Model inter-comparison design for large-scale water quality models

Michelle TH van Vliet, Martina Flörke, John A. Harrison, Nynke Hofstra, Virginie Keller, Fulco Ludwig, J. Emiel Spanier, Maryna Strokal, Yoshihide Wada, Yingrong Wen, Richard J. Williams

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Several model inter-comparison projects (MIPs) have been carried out recently by the climate, hydrological, agricultural and other modelling communities to quantify modelling uncertainties and improve modelling systems. Here we focus on MIP design for large-scale water quality models. Water quality MIPs can be useful to improve our understanding of pollution problems and facilitate the development of harmonized estimates of current and future water quality. This can provide new opportunities for assessing robustness in estimates of water quality hotspots and trends, improve understanding of processes, pollution sources, water quality model uncertainties, and to identify priorities for water quality data collection and monitoring. Water quality MIP design should harmonize relevant model input datasets, use consistent spatial/temporal domains and resolutions, and similar output variables to improve understanding of water quality modelling uncertainties and provide harmonized water quality data that suit the needs of decision makers and other users.
Original languageEnglish (US)
Pages (from-to)59-67
Number of pages9
JournalCurrent Opinion in Environmental Sustainability
StatePublished - Feb 1 2019
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-18

ASJC Scopus subject areas

  • General Environmental Science
  • General Social Sciences


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