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Effective urban land-use re-planning and the strategic arrangement of drainage pipe networks can significantly enhance urban flood defense capacity. Aimed at reducing the potential risks of urban flooding, this paper presents a straightforward and efficient approach to an urban distributed runoff model (UDRM). The model is developed to quantify the discharge and water depth within urban drainage pipe networks under varying rainfall intensities and land-use scenarios. The Nash efficiency coefficient of UDRM exceeds 0.9, which indicates its high computational efficiency and potential benefit in predicting urban flooding. The prediction of drainage conditions under both current and re-planned land-use types is achieved by adopting different flood recurrence intervals. The findings reveal that the re-planned land-use strategies could effectively diminish flood risk upstream of the drainage pipe network across 20-year and 50-year flood recurrence intervals. However, in the case of extreme rainfall events (a 100-year flood recurrence), the re-planned land-use approach fell short of fulfilling the requirements necessary for flood disaster mitigation. In these instances, the adoption of larger-diameter drainage pipes becomes an essential requisite to satisfy drainage needs. Accordingly, the proposed UDRM effectively combines land-use information with pipeline data to give practical suggestions for pipeline modification and land-use optimization to combat urban floods. Therefore, this methodology warrants further promotion in the field of urban re-planning.

Based on a typical residential area, this paper studies the characteristics of pollutant concentration changes in two rainfall runoffs and the first flush effect of rainfall. In rainfall runoff, the concentrations of seven pollutants (CODMn, TN, DTN, NH3-N, TP, DTP, and PO43−) increased during the initial rainfall period and decreased in the later period. Rainfall causes the erosion of pollutants on the underlying surface so that water pollution begins when rainfall runoff occurs, and the pollution level drops over time. The seven pollutants all experience this first flush effect, of which, rainfall has the strongest scouring effect on NH3-N produced by domestic sewage. The significant excess of pollutants in rainfall runoff should be considered by management departments. In addition, the existence of the first flush effect makes it possible in theory to partially intercept rainfall runoff to control water pollution, thereby reducing the cost of pollution control.

Urban Sustainability and River Restoration: Green and Blue Infrastructure considers the integration of green and blue infrastructure in cities as a strategy useful for acting on causes and effects of environmental and ecological issues.

The regulation and spatial differences of urban runoffs are of great concern in contemporary hydrological research. However, owing to a shortage of basic data sources and restrictions on urban hydrological simulation functions, simulating and investigating the regulation mechanism behind rainfall-runoff processes remain significantly challenging. In this study, the Time Variant Gain Model (TVGM), a hydrological nonlinear system model, was extrapolated to the hydrodynamic model of an urban drainage network system by integrating it with the widely used Stormwater Management Model (SWMM) to adequately simulate urban runoff events while considering various underlying surfaces and runoff routing modes, such as surface, drainage network and river runoff, in urban regions (i.e., TVGM-SWMM). Moreover, runoff events were characterized using the following four runoff regime metrics: runoff coefficient, capture ratio of annual runoff volume, standardized flood timescale, and the ratio of occurrence time differences between flow and rainfall peak to event duration (peak flow delay time). The characteristics and spatial differences of urban runoff regulations were investigated, and the key impact factors and their relative contributions were identified using multivariate statistical analyses. Four communities were selected as our study areas, consisting of communities from Beijing, Shenzhen, Wuhan, and Chongqing. Our results showed that the TVGM-SWMM performed considerably better than SWMM alone. The comprehensive simulation accuracy of 60% of the events (12/20) improved by 486%, with the bias improving the most, followed by the efficiency coefficient. Barring the runoff coefficient, significant spatial differences were identified at the patch scale for the runoff regime metrics, with differences of 0.43, 0.22, and 0.16 ( p <0.05). The key impact factors were the pipe length ( r =0.51) in the drainage network system and the forest area ratios ( r =0.56), sponge measures ( r =0.52), grassland ( r =0.48), and impervious surface ( r =0.46) in the underlying surfaces. The contributions of the drainage network system and the underlying surfaces were 4.27% and 37.83%, respectively. Regulation in the Beijing community, dominated by grassland regulation, delayed and reduced the peak flow and total runoff volume. In the Shenzhen community, sharp and thin runoff events were mainly generated by impervious surfaces and were not adequately regulated. Forest regulation was the dominant regulation type in the Wuhan community, which reduced the total runoff volume and delayed the peak flow. Waterbody regulation was the primary regulation type in the Chongqing community, which reduced the total runoff volume and peak flow. This study aims to introduce a comprehensive theoretical and technical assessment of the hydrological effects of urbanization and the performance of sponge city construction and provide a reference for urban hydrological model improvements in China.

Urban runoff poses a significant management challenge due to its potential to damage infrastructure and communities. Accurate runoff modeling is essential for flood mitigation and urban planning. In this study, a Cellular Automata (CA) model was developed to simulate urban runoff. The model uses three transition rules to identify flow-receiving neighbors, distribute flow, and calculate cell flow, considering elevation, precipitation, buildings, and infiltration. Optimal parameters for pixel size, neighborhood configuration, and the flow-direction algorithm were determined. The model was applied to the urban area of Karaj City and validated against FLO-2D. Results show that rasterizing vector data using a 1-m cell size improved RMSE by about 40% compared with a 30-m cell size, while using eight instead of four neighbors improved RMSE by about 27%. Applying the minimization-of-differences algorithm reduced RMSE by about 10% compared with a steepest-direction approach. Moreover, primary streets were the most vulnerable, and impervious land uses generated higher runoff and larger inundated areas than green spaces. Robustness was evaluated through validation under an additional rainfall event, together with sensitivity and uncertainty analyses. The proposed CA model demonstrated good agreement with FLO-2D. Its simplicity and low data requirements make it a practical tool for urban runoff modeling.