Models, decision-making and flood risk: doing simulation modelling differently
A Relu Policy and Practice Note (No. 22) that summarises research suggesting that, in situations of environmental controversy, local knowledge could play an important role in making better simulation models, and in making more effective use of them.
Year of Publication2010
Local people, such as householders or farmers, often mistrust the computer simulation models that ‘experts’ use to address their environmental problems. But, if local knowledge can be used in building and using these models, they may have greater credibility. Models, nowadays based on computer simulations, allow predictions to be made of events that are distant in time and space. Governments, technical agencies, companies and professionals use them all the time, to design, to plan and to regulate. The apparent predictive power of models often seems to give distant officials and experts, knowledge and insights that are superior to those of ‘non experts’. But Relu research suggests that, in situations of environmental controversy, local knowledge could play an important role in making better models, and in making more effective use of them. Researchers have investigated new approaches to interdisciplinary science, in which non-scientists, together with natural and social scientists, are engaged throughout the process of model building and application. The particular focus of this work was a major environmental management issue linked to rural land management – namely flooding – but the work has relevance to any kind of problem that uses models to make decisions about policy or management.
This item is categorised as follows
- Subject Collection > Soils & water > Water resource management
- Subject Collection > Soils & water > Rivers & lakes
- Subject Collection > Environmental impact > Flood & coastal defence
- Subject Collection > Rural policy & development
- Subject Collection > Rural policy & development > UK rural policy
Additional keywords/tagsflood riskrisk management
Harnessing the social and natural sciences for sustainable rural developmentWebsite
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