Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2609-2020
© 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-24-2609-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Should altitudinal gradients of temperature and precipitation inputs be inferred from key parameters in snow-hydrological models?
Denis Ruelland
CORRESPONDING AUTHOR
CNRS, HydroSciences Montpellier, University of Montpellier, Place E. Bataillon, 34395 Montpellier CEDEX 5, France
Related authors
Nilo Lima-Quispe, Denis Ruelland, Antoine Rabatel, Waldo Lavado-Casimiro, and Thomas Condom
EGUsphere, https://doi.org/10.5194/egusphere-2024-2370, https://doi.org/10.5194/egusphere-2024-2370, 2024
Short summary
Short summary
This study estimated the water balance of Lake Titicaca using an integrated modeling framework that considers natural hydrological processes and net irrigation consumption. The proposed approach was implemented at a daily scale for a period of 35 years. This framework is able to simulate lake water levels with good accuracy over a wide range of hydroclimatic conditions. The findings demonstrate that a simple representation of hydrological processes is suitable for use in poorly-gauged regions.
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
Short summary
Short summary
This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
Short summary
Short summary
Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
Short summary
Short summary
This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
D. Ruelland, P. Hublart, and Y. Tramblay
Proc. IAHS, 371, 75–81, https://doi.org/10.5194/piahs-371-75-2015, https://doi.org/10.5194/piahs-371-75-2015, 2015
Short summary
Short summary
This study explores various hydrological projections while accounting for propagation uncertainties that arise from the methods used to generate climate projections and to simulate streamflow responses from four basins in the Mediterranean. Hydrological projections based on temperature ensemble scenarios generally agree on a runoff decrease during all seasons while projections mixing temperature and precipitation ensemble scenarios only agreed on a trend to runoff decrease during spring.
J. Fabre, D. Ruelland, A. Dezetter, and B. Grouillet
Proc. IAHS, 371, 43–48, https://doi.org/10.5194/piahs-371-43-2015, https://doi.org/10.5194/piahs-371-43-2015, 2015
Short summary
Short summary
Socio-economic and hydroclimatic data were integrated in a modeling framework to simulate water resources and demand. We successfully modeled water stress changes in space and time in two basins over the past 40 years, and explained changes in discharge by separating human and hydroclimatic trends. The framework was then applied under 4 combinations of climate and water use scenarios at the 2050 horizon. Results showed that projected water uses are not sustainable under climate change scenarios.
P. Hublart, D. Ruelland, I. García De Cortázar Atauri, and A. Ibacache
Proc. IAHS, 371, 203–209, https://doi.org/10.5194/piahs-371-203-2015, https://doi.org/10.5194/piahs-371-203-2015, 2015
Short summary
Short summary
This paper explores the reliability of low-flow simulations by conceptual models in a semi-arid, Andean catchment facing climate variability and water-use changes. A parsimonious hydrological model (GR4J) was combined with a model of irrigation water-use (IWU) to provide a new model of the catchment behavior (called GR4J/IWU). The original GR4J model and the GR6J model were also used as benchmarks to evaluate the usefulness explicitly accounting for water abstractions.
P. Hublart, D. Ruelland, A. Dezetter, and H. Jourde
Hydrol. Earth Syst. Sci., 19, 2295–2314, https://doi.org/10.5194/hess-19-2295-2015, https://doi.org/10.5194/hess-19-2295-2015, 2015
Short summary
Short summary
This study aimed at reducing structural uncertainty in the conceptual modelling of a semi-arid Andean catchment. A multiple-hypothesis framework was combined with a multi-criteria assessment scheme to characterize both model non-uniqueness and model inadequacy. This led to retaining eight model structures as a representation of the minimum structural uncertainty that could be obtained with this modelling framework.
J. Fabre, D. Ruelland, A. Dezetter, and B. Grouillet
Hydrol. Earth Syst. Sci., 19, 1263–1285, https://doi.org/10.5194/hess-19-1263-2015, https://doi.org/10.5194/hess-19-1263-2015, 2015
Short summary
Short summary
Socioeconomic and hydro-climatic data were used to model water resources, water demand and their interactions in two river basins. By using an integrative framework we successfully modeled variations in water stress over the past 40 years, accounting for climate and human pressures and changes in water management strategies over time. We explained past changes in discharge by separating human and hydro-climatic trends. This work will help assess future water stress and design adaptation plans.
