Water resources data, models and decisions: international expert opinion on knowledge management for an uncertain but resilient future
Author(s) -
Sarah Ward,
D. Scott Borden,
Amos T. Kabobah,
Abdul Nasirudeen Fatawu,
Xavier Francis Mwinkom
Publication year - 2018
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2018.104
Subject(s) - delphi method , expert elicitation , computer science , knowledge management , identification (biology) , adaptive management , management science , decision support system , water resources , data science , environmental resource management , operations research , data mining , engineering , geography , economics , ecology , botany , artificial intelligence , meteorology , biology
© 2019 The Authors. Assessing the resilience of water resources systems requires knowledge of properties and performance, which depends on data availability and use within models and decision making. Connections between data, models and decision making are crucial to plan for uncertainty and invest in interventions. To explore international perceptions of these connections, we conducted a threeround Delphi survey with an expert panel (see Supplementary material, available with the online version of this paper). Consensus and divergence existed within and between countries on ability to manage data, modelling and decision making, with the most consensus seen on use of hydrometric databases. There was a wide range of models and tools utilised by participants and a shift occurred between first and second rounds to a preference for trying new modelling. There was consensus between and within all countries that every data type was important. River flow data consistently scored highest. Access to data and models primarily impacted evaluating future capacity, planning under uncertainty, policy implementation and conflict resolution. The panel called for reviewing existing and developing new policy, collaborative research and available funding all focusing on water resources data-model-decision integration. Findings offer a strategic view on knowledge management regarding connections between data, models and decision making through identification of consensus areas for future focus and dissensus areas for reprioritisation.
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