Estimating Uncertainty in Crop Models

About Ranju

Ranju is a young researcher originally from Nepal. Ranju’s research interest is within the field of water resources considering climate change impact and adaptation in water resources, ecohydrology, and agriculture. She did her Master in Water Engineering and Management at the Asian Institute of Technology and then she worked as Research Associate for three years before starting her Ph.D. at UTAS.

Contact: [email protected]

About the project

This project aims to quantify model prediction uncertainty in crop model system using example crops such as potato, for Tasmania and Australia and to test the hypothesis that predicted model outputs vary with the different sources of input, models used for simulation and model parameters.

General research question

  • How do model outputs (e.g. crop yield, water, and energy use efficiency) vary with different inputs, simulation models and model parameters while predicting uncertainty for crop model system using example crops such as potato at a regional and national scale?

Specific research questions

  • What are the dominant sources of uncertainty in crop model systems, using potato and wheat as example crops?
  • How much weight does each uncertainty source contribute to the total uncertainty?
  • What is the relative contribution of different sources of uncertainty with crop model systems, using potato as an example crop?

Hypotheses

  • Uncertainty in soil data outweighs uncertainty due to climate and management practices in crop model systems.
  • The weight of climate uncertainty is higher than other uncertainty sources in crop model systems.
  • The ensemble of crop models reduces uncertainty.

Objectives

  • To assess uncertainty in crop model outputs (crop yield, water use efficiency and energy use efficiency) using example systems such as wheat and potato at state (Tasmania) and national scale.
  • To investigate the variability of uncertainty over time and space.
  • To determine the contribution made by each source to predict uncertainty.

Location

Tasmanian Institute of Agriculture, University of Tasmania, Tasmania, Australia

Period

From March 2019 to March 2023

Supervisors

Dr Jonathan Ojeda (primary supervisor), Dr Bec Harris and Dr Tom Remenyi (Geography and Spatial Sciences-UTAS), Dr Neil Huth and Dr Jaci Brown (CSIRO), Prof Caroline Mohammed (TIA-UTAS).

Funded by

University of Tasmania and Australian Sustainable Agriculture Elite Scholarship (CSIRO-TIA/UTAS)

Grant amount

Total: AUD$303,226

  • UTAS Tuition Fee: AUD$144,900
  • Tasmania Graduate Research Scholarship living allowance: AUD$108,328
  • Australian Sustainable Agriculture Elite Scholarship: AUD$49,998
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Jonathan Ojeda (Jony)
Crop Ecophysiologist - Cropping Systems Modeller - Data Scientist

I use crop models to understand GxExM interactions and quantify sources of uncertainties in agricultural predictions.

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