Paradigm shift in engineering of pluvial floods: From historical recurrence intervals to risk-based design for an uncertain future

Haghighatafshar, Salar; Becker, Per; Moddemeyer, Steve; Persson, Andreas, et al. (2020-06-06). Paradigm shift in engineering of pluvial floods: From historical recurrence intervals to risk-based design for an uncertain future. Sustainable Cities and Society, 61,
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| Published | English
Authors:
Haghighatafshar, Salar ; Becker, Per ; Moddemeyer, Steve ; Persson, Andreas , et al.
Department:
Division of Chemical Engineering
Division of Risk Management and Societal Safety
Centre for Geographical Information Systems (GIS Centre)
Dept of Physical Geography and Ecosystem Science
Division of Water Resources Engineering
Project:
Sustainable Urban Flood Management
Abstract:
Precipitation is intrinsically associated with high uncertainty, which is exacerbated exponentially over time—especially concerning climate change. However, the current design practice in urban drainage infrastructure remains firmly bound to deterministic assumptions regarding the design load. This approach is too simplified—focusing only on the return period of the design event—and ignores the complexity of drainage systems and the potential changes in catchment hydrology and the at-risk valuable assets within. Therefore, the current design approach is inherently an unsustainable practice that cannot deal with extreme uncertainties associated with urban drainage and flood resilience in changing climate and society. This paper examines the current deterministic design practice and encourages a collective discussion on the need for a paradigm shift in the engineering of pluvial floods toward a risk-based design. We believe that adopting a risk-based design will partially address the uncertainty and complexity of climate and urban drainage, respectively, although a method for the new practice in a risk-based design paradigm must be developed.

Keywords:
pluvial floods ; urban flood risk ; drainage infrastructure ; climate change ; deterministic design ; probabilistic design
ISSN:
2210-6707
LUP-ID:
2651224f-45c0-4672-a60b-f78b356caa5c | Link: https://lup.lub.lu.se/record/2651224f-45c0-4672-a60b-f78b356caa5c | Statistics

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