Unlocking local knowledge for global water reanalysis

A new research initiative funded by Schmidt Sciences has been launched to advance the integration of local knowledge and community-generated data into global water system models. The project, titled “Unlocking Local Knowledge Production for Global Water Reanalysis”, seeks to create a transformational framework that supports the use of under-utilized local information in large-scale hydrological modelling and analysis.

The project will focus on increasing the readiness and usability of data collected through volunteer monitoring, citizen observations, and local knowledge systems. By leveraging technologies such as semantic data models and machine learning, the research team will design knowledge integration workflows capable of incorporating diverse data sources into global modelling frameworks. Particular attention will be given to quantifying and managing uncertainties associated with locally generated data.

The research will address a range of key hydrological variables, including precipitation, river stage, reservoir levels, groundwater levels, river discharge, soil moisture, and river water abstractions. The team will also develop a simulation system blueprint designed to support local and regional decision-making, while identifying and prioritizing critical gaps in locally available knowledge and data.

Field data collection and collaboration activities are planned in several regions where local knowledge plays a vital role in water management, including the Andes, Ghana, Ethiopia, Laos, and India.

The project brings together an international and interdisciplinary team of researchers and practitioners. Principal Investigators include: Wouter Buytaert (Imperial College London, Lead PI), Seifu Tilahun (International Water Management Institute, Lead PI), Ana Mijic (Imperial College London), Sara Bonetti (EPFL), Athanasios Paschalis (University of Cyprus), Boris Ochoa-Tocachi (ATUK), Rossella Arcucci (Imperial College London), Patricio Crespo (University of Cuenca), Fabian Drenkhan (PUCP Lima), Samuel Agyei-Mensah (University of Ghana), Brahma Vishwakarma (Indian Institute of Science Bangalore).

CHANGE Lab is actively involved in the project, contributing expertise in ecohydrological modeling. Through this collaboration, the initiative aims to strengthen the connection between local observations and global-scale water intelligence, ultimately improving water monitoring, modelling, and decision-making worldwide.

More info on the project and other inititives within the Schmidt Sciences Virtual Institute for Earth’s Water (VIEW) can be found here.