Lessons learnt from checking the quality of openly accessible river flow data worldwide

Research output: Contribution to journalArticle

Abstract

Advances in open data science serve large-scale model developments and, subsequently, hydroclimate services. Local river flow observations are key in hydrology but data sharing remains limited due to unclear quality, or to political, economic or infrastructure reasons. This paper provides methods for quality checking openly accessible river-flow time series. Availability, outliers, homogeneity and trends were assessed in 21 586 time series from 13 data providers worldwide. We found a decrease in data availability since the 1980s, scarce open information in southern Asia, the Middle East and North and Central Africa, and significant river-flow trends in Africa, Australia, southwest Europe and Southeast Asia. We distinguish numerical outliers from high-flow peaks, and to integrate all investigated quality characteristics in a composite indicator. We stress the need to maintain existing gauging networks, and highlight opportunities in extending existing global databases, understanding drivers for trends and inhomogeneity, and in innovative acquisition methods in data-scarce regions.

Keywords: open data, river flow, global hydrology, quality control, time series

Details

Authors
  • Louise Crochemore
  • Kristina Isberg
  • Rafael Pimentel
  • Luis Pineda
  • Abdulghani Hasan
  • Berit Arheimer
External organisations
  • Swedish Meteorological and Hydrological Institute
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Engineering and Technology

Keywords

  • open data, river flow, global hydrology, quality control, time series
Original languageEnglish
JournalHydrological Sciences Journal / Journal des Sciences Hydrologiques
Publication statusE-pub ahead of print - 2019 Sep 17
Publication categoryResearch
Peer-reviewedYes
Externally publishedYes