The role of evidence-based information in regional operational water management in the Netherlands
Bibliographic Data
| ID | 12669132 |
|---|---|
| Authors | Michiel Pezij (0000-0003-3955-6412, University of Twente, corresponding author), Denie Augustijn (0000-0001-5841-5506, University of Twente), Dimmie Hendriks (Deltares), Dimmie M D Hendriks, Suzanne J M H Hulscher (0000-0002-8734-1830, University of Twente) |
| Year | 2018 |
| Volume | 93 |
| Pages | 75-82 |
| Publication date | 2018-12-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Science & Policy (JOURNAL) |
| Journal identifiers | ISSN: 1462-9011 • E-ISSN: 1873-6416 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.envsci.2018.12.025 |
| OpenAlex | W2907934323 |
| Language | EN |
| Citations received | 2 |
| References cited | 48 |
The integration of evidence-based information in operational water management is essential for robust decision-making. We investigated the current use of experiential and evidence-based information in Dutch regional operational water management. Interviews with operational water managers at regional water authorities in the Netherlands reveal that they use both evidence-based and experiential information for decision-making. While operational water management is shifting towards an evidence-based approach, experiential information is still important for decision-making. To fulfil the current information need, the operational water managers indicate they would like to have access to high-resolution spatial data, value-added products and tools for communication to stakeholders. We argue that hydrological models are suitable tools to support these needs. However, while several evidence-based information types are used by operational water managers, hydrological models are limitedly applied. Hydrological models are regarded as inaccurate for operational water management at desired spatial scales. Also, operational water managers often struggle to correctly interpret hydrological model output. We propose several means to overcome these problems, including educating operational water managers to interpret hydrological model output and selecting suitable indicators for evidence-based decision-making
Business · Data mining · Decision support system · Environmental resource management · Experiential learning · Information system · Operational efficiency · Process management · Computer Science · Engineering · Environmental Science · Flood Risk Assessment and Management · Hydrology and Watershed Management Studies · Water resources management and optimization · Marketing
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| Citations per year | 0.5 |
|---|---|
| Citation span | 2022 - 2025 (4) |
| Highly cited | No |