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Developing knowledge systems for urban resilience to cloudburst rain events.

Authors :
Rosenzweig, Bernice
Ruddell, Benjamin L.
McPhillips, Lauren
Hobbins, Robert
McPhearson, Timon
Cheng, Zhongqi
Chang, Heejun
Kim, Yeowon
Source :
Environmental Science & Policy; Sep2019, Vol. 99, p150-159, 10p
Publication Year :
2019

Abstract

• Partnerships between cities can play an important role in cloudburst knowledge systems. • There is a need for improved projections of cloudburst intensity with climate change. • There is a need for social science research to improve cloudburst risk dimensioning. • Policymakers need support in decision-making under climate change associated uncertainties. Cities are particularly vulnerable to cloudbursts - short-duration, intense rainfall events – which are often inadequately addressed through conventional stormwater and flood management policy. Climate change is projected to increase the frequency and intensity of cloudbursts in many cities. As minor cloudburst events become more frequent and extreme events more severe, cities will need to rapidly transform their stormwater drainage and interdependent systems, and the knowledge systems that guide their infrastructure decisions and policy. In this paper, we discuss the evolution of knowledge systems to address these challenges, using three diverse cities (Phoenix, USA; Copenhagen, Denmark; and New York City, USA) as case studies. We found that partnerships between cities – even across national boundaries – can be a particularly important component of cloudburst knowledge systems. We also identified limitations in knowledge systems related to non-stationary climate, the vulnerability of private property and the representation of cloudburst infrastructure in integrated water management, which present opportunities for future research to support decision-making. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14629011
Volume :
99
Database :
Supplemental Index
Journal :
Environmental Science & Policy
Publication Type :
Academic Journal
Accession number :
137163789
Full Text :
https://doi.org/10.1016/j.envsci.2019.05.020