Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-741-2019
© Author(s) 2019. 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-23-741-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2019
Research article |
| 08 Feb 2019
| 08 Feb 2019
Parameter-state ensemble thinning for short-term hydrological prediction
Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada
Vincent Fortin
Environment and Climate Change Canada, Montreal, Quebec, Canada
Alain Pietroniro
Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada
Man K. Yau
McGill University, Montreal, Quebec, Canada
Robert Leconte
Université de Sherbrooke, Sherbrooke, Quebec, Canada
Related authors
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Fuad Yassin, Saman Razavi, Mohamed Elshamy, Bruce Davison, Gonzalo Sapriza-Azuri, and Howard Wheater
Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, https://doi.org/10.5194/hess-23-3735-2019, 2019
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
EGUsphere, https://doi.org/10.5194/egusphere-2023-3040, https://doi.org/10.5194/egusphere-2023-3040, 2024
Short summary
Short summary
Forecasting river flows months in advance is crucial for many water sectors and society. In N. America, snowmelt is a key driver of river flow. This study presents a statistical workflow using snow data to forecast flows months ahead in N. American snow-fed rivers. Variations in predictability across the continent are evident, raising concerns about future river flow predictability amid a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Dikraa Khedhaouiria, Stéphane Bélair, Vincent Fortin, Guy Roy, and Franck Lespinas
Nonlin. Processes Geophys., 29, 329–344, https://doi.org/10.5194/npg-29-329-2022, https://doi.org/10.5194/npg-29-329-2022, 2022
Short summary
Short summary
This study introduces a well-known use of hybrid methods in data assimilation (DA) algorithms that has not yet been explored for precipitation analyses. Our approach combined an ensemble-based DA approach with an existing deterministically based DA. Both DA scheme families have desirable aspects that can be leveraged if combined. The DA hybrid method showed better precipitation analyses in regions with a low rate of assimilated surface observations, which is typically the case in winter.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
Short summary
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945, https://doi.org/10.5194/hess-25-4917-2021, https://doi.org/10.5194/hess-25-4917-2021, 2021
Short summary
Short summary
In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Bipin Kumar, Rahul Ranjan, Man-Kong Yau, Sudarsan Bera, and Suryachandra A. Rao
Atmos. Chem. Phys., 21, 12317–12329, https://doi.org/10.5194/acp-21-12317-2021, https://doi.org/10.5194/acp-21-12317-2021, 2021
Short summary
Short summary
The characteristics of turbulent clouds are affected by the entrainment of ambient dry air and its subsequent mixing. A turbulent flow generates vorticities of different intensities, and regions with high vorticity (HV) and low vorticity (LV) exist. This study provides a detailed analysis of different properties of turbulent flows and cloud droplets in the HV and LV regions in order to understand the impact of vorticity production on cloud microphysical and mixing processes.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Jean Bergeron, Gabriela Siles, Robert Leconte, Mélanie Trudel, Damien Desroches, and Daniel L. Peters
Hydrol. Earth Syst. Sci., 24, 5985–6000, https://doi.org/10.5194/hess-24-5985-2020, https://doi.org/10.5194/hess-24-5985-2020, 2020
Short summary
Short summary
We want to assess how well the Surface Water and Ocean Topography (SWOT) satellite mission will be able to provide information on lake surface water elevation and how much of an impact wind conditions (speed and direction) can have on these retrievals.
Sisi Chen, Lulin Xue, and Man-Kong Yau
Atmos. Chem. Phys., 20, 10111–10124, https://doi.org/10.5194/acp-20-10111-2020, https://doi.org/10.5194/acp-20-10111-2020, 2020
Short summary
Short summary
This study employs a parcel–DNS (direct numerical simulation) modeling framework to accurately resolve the aerosol–droplet–turbulence interactions in an ascending air parcel. The effect of turbulence, aerosol hygroscopicity, and aerosol mass loading on droplet growth and rain formation is investigated through a series of in-cloud seeding experiments in which hygroscopic particles were seeded near the cloud base.
