Articles | Volume 9, issue 12
https://doi.org/10.5194/gmd-9-4491-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-4491-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
21 Dec 2016
Model description paper |
| 21 Dec 2016
StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction
Aurélien Gallice
School of Architecture, Civil and Environmental Engineering (ENAC),
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
SLF, WSL Institute for Snow and Avalanche Research, 7260 Davos,
Switzerland
Tristan Brauchli
School of Architecture, Civil and Environmental Engineering (ENAC),
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Francesco Comola
School of Architecture, Civil and Environmental Engineering (ENAC),
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Michael Lehning
School of Architecture, Civil and Environmental Engineering (ENAC),
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
SLF, WSL Institute for Snow and Avalanche Research, 7260 Davos,
Switzerland
Hendrik Huwald
School of Architecture, Civil and Environmental Engineering (ENAC),
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Related authors
A. Gallice, B. Schaefli, M. Lehning, M. B. Parlange, and H. Huwald
Hydrol. Earth Syst. Sci., 19, 3727–3753, https://doi.org/10.5194/hess-19-3727-2015, https://doi.org/10.5194/hess-19-3727-2015, 2015
Short summary
Short summary
This study presents a new model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country. Contrary to the other approaches developed to date, which are usually based on standard regression techniques, our model makes use of the understanding that we have about the physics controlling stream temperature. On top of its accuracy being comparable to that of the other models, it can be used to gain some knowledge about the stream temperature dynamics
Sonja Wahl, Benjamin Walter, Franziska Aemisegger, Luca Bianchi, and Michael Lehning
EGUsphere, https://doi.org/10.5194/egusphere-2024-745, https://doi.org/10.5194/egusphere-2024-745, 2024
Short summary
Short summary
Wind-driven airborne transport of snow is a frequent phenomenon in snow-covered regions and a process difficult to study in the field as it is unfolding over large distances. Thus, we use a ring wind tunnel with infinite fetch positioned in a cold-laboratory to study the evolution of the shape and size of airborne snow. With the help of stable water isotope analyses, we identify the hitherto unobserved process of airborne snow metamorphism that leads to snow particle rounding and growth.
Dylan Reynolds, Louis Quéno, Michael Lehning, Mahdi Jafari, Justine Berg, Tobias Jonas, Michael Haugeneder, and Rebecca Mott
EGUsphere, https://doi.org/10.5194/egusphere-2024-489, https://doi.org/10.5194/egusphere-2024-489, 2024
Short summary
Short summary
Accurate information about atmospheric variables are needed to produce simulations of mountain snowpacks. Here we present a model which can represent processes that shape mountain snowpack, focusing on the accumulation of snow. Simulations show that this model can simulate the complex path that a snowflake takes towards the ground, and that this leads to differences in the distribution of snow by the end of the winter. Overall, this model shows promise to improve forecasts of snow in mountains.
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, Nander Wever, Adrien Michel, Michael Lehning, and Pierre-Erik Isabelle
EGUsphere, https://doi.org/10.5194/egusphere-2023-3012, https://doi.org/10.5194/egusphere-2023-3012, 2024
Short summary
Short summary
Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow (ROS) events lead to the formation of melt-freeze layers and that preferential flow is an important water transport mechanism in the subcanopy snowpack. Simulations with SNOWPACK generally show good agreement with observations, except for the reproduction of melt-freeze layers. This was improved by a time-based intercepted snow densification function, which also modulates ROS-induced runoff.
Riccardo Barella, Mathias Bavay, Francesca Carletti, Nicola Ciapponi, Valentina Premier, and Carlo Marin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2892, https://doi.org/10.5194/egusphere-2023-2892, 2024
Preprint archived
Short summary
Short summary
Unlocking the potential of melting calorimetry, traditionally confined to school labs, this paper demonstrates its application in the field for accurate measurement of liquid water content in snow. Dispelling misconceptions about measurement uncertainty, it provide a robust protocol and quantifies associated uncertainties. The findings endorse the broader adoption of melting calorimetry for quantification of snow liquid water content in operational context.
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068, https://doi.org/10.5194/gmd-16-5049-2023, https://doi.org/10.5194/gmd-16-5049-2023, 2023
Short summary
Short summary
The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.
Hongxiang Yu, Guang Li, Benjamin Walter, Michael Lehning, Jie Zhang, and Ning Huang
The Cryosphere, 17, 639–651, https://doi.org/10.5194/tc-17-639-2023, https://doi.org/10.5194/tc-17-639-2023, 2023
Short summary
Short summary
Snow cornices lead to the potential risk of causing snow avalanche hazards, which are still unknown so far. We carried out a wind tunnel experiment in a cold lab to investigate the environmental conditions for snow cornice accretion recorded by a camera. The length growth rate of the cornices reaches a maximum for wind speeds approximately 40 % higher than the threshold wind speed. Experimental results improve our understanding of the cornice formation process.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary
Short summary
Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
Short summary
Short summary
This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
Short summary
Short summary
High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Short summary
Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
Short summary
Short summary
This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Adrien Michel, Bettina Schaefli, Nander Wever, Harry Zekollari, Michael Lehning, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, https://doi.org/10.5194/hess-26-1063-2022, 2022
Short summary
Short summary
This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.
Mathias Bavay, Michael Reisecker, Thomas Egger, and Daniela Korhammer
Geosci. Model Dev., 15, 365–378, https://doi.org/10.5194/gmd-15-365-2022, https://doi.org/10.5194/gmd-15-365-2022, 2022
Short summary
Short summary
Most users struggle with the configuration of numerical models. This can be improved by relying on a GUI, but this requires a significant investment and a specific skill set and does not fit with the daily duties of model developers, leading to major maintenance burdens. Inishell generates a GUI on the fly based on an XML description of the required configuration elements, making maintenance very simple. This concept has been shown to work very well in our context.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
Short summary
Short summary
A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Benjamin Walter, Hendrik Huwald, Josué Gehring, Yves Bühler, and Michael Lehning
The Cryosphere, 14, 1779–1794, https://doi.org/10.5194/tc-14-1779-2020, https://doi.org/10.5194/tc-14-1779-2020, 2020
Short summary
Short summary
We applied a horizontally mounted low-cost precipitation radar to measure velocities, frequency of occurrence, travel distances and turbulence characteristics of blowing snow off a mountain ridge. Our analysis provides a first insight into the potential of radar measurements for determining blowing snow characteristics, improves our understanding of mountain ridge blowing snow events and serves as a valuable data basis for validating coupled numerical weather and snowpack simulations.