Nilo Lima-Quispe, Denis Ruelland, Antoine Rabatel, Waldo Lavado-Casimiro, and Thomas Condom
EGUsphere, https://doi.org/10.5194/egusphere-2024-2370, https://doi.org/10.5194/egusphere-2024-2370, 2024
Short summary
Short summary
This study estimated the water balance of Lake Titicaca using an integrated modeling framework that considers natural hydrological processes and net irrigation consumption. The proposed approach was implemented at a daily scale for a period of 35 years. This framework is able to simulate lake water levels with good accuracy over a wide range of hydroclimatic conditions. The findings demonstrate that a simple representation of hydrological processes is suitable for use in poorly-gauged regions.
Frédéric Satgé, Denis Ruelland, Marie-Paule Bonnet, Jorge Molina, and Ramiro Pillco
Hydrol. Earth Syst. Sci., 23, 595–619, https://doi.org/10.5194/hess-23-595-2019, https://doi.org/10.5194/hess-23-595-2019, 2019
Short summary
Short summary
This paper assesses the potential of satellite precipitation estimates (SPEs) for precipitation measurement and hydrological and snow modelling. A total of 12 SPEs is considered to provide a global overview of available SPE accuracy for users interested in such datasets. Results show that, over poorly monitored regions, SPEs represent a very efficient alternative to traditional precipitation gauges to follow precipitation in time and space and for hydrological and snow modelling.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
Short summary
Short summary
Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
Short summary
Short summary
This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
D. Ruelland, P. Hublart, and Y. Tramblay
Proc. IAHS, 371, 75–81, https://doi.org/10.5194/piahs-371-75-2015, https://doi.org/10.5194/piahs-371-75-2015, 2015
Short summary
Short summary
This study explores various hydrological projections while accounting for propagation uncertainties that arise from the methods used to generate climate projections and to simulate streamflow responses from four basins in the Mediterranean. Hydrological projections based on temperature ensemble scenarios generally agree on a runoff decrease during all seasons while projections mixing temperature and precipitation ensemble scenarios only agreed on a trend to runoff decrease during spring.
J. Fabre, D. Ruelland, A. Dezetter, and B. Grouillet
Proc. IAHS, 371, 43–48, https://doi.org/10.5194/piahs-371-43-2015, https://doi.org/10.5194/piahs-371-43-2015, 2015
Short summary
Short summary
Socio-economic and hydroclimatic data were integrated in a modeling framework to simulate water resources and demand. We successfully modeled water stress changes in space and time in two basins over the past 40 years, and explained changes in discharge by separating human and hydroclimatic trends. The framework was then applied under 4 combinations of climate and water use scenarios at the 2050 horizon. Results showed that projected water uses are not sustainable under climate change scenarios.
P. Hublart, D. Ruelland, I. García De Cortázar Atauri, and A. Ibacache
Proc. IAHS, 371, 203–209, https://doi.org/10.5194/piahs-371-203-2015, https://doi.org/10.5194/piahs-371-203-2015, 2015
Short summary
Short summary
This paper explores the reliability of low-flow simulations by conceptual models in a semi-arid, Andean catchment facing climate variability and water-use changes. A parsimonious hydrological model (GR4J) was combined with a model of irrigation water-use (IWU) to provide a new model of the catchment behavior (called GR4J/IWU). The original GR4J model and the GR6J model were also used as benchmarks to evaluate the usefulness explicitly accounting for water abstractions.
P. Hublart, D. Ruelland, A. Dezetter, and H. Jourde
Hydrol. Earth Syst. Sci., 19, 2295–2314, https://doi.org/10.5194/hess-19-2295-2015, https://doi.org/10.5194/hess-19-2295-2015, 2015
Short summary
Short summary
This study aimed at reducing structural uncertainty in the conceptual modelling of a semi-arid Andean catchment. A multiple-hypothesis framework was combined with a multi-criteria assessment scheme to characterize both model non-uniqueness and model inadequacy. This led to retaining eight model structures as a representation of the minimum structural uncertainty that could be obtained with this modelling framework.
