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Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M. |
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A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models |
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Journal Article |
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2015 |
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Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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73 |
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286-304 |
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model evaluation; performance indicators; stable correlation; solar-radiation; simulation-model; environmental-models; statistical-methods; crop nitrogen; validation; rice; uncertainty; calibration; software |
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Abstract |
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. (C) 2015 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM LiveM, ftnotmacsur |
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MA @ admin @ |
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4503 |
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Ben Touhami, H.; Bellocchi, G. |
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Bayesian calibration of the Pasture Simulation model (PaSim) to simulate European grasslands under water stress |
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Journal Article |
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Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
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30 |
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356-364 |
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Bayesian calibration framework; Grasslands; Pasture Simulation model; (PaSim); integrated assessment models; chain monte-carlo; climate-change; computation; impacts; vulnerability; likelihoods; france |
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As modeling becomes a more widespread practice in the agro-environmental sciences, scientists need reliable tools to calibrate models against ever more complex and detailed data. We present a generic Bayesian computation framework for grassland simulation, which enables parameter estimation in the Bayesian formalism by using Monte Carlo approaches. We outline the underlying rationale, discuss the computational issues, and provide results from an application of the Pasture Simulation model (PaSim) to three European grasslands. The framework was suited to investigate the challenging problem of calibrating complex biophysical models to data from altered scenarios generated by precipitation reduction (water stress conditions). It was used to infer the parameters of manipulated grassland systems and to assess the gain in uncertainty reduction by updating parameter distributions using measurements of the output variables. |
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1574-9541 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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4697 |
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Pulina, A.; Lai, R.; Salis, L.; Seddaiu, G.; Roggero, P.P.; Bellocchi, G. |
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Title |
Modelling pasture production and soil temperature, water and carbon fluxes in Mediterranean grassland systems with the Pasture Simulation Model |
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Journal Article |
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Year |
2018 |
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Grass and Forage Science |
Abbreviated Journal |
Grass Forage Sci. |
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73 |
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2 |
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272-283 |
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grassland production; Mediterranean pastures; model calibration; PaSim; sheep grazing systems; soil respiration |
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Grasslands play important roles in agricultural production and provide a range of ecosystem services. Modelling can be a valuable adjunct to experimental research in order to improve the knowledge and assess the impact of management practices in grassland systems. In this study, the PaSim model was assessed for its ability to simulate plant biomass production, soil temperature, water content, and total and heterotrophic soil respiration in Mediterranean grasslands. The study site was the extensively managed sheep grazing system at the Berchidda‐Monti Observatory (Sardinia, Italy), from which two data sets were derived for model calibration and validation respectively. A new model parameterization was derived for Mediterranean conditions from a set of eco‐physiological parameters. With the exception of heterotrophic respiration (Rh), for which modelling efficiency (EF) values were negative, the model outputs were in agreement with observations (e.g., EF ranging from ~0.2 for total soil respiration to ~0.7 for soil temperature). These results support the effectiveness of PaSim to simulate C cycle components in Mediterranean grasslands. The study also highlights the need of further model development to provide better representation of the seasonal dynamics of Mediterranean annual species‐rich grasslands and associated peculiar Rh features, for which the modelling is only implicitly being undertaken by the current PaSim release. |
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LiveM, ft_macsur |
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MA @ admin @ |
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4973 |
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