Urban waters represent a crucial component for the enhancement of urban resilience due to their importance in cities. Nature-based solutions (NBS) have emerged as sustainable solutions to contribute to urban resilience in order to meet the challenges of climate change. In order to promote the use of NBS for increasing urban resilience, tools that demonstrate the value of this type of solutions over the long-term are required. A performance assessment system provides an adequate basis for demonstrating this value, as well as for diagnosing the current city situation, selecting and monitoring the implementation of solutions. Regarding NBS management, some assessment approaches have been published, focusing on assessing the effectiveness of NBS in the face of climate change and supporting their design and impact assessment. Nevertheless, an integrated approach to assess the NBS contribution for urban resilience has not been published. This paper presents a comprehensive resilience assessment framework (RAF) to evaluate the NBS contribution for urban resilience, focused on solutions for stormwater management and control. Furthermore, details on stakeholders’ validation, with focus on the metrics’ relevance and applicability to cities, is also presented.
Flood risk management in urban areas adjacent to the coast is essential to increase their resilience. This study aims at improving scientific knowledge of flood risk alongside estuaries, considering different hazards and integrating estuarine and urban drainage modelling. Mathematical modelling of stormwater systems is a useful tool to evaluate the susceptibility to flooding and identify potential measures to reduce flood risk. The assessment of urban drainage flooding uses a coupled 1D/2D model, applying 1D model to the underground system and 2D model for the surface component. Assessment scenarios were based on variables rainfall, estuarine water level, and degree of obstruction in sewers and at system outfalls. Estuarine hydrodynamics were simulated using the SCHISM-WWM model. A web GIS platform was developed to support urban flood risk forecast and management providing urban analysis visualisation. The main objective is to forecast flooding in the Dafundo catchment supporting definition of population warnings. This paper proposes a flood risk assessment approach, using 1D/2D coupled modelling, estuarine hydrodynamics, integrating the assessment in a forecast web platform. The novelty is supporting an integrated flood risk management in stormwater systems, particularly in estuarine areas, providing an important improvement to assess flooding occurrence, regarding flood depth, area and duration. K E Y W O R D S estuary, flood modelling, flood risk assessment, integrated platform, urban drainage 1 | INTRODUCTION Urban areas adjacent to estuaries are particularly exposed to flood risks. Estuarine water levels often restrict the flow capacity of the urban drainage systems, a situation that can be significantly aggravated if occurrence of intense rainfall and high water levels in the estuary coincide. Severe conjoint conditions include high tidal levels together with storm surge episodes or with large freshwater discharges (Townend & Pethick, 2002). Rise in mean sea level as well as increasing frequency of extreme meteorological conditions (IPCC, 2013) are factors that
Cities face unprecedented demographic, environmental, economic, social, and spatial challenges. In recent years, the implementation of nature-based solutions (NBS) is becoming more relevant in cities to improve urban resilience and to cope with climate change. NBS represent cost effective solutions that simultaneously provide environmental, social, and economic benefits and help build resilience. A comprehensive and multi-dimension Resilience Assessment Framework (RAF) to evaluate the NBS contribution to urban resilience, focused on NBS for stormwater management and control, was developed. This RAF is aligned with the RESCCUE RAF and the main assessment frameworks focused on NBS and urban resilience. This RAF for NBS is driven by the definition of resilience objectives and is able to evaluate short- and long-term changes, considering a comprehensive definition of the urban resilience and addressing the environmental, social, and economic capabilities. Regarding the initial resilience maturity and the available information in the city, three analysis degrees were proposed for the RAF application, namely, the essential, complementary, and comprehensive degrees, for which a pre-defined selection of metrics is proposed. This paper aims to present the application of the RAF essential analysis degree and its extensive validation regarding cities with different resilience maturity and available information. The application to seven cities with different resilience and NBS challenges allowed an in-depth validation of the pre-defined metrics included in the RAF essential analysis. In this sense, the analysis of the resilience maturity of the participating cities is presented, the main challenges and consolidated aspects in the cities are identified, and the cities ready to apply the complementary analysis degree are recognized. To conclude, to validate the essential analysis degree, the assessment of the main requirements of the RAF for NBS are verified, based on the RAF metrics results for the cities. In this light, the main requirements of the RAF for NBS were aggregated in three main categories, namely, NBS aspects, resilience capabilities, and the performance, risk and cost analysis.
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.