Vincent Vionnet, Vincent Fortin, Etienne Gaborit, Guy Roy, Maria Abrahamowicz, Nicolas Gasset, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 24, 2141–2165, https://doi.org/10.5194/hess-24-2141-2020, https://doi.org/10.5194/hess-24-2141-2020, 2020
Short summary
Short summary
The 2013 Alberta flood in Canada was typical of late-spring floods in mountain basins combining intense precipitation with rapid melting of late-lying snowpack. Hydrological simulations of this event are mainly influenced by (i) the spatial resolution of the atmospheric forcing due to the best estimate of precipitation at the kilometer scale and changes in turbulent fluxes contributing to snowmelt and (ii) uncertainties in initial snow conditions at high elevations. Soil texture has less impact.
Ting-Chen Chen, Man-Kong Yau, and Daniel J. Kirshbaum
Geosci. Model Dev., 13, 1737–1761, https://doi.org/10.5194/gmd-13-1737-2020, https://doi.org/10.5194/gmd-13-1737-2020, 2020
Short summary
Short summary
Budget analysis helps to quantify the contribution of different terms in a selected prognostic equation within a numerical simulation. However, it is well acknowledged that non-negligible errors generally exist if such equations are analyzed in model post-processing. Here, we develop an inline budget retrieval method within the WRF model to give a high-accuracy budget closure. We also compare the inline and post-processed budgets to investigate the potential sources of errors in the latter.
Zhipeng Qu, Yi Huang, Paul A. Vaillancourt, Jason N. S. Cole, Jason A. Milbrandt, Man-Kong Yau, Kaley Walker, and Jean de Grandpré
Atmos. Chem. Phys., 20, 2143–2159, https://doi.org/10.5194/acp-20-2143-2020, https://doi.org/10.5194/acp-20-2143-2020, 2020
Short summary
Short summary
This study aims to better understand the mechanism of transport of water vapour through the mid-latitude tropopause. The results affirm the strong influence of overshooting convection on lower-stratospheric water vapour and highlight the importance of both dynamics and cloud microphysics in simulating water vapour distribution in the region of the upper troposphere–lower stratosphere.
Mohamed E. Elshamy, Daniel Princz, Gonzalo Sapriza-Azuri, Mohamed S. Abdelhamed, Al Pietroniro, Howard S. Wheater, and Saman Razavi
Hydrol. Earth Syst. Sci., 24, 349–379, https://doi.org/10.5194/hess-24-349-2020, https://doi.org/10.5194/hess-24-349-2020, 2020
Short summary
Short summary
Permafrost is an important feature of cold-region hydrology and needs to be properly represented in hydrological and land surface models (H-LSMs), especially under the observed and expected climate warming trends. This study aims to devise a robust, yet computationally efficient, initialization and parameterization approach for permafrost. We used permafrost observations from three sites along the Mackenzie River valley spanning different permafrost classes to test the validity of the approach.
Fuad Yassin, Saman Razavi, Mohamed Elshamy, Bruce Davison, Gonzalo Sapriza-Azuri, and Howard Wheater
Hydrol. Earth Syst. Sci., 23, 3735–3764, https://doi.org/10.5194/hess-23-3735-2019, https://doi.org/10.5194/hess-23-3735-2019, 2019
Zilefac Elvis Asong, Mohamed Elshamy, Daniel Princz, Howard Wheater, John Pomeroy, Alain Pietroniro, and Alex Cannon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-249, https://doi.org/10.5194/hess-2019-249, 2019
Publication in HESS not foreseen
Fuad Yassin, Saman Razavi, Jefferson S. Wong, Alain Pietroniro, and Howard Wheater
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-207, https://doi.org/10.5194/hess-2019-207, 2019
Preprint withdrawn
Mohammad Bizhanimanzar, Robert Leconte, and Mathieu Nuth
Hydrol. Earth Syst. Sci., 23, 2245–2260, https://doi.org/10.5194/hess-23-2245-2019, https://doi.org/10.5194/hess-23-2245-2019, 2019
Short summary
Short summary
Modelling of shallow water table fluctuations is usually carried out using physically based numerical models. These models have notable limitations regarding intensive required data and computational burden. This paper presents an alternative modelling approach for modelling of such cases by introducing modifications to the calculation of groundwater recharge and saturated flow of a conceptual hydrologic model.
