Open AccessExploring the Usability of Probabilistic Weather Forecasts for Water Resources Decision-Making in the United Kingdom
Author(s) -
Ana María López,
Sophie Haines
Publication year - 2017
Publication title -
weather, climate, and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.014
H-Index - 35
eISSN - 1948-8335
pISSN - 1948-8327
DOI - 10.1175/wcas-d-16-0072.1
Subject(s) - probabilistic logic , usability , resource (disambiguation) , computer science , consensus forecast , usable , water resources , expert elicitation , environmental science , operations research , environmental resource management , meteorology , econometrics , geography , engineering , economics , artificial intelligence , computer network , ecology , human–computer interaction , world wide web , biology
Over the last two decades, probabilistic weather forecasts have been developed to quantify the uncertainties inherent in modelling the climate system. The skill of these forecasts has steadily increased, but the question of whether they are usable for water resources management remains open. The interdisciplinary study described in this paper combined a modelling approach with qualitative methods to identify technical and non-technical factors that enhance or constrain the usability of probabilistic weather forecasts for reservoir management, using a case study of drought management decision-making by a water supply company in north-western England. The modelling approach calibrated and applied probabilistic medium- and extended-range precipitation forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) to a simplified water resources system, to study the technical quality of the forecasts that, in principle, could have informed management decisions during a drought event in 2010. The qualitative approach comprised initial semi-structured interviews with water managers and regulators, and follow-up discussions using the model experiment results to elicit further insights into the potential for incorporating probabilistic forecast information into decision-making processes. The technical analysis showed that even these post-processed forecasts did not have skill beyond the medium range; this constrains the type of management decisions the forecasts can inform. Regulatory frameworks and attitudes to risk in the water sector also inhibit the take-up of probabilistic forecasts for drought management decisions, owing to the high stakes of such decisions and considerations spanning entire water resource zones