Urban Flood Simulation Using MODCEL—An Alternative Quasi-2D Conceptual Model

Marcelo Gomes Miguez, Bruna Peres Battemarco, Matheus Martins De Sousa, Osvaldo Moura Rezende, Aline Pires Veról, Giancarlo Gusmaroli
2017 Water  
Urban flood modelling has been evolving in recent years, due to computational facilities as well as to the possibility of obtaining detailed terrain data. Flood control techniques have also been evolving to integrate both urban flood and urban planning issues. Land use control and flow generation concerns, as well as a set of possible distributed measures favouring storage and infiltration over the watershed, also gained importance in flood control projects, reinforcing the need to model the
more » ... ire basin space. However, the use of 2D equations with highly detailed digital elevation models do not guarantee good results by their own. Urban geometry, including buildings shapes, walls, earth fills, and other structures may cause significant interference on flood paths. In this context, this paper presents an alternative urban flood model, focusing on the system behaviour and its conceptual interpretation. Urban Flood Cell Model-MODCEL is a hydrological-hydrodynamic model proposed to represent a complex flow network, with a set of relatively simple information, using average values to represent urban landscape through the flow-cell concept. In this work, to illustrate model capabilities, MODCEL is benchmarked in a test proposed by the British Environmental Agency. Then, its capability to represent storm drains is verified using measured data and a comparison with Storm Water Management Model (SWMM). Finally, it is applied in a lowland area of the Venetian continental plains, representing floods in a complex setup at the city of Noale and in its surroundings. Water 2017, 9, 445 2 of 28 of such model may not be able to simulate the physical reality, because runoff processes cannot be represented within this approach and, in fact, the superficial flows may play a major role in the real flooding situation. Leandro et al. [1] posed that, unless in special cases where the flow remains confined within channel networks or limited by the streets, one-dimensional flow models are not applicable, and two-dimensional (2D) overland flow models should be used. These authors also recognise that overland flows in urban areas are highly complex due the interaction with manmade structures that drive flow paths. There is a tendency nowadays to combine 1D and 2D models to take advantage of what both have to offer. Simões et al. [2] say that flooding caused by surface flows, due to intense local storms that exceed the capacity of the drainage network takes place at smaller temporal and spatial scales when compared with inundation caused by river floods. This kind of event, until recently, has not been object of great attention. These authors stated that "forecasting such events is still in its infancy" (ibid). To simulate urban flooding in a more a realistic way, urban flood models need to couple the minor and the major drainage systems, what was referred to as the "dual drainage concept" by Djordjevic et al. [3]. This type of combined problem-river flooding and urban flooding-may occur in two different scales, which makes its modelling more complex. Apel et al. [4] highlighted that studies of a combined fluvial and pluvial flood hazard are hardly available. When observing the recent mathematical modelling trends, it is noticeable that the usage of 2D models is increasing and the detailed topographic information requested by these models is becoming easier to obtain. However, it is also perceived that a great amount of confidence is being put on these characteristics, in detriment of a soundly physical interpretation. Cunge [5] argued that, from the engineering point of view, the physical interpretation of the modelling process and consequent results is essential because computer output is bound to the simplification hypotheses introduced in the modelling phase. It is certainly desirable to have more information and the finest possible dimensional representation, but the fact is that these elements alone are not an absolute guarantee of adequate results. Except for very large urban-flooded areas, where great water depths may occur, it is difficult to observe a two-dimensional flow surface covering the entire affected area. Abbott and Vojinovic [6] point that mathematical modelling has been changing due to how knowledge is being produced and used in our society: a shifting is occurring and we are moving from a society of knowledge providers to knowledge consumers. In this context, these authors divide numerical models in developing phases, going from numerical solutions for physical equations, interpreting the phenomenon to overcome computational limitations, passing by tailor-made models to solve practical problems, then arriving in the commercial models phase and, lately, in the software-as-a-service phase. During this process, the users distanced themselves from modellers. This logic of knowledge consuming feeds the process of searching for more sophisticated flood models with complex and extensive topography data, even if it is not really required to solve the considered problem. Within this regard, Neal et al. [7] posed a question arguing: "How much physical complexity is needed to model flood inundation?" In this study, these authors highlight that, besides topography information, "a number of less obvious factors also cause differences in simulations as great or greater than physical complexity". When simulating subcritical gradually varied flows, with different models, these authors found values of flow velocities, water depths and inundated areas very similar amongst the tested models, with differences only as large as the ones caused by other modelling choices (e.g., topography sampling, recording of results, etc.). Moreover, even with the most accurate Digital Terrain Model (DTM), built with up-to-date accurate technologies, one will never be able to identify the actual particularities/anomalies of the drainage system, such as obstructions in the manholes, blocking of box-culvert section or flap gates, presence of rubbish in the canals, and so on. Only the information gathered on the field about how the watershed performs when flooded can supplement this information gap. The strict 2D modelling (or even 3D, if possible or available) may be too vulnerable to information gaps and unavoidable Water 2017, 9, 445 3 of 28
doi:10.3390/w9060445 fatcat:gsmmiysdazehjdag55ur32uphe