William Quinton, Aaron Berg, Michael Braverman, Olivia Carpino, Laura Chasmer, Ryan Connon, James Craig, Élise Devoie, Masaki Hayashi, Kristine Haynes, David Olefeldt, Alain Pietroniro, Fereidoun Rezanezhad, Robert Schincariol, and Oliver Sonnentag
Hydrol. Earth Syst. Sci., 23, 2015–2039, https://doi.org/10.5194/hess-23-2015-2019, https://doi.org/10.5194/hess-23-2015-2019, 2019
Short summary
Short summary
This paper synthesizes nearly three decades of eco-hydrological field and modelling studies at Scotty Creek, Northwest Territories, Canada, highlighting the key insights into the major water flux and storage processes operating within and between the major land cover types of this wetland-dominated region of discontinuous permafrost. It also examines the rate and pattern of permafrost-thaw-induced land cover change and how such changes will affect the hydrology and water resources of the region.
Zilefac Elvis Asong, Howard Simon Wheater, John Willard Pomeroy, Alain Pietroniro, Mohamed Ezzat Elshamy, Daniel Princz, and Alex Cannon
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2018-128, https://doi.org/10.5194/essd-2018-128, 2018
Preprint withdrawn
Short summary
Short summary
Cold regions hydrology is very sensitive to the impacts of climate warming. We need better hydrological models driven by reliable climate data in order to assess hydrologic responses to climate change. Cold regions often have sparse surface observations, particularly at high elevations that generate a major amount of runoff. We produce a long-term dataset that can be used to better understand and represent the seasonal/inter-annual variability of hydrological fluxes and the the timing of runoff.
Sisi Chen, Man-Kong Yau, Peter Bartello, and Lulin Xue
Atmos. Chem. Phys., 18, 7251–7262, https://doi.org/10.5194/acp-18-7251-2018, https://doi.org/10.5194/acp-18-7251-2018, 2018
Short summary
Short summary
This paper introduces a sophisticated approach to incorporate the droplet hydrodynamic collision and condensation processes into a single DNS modeling framework. Arguably, this model provides a sophisticated approach to study the warm-rain initiation problem that has puzzled the cloud physics community for decades. The results show the increased condensation-mediated collisions when turbulence intensifies, indicating a positive impact of turbulence on droplet condensational–collisional growth.
Rachel Bazile, Marie-Amélie Boucher, Luc Perreault, and Robert Leconte
Hydrol. Earth Syst. Sci., 21, 5747–5762, https://doi.org/10.5194/hess-21-5747-2017, https://doi.org/10.5194/hess-21-5747-2017, 2017
Short summary
Short summary
Meteorological forecasting agencies constantly work on pushing the limit of predictability farther in time. However, some end users need proof that climate model outputs are ready to be implemented operationally. We show that bias correction is crucial for the use of ECMWF System4 forecasts for the studied area and there is a potential for the use of 1-month-ahead forecasts. Beyond this, forecast performance is equivalent to using past climatology series as inputs to the hydrological model.
Étienne Gaborit, Vincent Fortin, Xiaoyong Xu, Frank Seglenieks, Bryan Tolson, Lauren M. Fry, Tim Hunter, François Anctil, and Andrew D. Gronewold
Hydrol. Earth Syst. Sci., 21, 4825–4839, https://doi.org/10.5194/hess-21-4825-2017, https://doi.org/10.5194/hess-21-4825-2017, 2017
Short summary
Short summary
The work presents an original methodology for optimizing streamflow simulations with the distributed hydrological model GEM-Hydro.
While minimizing the computational time required for automatic calibration, the approach allows us to end up with a spatially coherent and transferable parameter set. The GEM-Hydro model is useful because it allows simulation of all physical components of the hydrological cycle in every part of a domain.
It proves to be competitive with other distributed models.
Jean M. Bergeron, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 20, 4375–4389, https://doi.org/10.5194/hess-20-4375-2016, https://doi.org/10.5194/hess-20-4375-2016, 2016
Short summary
Short summary
We want to know how combined snow water equivalent (SWE) and streamflow data assimilation (DA) impacts streamflow predictions and how it compares with DA of SWE only and streamflow only. Results show that streamflow DA positively impacts short-term streamflow forecasts, while the impact of SWE DA lasts over a much longer horizon. Simultaneous DA of both SWE and streamflow performs better than its individual counterparts at all forecast horizons.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
HESS Opinions: A few camels or a whole caravan?
