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作者

Carel Dieperink;Stef H.A. Koop;Mado Witjes;Kees Van Leeuwen;Peter P.J. Driessen

来源

CITIES,Vol.135,Issue1,Article 104216

语言

英文

关键字

City-to-city learning;Water governance;City Blueprint;Governance capacity;Social learning;Twinning;City networks

作者单位

Copernicus Institute of Sustainable Development, Utrecht University, Princetonlaan 8a, 3584 CB Utrecht, the Netherlands;KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands;Province of Utrecht, Archimedeslaan 6, 3584 BA Utrecht, the Netherlands;The Netherlands Institute of Ecology (NIOO), Droevendaalsesteeg 10, 6708 PB Wageningen, the Netherlands;Copernicus Institute of Sustainable Development, Utrecht University, Princetonlaan 8a, 3584 CB Utrecht, the Netherlands;KWR Water Research Institute, Groningenhaven 7, 3433 PE Nieuwegein, the Netherlands;Province of Utrecht, Archimedeslaan 6, 3584 BA Utrecht, the Netherlands;The Netherlands Institute of Ecology (NIOO), Droevendaalsesteeg 10, 6708 PB Wageningen, the Netherlands

摘要

Cities face several water challenges which ask for more pro-active management approaches. One option that cities have is to start networking and build learning alliances with other cities. Forming meaningful alliances however asks for clear and easily accessible city-matching methodologies which are based on a standardised assessment approach and the presence of structured and large databases. The City Blueprint Approach is an example of such a methodology. Aim of this paper is to demonstrate the potential of this approach as a substantive methodology for enhancing learning on urban water management. This is done by illustrating the use of the approach in four cities, which were studied in the H2020 project POWER (Political and sOcial awareness on Water EnviRonmental challenges) and by comparing the results found with good practices present in the City Blueprint database. These good practices however cannot simply be copy-pasted from one city to another. We therefore outline in what way more in-depth city-to-city (C2C) learning results can be achieved and be tailored to best-fit particular urban areas. The paper concludes with some suggestions for enhancing the potential for C2C learning in urban water management networks.