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
Short summary
Short summary
Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
Adrien Michel, Tristan Brauchli, Michael Lehning, Bettina Schaefli, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 24, 115–142, https://doi.org/10.5194/hess-24-115-2020, https://doi.org/10.5194/hess-24-115-2020, 2020
Short summary
Short summary
This study constitutes the first comprehensive analysis of river
temperature in Switzerland combined with discharge and key meteorological variables, such as air temperature and precipitation. It is also the first study to discuss the large-scale seasonal behaviour of stream temperature in Switzerland. This research shows the clear increase of river temperature in Switzerland over the last few decades and may serve as a solid reference for future climate change scenario simulations.
Varun Sharma, Louise Braud, and Michael Lehning
The Cryosphere, 13, 3239–3260, https://doi.org/10.5194/tc-13-3239-2019, https://doi.org/10.5194/tc-13-3239-2019, 2019
Short summary
Short summary
Snow surfaces, under the action of wind, form beautiful shapes such as waves and dunes. This study is the first ever study to simulate these shapes using a state-of-the-art numerical modelling tool. While these beautiful and ephemeral shapes on snow surfaces are fascinating from a purely aesthetic point of view, they are also critical in regulating the transfer of heat and mass between the atmosphere and snowpacks, thus being of huge importance to the Earth system.
James M. Thornton, Gregoire Mariethoz, Tristan J. Brauchli, and Philip Brunner
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-181, https://doi.org/10.5194/tc-2019-181, 2019
Manuscript not accepted for further review
Short summary
Short summary
Meltwater runoff from steep mountainous terrain holds great societal and ecological importance. Predicting snow dynamics in unmonitored areas and/or under changed climate requires computer simulations. Yet variability in alpine snow patterns poses a considerable challenge. Here we combine existing tools with high-resolution observations to both constrain and quantify the uncertainty in historical simulations. Snowpack evolution was satisfactorily reproduced and uncertainty substantially reduced.
Anselm Köhler, Jan-Thomas Fischer, Riccardo Scandroglio, Mathias Bavay, Jim McElwaine, and Betty Sovilla
The Cryosphere, 12, 3759–3774, https://doi.org/10.5194/tc-12-3759-2018, https://doi.org/10.5194/tc-12-3759-2018, 2018
Short summary
Short summary
Snow avalanches show complicated flow behaviour, characterized by several flow regimes which coexist in one avalanche. In this work, we analyse flow regime transitions where a powder snow avalanche transforms into a plug flow avalanche by incorporating warm snow due to entrainment. Prediction of such a transition is very important for hazard mitigation, as the efficiency of protection dams are strongly dependent on the flow regime, and our results should be incorporated into avalanche models.
Varun Sharma, Francesco Comola, and Michael Lehning
The Cryosphere, 12, 3499–3509, https://doi.org/10.5194/tc-12-3499-2018, https://doi.org/10.5194/tc-12-3499-2018, 2018
Short summary
Short summary
The Thorpe-Mason (TM) model describes how an ice grain sublimates during aeolian transport. We revisit this classic model using simple numerical experiments and discover that for many common scenarios, the model is likely to underestimate the amount of ice loss. Extending this result to drifting and blowing snow using high-resolution turbulent flow simulations, the study shows that current estimates for ice loss due to sublimation in regions such as Antarctica need to be significantly updated.
Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning
The Cryosphere, 12, 3137–3160, https://doi.org/10.5194/tc-12-3137-2018, https://doi.org/10.5194/tc-12-3137-2018, 2018
Short summary
Short summary
A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.
Christian Gabriel Sommer, Nander Wever, Charles Fierz, and Michael Lehning
The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, https://doi.org/10.5194/tc-12-2923-2018, 2018
Short summary
Short summary
Wind packing is how wind produces hard crusts at the surface of the snowpack. This is relevant for the local mass balance in polar regions. However, not much is known about this process and it is difficult to capture its high spatial and temporal variability. A wind-packing event was measured in Antarctica. It could be quantified how drifting snow leads to wind packing and generates barchan dunes. The documentation of these deposition dynamics is an important step in understanding polar snow.
Martin Beniston, Daniel Farinotti, Markus Stoffel, Liss M. Andreassen, Erika Coppola, Nicolas Eckert, Adriano Fantini, Florie Giacona, Christian Hauck, Matthias Huss, Hendrik Huwald, Michael Lehning, Juan-Ignacio López-Moreno, Jan Magnusson, Christoph Marty, Enrique Morán-Tejéda, Samuel Morin, Mohamed Naaim, Antonello Provenzale, Antoine Rabatel, Delphine Six, Johann Stötter, Ulrich Strasser, Silvia Terzago, and Christian Vincent
The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, https://doi.org/10.5194/tc-12-759-2018, 2018
Short summary
Short summary
This paper makes a rather exhaustive overview of current knowledge of past, current, and future aspects of cryospheric issues in continental Europe and makes a number of reflections of areas of uncertainty requiring more attention in both scientific and policy terms. The review paper is completed by a bibliography containing 350 recent references that will certainly be of value to scholars engaged in the fields of glacier, snow, and permafrost research.
