A Framework to Evaluate Urban Flood Resilience of Design Alternatives for Flood Defence Considering Future Adverse Scenarios

Abstract

In urbanized plains that are subject to flooding, the socioeconomic aspects, climate characteristics, built environment, and riverine processes exhibit bi-univocal relationships with the flood formation itself, creating a pattern of development without a predefined equilibrium state. The complexity of processes involved in flood management and the need for a comparative assessment method to hierarchise different design alternatives or planning scenarios requires practical and quantitative methods for urban diagnoses, including flood risk and resilience aspects. This paper proposes an alternative pathway to evaluate design alternatives for urban flood mitigation, assessing resilience in quantitative terms. In this way, a methodological framework is presented suppress to evaluate flood resilience in urban watersheds planning, through the application of the Urban Flood Resilience Index (UFRI) and Future Scenarios Criteria (FSC). A case study illustrates the method using an urban watershed in Rio de Janeiro/Brazil. This study considered two possible design alternatives for flood control, with concentrated and distributed measures. The resilience mapping using the UFRI showed that the adoption of distributed measures could increase the areas classified as showing very high resilience by 41%, while very low resilience areas would be reduced by 87%. The FSC is able to present the integrated results of resilience variation from present and future conditions, considering, for example, climate change effects or unplanned urbanisation scenarios. The framework is able to perform comparisons between alternatives, showing the advantages associated with adopting distributed measures over the watershed, which reflected in a resilience value that was 24% higher when compared to the results obtained for the concentrated solutions scenario.

GIS-Based Urban Flood Resilience Assessment Using Urban Flood Resilience Model: A Case Study of Peshawar City, Khyber Pakhtunkhwa, Pakistan

“…Almost the same situation has occurred in the 2015 floods when 224 houses became partially damaged, 19 were fully damaged and 7 persons lost their lives [35]. According to Rezende et al 2019 [78], unplanned development, high population density, rapid urbanization, and poor sewerage system are the triggering elements of urban flooding in the study area. It is projected that the frequency and intensity of urban floods in the study area would be exacerbated in the coming decades due to dynamic changes in climate, coupled with a high influx of human population, rapid urbanization, poor developmental interventions, and low adaptive capacity [14,37,52].…”

Innovations in Best Practices: Approaches to Managing Urban Areas and Reducing Flood Risk in Reggio Calabria (Italy)

“…MODCEL proved to be a useful tool when compared to different models [57] and can be found in detail in Miguez et al [44]. Some previous applications of this model can be found in the literature [21,[58][59][60][61].…”

Current Issues in Early Warning and Development Initiatives Towards Enhanced Flood-Related Resilience in Nigeria

“…Similarly, initiative toward developmental infrastructure, which includes public health facilities, microfinance institutions and insurance companies, effective communications systems and good traffic networks for easy connectivity, safe drinking water, public housing scheme, proper waste management and sanitation facilities, public recreation facilities, green spaces, community centers, geospatial data platforms, quality internet-of-things (IoT), sustainable drainage systems (SUDS), resilient houses, etc., can facilitate preparedness, emergency response, rescue, and recovery-relating to a disaster management framework-as well as enhance the resilience of communities toward disaster reduction. Speaking of floods, evidence from a growing body of scientific research indicates that the frequency of occurrence of extreme events, which possess potential for large-scale impacts, is much higher in recent times and likely to increase over the coming decades as a consequence of global climate change [3,26,27]. This fact cannot be more obvious; due to the inexorable nature of these disasters which suggest that risk reduction concepts are the only possible solution therefore, modern disaster mitigation techniques must take advantage of opportunities in meteorological forecasting as well as the development and implementation of EWS that targets vulnerable regions and populations.…”