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Updated: Jul 10, 2026
12:44
Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Operationalising uncertainty in data and models for integrated water resources management
1Ministry of Transport, Public Works and Water Management, Institute for Inland Water Management and Waste Water Treatment/RIZA, P.O. Box 17, 8200 AA, Lelystad, The Netherlands. m.blind@riza.rws.minvenw.nl
Summary
This study addresses uncertainty in water resources management, developing tools for data and hydrological model uncertainties. It calls for integrating uncertainty analysis into decision-making for better water management.
Area of Science:
- Hydrology
- Water Resources Management
- Decision Science
Background:
- Uncertainty in water resources management stems from data, hydrological models, and decision-making contexts.
- Effective water management requires robust assessment and use of uncertainty information.
Purpose of the Study:
- To present tools and methods for assessing uncertainty in water resources management, focusing on data and model uncertainties.
- To discuss the integration of uncertainty and risk assessment into decision support processes.
- To outline future needs for adopting uncertainty analysis in water management.
Main Methods:
- Development of tools and methods for assessing uncertainty in data and hydrological models.
- Engagement in discussions on uncertainty and risk assessment for decision-making.
- Analysis of project results and experiences.
Main Results:
- The HarmoniRiB project produced tools and methods for assessing data and model uncertainties.
- Discussions highlighted the importance of uncertainty and risk assessment in water management decisions.
- Key conclusions were drawn regarding future needs for uncertainty analysis adoption.
Conclusions:
- Further scientific research is needed for specific uncertainties.
- Development of dedicated guidelines for operational use of uncertainty analysis is crucial.
- Capacity building at all levels is essential for successful adoption of uncertainty analysis in decision support.
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