Thomas Grünewald, Fabian Wolfsperger, and Michael Lehning
The Cryosphere, 12, 385–400, https://doi.org/10.5194/tc-12-385-2018, https://doi.org/10.5194/tc-12-385-2018, 2018
Short summary
Short summary
Snow farming is the conservation of snow during summer. Large snow piles are covered with a sawdust insulation layer, reducing melt and guaranteeing a specific amount of available snow in autumn, independent of the weather conditions. Snow volume changes in two heaps were monitored, showing that about a third of the snow was lost. Model simulations confirmed the large effect of the insulation on energy balance and melt. The model can now be used as a tool to examine future snow-farming projects.
Nander Wever, Francesco Comola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 21, 4053–4071, https://doi.org/10.5194/hess-21-4053-2017, https://doi.org/10.5194/hess-21-4053-2017, 2017
Short summary
Short summary
The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the
linkage between the snow cover, soil and discharge in the stream network. Simulations of soil moisture and streamflow were performed and compared with observations. It was found that discharge at the catchment outlet during intense rainfall or snowmelt periods correlates positively with the initial soil moisture state, in both measurements and simulations.
Sebastian Würzer, Nander Wever, Roman Juras, Michael Lehning, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 1741–1756, https://doi.org/10.5194/hess-21-1741-2017, https://doi.org/10.5194/hess-21-1741-2017, 2017
Short summary
Short summary
We discuss a dual-domain water transport model in a physics-based snowpack model to account for preferential flow (PF) in addition to matrix flow. So far no operationally used snow model has explicitly accounted for PF. The new approach is compared to existing water transport models and validated against in situ data from sprinkling and natural rain-on-snow (ROS) events. Our work demonstrates the benefit of considering PF in modelling hourly snowpack runoff, especially during ROS conditions.
Anna Haberkorn, Nander Wever, Martin Hoelzle, Marcia Phillips, Robert Kenner, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 585–607, https://doi.org/10.5194/tc-11-585-2017, https://doi.org/10.5194/tc-11-585-2017, 2017
Short summary
Short summary
The effects of permafrost degradation on rock slope stability in the Alps affect people and infrastructure. Modelling the evolution of permafrost is therefore of great importance. However, the snow cover has generally not been taken into account in model studies of steep, rugged rock walls. Thus, we present a distributed model study on the influence of the snow cover on rock temperatures. The promising results are discussed against detailed rock temperature measurements and snow depth data.
Christoph Marty, Sebastian Schlögl, Mathias Bavay, and Michael Lehning
The Cryosphere, 11, 517–529, https://doi.org/10.5194/tc-11-517-2017, https://doi.org/10.5194/tc-11-517-2017, 2017
Short summary
Short summary
We simulate the future snow cover in the Alps with the help of a snow model, which is fed by projected temperature and precipitation changes from a large set of climate models. The results demonstrate that snow below 1000 m is probably a rare guest at the end of the century. Moreover, even above 3000 m the simulations show a drastic decrease in snow depth. However, the results reveal that the projected snow cover reduction can be mitigated by 50 % if we manage to keep global warming below 2°.
Nander Wever, Sebastian Würzer, Charles Fierz, and Michael Lehning
The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, https://doi.org/10.5194/tc-10-2731-2016, 2016
Short summary
Short summary
The study presents a dual domain approach to simulate liquid water flow in snow using the 1-D physics based snow cover model SNOWPACK. In this approach, the pore space is separated into a part for matrix flow and a part that represents preferential flow. Using this approach, water can percolate sub-freezing snow and form dense (ice) layers. A comparison with snow pits shows that some of the observed ice layers were reproduced by the model while others remain challenging to simulate.
Rebecca Mott, Enrico Paterna, Stefan Horender, Philip Crivelli, and Michael Lehning
The Cryosphere, 10, 445–458, https://doi.org/10.5194/tc-10-445-2016, https://doi.org/10.5194/tc-10-445-2016, 2016
Short summary
Short summary
For the first time, this contribution investigates atmospheric decoupling above melting snow in a wind tunnel study. High-resolution vertical profiles of
sensible heat fluxes are measured directly over the melting snow patch.
The study shows that atmospheric decoupling is strongly increased in topographic sheltering but only for low wind velocities. Then turbulent mixing close to the surface is strongly suppressed, facilitating the formation of cold-air pooling in local depressions.
N. Wever, L. Schmid, A. Heilig, O. Eisen, C. Fierz, and M. Lehning
The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, https://doi.org/10.5194/tc-9-2271-2015, 2015
Short summary
Short summary
A verification of the physics based SNOWPACK model with field observations showed that typical snowpack properties like density and temperature are adequately simulated. Also two water transport schemes were verified, showing that although Richards equation improves snowpack runoff and several aspects of the internal snowpack structure, the bucket scheme appeared to have a higher agreement with the snow microstructure. The choice of water transport scheme may depend on the intended application.
W. Steinkogler, B. Sovilla, and M. Lehning
The Cryosphere, 9, 1819–1830, https://doi.org/10.5194/tc-9-1819-2015, https://doi.org/10.5194/tc-9-1819-2015, 2015
Short summary
Short summary
Infrared radiation thermography (IRT) was used to assess the surface temperature of avalanches with high spatial resolution. Thermal energy increase due to friction was mainly depending on the elevation drop of the avalanche. Warming due to entrainment was very specific to the individual avalanche and depends on the temperature of the snow along the path and the erosion depth. The warmest temperatures were located in the deposits of the dense core.
A. Gallice, B. Schaefli, M. Lehning, M. B. Parlange, and H. Huwald
Hydrol. Earth Syst. Sci., 19, 3727–3753, https://doi.org/10.5194/hess-19-3727-2015, https://doi.org/10.5194/hess-19-3727-2015, 2015
Short summary
Short summary
This study presents a new model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country. Contrary to the other approaches developed to date, which are usually based on standard regression techniques, our model makes use of the understanding that we have about the physics controlling stream temperature. On top of its accuracy being comparable to that of the other models, it can be used to gain some knowledge about the stream temperature dynamics
E. Trujillo and M. Lehning
The Cryosphere, 9, 1249–1264, https://doi.org/10.5194/tc-9-1249-2015, https://doi.org/10.5194/tc-9-1249-2015, 2015
Short summary
Short summary
In this article, we present a methodology for the objective evaluation of the error in capturing mean snow depths from point measurements. We demonstrate, using LIDAR snow depths, how the model can be used for assisting the design of survey strategies such that the error is minimized or an estimation threshold is achieved. Furthermore, the model can be extended to other spatially distributed snow variables (e.g., SWE) whose statistical properties are comparable to those of snow depth.