J. Fabre, D. Ruelland, A. Dezetter, and B. Grouillet
Hydrol. Earth Syst. Sci., 19, 1263–1285, https://doi.org/10.5194/hess-19-1263-2015, https://doi.org/10.5194/hess-19-1263-2015, 2015
Short summary
Short summary
Socioeconomic and hydro-climatic data were used to model water resources, water demand and their interactions in two river basins. By using an integrative framework we successfully modeled variations in water stress over the past 40 years, accounting for climate and human pressures and changes in water management strategies over time. We explained past changes in discharge by separating human and hydro-climatic trends. This work will help assess future water stress and design adaptation plans.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Learning landscape features from streamflow with autoencoders
On the use of streamflow transformations for hydrological model calibration
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Heavy-tailed flood peak distributions: What is the effect of the spatial variability of rainfall and runoff generation?
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
State updating in the Xin'anjiang Model: Joint assimilating streamflow and multi-source soil moisture data via Asynchronous Ensemble Kalman Filter with enhanced Error Models
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
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
Lack of robustness of hydrological models: A large-sample diagnosis and an attempt to identify the hydrological and climatic drivers
The Significance of the Leaf-Area-Index on the Evapotranspiration Estimation in SWAT-T for Characteristic Land Cover Types of Western Africa
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
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
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
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
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
Short summary
Short summary
The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
Short summary
Short summary
We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
Short summary
Short summary
Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
Short summary
Short summary
We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 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.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-181, https://doi.org/10.5194/hess-2024-181, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small compared to large catchments, and that spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show an effect. The results can improve estimations of occurrence probabilities of extreme floods.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a 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 the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 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.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-211, https://doi.org/10.5194/hess-2024-211, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping better prepare for and respond to floods.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
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.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-131, https://doi.org/10.5194/hess-2024-131, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
ET is computed from vegetation (plant transpiration) and soil (soil evaporation). In Western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented with the leaf-area-index (LAI). In this study, we evaluate the importance of LAI for the ET calculation. We take a close look at the LAI-ET interaction and show the relevance to consider both, LAI and ET. Our work contributes to the understanding of the processes of the terrestrial water cycle.
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.
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.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-57, https://doi.org/10.5194/hess-2024-57, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. In this work we investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analysis indicate that adding two vegetation is enough to improve the representation of evaporation, and the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
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.
Cited articles
Ahmed, S. and de Marsily, G.: Comparison of geostatistical methods for estimating transmissivity using data on transmissivity and specific capacity, Water Resour. Res., 23, 1717–1737, https://doi.org/10.1029/WR023i009p01717, 1987.
Andréassian, V. and Perrin, C.: On the ambiguous interpretation of the
Turc–Budyko nondimensional graph, Water Resour. Res., 48, W10601,
https://doi.org/10.1029/2012WR012532, 2012.
Bárdossy, A. and Pegram, G.: Interpolation of precipitation under topographic influence at different time scales, Water Resour. Res., 49,
4545–4565, https://doi.org/10.1002/wrcr.20307, 2013.
Barry, R. G. and Chorley, R. J.: Atmosphere, Weather and Climate, 9th Edn., London, Routledge, 516 pp., 2010.
Beck, H., van Dijk, A. I. J. M., de Roo, A., Miralles, D. G. McVicar, T. R.,
Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of
hydrologic model parameters, Water Resour. Res., 52, 3599–3622, https://doi.org/10.1002/2015WR018247, 2016.
Bergström, S.: Development of a snow routine for the HBV-2 model, Nord.
Hydrol., 6, 73–92, https://doi.org/10.2166/nh.1975.0006, 1975.
Berndt, C. and Haberlandt, U.: Spatial interpolation of climate variables in Northern Germany – Influence of temporal resolution and network density, J. Hydrol. Reg. Stud., 15, 184–202, https://doi.org/10.1016/j.ejrh.2018.02.002, 2018.
Dettinger, M.: Impacts in the third dimension, Nat. Geosci., 7, 166–167,
https://doi.org/10.1038/ngeo2096, 2014.
Deutsch, C. V.: Correcting for negative weights in ordinary kriging, Comput.
