Communicating the Uncertainty in Predictions from a GIS-Modelling Framework
- 1Net-zero and resilient farming, Rothamsted Research, Harpenden, Hertfordshire, AL5 2JQ, United Kingdom
- 2Cranfield University, College Road, Cranfield, Bedford, MK43 0AL, United Kingdom
- 3Mohammed IV Polytechnic University, Benguerir, Morocco
Policy makes and other stakeholders working to improve the sustainability of agriculture need access to information on soil spatial variation, and the impacts of management strategies that policy might promote. Models and data can provide such information but typically such products are developed in isolation and so do not allow for an integrated trade-off analysis. To overcome this limitation, we have developed a GIS- modelling framework (GIS-MF) that allows users to interrogate integrated models and data layers. This GIS-MF prototype has been developed for the Tensift watershed which is in the region of Marakesh-Safi, Morocco. The alpha version of the software contains four main components: (i) a field to watershed-scale Digital Soil Mapping viewer, (ii) a watershed scale Ecosystems Services Report viewer (iii) an Interactive Ecosystem Service and Environmental Impacts viewer that allows trade-offs to be explored and (iv) a field-scale yield prediction tool. For each component it is essential to communicate the uncertainties associated with predictions in a way that is both informative and intuitive to the end users. We have explored several ways for communicating uncertainty that we will present. For the DSM viewer we consider both methods that show uncertainty distributions as well as the probability of exceeding agronomically relevant thresholds. We take a similar approach for the Ecosystems Services Report viewer, and the yield prediction tool. For the uncertainties related to our integrated trade-offs we consider approaches to communicate the changes in multiple objectives. We draw on previous analyses to make conclusions and we will ask the EGU audience their views on each of the methods.
How to cite: Milne, A., Oulaid, B., el fartassi, I., Zawadzka, J., el Alami, R., Tabiti, K., Metcalfe, H., Diarra, A., Alonso chavez, V., Wayne, T., and Corstanje, R.: Communicating the Uncertainty in Predictions from a GIS-Modelling Framework, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15802, https://doi.org/10.5194/egusphere-egu23-15802, 2023.