15 minutes with James Skates, Head of Modelling, Monitoring and Geospatial activities in the Welsh Government discussing what an effective land use decision-making tool looks like.
I lead work on an integrated modelling platform that supports decision-making by policy and operational teams across the Welsh Government. The platform brings together a series of models that enable us to look at the drivers and potential solutions in the area of land use and agriculture. It represents a significant change in how we develop policy as we can evaluate the likely impacts of a policy before it’s operationalised. For example, the platform has been used to explore how potential trade deals will impact the agricultural sector through farmers’ choices about how they use their land, and the knock on effects on things like employment, soil quality and water quality. The underlying aim is always to get the best value for money from public finances.
Good quality data is essential. We collect rich environmental data so that we can develop complex and detailed spatial models that can be applied to big questions and challenges. The ability to model at the highest resolution (e.g. 0.25 hectare sq) is very important for policymakers, in order to help them understand how land use will change as a consequence of different drivers at a very granular level. From there, you can aggregate upwards to the county or national level as required. However, sometimes the land cover map data we rely on isn’t as spatially detailed as the modelling we’re capable of. In the future, it will be a great step forward if we’re able to utilise high-cadence earth observation data in the model, which would be at a far higher resolution and produce insights in near real time.
The work we do with policy teams is very iterative. We need to fully understand the problem they’re dealing with, including any regulatory frameworks, and then we try to quantify the issue, whether that’s a trade deal or net zero. We work together to explore opportunity spaces in policy and go through several phases where we gradually populate the model. As the policy thinking becomes more informed, so does the model. It’s also very important that the model is transparent and that you have time to ensure that policy colleagues understand its limitations.
An effective land use decision-making tool has to hit the sweet spot between being useful and overly complex. You have to avoid the temptation to continually make the model more complex as this reduces transparency, increases uncertainties and leads to less confidence in the model’s outputs.
And finally, don’t always assume that maps are the best outputs. We tailor our outputs for the policy teams we work with, but maps can sometimes be misleading and hard to interpret – they can imply a higher level of certainty than we can really get to with modelling. Sometimes a simple bar chart is a better way of conveying expected changes, whether in farm business income or water quality.