作者: Stewart Burn , Magnus Moglia , Pascal Perez , S. Pope
DOI:
关键词:
摘要: Despite well meaning intentions, many aid interventions fail for one reason or another. The reasons are varied: lack of consideration local circumstances and process requirements, in particular inadequate involvement affected stakeholders as cross-sectorial coordination. This is not surprising given poor organizational memory combined with decisions being made under time pressure strict deadlines little adaptive capacity. Additionally, information about the importance requirements engagement qualitative such unfortunately often secondary importance. To address this, we suggest a Risk assessment component part project design phase based on Bayesian Networks (BNs) utilizing expert knowledge. only improves transparency but also provides direct link assessing cost benefits minimizing risk failure. Most importantly this prioritizes engagement, processes an understanding context. paper describes how BNs have been developed tested water supply town Tarawa, Kiribati. Models populated using data from interviews literature to evaluate options, i.e. rainwater harvesting, desalination reserve extensions; reports model relating reserves extension, new protection groundwater extracted distribution purposes. (Resume d'auteur)