Pluvial flooding in urban areas is characterized by a gradually varying inundation process caused by surcharge of the sewer manholes. Therefore urban flood models need to simulate the interaction between the sewer network and the overland flow in order to accurately predict the flood inundation extents. In this work we present a methodology for linking 2D overland flow models with the storm sewer model SWMM 5. SWMM 5 is a well-known free open-source code originally developed in 1971. The latest major release saw its structure re-written in C ++ allowing it to be compiled as a command line executable or through a series of calls made to function inside a dynamic link library (DLL). The methodology developed herein is written inside the same DLL in C + +, and is able to simulate the bi-directional interaction between both models during simulation. Validation is done in a real case study with an existing urban flood coupled model. The novelty herein is that the new methodology can be added to SWMM without the need for editing SWMM's original code. Furthermore, it is directly applicable to other coupled overland flow models aiming to use SWMM 5 as the sewer network model.

In the near future, a higher occurrence of wildfires is expected due to climate change, carrying social, environmental, and economic implications. Such impacts are often associated with an increase of post‐fire hydrological and erosive responses, which are difficult to predict. Soil erosion models have been proven to be a valuable tool in the decision‐making process, from emergency response to long‐term planning, however, they were not designed for post‐fire conditions, so need to be adapted to include fire‐induced changes.In recent years, there have been an increasing number of studies testing different models and adaptations for the prediction of post‐fire soil erosion. However, many of these adaptations are being applied without field validation or model performance assessment. Therefore, this study aims to describe the scientific advances in the last 20 years in post‐fire soil erosion modelling research and evaluate model adaptations to burned areas that aim to include: (i) fire‐induced changes in soil and ground cover; (ii) fire‐induced changes in infiltration; (iii) burn severity; and (iv) mitigation measures in their predictions. This study also discusses the strengths and weaknesses of these approaches, suggests potential improvements, and identifies directions for future research.Results show that studies are not homogeneously distributed worldwide, according to the model type used or by region most affected by wildfire. During calibration, 73% of cases involved model adaptation to burned conditions, and only 21% attempted to accommodate new processes. Burn severity was addressed in 75% of cases, whilst mitigation measures were simulated in 27%. Additionally, only a minor percentage of model predictions were validated with independent field data (17%) or assessed for uncertainties (13%). Therefore, further efforts are required in the adaptation of erosion models to burned conditions, to be widely used for post‐fire management decisions. © 2020 John Wiley & Sons, Ltd.

In this study we compared three overland flow models, a full dynamic model (shallow water equation), a local inertial equations model (gravity wave model), and a diffusive wave model (parallel diffusive wave model). The three models are coupled with the same full dynamic sewer network model (SIPSON). We adopted the volume exchange between sewer and overland flow models, and the hydraulic head and discharge rates at the linked manholes to evaluate differences between the models. For that purpose we developed a novel methodology based on RGB scale. The test results of a real case study show a close agreement between coupled models in terms of the extents of flooding, depth and volume exchanged, despite highly complex flows and geometries. The diffusive wave model gives slightly higher maximum flood depths and a slower propagation of the flood front when compared to the other two models. The local inertial model shows to a slight extent higher depths downstream as the wave front is slower than the one in the fully dynamic model. Overall, the simplified overland models can produce comparable results to fully dynamic models with less computational cost.

Urbanization leads to changes in the surface cover that alter the hydrological cycle of cities, particularly by increasing the impervious area and, thereby, reducing the interception, storage and infiltration capacity of rainwater. Nature-based solutions (NBS) can contribute to flood risk mitigation in urbanized areas by restoring hydrological functions. However, the effects of NBS on flood risk mitigation are complex and can differ substantially with the type of the NBS. Therefore, the effectiveness of NBS at the urban catchment scale is still subject to much debate, especially at the scale of urban catchments. In this study, the effects of different NBS on urban flood mitigation were evaluated for the city of Eindhoven in The Netherlands, as it has a history of urban flood events. To this end, various NBS scenarios were defined by municipal stakeholders and their impacts modelled with the numerical model Infoworks ICM. This was done for design storms with short, medium and long return periods (5, 10 and 100 years). Overall, the simulated NBS were effective in flood risk mitigation, reducing the flooded area as well as flood depth. The effectiveness of the individual NBS scenarios, however, depended strongly on the location and extension of the NBS, as well as on storm intensity. The effectiveness tended to increase with the increase in NBS surface area, while it tended to decrease with increasing storm intensity and, hence, return period. The NBS solution increasing street water storage was revealed to be more effective than those involving green car parks and green roofs. This study showed that numerical flooding models can be useful tools to assess the effects of NBS to reduce flood extent, water depth and/or velocity, providing insights that can support city planners to design and compare alternative strategies and plans for urban flood risk mitigation.