Environmental modelling
Development of tools and models to aid decision making
ADAS has a long history of developing tools and models to support decision making at a range of spatial scales from individual fields up to national level. This enables our clients to maximise the value of their data in improving current and future management decisions.
Developing tools and models requires a thorough understanding of the data available and related published research to ensure that appropriate logic chains are used to support the decision making process. We use a range of analysis techniques to condense the information in large datasets as the foundation for development of algorithms to describe the important trends in the data.
Through development of appropriate interfaces, we create bespoke modelling tools that allow clients to investigate the impacts of various decisions on key outcomes. The outputs from these models can then be converted into decision support tools that summarise the information in the form of practical advice and guidance.
Service lead
Dr Steve Anthony
Principal Research Consultant – ADAS Sustainable Agricultural Systems
Supporting decision making processes
ADAS tools and models are used nationally by policymakers and land managers to support their decision making process (e.g., Farmscoper, NEAP-N, PSYCHIC, EAgRET). We are also working to increase the availability of decision support tools for integrated pest management through the IPM Decisions Platform.
Data analysis
Analysis of qualitative and quantitative data to provide insights about key trends and outcomes that enable development of algorithms, models and decisions.
Scenario analysis
Exploration of datasets through modelling to understand the potential outcomes that can be expected under a range of different decisions.
System optimisation
Identification of optimal solutions through modelling of interactions between costs and benefits (e.g., identifying the most cost-effective strategy for reducing diffusion pollution on farms).
Quantifying the unknown
Use of models to determine outcomes for situations where measurement is impractical or impossible (e.g., predicting national scale impacts of uptake of mitigation measures, quantifying the impacts of climate change or predicting biodiversity response to changes in land use).
Design and assessment of regulation
Providing robust evidence-based guidance to policymakers on expected and potential impacts of regulation through the integration of survey data, environmental data and modelling.
Better decision-making with innovative solutions
Our easy-to-use digital solutions help with strategy planning and accurate reporting.
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