J. Schwaab, M. Bavay, E. Davin, F. Hagedorn, F. Hüsler, M. Lehning, M. Schneebeli, E. Thürig, and P. Bebi
Biogeosciences, 12, 467–487, https://doi.org/10.5194/bg-12-467-2015, https://doi.org/10.5194/bg-12-467-2015, 2015
T. Grünewald, Y. Bühler, and M. Lehning
The Cryosphere, 8, 2381–2394, https://doi.org/10.5194/tc-8-2381-2014, https://doi.org/10.5194/tc-8-2381-2014, 2014
Short summary
Short summary
Elevation dependencies of snow depth are analysed based on snow depth maps obtained from airborne remote sensing. Elevation gradients are characterised by a specific shape: an increase of snow depth with elevation is followed by a distinct peak at a certain level and a decrease in the highest elevations. We attribute this shape to an increase of precipitation with altitude, which is modified by topographical-induced redistribution processes of the snow on the ground (wind, gravitation).
M. Bavay and T. Egger
Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, https://doi.org/10.5194/gmd-7-3135-2014, 2014
Short summary
Short summary
The open-source MeteoIO library has been designed to perform the data preprocessing required by numerical models using large meteorological data sets, with a strong emphasis on simplicity and modularity. It retrieves, filters and resamples the data if necessary as well as provides spatial interpolations and parameterizations. It presents a uniform interface to meteorological data in the models, hides the complexity of the preprocessing and guarantees a robust behaviour in case of data errors.
N. Wever, T. Jonas, C. Fierz, and M. Lehning
Hydrol. Earth Syst. Sci., 18, 4657–4669, https://doi.org/10.5194/hess-18-4657-2014, https://doi.org/10.5194/hess-18-4657-2014, 2014
Short summary
Short summary
We simulated a severe rain-on-snow event in the Swiss Alps in October 2011 with a detailed multi-layer snow cover model. We found a strong modulating effect of the incoming rainfall signal by the snow cover. Initially, water from both rainfall and snow melt was absorbed by the snowpack. But once the snowpack released the stored water, simulated outflow rates exceeded rainfall and snow melt rates. The simulations suggest that structural snowpack changes enhanced the outflow during this event.
N. Wever, C. Fierz, C. Mitterer, H. Hirashima, and M. Lehning
The Cryosphere, 8, 257–274, https://doi.org/10.5194/tc-8-257-2014, https://doi.org/10.5194/tc-8-257-2014, 2014
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, https://doi.org/10.5194/hess-17-3005-2013, 2013
C. D. Groot Zwaaftink, A. Cagnati, A. Crepaz, C. Fierz, G. Macelloni, M. Valt, and M. Lehning
The Cryosphere, 7, 333–347, https://doi.org/10.5194/tc-7-333-2013, https://doi.org/10.5194/tc-7-333-2013, 2013
Related subject area
Hydrology
Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2
GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications
GEMS v1.0: Generalizable Empirical Model of Snow Accumulation and Melt, based on daily snow mass changes in response to climate and topographic drivers
mesas.py v1.0: a flexible Python package for modeling solute transport and transit times using StorAge Selection functions
rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment
GLOBGM v1.0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model
Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)
HGS-PDAF (version 1.0): A modular data assimilation framework for an integrated surface and subsurface hydrological model
pyESDv1.0.1: an open-source Python framework for empirical-statistical downscaling of climate information
Representing the impact of Rhizophora mangroves on flow in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Dynamically weighted ensemble of geoscientific models via automated machine-learning-based classification
Enhancing the representation of water management in global hydrological models
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Reservoir Assessment Tool Version 3.0: A Scalable and User-Friendly Software Platform to Mobilize the Global Water Management Community
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
HydroFATE (v1): A high-resolution contaminant fate model for the global river system
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
Wflow_sbm v0.6.1, a spatially distributed hydrologic model: from global data to local applications
Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains
The eWaterCycle platform for open and FAIR hydrological collaboration
Evaluating the Atibaia River hydrology using JULES6.1
A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector
Pedro Felipe Arboleda-Obando, Agnès Ducharne, Zun Yin, and Philippe Ciais
Geosci. Model Dev., 17, 2141–2164, https://doi.org/10.5194/gmd-17-2141-2024, https://doi.org/10.5194/gmd-17-2141-2024, 2024
Short summary
Short summary
We show a new irrigation scheme included in the ORCHIDEE land surface model. The new irrigation scheme restrains irrigation due to water shortage, includes water adduction, and represents environmental limits and facilities to access water, due to representing infrastructure in a simple way. Our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, even if there are difficulties due to shortcomings and limited information.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev., 17, 911–929, https://doi.org/10.5194/gmd-17-911-2024, https://doi.org/10.5194/gmd-17-911-2024, 2024
Short summary
Short summary
We present a parsimonious snow model which simulates snow mass without the need for extensive calibration. The model is based on a machine learning algorithm that has been trained on diverse set of daily observations of snow accumulation or melt, along with corresponding climate and topography data. We validated the model using in situ data from numerous new locations. The model provides a promising solution for accurate snow mass estimation across regions where in situ data are limited.
Ciaran J. Harman and Esther Xu Fei
Geosci. Model Dev., 17, 477–495, https://doi.org/10.5194/gmd-17-477-2024, https://doi.org/10.5194/gmd-17-477-2024, 2024
Short summary
Short summary
Over the last 10 years, scientists have developed StorAge Selection: a new way of modeling how material is transported through complex systems. Here, we present some new, easy-to-use, flexible, and very accurate code for implementing this method. We show that, in cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other codes to the right answer in an important way: it conserves mass.
