM), this study proposes a rapid construction method of SWMM based on the principle of single urban functional area combined with K-means clustering algorithm, The research area is the southern part of Jinshui District, Zhengzhou City. The Hydrological Response Unit (HRU) contains only a single urban functional area, divided by combining the natural and social attributes of the urban surface. Calibrated uncertain parameters from 76 papers were selected as samples, and the K-means clustering algorithm was used to cluster and calculate the parameter values, to improve the SWMM model, selecting three typical rainfall runoff processes for validation application. The results show that simulated runoff is consistent with measured runoff trends, with the NSE and R 2 value scores of the flow processes of the three floods above 0.86 and the, locations and numbers of flooded nodes are consistent with the actual research. This provides a new idea and technical support for the construction of urban flood models in flood prevention and mitigation. The relevant results can provide scientific decisionmaking reference for urban flood forecasting and warning.

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In order to realize the reproduction and simulation of urban rainstorm and waterlogging scenarios with complex underlying surfaces. Based on the Mike series models, we constructed an urban storm-flood coupling model considering one-dimensional river channels, two-dimensional ground and underground pipe networks. Luoyang City was used as a pilot to realize the construction of a one-dimensional and two-dimensional coupled urban flood model and flood simulation. where is located in the western part of Henan Province, China. The coupled model was calibrated and verified by the submerged water depths of 16 survey points in two historical storms flood events. The average relative error of the calibration simulated water depth was 22.65%, and the average absolute error was 13.93cm; the average relative error of the verified simulated water depth was 15.27%, The average absolute error is 7.54cm, and the simulation result is good. Finally, 28 rains with different return periods and different durations were designed to simulate and analyze the rainstorm inundation in the downtown area of Luoyang. The result shows that the R2 of rainfall and urban rainstorm inundation is 0.8776, and the R2 of rainfall duration and urban rainstorm inundation is 0.8141. Therefore, rainfall is the decisive factor in the formation of urban waterlogging disasters, which is actually the rainfall duration. The study results have important practical significance for urban flood prevention, disaster reduction and traffic emergency management.