Reconstructed monthly river flows for Irish catchments 1766–2016. (8th October 2020)
- Record Type:
- Journal Article
- Title:
- Reconstructed monthly river flows for Irish catchments 1766–2016. (8th October 2020)
- Main Title:
- Reconstructed monthly river flows for Irish catchments 1766–2016
- Authors:
- O'Connor, Paul
Murphy, Conor
Matthews, Tom
Wilby, Robert L. - Abstract:
- Abstract: A 250‐year (1766–2016) archive of reconstructed river flows is presented for 51 catchments across Ireland. By leveraging meteorological data rescue efforts with gridded precipitation and temperature reconstructions, we develop monthly river flow reconstructions using the GR2M hydrological model and an Artificial Neural Network. Uncertainties in reconstructed flows associated with hydrological model structure and parameters are quantified. Reconstructions are evaluated by comparison with those derived from quality assured long‐term precipitation series for the period 1850–2000. Assessment of the reconstruction performance across all 51 catchments using metrics of MAE (9.3 mm/month; 13.3%), RMSE (12.6 mm/month; 18.0%) and mean bias (−1.16 mm/month; −1.7%), indicates good skill. Notable years with highest/lowest annual mean flows across all catchments were 1877/1855. Winter 2015/16 had the highest seasonal mean flows and summer 1826 the lowest, whereas autumn 1933 had notable low flows across most catchments. The reconstructed database will enable assessment of catchment specific responses to varying climatic conditions and extremes on annual, seasonal and monthly timescales. Abstract : Long‐term river flow records are fundamental for understanding the risk posed by drought and high flow events. Whilst in many locations long‐term flow records are lacking, precipitation data rescue efforts have made extended climatic data readily available and when employed in tandemAbstract: A 250‐year (1766–2016) archive of reconstructed river flows is presented for 51 catchments across Ireland. By leveraging meteorological data rescue efforts with gridded precipitation and temperature reconstructions, we develop monthly river flow reconstructions using the GR2M hydrological model and an Artificial Neural Network. Uncertainties in reconstructed flows associated with hydrological model structure and parameters are quantified. Reconstructions are evaluated by comparison with those derived from quality assured long‐term precipitation series for the period 1850–2000. Assessment of the reconstruction performance across all 51 catchments using metrics of MAE (9.3 mm/month; 13.3%), RMSE (12.6 mm/month; 18.0%) and mean bias (−1.16 mm/month; −1.7%), indicates good skill. Notable years with highest/lowest annual mean flows across all catchments were 1877/1855. Winter 2015/16 had the highest seasonal mean flows and summer 1826 the lowest, whereas autumn 1933 had notable low flows across most catchments. The reconstructed database will enable assessment of catchment specific responses to varying climatic conditions and extremes on annual, seasonal and monthly timescales. Abstract : Long‐term river flow records are fundamental for understanding the risk posed by drought and high flow events. Whilst in many locations long‐term flow records are lacking, precipitation data rescue efforts have made extended climatic data readily available and when employed in tandem with hydrological models such data can be used to generate historic flows. Here, we use such an approach to generate a 250 year (1766–2016) monthly flow reconstruction archive for 51 catchments in Ireland. … (more)
- Is Part Of:
- Geoscience data journal. Volume 8:Number 1(2021)
- Journal:
- Geoscience data journal
- Issue:
- Volume 8:Number 1(2021)
- Issue Display:
- Volume 8, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 8
- Issue:
- 1
- Issue Sort Value:
- 2021-0008-0001-0000
- Page Start:
- 34
- Page End:
- 54
- Publication Date:
- 2020-10-08
- Subjects:
- hydrological modelling -- Ireland -- reconstruction -- river flow -- time series
Earth sciences -- Research -- Periodicals
Earth sciences -- Data processing -- Periodicals
Earth sciences -- Documentation -- Periodicals
550.28557 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2049-6060 ↗
http://rmets.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2049-6060/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/gdj3.107 ↗
- Languages:
- English
- ISSNs:
- 2049-6060
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19893.xml