Articles | Volume 24, issue 3
https://doi.org/10.5194/hess-24-1031-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1031-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets?
Thibault Hallouin
CORRESPONDING AUTHOR
UCD Dooge Centre for Water Resources Research, School of Civil Engineering, University College Dublin, Dublin, Ireland
now at: National Centre for Atmospheric Science, Reading, UK
now at: Department of Meteorology, University of Reading, Reading, UK
Michael Bruen
UCD Dooge Centre for Water Resources Research, School of Civil Engineering, University College Dublin, Dublin, Ireland
UCD Earth Institute, University College Dublin, Dublin, Ireland
Fiachra E. O'Loughlin
UCD Dooge Centre for Water Resources Research, School of Civil Engineering, University College Dublin, Dublin, Ireland
UCD Earth Institute, University College Dublin, Dublin, Ireland
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Cited
16 citations as recorded by crossref.
- Probabilistic Predictions of Ecologically Relevant Hydrologic Indices Using a Hydrological Model J. Hernandez‐Suarez & A. Nejadhashemi 10.1029/2021WR031104
- Changes in the surface water – Groundwater interactions of the Murray-Darling basin (Australia) over the past half a century R. Crosbie et al. 10.1016/j.jhydrol.2023.129683
- Improving reservoir inflow prediction via rolling window and deep learning-based multi-model approach: case study from Ermenek Dam, Turkey H. Feizi et al. 10.1007/s00477-022-02185-3
- Climate Change Impacts on Irish River Flows: High Resolution Scenarios and Comparison with CORDEX and CMIP6 Ensembles C. Murphy et al. 10.1007/s11269-023-03458-4
- Simulated Changes in Seasonal and Low Flows with Climate Change for Irish Catchments H. Meresa et al. 10.3390/w14101556
- Hunting for Information in Streamflow Signatures to Improve Modelled Drainage R. Schneider et al. 10.3390/w14010110
- Future Change Projections of Extreme Floods at Catchment Scale and Hydrodynamic Response of Its Downstream Lake Based on Catchment‐Waterbody Relationship Simulation R. Hua et al. 10.1029/2022JD037972
- Propagation and Characteristics of Hydrometeorological Drought Under Changing Climate in Irish Catchments H. Meresa et al. 10.1029/2022JD038025
- Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data C. O'Sullivan et al. 10.1016/j.scitotenv.2021.151139
- Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships M. Eddy et al. 10.1002/eco.2387
- A novel multi-objective model calibration method for ecohydrological applications J. Hernandez-Suarez et al. 10.1016/j.envsoft.2021.105161
- Estimation of flood hydrographs in the ungauged mountainous watershed with Gray synthetic unit hydrograph model E. Bahrami et al. 10.1007/s12517-022-10029-1
- Far-future hydrology will differentially change the phosphorus transfer continuum P. Mellander et al. 10.1007/s44288-024-00067-5
- Flow Prediction Using Remotely Sensed Soil Moisture in Irish Catchments C. Yang & F. O’Loughlin 10.3390/w12082202
- Disaggregated monthly hydrological models can outperform daily models in providing daily flow statistics and extrapolate well to a drying climate A. John et al. 10.1016/j.jhydrol.2021.126471
- Using Deep Learning Algorithms for Intermittent Streamflow Prediction in the Headwaters of the Colorado River, Texas F. Forghanparast & G. Mohammadi 10.3390/w14192972
16 citations as recorded by crossref.
- Probabilistic Predictions of Ecologically Relevant Hydrologic Indices Using a Hydrological Model J. Hernandez‐Suarez & A. Nejadhashemi 10.1029/2021WR031104
- Changes in the surface water – Groundwater interactions of the Murray-Darling basin (Australia) over the past half a century R. Crosbie et al. 10.1016/j.jhydrol.2023.129683
- Improving reservoir inflow prediction via rolling window and deep learning-based multi-model approach: case study from Ermenek Dam, Turkey H. Feizi et al. 10.1007/s00477-022-02185-3
- Climate Change Impacts on Irish River Flows: High Resolution Scenarios and Comparison with CORDEX and CMIP6 Ensembles C. Murphy et al. 10.1007/s11269-023-03458-4
- Simulated Changes in Seasonal and Low Flows with Climate Change for Irish Catchments H. Meresa et al. 10.3390/w14101556
- Hunting for Information in Streamflow Signatures to Improve Modelled Drainage R. Schneider et al. 10.3390/w14010110
- Future Change Projections of Extreme Floods at Catchment Scale and Hydrodynamic Response of Its Downstream Lake Based on Catchment‐Waterbody Relationship Simulation R. Hua et al. 10.1029/2022JD037972
- Propagation and Characteristics of Hydrometeorological Drought Under Changing Climate in Irish Catchments H. Meresa et al. 10.1029/2022JD038025
- Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data C. O'Sullivan et al. 10.1016/j.scitotenv.2021.151139
- Predictability of flow metrics calculated using a distributed hydrologic model across ecoregions and stream classes: Implications for developing flow–ecology relationships M. Eddy et al. 10.1002/eco.2387
- A novel multi-objective model calibration method for ecohydrological applications J. Hernandez-Suarez et al. 10.1016/j.envsoft.2021.105161
- Estimation of flood hydrographs in the ungauged mountainous watershed with Gray synthetic unit hydrograph model E. Bahrami et al. 10.1007/s12517-022-10029-1
- Far-future hydrology will differentially change the phosphorus transfer continuum P. Mellander et al. 10.1007/s44288-024-00067-5
- Flow Prediction Using Remotely Sensed Soil Moisture in Irish Catchments C. Yang & F. O’Loughlin 10.3390/w12082202
- Disaggregated monthly hydrological models can outperform daily models in providing daily flow statistics and extrapolate well to a drying climate A. John et al. 10.1016/j.jhydrol.2021.126471
- Using Deep Learning Algorithms for Intermittent Streamflow Prediction in the Headwaters of the Colorado River, Texas F. Forghanparast & G. Mohammadi 10.3390/w14192972
Latest update: 23 Nov 2024
Short summary
A hydrological model was used to compare different parameterisation strategies in view of predicting ecologically relevant streamflow indices in 33 Irish catchments. Compared for 14 different periods, a strategy fitting simulated and observed streamflow indices yielded better performance than fitting simulated and observed streamflow, but it also yielded a less consistent ensemble of parameter sets, suggesting that these indices may not be hydrologically relevant for model parameterisation.
A hydrological model was used to compare different parameterisation strategies in view of...