Lele Shu, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li
Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, https://doi.org/10.5194/gmd-17-497-2024, 2024
Short summary
Short summary
Our team developed rSHUD v2.0, a toolkit that simplifies the use of the SHUD, a model simulating water movement in the environment. We demonstrated its effectiveness in two watersheds, one in the USA and one in China. The toolkit also facilitated the creation of the Global Hydrological Data Cloud, a platform for automatic data processing and model deployment, marking a significant advancement in hydrological research.
Jarno Verkaik, Edwin H. Sutanudjaja, Gualbert H. P. Oude Essink, Hai Xiang Lin, and Marc F. P. Bierkens
Geosci. Model Dev., 17, 275–300, https://doi.org/10.5194/gmd-17-275-2024, https://doi.org/10.5194/gmd-17-275-2024, 2024
Short summary
Short summary
This paper presents the parallel PCR-GLOBWB global-scale groundwater model at 30 arcsec resolution (~1 km at the Equator). Named GLOBGM v1.0, this model is a follow-up of the 5 arcmin (~10 km) model, aiming for a higher-resolution simulation of worldwide fresh groundwater reserves under climate change and excessive pumping. For a long transient simulation using a parallel prototype of MODFLOW 6, we show that our implementation is efficient for a relatively low number of processor cores.
Han Qiu, Gautam Bisht, Lingcheng Li, Dalei Hao, and Donghui Xu
Geosci. Model Dev., 17, 143–167, https://doi.org/10.5194/gmd-17-143-2024, https://doi.org/10.5194/gmd-17-143-2024, 2024
Short summary
Short summary
We developed and validated an inter-grid-cell lateral groundwater flow model for both saturated and unsaturated zone in the ELMv2.0 framework. The developed model was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model and showed comparable performance with PFLOTRAN. The developed model was also applied to the Little Washita experimental watershed. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset.
Qi Tang, Hugo Delottier, Wolfgang Kurtz, Lars Nerger, Oliver S. Schilling, and Philip Brunner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-229, https://doi.org/10.5194/gmd-2023-229, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We have developed a new data assimilation framework by coupling an integrated hydrological model HydroGeoSphere with the data assimilation software PDAF. Compared to existing hydrological data assimilation systems, the advantage of our newly developed framework lies in its consideration of the physically based model, its large selection of different assimilation algorithms and its modularity with respect to the combination of different types of observations, states and parameters.
Daniel Boateng and Sebastian G. Mutz
Geosci. Model Dev., 16, 6479–6514, https://doi.org/10.5194/gmd-16-6479-2023, https://doi.org/10.5194/gmd-16-6479-2023, 2023
Short summary
Short summary
We present an open-source Python framework for performing empirical-statistical downscaling of climate information, such as precipitation. The user-friendly package comprises all the downscaling cycles including data preparation, model selection, training, and evaluation, designed in an efficient and flexible manner, allowing for quick and reproducible downscaling products. The framework would contribute to climate change impact assessments by generating accurate high-resolution climate data.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
Short summary
Short summary
Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
Geosci. Model Dev., 16, 5685–5701, https://doi.org/10.5194/gmd-16-5685-2023, https://doi.org/10.5194/gmd-16-5685-2023, 2023
Short summary
Short summary
Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here propose an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrate the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A. F. M. Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev., 16, 5449–5472, https://doi.org/10.5194/gmd-16-5449-2023, https://doi.org/10.5194/gmd-16-5449-2023, 2023
Short summary
Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Short summary
NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-130, https://doi.org/10.5194/gmd-2023-130, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The Reservoir Assessment Tool (RAT) version 3.0 represents a scalable and customizable software based on hydrologic modeling and satellite remote sensing to monitor the reservoir's dynamic state. The architecture of RAT 3.0 has been designed in such a way that it requires minimal user input with additional flexibility added for the more advanced users. It is more robust and less susceptible to data gaps or instability that satellite remote sensing systems can sometimes experience.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
Short summary
Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
Short summary
Short summary
Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Heloisa Ehalt Macedo, Bernhard Lehner, Jim Nicell, and Günther Grill
EGUsphere, https://doi.org/10.5194/egusphere-2023-1590, https://doi.org/10.5194/egusphere-2023-1590, 2023
Short summary
Short summary
Pharmaceuticals and household chemicals released into surface waters through wastewater pose risks to aquatic ecosystems and human health. HydroFATE, a new global model, estimates contaminant concentrations in rivers, helping identify areas of elevated exposure. It predicted concentrations above ecological thresholds of the antibiotic sulfamethoxazole in 390,000 km of rivers worldwide. HydroFATE can guide monitoring and mitigation efforts to safeguard water systems and human well-being.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
Short summary
Short summary
Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
Short summary
Short summary
Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
Short summary
In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
Short summary
Short summary
We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
Short summary
During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
Short summary
Short summary
It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
Short summary
Short summary
Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
Short summary
Short summary
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
Short summary
Short summary
Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
Short summary
Short summary
Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
Short summary
Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
Short summary
Short summary
The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
Short summary
Short summary
A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
Short summary
Short summary
A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
Short summary
Short summary
We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
Short summary
Short summary
Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
Short summary
Short summary
This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
Short summary
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
Short summary
Short summary
We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
Short summary
Short summary
This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ji Li, Daoxian Yuan, Fuxi Zhang, Jiao Liu, and Mingguo Ma
Geosci. Model Dev., 15, 6581–6600, https://doi.org/10.5194/gmd-15-6581-2022, https://doi.org/10.5194/gmd-15-6581-2022, 2022
Short summary
Short summary
A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
Short summary
Short summary
MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
Short summary
Short summary
Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-182, https://doi.org/10.5194/gmd-2022-182, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
We present the wflow_sbm distributed hydrologic model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast run-time making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
Short summary
Short summary
Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
Short summary
Short summary
With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
Short summary
Short summary
Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Cited articles
Aschwanden, H. and Weingartner, R.: Die Abflussregimes der Schweiz, Publikation gewässerkunde nr. 65, Geographisches Institut der Universität Bern, 1985.
