WaterTheft

Tackling Water Theft: Forecasting Adaptation Surprises

Project Info

Call: ERC-2023-COG
Project starting date: 1 april 2024
Project end date: 31 march 2029

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Project

Introduction

«Water theft claims 30%-50% of the global water supply – and is 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 and ecological processes 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.

Combine microeconomic mathematical programming models with behavioral economics methods to predict the nonlinear adaptive responses of individual agents over time.

Integrate the behavior of individual agents into agent-based and macroeconomic models to predict nonlinear spatial trends arising from human interactions at local and global levels.

Endogenize these socioeconomic processes in water and human systems models to predict nonlinear sociohydrological phenomena.

Use ensemble experiments to quantify scenario and model uncertainties, and predict nonlinearities that may arise or be amplified due to model parameterization/structure problems or scenario design.

Objetive

The overall objective of WaterTheft is to develop a novel approach to forecast adaptation surprises in complex human-water systems. Methods are empirically applied and tested in 3 living labs experiencing water theft, in Spain, Australia, and the US.

Methodology

WaterTheft will integrate data and methods from hydrology, economics, and ensemble techniques to:
1) forecast the nonlinear adaptive responses of individual agents over time;
2) forecast nonlinear spatial trends emerging from human interactions at the local to global level;
3) forecast nonlinear socio-hydrological phenomena emerging across complex human-water systems; and
4) quantify scenario and modeling uncertainties to forecast nonlinearities that may emerge or be amplified due to issues of model parameterization/structure or scenario design. These innovations will allow me to forecast the emergence of nonlinearities and track their impact across coupled human-water systems, thus discovering adaptation surprises and their drivers.

Human Behavior

Human interactions

Human-water systems

Uncertainty quantification and Grand Ensemble

WaterTheft

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Project

Introduction

Objetive

Methodology

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Funding Entity

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Partners