Evaluation of ensemble streamflow predictions in Europe

JOURNAL OF HYDROLOGY

卷:517

Article

Alfieri, Lorenzo^1,2  Pappenberger, Florian¹  Wetterhall, Fredrik¹  Haiden, Thomas¹  Richardson, David¹  Salamon, Peter² 

[1] European Ctr Medium Range Weather Forecasts, Reading RG2 9AX, Berks, England

[2] Commiss European Communities, Joint Res Ctr, I-21027 Ispra, VA, Italy

关键词: Flood early warning;    Ensemble streamflow predictions;    CRPS;    Skill scores;    Distributed hydrological modelling;   

DOI  :  10.1016/j.jhydrol.2014.06.035

来源: Elsevier

【 摘 要 】

In operational hydrological forecasting systems, improvements are directly related to the continuous monitoring of the forecast performance. An efficient evaluation framework must be able to spot issues and limitations and provide feedback to the system developers. In regional systems, the expertise of analysts on duty is a major component of the daily evaluation. On the other hand, large scale systems need to be complemented with semi-automated tools to evaluate the quality of forecasts equitably in every part of their domain. This article presents the current status of the monitoring and evaluation framework of-the European Flood Awareness System (EFAS). For each grid point of the European river network, 10-day ensemble streamflow predictions are evaluated against a reference simulation which uses observed meteorological fields as input to a calibrated hydrological model. Performance scores are displayed over different regions, forecast lead times, basin sizes, as well as in time, considering average scores for moving 12-month windows of forecasts. Skilful predictions are found in medium to large rivers over the whole 10-day range. On average, performance drops significantly in river basins with upstream area smaller than 300 km(2), partly due to underestimation of the runoff in mountain areas. Model limitations and recommendations to improve the evaluation framework are discussed in the final section. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.orgflicenses/by-nc-nd/3.0/).

【 授权许可】

Free