Felipe Fileni, Hayley Fowler, Elizabeth Lewis, Fiona McLay, Longzhi Yang
{"title":"A quality-control framework for sub-daily flow and level data for hydrological modelling in Great Britain","authors":"Felipe Fileni, Hayley Fowler, Elizabeth Lewis, Fiona McLay, Longzhi Yang","doi":"10.2166/nh.2023.045","DOIUrl":null,"url":null,"abstract":"Abstract The absence of an accessible and quality-assured national flow dataset is a limiting factor in sub-daily hydrological modelling in Great Britain. The recent development of measuring authority APIs and projects such as the Floods and Droughts Research Infrastructure (FDRI) programme aim to facilitate access to such data. Basic quality-control (QC) of 15-minute data is performed by the data collection authorities and the National River Flow Archive (NRFA). Still, there is a need for a comprehensible and verifiable quality control methodology. This paper presents an initial assessment of the available data and examines what needs to be done for applicability of the data at national scale. The 15-minute flow series has many inconsistencies, and there are also inconsistencies with the NRFA Annual Maximum values. When producing a QCed dataset, decisions regarding the retention of data values need to be taken and recorded. Furthermore, QC should remove and rectify erroneous values, such as negative and above world record flows; and an assessment of homogeneity and truncated values in the stations could be beneficial to flag suspect data. The complex chain for production and changeability of flow and level data makes data curation and governance imperative to assure the longevity of the dataset.","PeriodicalId":13096,"journal":{"name":"Hydrology Research","volume":"46 1","pages":"0"},"PeriodicalIF":2.6000,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/nh.2023.045","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The absence of an accessible and quality-assured national flow dataset is a limiting factor in sub-daily hydrological modelling in Great Britain. The recent development of measuring authority APIs and projects such as the Floods and Droughts Research Infrastructure (FDRI) programme aim to facilitate access to such data. Basic quality-control (QC) of 15-minute data is performed by the data collection authorities and the National River Flow Archive (NRFA). Still, there is a need for a comprehensible and verifiable quality control methodology. This paper presents an initial assessment of the available data and examines what needs to be done for applicability of the data at national scale. The 15-minute flow series has many inconsistencies, and there are also inconsistencies with the NRFA Annual Maximum values. When producing a QCed dataset, decisions regarding the retention of data values need to be taken and recorded. Furthermore, QC should remove and rectify erroneous values, such as negative and above world record flows; and an assessment of homogeneity and truncated values in the stations could be beneficial to flag suspect data. The complex chain for production and changeability of flow and level data makes data curation and governance imperative to assure the longevity of the dataset.
期刊介绍:
Hydrology Research provides international coverage on all aspects of hydrology in its widest sense, and welcomes the submission of papers from across the subject. While emphasis is placed on studies of the hydrological cycle, the Journal also covers the physics and chemistry of water. Hydrology Research is intended to be a link between basic hydrological research and the practical application of scientific results within the broad field of water management.