Bárdossy, A.: Calibration of hydrological model parameters for ungauged catchments, Hydrol. Earth Syst. Sci., 11, 703–710, https://doi.org/10.5194/hess-11-703-2007, 2007.
Barnett, T., Adam, J., and Lettenmaier, D.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning. Part I: numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002.
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, 2014.
Bavay, M., Lehning, M., Jonas, T., and Löwe, H.: Simulations of future snow cover and discharge in Alpine headwater catchments, Hydrol. Process., 23, 95–108, https://doi.org/10.1002/hyp.7195, 2009.
Bavay, M., Grünewald, T., and Lehning, M.: Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland, Adv. Water Resour/, 55, 4–16, https://doi.org/10.1016/j.advwatres.2012.12.009, 2013.
Beniston, M.: Impacts of climatic change on water and associated economic activities in the Swiss Alps, J. Hydrol., 412–413, 291–296, https://doi.org/10.1016/j.jhydrol.2010.06.046, 2012.
Berger, M., Aftosmis, M. J., and Murman, S. M.: Analysis of Slope Limiters on Irregular Grids, in: 43rd AIAA Aerospace Sciences Meeting, Reno, NV, USA, nAS Technical Report NAS-05-007, 2005.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Beven, K. J.: Rainfall-Runoff Modelling: The Primer, 2nd Edn., Wiley-Blackwell, 2012.
Bicknell, B. R., Imhoff, J. C., Kittle, J. L., Donigian, A. S., and Johanson, R. C.: Hydrological Simulation Program–FORTRAN User's Manual for Version 11, U.S. Environmental Protection Agency, National Exposure Research Laboratory, Athens, GA, USA, 1997.
Booch, G., Rumbaugh, J., and Jacobson, I.: The Unified Modeling Language User Guide, 2nd Edn., Addison-Wesley Professional, 2005.
Bürger, G., Schulla, J., and Werner, A. T.: Estimates of future flow, including extremes, of the Columbia River headwaters, Water Resour. Res., 47, W10520, https://doi.org/10.1029/2010WR009716, 2011.
Butman, D. and Raymond, P.: Significant efflux of carbon dioxide from streams and rivers in the United States, Nat. Geosci., 4, 839–842, https://doi.org/10.1038/ngeo1294, 2011.
Caissie, D.: The thermal regime of rivers: a review, Freshwater Biol., 51, 1389–1406, https://doi.org/10.1111/j.1365-2427.2006.01597.x, 2006.
Caldwell, R. J., Gangopadhyay, S., Bountry, J., Lai, Y., and Elsner, M. M.: Statistical modeling of daily and subdaily stream temperatures: Application to the Methow River Basin, Washington, Water Resour. Res., 49, 4346–4361, https://doi.org/10.1002/wrcr.20353, 2013.
Chen, Y., Carsel, R., McCutcheon, S., and Nutter, W.: Stream Temperature Simulation of Forested Riparian Areas: I. Watershed-Scale Model Development, J. Environ. Eng., 124, 304–315, https://doi.org/10.1061/(ASCE)0733-9372(1998)124:4(304), 1998.
Comola, F., Schaefli, B., Rinaldo, A., and Lehning, M.: Thermodynamics in the hydrologic response: Travel time formulation and application to Alpine catchments, Water Resour. Res., 51, 1671–1687, https://doi.org/10.1002/2014WR016228, 2015.
Cunge, J. A.: On the subject of a flood propagation computation method (Muskingum method), J. Hydraul. Res., 7, 205–230, https://doi.org/10.1080/00221686909500264, 1969.
Elliott, J. M. and Elliott, J. A.: Temperature requirements of Atlantic salmon Salmo salar, brown trout Salmo trutta and Arctic charr Salvelinus alpinus: predicting the effects of climate change, J. Fish Biol., 77, 1793–1817, https://doi.org/10.1111/j.1095-8649.2010.02762.x, 2010.
Fatichi, S., Rimkus, S., Burlando, P., Bordoy, R., and Molnar, P.: High-resolution distributed analysis of climate and anthropogenic changes on the hydrology of an Alpine catchment, J. Hydrol., 525, 362–382, https://doi.org/10.1016/j.jhydrol.2015.03.036, 2015.
Ferrari, M. R., Miller, J. R., and Russell, G. L.: Modeling changes in summer temperature of the Fraser River during the next century, J. Hydrol., 342, 336–346, https://doi.org/10.1016/j.jhydrol.2007.06.002, 2007.
Ficklin, D. L., Luo, Y., Stewart, I. T., and Maurer, E. P.: Development and application of a hydroclimatological stream temperature model within the Soil and Water Assessment Tool, Water Resour. Res., 48, W01511, https://doi.org/10.1029/2011WR011256, 2012.
Ficklin, D. L., Barnhart, B. L., Knouft, J. H., Stewart, I. T., Maurer, E. P., Letsinger, S. L., and Whittaker, G. W.: Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers, Hydrol. Earth Syst. Sci., 18, 4897–4912, https://doi.org/10.5194/hess-18-4897-2014, 2014.
Finger, D., Heinrich, G., Gobiet, A., and Bauder, A.: Projections of future water resources and their uncertainty in a glacierized catchment in the Swiss Alps and the subsequent effects on hydropower production during the 21st century, Water Resour. Res., 48, W02521, https://doi.org/10.1029/2011WR010733, 2012.
Gallice, A., Schaefli, B., Lehning, M., Parlange, M. B., and Huwald, H.: Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model, Hydrol. Earth Syst. Sci., 19, 3727–3753, https://doi.org/10.5194/hess-19-3727-2015, 2015.
