Imagine trying to split a single cake between two neighbors who don't agree on the rules, while the cake keeps shrinking. This project builds a smart digital tool that tracks exactly how much water is available and who needs it in real-time. It helps different countries share water fairly so that farms and power plants don't run dry during droughts.
Water scarcity and conflicting legal frameworks in transboundary basins lead to inefficient allocation and economic instability for agriculture and energy sectors.
A climate-sensitive Decision Support System (DSS) and a real-time data supply chain using machine learning to monitor water availability and demand.
If you are an irrigation provider dealing with unpredictable water shortages in Central Asia — this project developed a Decision Support System that predicts water availability and helps set fair tariffs to increase water use efficiency.
If you are a power plant operator dealing with changing river flows due to climate change — this project developed a real-time monitoring and modeling chain that helps manage water resources for energy production more effectively.
If you are a software firm dealing with the need for precise hydrological data in transboundary regions — this project developed a machine-learning based data supply chain that integrates demand and availability modeling.
Based on available project data, specific pricing or cost structures for the Decision Support System are not provided.
The project focuses on the Naryn and Kara Darya catchments, but the underlying data supply chain and machine-learning approach could potentially be adapted to other transboundary contexts.
Based on available project data, the project strives for open access to detailed information for local communities and civil society organizations, but specific commercial licensing terms are not listed.
The system is built on a reliable data supply chain based on real-time monitoring and integrated water demand and availability modeling.
The project period runs from 2023-01-01 to 2026-12-31, indicating the development and testing phase is currently active.
The consortium is well-balanced for a technology transfer project, featuring a 40% industry ratio with 6 industrial partners, 6 of whom are SMEs. This mix of 5 universities and 2 research centers alongside 6 companies suggests a strong bridge between academic hydrological modeling and practical commercial application across 9 countries.
Contact Technische Universität München regarding the Decision Support System for Central Asian water basins.
Contact us to connect with the WE-ACT consortium for pilot integration.
