Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters

Confalonieri, Roberto; Bellocchi, Gianni; Tarantola, Stefano; Acutis, Marco; Donatelli, Marcello; Giampiero, Genovese

doi:10.1016/j.envsoft.2009.10.005

Cited by 92 publications

(53 citation statements)

References 19 publications

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“…Results of SA are influenced by the conditions explored (Confalonieri et al, 2010b;Martre et al, 2015;Casadebaig et al, http://dx.doi.org/10.1016Casadebaig et al, http://dx.doi.org/10. /j.ecolmodel.2016.008 0304-3800/© 2016 Elsevier B.V. All rights reserved.…”

Section: Introductionmentioning

confidence: 95%

Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions

Paleari

Confalonieri

2016

Ecological Modelling

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Section: Introductionmentioning

confidence: 95%

Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions

Paleari

Confalonieri

2016

Ecological Modelling

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“…Morris' method has undergone further enhancement by Campolongo et al, [161] and has been validated against qualitative variance based methods (such as the method of Sobol') by a number of researchers [158,162,163,164]. One of the main advantages of the Morris method is the low sample size required to evaluate the effect of each factor.…”

Section: Elementary Effects Methodsmentioning

confidence: 99%

An investigation into future performance and overheating risks in Passivhaus dwellings

McLeod

Hopfe

Kwan

2013

Building and Environment

203

126

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In response to UK government policy mandating the construction of 'zero carbon' homes by 2016 there have been significant changes in the way dwellings are being designed and built. Recent years have seen a rapid uptake in the adoption of the German Passivhaus standard as a template for ultra-low energy and zero carbon buildings in the UK. Despite genuine motivations to mitigate climate change and fuel poverty there is a lack of research investigating the long-term performance of Passivhaus buildings in a rapidly changing UK climate. This paper sets out to investigate whether Passivhaus dwellings will be able to provide high standards of thermal comfort in the future or whether they are inherently vulnerable to overheating risks. Scenario modelling using probabilistic data derived from the UKCP09 weather generator (WG) in conjunction with dynamic simulation and global sensitivity analysis techniques are used to assess the future performance of a range of typical Passivhaus dwellings relative to an identical Fabric Energy Efficiency Standard (FEES) compliant dwelling over its notional future lifespan. The emphasis of this study is to understand what impact climate change will pose to overheating risks for Passivhaus dwellings relative to the de facto (i.e. FEES) alternative, and which design factors play a dominant role in contributing to this risk. The results show that optimization of a small number of design inputs, including glazing ratios and external shading devices, can play a significant role in mitigating future overheating risks.

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“…In the context of crop growth modelling, Richter et al (2010) used the Morris SA method (Morris 1991) to identify the parameters of a complex crop model with the highest impact on Durum wheat yield formation at two locations, identifying the parameters involved with development and early light interception as the most relevant. Confalonieri et al (2010b) applied the Morris and Sobol' (1993) methods to a model for rice growth and development, comparing the SA results obtained for five European countries and, within each country, for 3 years characterized by different degree of continentality.…”

Section: Introductionmentioning

confidence: 99%

Combining a weather generator and a standard sensitivity analysis method to quantify the relevance of weather variables on agrometeorological models outputs

Confalonieri

2011

Theor Appl Climatol

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Sensitivity analysis (SA) is increasingly used to explain models behaviour in response to inputs variation. Agrometeorologists are used to apply standard SA methods only on model parameters because of the difficulty of applying standard sampling techniques to derive series of weather data where each value cannot be sampled independently from those of the neighbouring days and from other variables in the same day. The impact of weather variability on a crop model was here analysed by coupling the Morris SA method to a weather generator. Spring barley in northern Italy was simulated and different outputs considered. Under the explored conditions, parameters involved with temperature generation resulted the most relevant in determining yield and maturity date. Radiationrelated parameters were high-ranked for cumulated drainage and actual evapotranspiration. According to the author, this is the first time the sensitivity of a cropping system model to weather variables is quantified using standard SA techniques.

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Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters

Cited by 92 publications

References 19 publications

Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions

Sensitivity analysis of a sensitivity analysis: We are likely overlooking the impact of distributional assumptions

An investigation into future performance and overheating risks in Passivhaus dwellings

Combining a weather generator and a standard sensitivity analysis method to quantify the relevance of weather variables on agrometeorological models outputs

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