Abstract:In tropical countries like Brazil, fast and uncontrolled urbanization, together with high rainfall intensities, makes flooding a frequent event. The implementation of decentralized stormwater controls is a promising strategy aiming to reduce surface runoff and pollution through retention, infiltration, filtration, and evapotranspiration of stormwater. Although the application of such controls has increased in the past years in developed countries, they are still not a common approach in developing countries, such as Brazil. In this paper we evaluate to what extend different low impact development (LID) techniques are able to reduce the flood risk in an area of high rainfall intensities in a coastal region of South Brazil. Feasible scenarios of placing LID units throughout the catchment were developed, analyzed with a hydrodynamic solver, and compared against the baseline scenario to evaluate the potential of flood mitigation. Results show that the performance improvements of different LID scenarios are highly dependent on the rainfall events. On average, a total flood volume reduction between 30% and 75% could be achieved for seven LID scenarios. For this case study the best results were obtained when using a combination of central and decentral LID units, namely detention ponds, infiltration trenches, and rain gardens.
Traditional (technical) concepts to ensure a reliable water supply, a safe handling of wastewater and flood protection are increasingly criticised as outdated and unsustainable. These so-called centralised urban water systems are further maladapted to upcoming challenges because of their long lifespan in combination with their short-sighted planning and design. A combination of (existing) centralised and decentralised infrastructure is expected to be more reliable and sustainable. However, the impact of increasing implementation of decentralised technologies on the local technical performance in sewer or water supply networks and the interaction with the urban form has rarely been addressed in the literature. In this work, an approach which couples the UrbanBEATS model for the planning of decentralised strategies together with a water supply modelling approach is developed and applied to a demonstration case. With this novel approach, critical but also favourable areas for such implementations can be identified. For example, low density areas, which have high potential for rainwater harvesting, can result in local water quality problems in the supply network when further reducing usually low pipe velocities in these areas. On the contrary, in high demand areas (e.g., high density urban forms) there is less effect of rainwater harvesting due to the limited available space. In these high density areas, water efficiency measures result in the highest savings in water volume, but do not cause significant problems in the technical performance of the potable water supply network. For a more generalised and case-independent conclusion, further analyses are performed for semi-virtual benchmark networks to answer the question of an appropriate representation of the water distribution system in a computational model for such an analysis. Inappropriate hydraulic model assumptions and characteristics were identified for the stated problem, which have more impact on the assessments than the decentralised measures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.