Where the Wild Things Are: Smarter Decisions for Nature, Water and Infrastructure
Nature-based Solutions (NbS) are demonstrated to improve water quality, reduce flood risk, lock in carbon, restore biodiversity and improve public health.
Yet they are not deployed to their full potential as their costs, risks and outcomes cannot yet be quantified to a standard that meets regulators and investors requirements. The NbS evidence base is fragmented, the market incentives are misaligned, and nature itself has no voice in the planning process. This sprint addresses all three problems at once.
By harnessing the power of novel AI technology and remote sensing, we can improve our understanding of how existing NbS in the UK and elsewhere in the world have performed over time, helping close the performance data gap. Our outputs can connect to existing market mechanisms to motivate investment. And ultimately, we have the opportunity of making nature an active participant, and beneficiary, of water management planning, moving from a purely human-centered approach to a regenerative one.
This sprint asks:
How might we create frameworks and tools to enable practitioners to quantify NbS benefits to match regulators requirements, investors to trade water benefits, and nature to take an active part in the co-creation process?
This sprint will shape the concept of “Where the Wild Things Are”
An open-source and AI-enabled infrastructure for predicting NbS performance over time, understanding how NbS can be transposed from one context to another, and for representing ecological perspectives in design.
Together, we will:
- Explore how an open infrastructure can support decisions in the design of schemes that consider grey, blue and green solutions and multiple perspectives (human and non-human)
- Co-create frameworks to assess NbS performance over time in similar climatic and geographic conditions
- Co-create ways to represent nature in the decision-making process, ensuring that the needs of nature (biodiversity, biota, rivers, etc) are represented and communicated in the scheme design process.
- Define ways in which models outputs can be used by existing marketplaces.
Participants will collaborate through a series of structured design and innovation sessions where:
- Participants will be introduced to the main sprint themes to create a shared understanding (NbS, AI, Agentic AI).
- Participants will explore challenges and barriers in defining a framework to calculate NbS performance and assess gaps in monitoring standards.
- Participants will be introduced to AI, ML, remote sensing approaches to potentially measure and monitor NbS performance.
- Participants will explore the potential to connect to existing marketplaces to motivate NbS adoption.
- Participants will explore methodologies to represent nature’s needs in the decision-making process (e.g. AI personas, more-than-human storytelling, etc.).
- Participants will reflect on the role of AI and Agentic AI in the design of models that augment human decision-making.
By the end of the sprint, we aim to deliver:
- A framework for measuring and communicating NbS performance that defines which models do we need to build, and which parameters do they output?
- A vision for how an open and AI-driven infrastructure can be adopted by the industry and incorporated in existing or emerging tools
- A framework for leveraging on existing marketplaces.
- Concepts and/or prototypes to communicate nature’s needs in the design of schemes (e.g. AI personas, storytelling, etc.).
- Water company planners, with greater confidence in infrastructure decisions.
- Regulators, with improved visibility and trust in evidence-based approaches
- Catchment and environmental bodies, supporting more effective nature recovery
- Communities, benefiting from better environmental outcomes and resilient infrastructure
- The wider sector, through access to a shared and growing evidence base
- Technical skills: Water management, hydrology, data science, creative technologist, design, ethnography