Assessing Decentralised Water Solutions: Towards a Framework for Adaptive Learning

Magnus Moglia*, Stephen Cook, Ashok K. Sharma, Stewart Burn

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

This paper reports on the use of qualitative analysis to inform a risk analysis framework for decentralised water systems. To realise the benefits from these technologies, a methodology is applied to learn from previous difficulties in implementing and managing them. A workshop process was used to capture stories from industry professionals on difficulties they have encountered in planning and implementation. Qualitative analysis of story narratives revealed stages where there was some type of development process failure; as well as failure modes and factors influencing the difficulties encountered. The analysis also generated insights: difficulties in one part of the development process tends to propagate to subsequent stages; system difficulties most often occurred in the policy stage of development due to institutional inertia and lack of adaptive governance; and the best indicator of problems with a decentralised system was complaints of poor water quality. Furthermore, this paper also provides a method to learn from past difficulties by identifying what data needs to be collected in order to populate a risk model which can be used for improving risk assessment of the development process for decentralised systems. This can provide a basis for better decision making, policy and guidelines; an important factor in mainstream acceptance.

Original languageEnglish
Pages (from-to)217-238
Number of pages22
JournalWater Resources Management
Volume25
Issue number1
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes

Fingerprint

Dive into the research topics of 'Assessing Decentralised Water Solutions: Towards a Framework for Adaptive Learning'. Together they form a unique fingerprint.

Cite this