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Evolution of river regime in the Mekong River basin over eight decades and role of dams in recent hydrologic extremes
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Projected future changes in cryosphere and hydrology of a mountainous catchment in the Upper Heihe River, China
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling
Modelling flood frequency and magnitude in a glacially conditioned, heterogeneous landscape: testing the importance of land cover and land use
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Skill of seasonal flow forecasts at catchment-scale: an assessment across South Korea
Modelling the regional sensitivity of snowmelt, soil moisture, and streamflow generation to climate over the Canadian Prairies using a basin classification approach
To what extent does river routing matter in hydrological modeling?
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
An advanced tool integrating failure and sensitivity analysis into novel modeling of the stormwater flood volume
airGRteaching: an open-source tool for teaching hydrological modeling with R
To What Extent Do Extreme Storm Events Change Future Flood Hazards?
Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
Short summary
A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary
Short summary
Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
Short summary
Short summary
Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
Short summary
Short summary
In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
Short summary
Short summary
It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Franziska Maria Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
EGUsphere, https://doi.org/10.5194/egusphere-2024-864, https://doi.org/10.5194/egusphere-2024-864, 2024
Short summary
Short summary
We compare the catchment forcing data provided in large-sample datasets, namely the Caravan dataset and three of the original CAMELS datasets (US, BR, GB). We show that the differences affect hydrological model performance and that the data quality in the Caravan dataset is lower than the one in the CAMELS datasets, both for precipitation and potential evapotranspiration. We want to raise awareness of the lower data quality in Caravan and we suggest possible improvements for the Caravan dataset.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
Short summary
Short summary
Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
Short summary
Short summary
This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
Short summary
Short summary
To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
EGUsphere, https://doi.org/10.5194/egusphere-2024-629, https://doi.org/10.5194/egusphere-2024-629, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
Short summary
Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
Short summary
Short summary
In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
Short summary
Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
Short summary
Short summary
This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
Short summary
Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
Short summary
Short summary
We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Short summary
Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
Short summary
How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Huy Dang and Yadu Pokhrel
EGUsphere, https://doi.org/10.5194/egusphere-2023-3158, https://doi.org/10.5194/egusphere-2023-3158, 2024
Short summary
Short summary
By examining basin-wide simulations of the river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River Basin (MRB) over the long-term; however, dams have largely altered the seasonality of Mekong’s flow regime and annual flooding patterns at major downstream areas in recent years. These findings could help rethink the planning of future dams and water resource management in the MRB.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
Short summary
Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary
Short summary
Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
EGUsphere, https://doi.org/10.5194/egusphere-2023-3043, https://doi.org/10.5194/egusphere-2023-3043, 2023
Short summary
Short summary
An integrated cryospheric-hydrologic model, FLEX-Cryo, was developed, considered glaciers, snow cover, frozen soil, and their dynamic impacts on hydrology. We utilized the model to simulate the future changes in cryosphere and hydrology in Hulu catchment. Our projections showed that the two glaciers will melt out around 2050; snow cover will reduce; and permafrost will degrade. For hydrology, runoff will decrease after glacier melt out; and permafrost degradation will increase baseflow.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
Short summary
Short summary
Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
Short summary
Short summary
Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
Short summary
Short summary
An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn E. Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-258, https://doi.org/10.5194/hess-2023-258, 2023
Revised manuscript accepted for HESS
Short summary
Short summary
Wouldn't it be nice to have both the accuracy of neural networks (NNs) and the interpretability of process-based models (PBMs)? Differentiable modeling gives you the best of both worlds by connecting NNs with PBMs. However, there was previously a major issue that iterative solution schemes would run into memory use trouble. This paper presents an operator called adjoint, which liberates all the iterative solvers. This is the first time adjoint is applied to large-scale hydrologic modeling.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
Short summary
Short summary
This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
EGUsphere, https://doi.org/10.5194/egusphere-2023-2169, https://doi.org/10.5194/egusphere-2023-2169, 2023
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (one or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
Short summary
Short summary
This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
Short summary
Short summary
This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
Short summary
Short summary
The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
Short summary
Short summary
A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
Short summary
Short summary
Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969, https://doi.org/10.5194/egusphere-2023-1969, 2023
Short summary
Short summary
Due to climate change, flooding is expected to become more frequent globally in the coming decades. Locally, storm-induced channel geometry changes can drastically affect flood hazards, yet rivers are mostly treated as static elements in flood studies. This study tried to gain an understanding of the effects of major storm events on future flood hazards, promoting a framework for incorporating channel conveyance adjustments into flood hazard assessment.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
Short summary
Short summary
This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emilio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
EGUsphere, https://doi.org/10.5194/egusphere-2023-1755, https://doi.org/10.5194/egusphere-2023-1755, 2023
Short summary
Short summary
The authors compared different regionalization methods for river flow prediction in watersheds with few data. We collected data on precipitation, evapotranspiration, river flow, and geographical and climatic factors for 126 catchments in the Paraná state, Brazil. The regionalization method based on physiographic-climatic similarity showed to be the most robust for predicting daily and Q95 reference flow. We also found patterns in data, grouping locations based on similarities.