Geosci., 22, 765–773, https://doi.org/10.1016/0098-3004(96)00005-2, 1996.
Diggle, P. J. and Ribeiro, P. J.: Model-Based Geostatistics, in: Springer Series in Statistics, Springer, New York, NY, https://doi.org/10.1007/978-0-387-48536-2, 2007.
Dodson, J. and Marks, D.: Daily air temperature interpolated at high spatial resolution over a large mountainous region, Clim. Res. 8, 1–20, https://doi.org/10.3354/cr008001, 1997.
Douguédroit, A. and de Saintignon, M. F.: Les gradients de température et de précipitation en montagne, Rev. Geogr. Alp., 72,
225–240, https://doi.org/10.3406/rga.1984.2566, 1984.
Drogue, G., Humbert, J., Deraisme, J., Mahr, N., and Freslon, N.: A statistical topographic model using an omnidirectional parameterization of
the relief for mapping orographic rainfall, Int. J. Climatol., 22, 599–613,
https://doi.org/10.1002/joc.671, 2002.
Duan, Q., Sorooshian, S., and Gupta, V.: Optimal use of the SCE-UA global optimization method for calibrating watershed models, J. Hydrol., 158, 265–284, https://doi.org/10.1016/0022-1694(94)90057-4, 1994.
Duan, Q. Y., Sorooshian, S., and Gupta, V.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour. Res., 28,
1015–1031, https://doi.org/10.1029/91WR02985, 1992.
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.: The shuttle radar topography mission, Rev. Geophys., 45, RG2004,
https://doi.org/10.1029/2005RG000183, 2007.
Fortin, V., and Turcotte, R.: Le modèle hydrologique MOHYSE, Note de cours pour SCA7420, Université du Québec à Montréal, Département des sciences de la terre et de l'atmosphẽre, Québec, 2006.
Franz, K. J. and Karsten, L. R.: Calibration of a distributed snow model using MODIS snow covered area data, J. Hydrol., 494, 160–175, https://doi.org/10.1016/j.jhydrol.2013.04.026, 2013.
Frei, C.: Interpolation of temperature in a mountainous region using nonlinear profiles and non-Euclidean distances, Int. J. Climatolotol., 34,
1585–1605, https://doi.org/10.1002/joc.3786, 2014.
Frei, C. and Schär, C.: A precipitation climatology of the Alps from
high-resolution rain-gauge observations, Int. J. Climatol., 18, 873–900,
https://doi.org/10.1002/(SICI)1097-0088(19980630)18:8<873::AID-JOC255>3.0.CO;2-9, 1998.
Frey, S. and Holzmann H.: A conceptual, distributed snow redistribution model, Hydrol. Earth Syst. Sci., 19, 4517–4530, https://doi.org/10.5194/hess-19-4517-2015, 2015.
Gafurov, A. and Bárdossy, A.: Cloud removal methodology from MODIS snow
cover product, Hydrol. Earth Syst. Sci., 13, 1361–1373, https://doi.org/10.5194/hess-13-1361-2009, 2009.
Garavaglia, F., Le Lay, M., Gottardi, F., Garçon, R., Gailhard, J., Paquet, E., and Mathevet, T.: Impact of model structure on flow simulation
and hydrological realism from lumped to semi-distributed approach, Hydrol.
Earth Syst. Sci., 21, 3937–3952, https://doi.org/10.5194/hess-21-3937-2017, 2017.
Garen, D. C. and Marks, D.: Spatially distributed energy balance snowmelt modelling in a mountainous river basin: estimation of meteorological inputs and verification of model results, J. Hydrol., 315, 126–153, https://doi.org/10.1016/j.jhydrol.2005.03.026, 2005.
Gascoin, S., Hagolle, O., Huc, M., Jarlan, L., Dejoux, J.-F., Szczypta, C.,
Marti, R., and Sánchez, R.: A snow cover climatology for the Pyrenees from MODIS snow products, Hydrol. Earth Syst. Sci., 19, 2337–2351,
https://doi.org/10.5194/hess-19-2337-2015, 2015.
Goovaerts, P.: Geostatistical approaches for incorporating elevation into
the spatial interpolation of rainfall, J. Hydrol., 228, 113–129, https://doi.org/10.1016/S0022-1694(00)00144-X, 2000.
