SDG 17 - Partnerships for the Goals

SDG 17 - Partnerships for the Goals - 1. 5. Collaboration with NGOs for SDGs

Last modified: 24. November 2025


1. 5. Collaboration with NGOs for SDGs

MATE’s Department of Water Management and Climate Adaptation actively encourages students to apply their water-management knowledge within their local communities. Beyond teaching and research, the department aims to provide off-campus support for water conservation initiatives. Students enrolled in courses such as Agrometeorology and Water Management, Water Treatment and Utilization, Water Management, Water Quality, and Water Resources Engineering are motivated to share their skills and expertise outside the university. Particular emphasis is placed on working with communities in the watershed of the Rákos Stream, located near the Szent István Campus. To support public access to environmental information, the department makes data from its meteorological station in Gödöllő openly available and is developing a local soil-moisture estimation system to offer timely irrigation guidance based on ongoing research.

https://environment.uni-mate.hu/en/department-of-water-management-and-climate-adaptation

They have demonstrated their related expertise at a conference organized by local NGO’s (link). Data from their meteorological station in Gödöllő is publicly available (link), and they are also currently developing a local soil moisture estimation system, to provide timely information for irrigation to locals, based on the results of their research project (FK12480). 

Researchers froms MATE explores advanced climate‑modeling methods to improve predictions of the El Niño–Southern Oscillation (ENSO). By enhancing forecasting techniques, the project aims to increase lead times and accuracy, which is crucial for understanding and anticipating the impacts of climate change on global weather patterns. Better El Niño forecasts could help in preparing for extreme climate events such as droughts and floods, and support more resilient adaptation and mitigation strategies in sectors like agriculture, water management, and environmental conservation.

https://research.uni-mate.hu/hu/hir/-/content-viewer/forecasting-el-ni%C3%B1o-just-got-better-1/10850768 

A breakthrough forecast model that delivers the most accurate ENSO predictions to date, and the data-driven seasonal forecast can be accessed here: 

http://bodaimatlab.zapto.org:9988/webapps/home/session.html?app=ENSO%2FXDROMp_forecast_service_01_app