Cited articles
Abaza, M., Anctil, F., Fortin, V., and Turcotte, R.: A comparison of the
Canadian global and regional meteorological ensemble prediction systems for
short-term hydrological forecasting, Mon. Weather Rev., 141, 3462–3476, 2013.
Agriculture and Agri-Food Canada: National Ecological Framework, digital
media, available at: http://sis.agr.gc.ca/cansis/nsdb/ecostrat/index.html
(last access: 6 January 2019), 2015.
Asch, M., Bocquet, M., and Nodet, M.: Data assimilation: methods, algorithms,
and applications, in: vol. 11, SIAM, Philadelphia, 2016.
Bard, Y.: Nonlinear parameter estimation, in: vol. 513, Academic Press, New York, 1974.
Beck, M. B.: Water quality modeling: a review of the analysis of uncertainty,
Water Resour. Res., 23, 1393–1442, 1987.
Beven, K.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, 1993.
Beven, K. and Binley, A.: The future of distributed models: model calibration
and uncertainty prediction, Hydrol. Process., 6, 227–246, 1992.
Bi, H., Ma, J., Qin, S., and Zhang, H.: Simultaneous estimation of soil moisture
and hydraulic parameters using residual resampling particle filter, Sci. China
Earth Sci., 57, 824–838, 2014.
Biau, G., Cérou, F., and Guyader, A.: New insights into Approximate Bayesian
Computation, Annales de l'Institut Henri Poincaré, Probabilités et
Statistiques, 51, 376–403, 2015.
Brown, J. D., Demargne, J., Seo, D.-J., and Liu, Y.: The Ensemble Verification
System (EVS): A software tool for verifying ensemble forecasts of
hydrometeorological and hydrologic variables at discrete locations, Environ.
Model. Softw., 25, 854–872, 2010.
Carrera, M. L., Bélair, S., and Bilodeau, B.: The Canadian Land Data
Assimilation System (CaLDAS): Description and Synthetic Evaluation Study, J.
Hydrometeorol., 16, 1293–1314, 2015.
Côté, J., Gravel, S., Méthot, A., Patoine, A., Roch, M., and
Staniforth, A.: The operational CMC-MRB global environmental multiscale (GEM)
model. Part I: Design considerations and formulation, Mon. Weather Rev.,
126, 1373–1395, 1998a.
Crins, W. J., Gray, P. A., Uhligh, P. W., and Wester, M. C.: The Ecosystems of
Ontario, Part 1: Ecozones and Ecoregions, Tech. Rep. SIB TER IMA R-01, Ontario
Ministry of Natural Resources, Peterborough, Ontario, 2009.
Davison, B., Fortin, V., Pietroniro, A., Yau, M. K., and Leconte, R.:
Parameter-state ensemble data assimilation using Approximate Bayesian Computing
for short-term hydrological prediction, Hydrol. Earth Syst. Sci. Discuss.,
https://doi.org/10.5194/hess-2017-482, in review, 2017.
Demargne, J., Brown, J., Liu, Y., Seo, D.-J., Wu, L., Toth, Z., and Zhu, Y.:
Diagnostic verification of hydrometeorological and hydrologic ensembles, Atmos.
