Articles | Volume 29, issue 15
https://doi.org/10.5194/hess-29-3615-2025
© Author(s) 2025. 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-29-3615-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Aug 2025
Research article |
| 08 Aug 2025
| 08 Aug 2025
Assessment of uncertainties in stage–discharge rating curves: a large-scale application to Quebec hydrometric network
Institut national de la recherche scientifique, Centre Eau, Terre et Environnement, Québec, G1K 9A9, Quebec, Canada
Guillaume Talbot
Institut national de la recherche scientifique, Centre Eau, Terre et Environnement, Québec, G1K 9A9, Quebec, Canada
Samuel Bolduc
Institut national de la recherche scientifique, Centre Eau, Terre et Environnement, Québec, G1K 9A9, Quebec, Canada
Claudine Fortier
Direction de l'hydrométrie et des prévisions hydrologiques, Ministère de l'Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs, Québec, G1R 5V7, Quebec, Canada
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Silvia Innocenti, Alain Mailhot, and Anne Frigon
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The relationship among the extreme rainfall probability distributions and the temporal scales of observation is characterized by the use of scaling models. The validity, the magnitude, and the spatial variability of the estimated scaling laws are evaluated for ~2700 stations in North America. Results demonstrate an improvement of extreme rainfall inference and provide evidence for the influence of both local geographical characteristics and regional climatic features on rainfall scaling.
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The relationship among the extreme rainfall probability distributions and the temporal scales of observation is characterized by the use of scaling models. The validity, the magnitude, and the spatial variability of the estimated scaling laws are evaluated for ~2700 stations in North America. Results demonstrate an improvement of extreme rainfall inference and provide evidence for the influence of both local geographical characteristics and regional climatic features on rainfall scaling.
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Subject: Water Resources Management | Techniques and Approaches: Uncertainty analysis
Actionable human–water system modelling under uncertainty
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Evaluating the impact of post-processing medium-range ensemble streamflow forecasts from the European Flood Awareness System
Coupled effects of observation and parameter uncertainty on urban groundwater infrastructure decisions
Disentangling sources of future uncertainties for water management in sub-Saharan river basins
Possibilistic response surfaces: incorporating fuzzy thresholds into bottom-up flood vulnerability analysis
Future hot-spots for hydro-hazards in Great Britain: a probabilistic assessment
Evaluation of impacts of future climate change and water use scenarios on regional hydrology
Planning for climate change impacts on hydropower in the Far North
Describing the interannual variability of precipitation with the derived distribution approach: effects of record length and resolution
Dissolved oxygen prediction using a possibility theory based fuzzy neural network
Projected changes in US rainfall erosivity
Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data
Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation
Robust global sensitivity analysis of a river management model to assess nonlinear and interaction effects
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On an improved sub-regional water resources management representation for integration into earth system models
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Prioritization of water management under climate change and urbanization using multi-criteria decision making methods
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Laura Gil-García, Nazaret M. Montilla-López, Carlos Gutiérrez-Martín, Ángel Sánchez-Daniel, Pablo Saiz-Santiago, Josué M. Polanco-Martínez, Julio Pindado, and Carlos Dionisio Pérez-Blanco
Hydrol. Earth Syst. Sci., 28, 4501–4520, https://doi.org/10.5194/hess-28-4501-2024, https://doi.org/10.5194/hess-28-4501-2024, 2024
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This paper presents an interdisciplinary model for quantifying uncertainties in water allocation under climate change. It combines climate, hydrological, and microeconomic experiments with a decision support system. Multi-model analyses reveal potential futures for water management policies, emphasizing non-linear climate responses. As illustrated in the Douro River basin, minor water allocation changes have significant economic impacts, stresssing the need for adaptation strategies.
Jitao Zhang, Dimitri Solomatine, and Zengchuan Dong
Hydrol. Earth Syst. Sci., 28, 3739–3753, https://doi.org/10.5194/hess-28-3739-2024, https://doi.org/10.5194/hess-28-3739-2024, 2024
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Faced with the problem of uncertainty in the field of water resources management, this paper proposes the Copula Multi-objective Robust Optimization and Probabilistic Analysis of Robustness (CM-ROPAR) approach to obtain robust water allocation schemes based on the uncertainty of drought and wet encounters and the uncertainty of inflow. We believe that this research article not only highlights the significance of the CM-ROPAR approach but also provides a new concept for uncertainty analysis.
Gwyneth Matthews, Christopher Barnard, Hannah Cloke, Sarah L. Dance, Toni Jurlina, Cinzia Mazzetti, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 2939–2968, https://doi.org/10.5194/hess-26-2939-2022, https://doi.org/10.5194/hess-26-2939-2022, 2022
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The European Flood Awareness System creates flood forecasts for up to 15 d in the future for the whole of Europe which are made available to local authorities. These forecasts can be erroneous because the weather forecasts include errors or because the hydrological model used does not represent the flow in the rivers correctly. We found that, by using recent observations and a model trained with past observations and forecasts, the real-time forecast can be corrected, thus becoming more useful.
