Michelle Viswanathan
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View article: Improving winter wheat yield prediction by accounting for weather and model parameter uncertainty while assimilating LAI and updating weather data within a crop model
Improving winter wheat yield prediction by accounting for weather and model parameter uncertainty while assimilating LAI and updating weather data within a crop model Open
Accurate crop yield predictions play a crucial role in enabling informed policy-making to ensure food security. Beyond using advanced methods such as remote sensing and data assimilation (DA), it is essential to comprehend the influence of…
View article: Bayesian multi-level calibration of a process-based maize phenology model
Bayesian multi-level calibration of a process-based maize phenology model Open
Plant phenology models are important components in process-based crop models, which are used to assess the impact of climate change on food production. For reliable model predictions, parameters in phenology models have to be accurately kn…
View article: Data and code: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize
Data and code: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize Open
Data and code supporting the research article: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize - M. Viswanathan, A. Scheidegger, T. Streck, S. Gayler, T.K.D. Weber. This includes R code for the implemen…
View article: Data and code: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize
Data and code: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize Open
Data and code supporting the research article: Bayesian Multi-level model calibration of the SPASS phenology model for silage maize - M. Viswanathan, A. Scheidegger, T. Streck, S. Gayler, T.K.D. Weber. This includes R code for the implemen…
View article: Bayesian multi-level calibration of a process-based maize phenology model
Bayesian multi-level calibration of a process-based maize phenology model Open
Plant phenology models are important components in process-based crop models, which are used to assess the impact of climate change on food production. For reliable model predictions, parameters in phenology models have to be accurately kn…
View article: A Bayesian sequential updating approach to predict phenology of silage maize
A Bayesian sequential updating approach to predict phenology of silage maize Open
Crop models are tools used for predicting year-to-year crop development on field to regional scales. However, robust predictions are hampered by uncertainty in crop model parameters and in the data used for calibration. Bayesian calibratio…
View article: An alternative strategy for combining likelihood values in Bayesian calibration to improve model predictions
An alternative strategy for combining likelihood values in Bayesian calibration to improve model predictions Open
<p>Conveying uncertainty in model predictions is essential, especially when these predictions are used for decision-making. Models are not only expected to achieve the best possible fit to available calibration data but to also captu…
View article: Reply on RC1
Reply on RC1 Open
Abstract. Crop models are tools used for predicting year-to-year crop development on field to regional scales. However, robust predictions are hampered by uncertainty in crop model parameters and in the data used for calibration. Bayesian …
View article: Comment on bg-2021-238
Comment on bg-2021-238 Open
Abstract. Crop models are tools used for predicting year-to-year crop development on field to regional scales. However, robust predictions are hampered by uncertainty in crop model parameters and in the data used for calibration. Bayesian …
View article: A Bayesian sequential updating approach to predict phenology of silage maize
A Bayesian sequential updating approach to predict phenology of silage maize Open
Crop models are tools used for predicting year to year crop development on field to regional scales. However, robust predictions are hampered by factors such as uncertainty in crop model parameters and in the data used for calibration. Bay…
View article: A Bayesian hierarchical approach to improve model parameter estimates and predictions of silage maize phenology in Germany
A Bayesian hierarchical approach to improve model parameter estimates and predictions of silage maize phenology in Germany Open
<p>Crop models are used to evaluate the impact of climate change on food security by simulating plant phenology, yield, biomass and leaf area index. Plant phenology defines the timing of crucial growth stages and physiological proces…