Sci. Lett., 11, 114–122, 2010.
Dingman, S. L.: Physical Hydrology, 2nd Edn., Prentice-Hall Inc., Upper Saddle
River, New Jersey, 2002.
Drécourt, J.-P., Madsen, H., and Rosbjerg, D.: Calibration framework for a
Kalman filter applied to a groundwater model, Adv. Water Resour., 29, 719–734, 2006.
Erfani, A., Frenette, R., Gagnon, N., Charron, M., Beauregard, S., Giguère,
A., and Parent, A.: The New Regional Ensemble prediction System (REPS) at
15 km horizontal grid spacing (from version 1.1.0 to 2.0.1), Tech. rep.,
Meteorological Research Branch, National Predictions Development, and National
Operations Divistions at the Canadian Meteorological Center, Environment Canada,
Dorval, Quebec, 2014.
Gupta, H. V., Wagener, T., and Liu, Y.: Reconciling theory with observations:
elements of a diagnostic approach to model evaluation, Hydrol. Process., 22, 3802–3813, 2008.
Jackson, T. J., Bindlish, R., Cosh, M. H., Zhao, T., Starks, P. J., Bosch, D.
D., Seyfried, M., Moran, M. S., Goodrich, D. C., Kerr, Y. H., and Leroux, D.:
Validation of soil moisture and ocean salinity (SMOS) soil moisture over
watershed networks in the US, IEEE T. Geosci. Remote, 50, 1530–1543, 2012.
Kouwen, N. and Mousavi, S.: WATFLOOD/SPL9 hydrological model & flood forecasting
system, Mathematical Models of Large Watershed Hydrology, edited by: Singh, V.
and Frevert, D., Water Resource Publications, LLC, Highlands Ranch, Colorado, 649–685, 2002.
Krzysztofowicz, R.: The case for probabilistic forecasting in hydrology, J.
Hydrol., 249, 2–9, 2001.
Labarre, D., Grivel, E., Berthoumieu, Y., Todini, E., and Najim, M.: Consistent
estimation of autoregressive parameters from noisy observations based on two
interacting Kalman filters, Signal Process., 86, 2863–2876, 2006.
Lall, U. and Sharma, A.: A nearest neighbor bootstrap for resampling hydrologic
time series, Water Resour. Res., 32, 679–693, 1996.
Lespinas, F., Fortin, V., Roy, G., Rasmussen, P., and Stadnyk, T.: Performance
Evaluation of the Canadian Precipitation Analysis (CaPA), J. Hydrometeorol.,
16, 2045–2064, 2015.
Liu, Y. and Gupta, H. V.: Uncertainty in hydrologic modeling: Toward an
integrated data assimilation framework, Water Resour. Res., 43, W07401,
https://doi.org/10.1029/2006WR005756, 2007.
Mackey, B. G., McKenney, D. W., Yang, Y.-Q., McMahon, J. P., and Hutchinson, M.
F.: Erratum: Site regions revisited: a climatic analysis of Hills' site regions
for the province of Ontario using a parametric method, Can. J. Forest Res.,
26, 1112, https://doi.org/10.1139/x26-038, 1996.
Mahfouf, J.-F., Brasnett, B., and Gagnon, S.: A Canadian precipitation analysis (CaPA)
project: Description and preliminary results, Atmos.-Ocean, 45, 1–17, 2007.
Matott, L. S., Babendreier, J. E., and Purucker, S. T.: Evaluating uncertainty
in integrated environmental models: A review of concepts and tools, Water
Resour. Res., 45, W06421, https://doi.org/10.1029/2008WR007301, 2009.
McKay, M. D., Beckman, R. J., and Conover, W. J.: A comparison of three methods
for selecting values of input variables in the analysis of output from a computer
code, Technometrics, 21, 239–245, 1979.
Mecklenburg, S., Drusch, M., Kerr, Y. H., Font, J., Martin-Neira, M., Delwart,
S., Buenadicha, G., Reul, N., Daganzo-Eusebio, E., Oliva, R., and Crapolicchio,
R.: ESA's soil moisture and ocean salinity mission: Mission performance and
operations, IEEE T. Geosci. Remote, 50, 1354–1366, 2012.