Gottardi, F., Obled, C., Gailhard, J., and Paquet, E.: Statistical reanalysis of precipitation fields based on ground network data and weather patterns: Application over French mountains, J. Hydrol., 432–433, 154–167,
https://doi.org/10.1016/j.jhydrol.2012.02.014, 2012.
Hall, D., Riggs, G., and Salomonson, V.: MODIS/Terra Snow Cover Daily L3 Global 500 m Grid V005, National Snow and Ice Data Center, Boulder, Colorado, USA, 2006.
Hall, D., Riggs, G., and Salomonson, V.: MODIS/Aqua Snow Cover Daily L3
Global 500 m Grid V005, National Snow and Ice Data Center, Boulder, Colorado, USA, 2007.
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., and New, M.: A European daily high-resolution gridded dataset of surface
temperature and precipitation, J. Geophys. Res., 113, D20119,
https://doi.org/10.1029/2008JD10201, 2008.
He, Z. H., Parajka, J., Tian, F. Q., and Blöschl, G.: Estimating degree-day factors from MODIS for snowmelt runoff modeling, Hydrol. Earth
Syst. Sci., 18, 4773–4789, https://doi.org/10.5194/hess-18-4773-2014, 2014.
Henn, B., Clark, M. P., Kavetski, D., McGurk, B., Painter, T. H., and Lundquist, J. D.: Combining snow, streamflow, and precipitation gauge observations to infer basin-mean precipitation, Water Resour. Res., 52, 8700–8723, https://doi.org/10.1002/2015WR018564, 2016.
Hock, R.: A distributed temperature-index ice- and snowmelt model including
potential direct solar radiation, J. Glaciol., 45, 101–111,
https://doi.org/10.3189/S0022143000003087, 1999.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol.,
282, 104–115, https://doi.org/10.1016/S0022-1694(03)00257-9, 2003.
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dynam., 35, 841–858, https://doi.org/10.1007/s00382-009-0698-1, 2010.
Hublart, P., Ruelland, D., Dezetter, A., and Jourde, H.: Reducing structural
uncertainty in conceptual hydrological modeling in the semi-arid Andes, Hydrol. Earth Syst. Sci., 19, 2295–2314, https://doi.org/10.5194/hess-19-2295-2015, 2015.
Hublart, P., Ruelland, D., Garcia de Cortázar-Atauri, I., Gascoin, S.,
Lhermitte, S., and Ibacache, A.: Reliability of lumped hydrological modelling in a semi-arid mountainous catchment facing water-use changes, Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, 2016.
Isotta, F. A., Frei, C., Weilguni, V., Percec Tadic, M., Lassègues, P., Rudolf, B., Pavan, V., Cacciamani, C., Antolini, G., Ratto, S. M., Munari, M., Micheletti, S., Bonati, V., Lussana, C., Ronchi, C., Panettieri, E., Marigo, G., and Vertacnik, G.: The climate of daily precipitation in the Alps: Development and analysis of a high-resolution grid dataset from pan-Alpine rain-gauge data, Int. J. Climatol., 34, 1657–1675, https://doi.org/10.1002/joc.3794, 2014.
Jarvis, C. H. and Stuart, N.: A comparison among strategies for interpolating maximum and minimum daily air temperatures. Part I: The selection of guiding topographic and land cover variables, J. Appl. Meteorol., 40, 1060–1074, https://doi.org/10.1175/1520-0450(2001)040<1060:ACASFI>2.0.CO;2, 2001.
Kuczera, G.: Efficient subspace probabilistic parameter optimization for catchment models, Water Resour. Res., 33, 177–185, https://doi.org/10.1029/96WR02671, 1997.
Leleu, I., Tonnelier, I., Puechberty, R., Gouin, P., Viquendi, I., Cobos, L., Foray, A., Baillon, M., and Ndima, P.-O.: Re-founding the national information system designed to manage and give access to hydrometric data, La Houille Blanche, 1, 25–32, https://doi.org/10.1051/lhb/2014004, 2014.
