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Developing best practice for infilling daily river flow data

By Catherine L. Harvey, Harry Dixon and Jamie Hannaford


Complete river flow time series are indispensable to the sustainable management of water resources and even very short gaps can severely compromise data utility. Suitably-flagged flow estimates, derived via judicious infilling, are thus highly beneficial. The UK National River Flow Archive provides stewardship of and access to daily river flow records from over 1500 gauging stations and, whilst the majority are sensibly complete, historical validation reveals a significant quantity of gaps. A full assessment of the suitability of existing techniques for infilling such gaps is lacking. This paper therefore presents an appraisal of various simple infilling techniques, including\ud regression, scaling and equipercentile analysis, according to their ability to generate daily flow estimates for 25 representative UK gauging stations. All of the techniques rely upon data transfer from donor stations and results reveal that the equipercentile and multiple regression approaches perform best. Case studies offer further insight and an example of infilling is presented, along with areas of future study. The results demonstrate the potential for developing generic infilling methodologies to ensure a consistent and auditable approach towards infilling, which could find wider application both within the UK and internationally

Topics: Data and Information, Hydrology
Publisher: British Hydrological Society
Year: 2010
OAI identifier:

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  5. (1994). Filling gaps in runoff time-series in West-Africa.
  6. (2000). Group-based estimation of missing hydrological data: II. Application to streamflows.
  7. (2001). Groups and neural networks based streamflow data infilling procedures.
  8. (2008). High-flow and flood trends in a network of undisturbed catchments in the UK.
  9. (2008). Hydrological data. In:
  10. (1977). Infilling missing flow data. In:
  11. (1992). Low flow estimation in the United Kingdom. Institute of Hydrology Report
  12. (2010). Managing national hydrometric data: from data to information. In:
  13. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations.
  14. (1995). Models for extending streamflow data: a case study. doi
  15. (1970). River flow forecasting through conceptual models. Part 1: A discussion of principles. doi
  16. (2008). UK Hydrometric Register. Hydrological data UK series. Centre for Ecology & Hydrology.

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