AI-DWM: Development of AI-based tools for Digital Watershed Management

Název projektu anglicky
AI-DWM: Development of AI-based tools for Digital Watershed Management
Anotace anglicky
The AI-DWM project aims to develop advanced AI-based tools for Digital Watershed Management by integrating real-time data, AI analysis, and simulation-driven forecasting to address pressing challenges in soil erosion, streamflow forecasting, and watershed management. The project focuses on three core objectives: (1) developing AI models for soil erosion vulnerability mapping, (2) applying state-of-the-art deep learning and transfer learning techniques for streamflow prediction, and (3) creating mechanism-informed AI models that incorporate watershed management practices. Despite the increasing global use of AI in hydrology, its application in the Czech Republic remains limited. This project will produce AI-based erosion maps, hybrid AI-process models for streamflow prediction, and decision-support tools for sustainable watershed management. In the short term, the project will deliver validated AI models, scientific publications, and capacity-building activities for researchers and stakeholders. In the long term, it will contribute to climate-resilient water management, improved policy-making, and international research cooperation.

Kategorie VaV
ZV - Základní výzkum
OECD FORD - hlavní obor
10503 - Water resources
OECD FORD - vedlejší obor
10501 - Hydrology
OECD FORD - další vedlejší obor
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CEP - odpovídající obory <br>(dle <a href="http://www.vyzkum.cz/storage/att/E6EF7938F0E854BAE520AC119FB22E8D/Prevodnik_oboru_Frascati.pdf">převodníku</a>)
DA - Hydrologie a limnologie

Důvěrnost údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Systémové označení dodávky dat
CEP25-MSM-LU-R
Datum dodání záznamu
12. 9. 2025

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