Gamma, E., Helm, R., Johnson, R., and Vlissides, J.: Design patterns: elements of reusable object-oriented software, Addison-Wesley, 1994.
Goodison, B., Louie, P., and Yang, D.: WMO Solid Precipitation Measurement Intercomparison, Tech. Rep. WMO/TD-No. 872, IOM No. 67, World Meteorological Organization, 1998.
Gouttevin, I., Lehning, M., Jonas, T., Gustafsson, D., and Mölder, M.: A two-layer canopy model with thermal inertia for an improved snowpack energy balance below needleleaf forest (model SNOWPACK, version 3.2.1, revision 741), Geosci. Model Dev., 8, 2379–2398, https://doi.org/10.5194/gmd-8-2379-2015, 2015.
Grillakis, M. G., Tsanis, I. K., and Koutroulis, A. G.: Application of the HBV hydrological model in a flash flood case in Slovenia, Nat. Hazards Earth Syst. Sci., 10, 2713–2725, https://doi.org/10.5194/nhess-10-2713-2010, 2010.
Groot Zwaaftink, C. D., Mott, R., and Lehning, M.: Seasonal simulation of drifting snow sublimation in Alpine terrain, Water Resour. Res., 49, 1581–1590, https://doi.org/10.1002/wrcr.20137, 2013.
Haag, I. and Luce, A.: The integrated water balance and water temperature model LARSIM-WT, Hydrol. Process., 22, 1046–1056, https://doi.org/10.1002/hyp.6983, 2008.
Hannah, D. M., Malcolm, I. A., Soulsby, C., and Youngson, A. F.: Heat exchanges and temperatures within a salmon spawning stream in the Cairngorms, Scotland: seasonal and sub-seasonal dynamics, River Res. Appl., 20, 635–652, https://doi.org/10.1002/rra.771, 2004.
Hari, R. E., Livingstone, D. M., Siber, R., Burkhardt-Holm, P., and Güttinger, H.: Consequences of climatic change for water temperature and brown trout populations in Alpine rivers and streams, Glob. Change Biol., 12, 10–26, https://doi.org/10.1111/j.1365-2486.2005.001051.x, 2006.
Hauer, F. R., Baron, J. S., Campbell, D. H., Fausch, K. D., Hostetler, S. W., Leavesley, G. H., Leavitt, P. R., McKnight, D. M., and Stanford, J. A.: Assessment of climate change and freshwater ecosystems of the rocky mountains, usa and canada, Hydrol. Process., 11, 903–924, https://doi.org/10.1002/(SICI)1099-1085(19970630)11:8<903::AID-HYP511>3.0.CO;2-7, 1997.
Hébert, C., Caissie, D., Satish, M., and El-Jabi, N.: Predicting hourly stream temperatures using the equilibrium temperature model, Journal of Water Resource and Protection, 7, 322–338, https://doi.org/10.4236/jwarp.2015.74026, 2015.
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci. Eng., 9, 90–95, 2007.
Isaak, D. J., Young, M. K., Luce, C. H., Hostetler, S. W., Wenger, S. J., Peterson, E. E., Ver Hoef, J. M., Groce, M. C., Horan, D. L., and Nagel, D. E.: Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity, P. Natl. Acad. Sci. USA, 113, 4374–4379, https://doi.org/10.1073/pnas.1522429113, 2016.
Khakbaz, B., Imam, B., Hsu, K., and Sorooshian, S.: From lumped to distributed via semi-distributed: Calibration strategies for semi-distributed hydrologic models, J. Hydrol., 418–419, 61–77, https://doi.org/10.1016/j.jhydrol.2009.02.021, 2012.
Kormann, C., Francke, T., and Bronstert, A.: Detection of regional climate change effects on alpine hydrology by daily resolution trend analysis in Tyrol, Austria, J. Water Clim. Change, 6, 124–143, https://doi.org/10.2166/wcc.2014.099, 2015a.
Kormann, C., Francke, T., Renner, M., and Bronstert, A.: Attribution of high resolution streamflow trends in Western Austria – an approach based on climate and discharge station data, Hydrol. Earth Syst. Sci., 19, 1225–1245, https://doi.org/10.5194/hess-19-1225-2015, 2015b.
Leach, J. A. and Moore, R. D.: Observations and modeling of hillslope throughflow temperatures in a coastal forested catchment, Water Resour. Res., 51, 3770–3795, https://doi.org/10.1002/2014WR016763, 2015.
Lehning, M., Bartelt, P., Brown, B., Russi, T., Stöckli, U., and Zimmerli, M.: SNOWPACK model calculations for avalanche warning based upon a new network of weather and snow stations, Cold Reg. Sci. Technol., 30, 145–157, https://doi.org/10.1016/S0165-232X(99)00022-1, 1999.
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning. Part III: meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, https://doi.org/10.1016/S0165-232X(02)00072-1, 2002a.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning. Part II: Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002b.
Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T. A., Stähli, M., and Zappa, M.: ALPINE3D: a detailed model of mountain surface processes and its application to snow hydrology, Hydrol. Process., 20, 2111–2128, https://doi.org/10.1002/hyp.6204, 2006.
Lehning, M., Löwe, H., Ryser, M., and Raderschall, N.: Inhomogeneous precipitation distribution and snow transport in steep terrain, Water Resour. Res., 44, W07404, https://doi.org/10.1029/2007WR006545, 2008.
LeVeque, R. J.: Finite volume methods for hyperbolic problems, Cambridge University Press, 2002.
Lippman, S. B., Lajoie, J., and Moo, B. E.: C++ Primer, 5th Edn., Addison-Wesley, 2012.
Loinaz, M. C., Davidsen, H. K., Butts, M., and Bauer-Gottwein, P.: Integrated flow and temperature modeling at the catchment scale, J. Hydrol., 495, 238–251, https://doi.org/10.1016/j.jhydrol.2013.04.039, 2013.
