A Bayesian hierarchical framework for emulating a complex crop yield simulator

07/26/2022
by   Muhammad Mahmudul Hasan, et al.
0

Emulation of complex computer simulations have become an effective tool in the exploration of the behaviour of the simulated processes. Agriculture is one such area where the simulation of crop growth, nutrition, soil condition and pollution could be invaluable in any land management decisions. In this paper, we study output from the EPIC simulation model to investigate the behaviour of crop yield in response to changes in inputs such as fertilizer levels, soil, steepness, and other environmental covariates. We build a model for crop yield around a non-linear Mitscherlich Baule growth model to make inferences about the response of crop yield to changes continuous input variables (fertiliser levels), as well as exploring the impact of categorical factor inputs such as land steepness and soil type. A Bayesian hierarchical approach to the modelling was taking for mixed inputs, requiring Markov Chain Monte Carlo simulations to obtain samples from the posterior distributions, to validate and illustrate the results, and to carry out model selection. Our results highlight a strong response of yield to nitrogen, but surprisingly a weak response to phosphorus and also shows the substantial improvement of the model after adding factor effects response to maximum yield for this particular simulator configuration and catchment.

READ FULL TEXT

page 6

page 18

page 23

page 31

page 32

page 33

research
09/21/2021

Bayes Linear Emulation of Simulated Crop Yield

The analysis of the output from a large scale computer simulation experi...
research
07/05/2022

Bayesian model selection for multilevel models using marginal likelihoods

Multilevel linear models allow flexible statistical modelling of complex...
research
10/24/2019

Reconstruction of Past Human land-use from Pollen Data and Anthropogenic land-cover Changes Scenarios

Accurate maps of past land cover and human land-use are necessary when s...
research
09/08/2022

Bayes factors for longitudinal model assessment via power posteriors

Bayes factor, defined as the ratio of the marginal likelihood functions ...
research
03/06/2012

Sequential Design for Computer Experiments with a Flexible Bayesian Additive Model

In computer experiments, a mathematical model implemented on a computer ...
research
07/17/2019

Factor copula models for mixed data

We develop factor copula models for analysing the dependence among mixed...
research
03/26/2022

Model Selection for Maternal Hypertensive Disorders with Symmetric Hierarchical Dirichlet Processes

Hypertensive disorders of pregnancy occur in about 10 around the world. ...

Please sign up or login with your details

Forgot password? Click here to reset