Le Moine, N., Andréassian, V., Perrin, C., and Michel, C.: How can
rainfall-runoff models handle intercatchment groundwater flows? Theoretical
study based on 1040 French catchments, Water Resour. Res., 43, W06428,
https://doi.org/10.1029/2006WR005608, 2007.
Le Moine, N., Hendrickx, F., Gailhard, J., Garçon, R., and Gottardi, F.:
Hydrologically aided interpolation of daily precipitation and temperature
fields in a mesoscale Alpine catchment, J. Hydrometeorol., 16, 2595–2618,
https://doi.org/10.1175/JHM-D-14-0162.1, 2015.
Ly, S., Charles, C., and Degré, A.: Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium, Hydrol. Earth Syst. Sci., 15, 2259–2274, https://doi.org/10.5194/hess-15-2259-2011, 2011.
Ly, S., Charles, C., and Degré, A.: Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological
modeling at watershed scale: A review, Biotechnol. Agron. Soc. Environ., 17,
392–406, 2013.
Masson, D. and Frei, C.: Spatial analysis of precipitation in a high-mountain region: exploring methods with multi-scale topographic predictors and circulation types, Hydrol. Earth Syst. Sci., 18, 4543–4563,
https://doi.org/10.5194/hess-18-4543-2014, 2014.
Naseer, A., Koike, T., Rasmy, M., Ushiyama, T., and Shrestha, M.: Distributed hydrological modeling framework for quantitative and spatial bias correction for rainfall, snowfall, and mixed-phase precipitation using vertical profile of temperature, J. Geophys. Res.-Atmos., 124, 4985–5009, https://doi.org/10.1029/2018JD029811, 2019.
Nicótina, L., Alessi Celegon, E., Rinaldo, A., and Marani, M.: On the
impact of rainfall patterns on the hydrologic response, Water Resour. Res.,
44, W12401, https://doi.org/10.1029/2007WR006654, 2008.
NSIDC: World Glacier Inventory, Version 1, NSIDC – National Snow and Ice Data Center, Boulder, Colorado, USA, https://doi.org/10.7265/N5/NSIDC-WGI-2012-02, 2012.
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil,
F., and Loumagne, C.: Which potential evapotranspiration input for a lumped
rainfall-runoff model? Part 2: towards a simple and efficient potential
evapotranspiration model for rainfall-runoff modelling, J. Hydrol., 303,
290–306, https://doi.org/10.1016/j.jhydrol.2004.08.025, 2005.
Oudin, L., Andréassian, V., Mathevet, T., Perrin, C., and Michel, C.:
Dynamic averaging of rainfall-runoff model simulations from complementary model parameterizations, Water Resour. Res., 42, W07410, https://doi.org/10.1029/2005WR004636, 2006.
Parajka, J. and Blöschl, G.: The value of MODIS snow cover data in validating and calibrating conceptual hydrologic models, J. Hydrol., 358,
240–258, https://doi.org/10.1016/j.jhydrol.2008.06.006, 2008.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289,
https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Rahman, K., Etienne, C., Gago-Silva, A., Maringanti, C., Beniston, M., and Lehmann, A.: Streamflow response to regional climate model output in the mountainous watershed: a case study from the Swiss Alps, Environ. Earth Sci., 72, 4357–4369, https://doi.org/10.1007/s12665-014-3336-0, 2014.
Riboust, P., Thirel, G., Le Moine, N., and Ribstein, P.: Revisiting a simple
degree-day model for integrating satellite data: implementation of SWE-SCA
hystereses, J. Hydrol. Hydromech., 67, 70–81, https://doi.org/10.2478/johh-2018-0004, 2019.
Rolland, C.: Spatial and seasonal variations of air temperature lapse rates in alpine regions, J. Climate, 16, 1032–1046, https://doi.org/10.1175/1520-0442, 2003.
Sevruk, B.: Regional dependency of precipitation–altitude relationship in
the Swiss Alps, Climatic Change, 36, 355–369, https://doi.org/10.1023/A:1005302626066, 1997.
Sevruk, B.: Hydrometeorology: rainfall measurement, gauges, in: Encyclopedia of Hydrological Sciences, Vol. 1, chap. 40, edited by: Anderson, M. G., Wiley & Sons Ltd., Chichester, UK, 529–535, 2005.
