# Delineation of the Flooded Areas in Urban Environments Based on a Simplified Approach
## 1 Introduction
The utilization of LID practices can lead to significant effects on reducing the surface runoff, the peak runoff, and the flood volume, but involves the replacement of important portions of the impervious urban area (25% in a study led by [13]). In the quoted study, the best performances of LID practices were ranked as follows: bio-retention cell > rain garden > green roof > permeable pavement. In principle, water companies need to develop a philosophy and culture of sustainable development, as do all contemporary companies [14]. To achieve such a goal, the use of information systems is a must for the efficient operation of a company and for the support of sustainable practices [14]. The information technologies are designed to perform tasks which largely exceed the capacity of the human brain, such as operating a very large volume of information, performing complex calculations, and controlling many simultaneous processes. Physically based models and GIS tools are the main pillars for simulating natural urban flooding and the delineation of the affected areas under torrential rainfall scenarios in a built-up environment. Different models were developed to derive the flooded urban areas, depending mainly on the available computation capabilities. All models uniquely take into consideration both the overland flow and the flow through the urban sewage network. The urban drainage system was divided [15] into a minor system (underground collectors of the sewage network) and a major system (streets, pathways connecting depression areas, or small water courses). Based on this concept, the dual drainage models 1D-1D generate the overland flow and consider the interaction with the sewage network through grate inlets [5; 16]. Due to usual lack of reliable knowledge over the configuration and characteristics of the sewage system, that system is indirectly accounted for by considering its evacuated flow as corresponding to its designed frequency. Coupled (lumped or distributed) hydrological and (1D or 2D) hydraulic models provide the flood hydrograph along the streets or at the outlet points. In the case of distributed hydrological models, the spatial-temporal distribution of rainfall should be considered [17]. The current trend in urban hydrology is to use integrated modelling of 2D urban surfaces and 1D sewer hydrodynamic processes [18] due to the advantages they provide, including reliable simulation of 2D overland flow [9], which leads to accurate flooding extension, water depths, and water velocity in raster format. For 2D models, the Digital Terrain Model (DTM) resolution of 1-2 m [19; 20] with a vertical accuracy of 0.1 m [21] is recommended. This resolution allows for a fair representation of the buildings, which can be included in the topographic map by raising the building footprint to the first-floor level (0.3-0.5 m or even higher) or considering a higher terrain roughness [22]. At the same time, the roads network should be lowered by 0.10-0.15 m to preserve the main directions of the urban flow [23]. Until recently, most of the urban flood simulations have been carried out at low spatial resolution due to the high computational cost involved. Now, GPU-accelerated hydrodynamic models can perform high-resolution simulations [19]. Even though the GPU provides a significant reduction in simulation time for 2D hydrodynamic models, due to the ongoing increase of the quality and resolution of input data for large cities, the simulation time for these types of models appears to still be an important factor that requires the modeler's attention. Despite the technological progress (Lidar, Radar, GPU), there are still numerous situations with limited available basic data, such as a detailed digital terrain model, the extension of the flooded areas, or the series of sewage discharges [24]. In these cases, some useful information (crowdsource data) can be collected from nonconventional (and usually less reliable) sources, including memories of local inhabitants, newspapers, social media, case histories of previous floods, etc.