Moradkhani, H., Hsu, K.-L., Gupta, H., and Sorooshian, S.: Uncertainty assessment
of hydrologic model states and parameters: Sequential data assimilation using
the particle filter, Water Resour. Res., 41, W05012, https://doi.org/10.1029/2004WR003604, 2005a.
Moradkhani, H., Sorooshian, S., Gupta, H. V., and Houser, P. R.: Dual
state–parameter estimation of hydrological models using ensemble Kalman filter,
Adv. Water Resour., 28, 135–147, 2005b.
Natural Resources Canada: Land Cover, circa 2000 – Vector, digital media,
available at: ftp://ftp.maps.canada.ca/pub/nrcan_rncan/vector/geobase_lcc_csc//doc/archive/Land_Cover.doc
(last access: 4 February 2019), 2015.
Nie, S., Zhu, J., and Luo, Y.: Simultaneous estimation of land surface scheme
states and parameters using the ensemble Kalman filter: identical twin experiments,
Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, 2011.
Nott, D. J., Marshall, L., and Brown, J.: Generalized likelihood uncertainty
estimation (GLUE) and approximate Bayesian computation: What's the connection?,
Water Resour. Res., 48, W12602, https://doi.org/10.1029/2011WR011128, 2012.
Pietroniro, A., Fortin, V., Kouwen, N., Neal, C., Turcotte, R., Davison, B.,
Verseghy, D., Soulis, E. D., Caldwell, R., Evora, N., and Pellerin, P.:
Development of the MESH modelling system for hydrological ensemble forecasting
of the Laurentian Great Lakes at the regional scale, Hydrol. Earth Syst. Sci.,
11, 1279–1294, https://doi.org/10.5194/hess-11-1279-2007, 2007.
Qin, J., Liang, S., Yang, K., Kaihotsu, I., Liu, R., and Koike, T.: Simultaneous
estimation of both soil moisture and model parameters using particle filtering
method through the assimilation of microwave signal, J. Geophys. Res.-Atmos.,
114, D15103, https://doi.org/10.1029/2008JD011358, 2009.
Rakovec, O., Weerts, A. H., Sumihar, J., and Uijlenhoet, R.: Operational aspects
of asynchronous filtering for flood forecasting, Hydrol. Earth Syst. Sci., 19,
2911–2924, https://doi.org/10.5194/hess-19-2911-2015, 2015.
Ridler, M.-E., Madsen, H., Stisen, S., Bircher, S., and Fensholt, R.: Assimilation
of SMOS-derived soil moisture in a fully integrated hydrological and
soil–vegetation–atmosphere transfer model in Western Denmark, Water Resour.
Res., 50, 8962–8981, 2014.
Sadegh, M. and Vrugt, J. A.: Bridging the gap between GLUE and formal statistical
approaches: approximate Bayesian computation, Hydrol. Earth Syst. Sci., 17,
4831–4850, https://doi.org/10.5194/hess-17-4831-2013, 2013.
Sadegh, M. and Vrugt, J. A.: Approximate bayesian computation using markov chain
monte carlo simulation: Dream (abc), Water Resour. Res., 50, 6767–6787, 2014.
Sadegh, M., Vrugt, J. A., Xu, C., and Volpi, E.: The stationarity paradigm
revisited: Hypothesis testing using diagnostics, summary metrics, and DREAM (ABC),
Water Resour. Res., 51, 9207–9231, 2015.
Shafii, M. and Tolson, B. A.: Optimizing hydrological consistency by incorporating
hydrological signatures into model calibration objectives, Water Resour. Res.,
51, 3796–3814, https://doi.org/10.1002/2014WR016520, 2015.
Soulis, E., Snelgrove, K., Kouwen, N., Seglenieks, F., and Verseghy, D.: Towards
closing the vertical water balance in Canadian atmospheric models: coupling of
the land surface scheme CLASS with the distributed hydrological model WATFLOOD,
Atmos.-Ocean, 38, 251–269, 2000.
Soulis, E., Craig, J., Fortin, V., and Liu, G.: A simple expression for the
bulk field capacity of a sloping soil horizon, Hydrol. Process., 25, 112–116, 2011.
