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

Crochemore, Louise ; Isberg, Kristina ; Pimentel, Rafael ; Pineda, Luis ; Hasan, Abdulghani LU and Arheimer, Berit (2019) In Hydrological Sciences Journal / Journal des Sciences Hydrologiques
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... (More)
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 (Less)
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author
publishing date
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Contribution to journal
publication status
epub
subject
keywords
open data, river flow, global hydrology, quality control, time series
in
Hydrological Sciences Journal / Journal des Sciences Hydrologiques
publisher
International Association of Hydrological Sciences
DOI
10.1080/02626667.2019.1659509
language
English
LU publication?
no
id
3de551f9-d995-4fd4-bc4e-c7d0bb5d4dcb
date added to LUP
2019-09-17 13:50:04
date last changed
2019-09-19 14:23:14
@article{3de551f9-d995-4fd4-bc4e-c7d0bb5d4dcb,
  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.<br/><br/>Keywords: open data, river flow, global hydrology, quality control, time series},
  author       = {Crochemore, Louise and Isberg, Kristina and Pimentel, Rafael and Pineda, Luis and Hasan, Abdulghani and Arheimer, Berit},
  language     = {eng},
  month        = {09},
  publisher    = {International Association of Hydrological Sciences},
  series       = {Hydrological Sciences Journal / Journal des Sciences Hydrologiques},
  title        = {Lessons learnt from checking the quality of openly accessible river flow data worldwide},
  url          = {http://dx.doi.org/10.1080/02626667.2019.1659509},
  doi          = {10.1080/02626667.2019.1659509},
  year         = {2019},
}