Shen, S. S. P., Dzikowski, P., Li, G. L., and Griffith, D.: Interpolation of
1961–1997 daily temperature and precipitation data onto Alberta polygons of
ecodistrict and soil landscapes of Canada, J. Appl. Meteorol., 40, 2162–2177, https://doi.org/10.1175/1520-0450(2001)040<2162:IODTAP>2.0.CO;2, 2001.
Spadavecchia, L. and Williams, M.: Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables?, Agr. Forest Meteorol., 149, 1105–1117, https://doi.org/10.1016/j.agrformet.2009.01.008, 2009.
Stahl, K., Moore, R. D., Floyer, J. A., Asplin, M. G., and McKendry, I. G.:
Comparison of approaches for spatial interpolation of daily air temperature
in a large region with complex topography and highly variable station density, Agr. Forest Meteorol., 139, 224–236, https://doi.org/10.1016/j.agrformet.2006.07.004, 2006.
Strasser, U., Bernhardt, M., Weber, M., Liston, G. E., and Mauser, W: Is snow sublimation important in the alpine water balance?, The Cryosphere, 2, 53–66, https://doi.org/10.5194/tc-2-53-2008, 2008.
Thirel, G., Salamon, P., Burek, P., and Kalas, M.: Assimilation of MODIS snow cover area data in a distributed hydrological model using the particle filter, Remote Sens., 5, 5825–5850, https://doi.org/10.3390/rs5115825, 2013.
Tobin, C., Nicótina, L., Parlange, M. B., Berne, A., and Rinaldo, A.:
Improved interpolation of meteorological forcings for hydrologic applications in a Swiss Alpine region, J. Hydrol., 401, 77–89, https://doi.org/10.1016/j.jhydrol.2011.02.010, 2011.
Turcotte, R., Fortin, L.-G., Fortin, V., Fortin, J.-P., and Villeneuve, J.-P.: Operational analysis of the spatial distribution and the temporal evolution of the snowpack water equivalent in southern Québec, Canada, Hydrol. Res., 38, 211–234, https://doi.org/10.2166/nh.2007.009, 2007.
USACE: Snow Hydrology: Summary Report of the Snow Investigation, North Pacific Division, Corps of Engineers, US Army, Portland, Oregon, 1956.
Valéry, A., Andréassian, V., and Perrin, C.: Inverting the hydrological cycle: when streamflow measurements help assess altitudinal
precipitation gradients in mountain areas, in: New approaches to hydrological prediction in data-sparse regions (Proc. of Symposium HS.2 at the Joint IAHS & IAH Convention, Hyderabad, India, September 2009), IAHS Publ., 333, 281–286, 2009.
Valéry, A., Andréassian, V., and Perrin, C.: Regionalization of
precipitation and air temperature over high-altitude catchments – learning
from outliers, Hydrolog. Sci. J., 55, 928–940, https://doi.org/10.1080/02626667.2010.504676, 2010.
Valéry, A., Andréassian, V., and Perrin, C.: As simple as possible but not simpler: What is useful in a temperature-based snow-accounting routine? Part 2 – Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments, J. Hydrol., 517, 1176–1187, https://doi.org/10.1016/j.jhydrol.2014.04.058, 2014.
WMO: Guide to hydrological practices. Volume I: Hydrology? From measurement
to hydrological information, 6th Edn., World Meteorological Organization, Geneva, 2008.
Zhang, F., Zhang, H., Hagen, S. C., Ye, M., Wang, D., Gui, D., Zeng, C., Tian, L., and Liu, J.: Snow cover and runoff modelling in a high mountain
catchment with scarce data: Effects of temperature and precipitation parameters, Hydrol. Process., 29, 52–65, https://doi.org/10.1002/hyp.10125, 2015.
Short summary
Interpolation methods accounting for elevation dependency from scattered gauges result in inaccurate inputs for snow-hydrological models. Altitudinal gradients of temperature and precipitation can be successfully inferred using an inverse snow-hydrological modelling approach. This approach can significantly improve the simulation of snow cover and streamflow dynamics through more parsimonious parametrization.
Interpolation methods accounting for elevation dependency from scattered gauges result in...