Spence, C.: A paradigm shift in hydrology: Storage thresholds across scales
influence catchment runoff generation, Geogr. Compass, 4, 819–833, 2010.
Sun, L., Seidou, O., Nistor, I., and Liu, K.: Review of the Kalman-type
hydrological data assimilation, Hydrolog. Sci. J., 61, 2348–2366, 2016.
Sutcliffe, R.: Proterozoic geology of the Lake Superior area, in: Geology of
Ontario, vol. 4, Part 1, edited by: Thurston, P. C., Williams, H. R., Sutcliffe,
R. H., and Stott, G. M., Ontario Geological Survey, Toronto, 27–658, 1991.
Thiemann, M., Trosset, M., Gupta, H., and Sorooshian, S.: Bayesian recursive
parameter estimation for hydrologic models, Water Resour. Res., 37, 2521–2535, 2001.
Tolson, B. A. and Shoemaker, C. A.: Efficient prediction uncertainty approximation
in the calibration of environmental simulation models, Water Resour. Res., 44,
W04411, https://doi.org/10.1029/2007WR005869, 2008.
Velázquez, J. A., Petit, T., Lavoie, A., Boucher, M.-A., Turcotte, R.,
Fortin, V., and Anctil, F.: An evaluation of the Canadian global meteorological
ensemble prediction system for short-term hydrological forecasting, Hydrol.
Earth Syst. Sci., 13, 2221–2231, https://doi.org/10.5194/hess-13-2221-2009, 2009.
Verseghy, D. L.: CLASS – A Canadian land surface scheme for GCMs. I. Soil model,
Int. J. Climatol., 11, 111–133, 1991.
Verseghy, D. L.: CLASS – The Canadian land surface scheme (Version 3.5), Technical
Documentation (Version 1), Environment Canada, Downsview, 2011.
Verseghy, D. L., McFarlane, N., and Lazare, M.: CLASS – A Canadian land surface
scheme for GCMs, II. Vegetation model and coupled runs, Int. J. Climatol.,
13, 347–370, 1993.
Vrugt, J. A. and Beven, K. J.: Embracing equifinality with efficiency: Limits
of Acceptability sampling using the DREAM (LOA) algorithm, J. Hydrol., 559, 954–971, 2018.
Vrugt, J. A. and Sadegh, M.: Toward diagnostic model calibration and evaluation:
Approximate Bayesian computation, Water Resour. Res., 49, 4335–4345, 2013.
Vrugt, J. A., Bouten, W., Gupta, H. V., and Sorooshian, S.: Toward improved
identifiability of hydrologic model parameters: The information content of
experimental data, Water Resour. Res., 38, 1312, https://doi.org/10.1029/2001WR001118, 2002.
Vrugt, J. A., Diks, C. G., Gupta, H. V., Bouten, W., and Verstraten, J. M.:
Improved treatment of uncertainty in hydrologic modeling: Combining the
strengths of global optimization and data assimilation, Water Resour. Res.,
41, W01017, https://doi.org/10.1029/2004WR003059, 2005.
Wagener, T., McIntyre, N., Lees, M., Wheater, H., and Gupta, H.: Towards reduced
uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability
analysis, Hydrol. Process., 17, 455–476, https://doi.org/10.1002/hyp.1135, 2003.
Xie, X. and Zhang, D.: A partitioned update scheme for state-parameter estimation
of distributed hydrologic models based on the ensemble Kalman filter, Water
Resour. Res., 49, 7350–7365, 2013.
Zhang, Y., Vaze, J., Chiew, F. H., Teng, J., and Li, M.: Predicting hydrological
signatures in ungauged catchments using spatial interpolation, index model, and
rainfall–runoff modelling, J. Hydrol., 517, 936–948, 2014.
Short summary
This paper explores a new method of predicting streamflow using a complex model. It makes use of streamflow observations to reduce an existing ensemble of model runs for predictive purposes. The study illustrated that the method could work given the proper constraints, which were only possible if there was enough knowledge about how the river responded to precipitation in the previous months. Ideas were discussed to allow the method to be used in a way to predict future streamflow.
This paper explores a new method of predicting streamflow using a complex model. It makes use of...
