A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models

Mattia Sanna, Gianni Bellocchi, Mattia Fumagalli, Marco Acutis

研究成果: 雜誌貢獻文章同行評審

3 引文 斯高帕斯(Scopus)

摘要

The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of "stable correlation", was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools.

原文英語
頁(從 - 到)286-304
頁數19
期刊Environmental Modelling and Software
73
DOIs
出版狀態已發佈 - 十一月 1 2015
對外發佈

ASJC Scopus subject areas

  • 軟體
  • 環境工程
  • 生態建模

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