Marina R. L. Mautner, Laura Foglia, and Jonathan D. Herman
Hydrol. Earth Syst. Sci., 26, 1319–1340, https://doi.org/10.5194/hess-26-1319-2022, https://doi.org/10.5194/hess-26-1319-2022, 2022
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Sensitivity analysis can be harnessed to evaluate effects of model uncertainties on planning outcomes. This study explores how observation and parameter uncertainty propagate through a hydrogeologic model to influence the ranking of decision alternatives. Using global sensitivity analysis and evaluation of aquifer management objectives, we evaluate how physical properties of the model and choice of observations for calibration can lead to variations in decision-relevant model outputs.
Alessandro Amaranto, Dinis Juizo, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 26, 245–263, https://doi.org/10.5194/hess-26-245-2022, https://doi.org/10.5194/hess-26-245-2022, 2022
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This study aims at designing water supply strategies that are robust against climate, social, and land use changes in a sub-Saharan river basin. We found that robustness analysis supports the discovery of policies enhancing the resilience of water resources systems, benefiting the agricultural, energy, and urban sectors. We show how energy sustainability is affected by water availability, while urban and irrigation resilience also depends on infrastructural interventions and land use changes.
Thibaut Lachaut and Amaury Tilmant
Hydrol. Earth Syst. Sci., 25, 6421–6435, https://doi.org/10.5194/hess-25-6421-2021, https://doi.org/10.5194/hess-25-6421-2021, 2021
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Response surfaces are increasingly used to identify the hydroclimatic conditions leading to a water resources system's failure. Partitioning the surface usually requires performance thresholds that are not necessarily crisp. We propose a methodology that combines the inherent uncertainty of response surfaces with the ambiguity of performance thresholds. The proposed methodology is illustrated with a multireservoir system in Canada for which some performance thresholds are imprecise.
Lila Collet, Shaun Harrigan, Christel Prudhomme, Giuseppe Formetta, and Lindsay Beevers
Hydrol. Earth Syst. Sci., 22, 5387–5401, https://doi.org/10.5194/hess-22-5387-2018, https://doi.org/10.5194/hess-22-5387-2018, 2018
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Floods and droughts cause significant damages and pose risks to lives worldwide. In a climate change context this work identifies hotspots across Great Britain, i.e. places expected to be impacted by an increase in floods and droughts. By the 2080s the western coast of England and Wales and northeastern Scotland would experience more floods in winter and droughts in autumn, with a higher increase in drought hazard, showing a need to adapt water management policies in light of climate change.
Seungwoo Chang, Wendy Graham, Jeffrey Geurink, Nisai Wanakule, and Tirusew Asefa
Hydrol. Earth Syst. Sci., 22, 4793–4813, https://doi.org/10.5194/hess-22-4793-2018, https://doi.org/10.5194/hess-22-4793-2018, 2018
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It is important to understand potential impacts of climate change and human water use on streamflow and groundwater levels. This study used climate models with an integrated hydrologic model to project future streamflow and groundwater level in Tampa Bay for a variety of future water use scenarios. Impacts of different climate projections on streamflow were found to be much stronger than the impacts of different human water use scenarios, but both were significant for groundwater projection.
Jessica E. Cherry, Corrie Knapp, Sarah Trainor, Andrea J. Ray, Molly Tedesche, and Susan Walker
Hydrol. Earth Syst. Sci., 21, 133–151, https://doi.org/10.5194/hess-21-133-2017, https://doi.org/10.5194/hess-21-133-2017, 2017
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We know that climate is changing quickly in the Far North (the Arctic and sub-Arctic). Hydropower continues to grow in this region because water resources are perceived to be plentiful. However, with changes in glacier extent and permafrost, and more extreme events, will those resources prove reliable into the future? This study amasses the evidence that quantitative hydrology modeling and uncertainty assessment have matured to the point where they should be used in water resource planning.
Claudio I. Meier, Jorge Sebastián Moraga, Geri Pranzini, and Peter Molnar
Hydrol. Earth Syst. Sci., 20, 4177–4190, https://doi.org/10.5194/hess-20-4177-2016, https://doi.org/10.5194/hess-20-4177-2016, 2016
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We show that the derived distribution approach is able to characterize the interannual variability of precipitation much better than fitting a probabilistic model to annual rainfall totals, as long as continuously gauged data are available. The method is a useful tool for describing temporal changes in the distribution of annual rainfall, as it works for records as short as 5 years, and therefore does not require any stationarity assumption over long periods.
Usman T. Khan and Caterina Valeo
Hydrol. Earth Syst. Sci., 20, 2267–2293, https://doi.org/10.5194/hess-20-2267-2016, https://doi.org/10.5194/hess-20-2267-2016, 2016
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This paper contains a new two-step method to construct fuzzy numbers using observational data. In addition an existing fuzzy neural network is modified to account for fuzzy number inputs. This is combined with possibility-theory based intervals to train the network. Furthermore, model output and a defuzzification technique is used to estimate the risk of low Dissolved Oxygen so that water resource managers can implement strategies to prevent the occurrence of low Dissolved Oxygen.
