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Tackling Water Theft: Forecasting Adaptation Surprises

Project description

Predicting adaptation surprises in complex human-water systems

Water theft represents a challenge, accounting for more than 30 % of global water supply loss and persisting despite policy efforts. Non-linear adaptive responses by economic agents, particularly irrigators, have complicated efforts to predict feedback loops and anticipate cascading consequences. This dynamic exacerbates water theft, leading to the depletion of water bodies and hindering sustainable development. The ERC-funded WaterTheft project aims to forecast the adaptive behaviour of individual agents over time within complex human-water systems. The project will integrate mathematical programming and experimental economics methods with hydrologic modelling and ensemble experiments. The aim is to be able to consistently and repeatably forecast nonlinear socio-hydrological phenomena emerging over space and time and identify their triggers.

Objective

Water theft claims between 30% and 50% of the global water supply, and despite policy efforts to tackle it, is still on the rise. The policy failure to tackle water theft has been attributed to the nonlinear adaptive responses by economic agents such as irrigators, which can affect and be affected by other socioeconomic (e.g. growing crop prices) and ecological processes (e.g. water scarcity) via feedback loops with cascading impacts that are difficult to foresee. This has led to adaptation surprises with unexpected policy consequences, which have increased rather than reduced water theft, thus depleting water bodies and hampering sustainable development.
Here I aim to break new ground by developing a novel approach to forecast adaptation surprises in complex human-water systems. To this end, I will 1) combine microeconomic mathematical programming models with behavioral economic methods to forecast the nonlinear adaptive responses of individual agents over time; 2) integrate the behavior of individual agents into agent-based models and macroeconomic models to forecast nonlinear spatial trends emerging from human interactions at the local to global level; 3) endogenize these socioeconomic processes into human-water system models to forecast nonlinear socio-hydrological phenomena; and 4) use ensemble experiments to quantify scenario and modeling uncertainties, and forecast nonlinearities that may emerge or be amplified due to issues of model parameterization/structure or scenario design. These innovations will allow me to predict the emergence of nonlinearities and track their impact across coupled human-water systems, thus discovering adaptation surprises and their drivers. Methods will be empirically applied and tested in 3 living labs in Spain, Australia, and the US experiencing water theft.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-COG

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Host institution

FUNDACION IMDEA AGUA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 2 000 000,00
Address
AVENIDA PUNTO COM N2
28805 Alcala De Henares Madrid
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 2 000 000,00

Beneficiaries (2)

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