M. Biasutti and R. Seager
Hydrol. Earth Syst. Sci., 19, 2945–2961, https://doi.org/10.5194/hess-19-2945-2015, https://doi.org/10.5194/hess-19-2945-2015, 2015
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We estimate future changes in US erosivity from the most recent ensemble projections of daily and monthly rainfall accumulation. The expectation of overall increase in erosivity is confirmed by these calculations, but a quantitative assessment is marred by large uncertainties. Specifically, the uncertainty in the method of estimation of erosivity is more consequential than that deriving from the spread in climate simulations, and leads to changes of uncertain sign in parts of the south.
M. C. Peel, R. Srikanthan, T. A. McMahon, and D. J. Karoly
Hydrol. Earth Syst. Sci., 19, 1615–1639, https://doi.org/10.5194/hess-19-1615-2015, https://doi.org/10.5194/hess-19-1615-2015, 2015
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We present a proof-of-concept approximation of within-GCM uncertainty using non-stationary stochastic replicates of monthly precipitation and temperature projections and investigate the impact of within-GCM uncertainty on projected runoff and reservoir yield. Amplification of within-GCM variability from precipitation to runoff to reservoir yield suggests climate change impact assessments ignoring within-GCM uncertainty would provide water resources managers with an unjustified sense of certainty
T. A. McMahon, M. C. Peel, and D. J. Karoly
Hydrol. Earth Syst. Sci., 19, 361–377, https://doi.org/10.5194/hess-19-361-2015, https://doi.org/10.5194/hess-19-361-2015, 2015
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Here we assess GCM performance from a hydrologic perspective. We identify five better performing CMIP3 GCMs that reproduce grid-scale climatological statistics of observed precipitation and temperature over global land regions for future hydrologic simulation. GCM performance in reproducing observed mean and standard deviation of annual precipitation, mean annual temperature and mean monthly precipitation and temperature was assessed and ranked, and five better performing GCMs were identified.
L. J. M. Peeters, G. M. Podger, T. Smith, T. Pickett, R. H. Bark, and S. M. Cuddy
Hydrol. Earth Syst. Sci., 18, 3777–3785, https://doi.org/10.5194/hess-18-3777-2014, https://doi.org/10.5194/hess-18-3777-2014, 2014
L. Zhuo, M. M. Mekonnen, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 18, 2219–2234, https://doi.org/10.5194/hess-18-2219-2014, https://doi.org/10.5194/hess-18-2219-2014, 2014
C. A. Scott, S. Vicuña, I. Blanco-Gutiérrez, F. Meza, and C. Varela-Ortega
Hydrol. Earth Syst. Sci., 18, 1339–1348, https://doi.org/10.5194/hess-18-1339-2014, https://doi.org/10.5194/hess-18-1339-2014, 2014
N. Voisin, H. Li, D. Ward, M. Huang, M. Wigmosta, and L. R. Leung
Hydrol. Earth Syst. Sci., 17, 3605–3622, https://doi.org/10.5194/hess-17-3605-2013, https://doi.org/10.5194/hess-17-3605-2013, 2013
D. Zhu, D. Z. Peng, and I. D. Cluckie
Hydrol. Earth Syst. Sci., 17, 1445–1453, https://doi.org/10.5194/hess-17-1445-2013, https://doi.org/10.5194/hess-17-1445-2013, 2013
B. L. Harding, A. W. Wood, and J. R. Prairie
Hydrol. Earth Syst. Sci., 16, 3989–4007, https://doi.org/10.5194/hess-16-3989-2012, https://doi.org/10.5194/hess-16-3989-2012, 2012
J.-S. Yang, E.-S. Chung, S.-U. Kim, and T.-W. Kim
Hydrol. Earth Syst. Sci., 16, 801–814, https://doi.org/10.5194/hess-16-801-2012, https://doi.org/10.5194/hess-16-801-2012, 2012
S. Quiroga, Z. Fernández-Haddad, and A. Iglesias
Hydrol. Earth Syst. Sci., 15, 505–518, https://doi.org/10.5194/hess-15-505-2011, https://doi.org/10.5194/hess-15-505-2011, 2011
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Short summary
Rating curves are used to estimate flow from recorded stage at hydrometric stations. Uncertainties in these flows are generally not estimated or reported. This paper proposed an approach to develop rating curves and to assess the corresponding uncertainties in estimated flow that can be readily applied to large-scale hydrometric networks. The mean standard deviations of estimated flows are of the order of 6.5 %. Uncertainties increase significantly for low stages and can reach values larger than 20 %.
Rating curves are used to estimate flow from recorded stage at hydrometric stations....