Lowney, C. L.: Stream temperature variation in regulated rivers: Evidence for a spatial pattern in daily minimum and maximum magnitudes, Water Resour. Res., 36, 2947–2955, https://doi.org/10.1029/2000WR900142, 2000.
MacDonald, R. J., Boon, S., and Byrne, J. M.: A process-based stream temperature modelling approach for mountain regions, J. Hydrol., 511, 920–931, https://doi.org/10.1016/j.jhydrol.2014.02.009, 2014.
Magnusson, J., Jonas, T., and Kirchner, J. W.: Temperature dynamics of a proglacial stream: Identifying dominant energy balance components and inferring spatially integrated hydraulic geometry, Water Resour. Res., 48, W06510, https://doi.org/10.1029/2011WR011378, 2012.
Majone, B., Villa, F., Deidda, R., and Bellin, A.: Impact of climate change and water use policies on hydropower potential in the south-eastern Alpine region, Sci. Total Environ., 543, Part B, 965–980, https://doi.org/10.1016/j.scitotenv.2015.05.009, 2016.
Mohseni, O., Stefan, H. G., and Erickson, T. R.: A nonlinear regression model for weekly stream temperatures, Water Resour. Res., 34, 2685–2692, https://doi.org/10.1029/98WR01877, 1998.
Moore, R. D., Sutherland, P., Gomi, T., and Dhakal, A.: Thermal regime of a headwater stream within a clear-cut, coastal British Columbia, Canada, Hydrol. Process., 19, 2591–2608, https://doi.org/10.1002/hyp.5733, 2005.
Morrison, J., Quick, M. C., and Foreman, M. G.: Climate change in the Fraser River watershed: flow and temperature projections, J. Hydrol., 263, 230–244, https://doi.org/10.1016/S0022-1694(02)00065-3, 2002.
Mott, R. and Lehning, M.: Meteorological modeling of very high-resolution wind fields and snow deposition for mountains, J. Hydrometeorol., 11, 934–949, https://doi.org/10.1175/2010JHM1216.1, 2010.
Mott, R., Scipión, D., Schneebeli, M., Dawes, N., Berne, A., and Lehning, M.: Orographic effects on snow deposition patterns in mountainous terrain, J. Geophys. Res.-Atmos., 119, 1419–1439, https://doi.org/10.1002/2013JD019880, 2014.
Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models part I – A discussion of principles, J. Hydrol., 10, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Null, S. E., Viers, J. H., Deas, M. L., Tanaka, S. K., and Mount, J. F.: Stream temperature sensitivity to climate warming in California's Sierra Nevada: impacts to coldwater habitat, Climatic Change, 116, 149–170, https://doi.org/10.1007/s10584-012-0459-8, 2013.
Padilla, A., Rasouli, K., and Déry, S. J.: Impacts of variability and trends in runoff and water temperature on salmon migration in the Fraser River Basin, Canada, Hydrol. Sci. J., 60, 523–533, https://doi.org/10.1080/02626667.2014.892602, 2015.
Phillips, J. and Tadayon, S.: Selection of Manning's roughness coefficient for natural and constructed vegetated and non-vegetated channels, and vegetation maintenance plan guidelines for vegetated channels in central Arizona, Tech. Rep. Scientic Investigations Report 2006–5108, U.S. Geological Survey, Reston, Virginia, USA, 2006.
Piccolroaz, S., Calamita, E., Majone, B., Gallice, A., Siviglia, A., and Toffolon, M.: Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches, Hydrol. Process., 30, 3901–3917, https://doi.org/10.1002/hyp.10913, 2016.
Ponce, V. and Changanti, P.: Variable-parameter Muskingum-Cunge method revisited, J. Hydrol., 162, 433–439, https://doi.org/10.1016/0022-1694(94)90241-0, 1994.
Ragettli, S., Cortés, G., McPhee, J., and Pellicciotti, F.: An evaluation of approaches for modelling hydrological processes in high-elevation, glacierized Andean watersheds, Hydrol. Process., 28, 5674–5695, https://doi.org/10.1002/hyp.10055, 2014.
Raymond, P., Hartmann, J., Lauerwald, R., Sobek, S., McDonald, C., Hoover, M., Butman, D., Striegl, R., Mayorga, E., Humborg, C., Kortelainen, P., Dürr, H., Meybeck, M., Ciais, P., and Guth, P.: Global carbon dioxide emissions from inland waters, Nature, 503, 355–359, https://doi.org/10.1038/nature12760, 2013.
Schaefli, B. and Gupta, H. V.: Do Nash values have value?, Hydrol. Process., 21, 2075–2080, https://doi.org/10.1002/hyp.6825, 2007.
Schaefli, B., Hingray, B., and Musy, A.: Climate change and hydropower production in the Swiss Alps: quantification of potential impacts and related modelling uncertainties, Hydrol. Earth Syst. Sci., 11, 1191–1205, https://doi.org/10.5194/hess-11-1191-2007, 2007.
Schaefli, B., Nicótina, L., Imfeld, C., Da Ronco, P., Bertuzzo, E., and Rinaldo, A.: SEHR-ECHO v1.0: a Spatially Explicit Hydrologic Response model for ecohydrologic applications, Geosci. Model Dev., 7, 2733–2746, https://doi.org/10.5194/gmd-7-2733-2014, 2014.
Short, R. A. and Ward, J. V.: Macroinvertebrates of a Colorado High Mountain Stream, The Southwestern Naturalist, 25, 23–32, 1980.
Stage, S. A.: Comments on an improvement to the Brent's method, International Journal of Experimental Algorithms, 4, 1–16, 2013.
Stewart, I. T., Cayan, D. R., and Dettinger, M. D.: Changes toward Earlier Streamflow Timing across Western North America, J. Climate, 18, 1136–1155, https://doi.org/10.1175/JCLI3321.1, 2005.
Stewart, I. T., Ficklin, D. L., Carrillo, C. A., and McIntosh, R.: 21st century increases in the likelihood of extreme hydrologic conditions for the mountainous basins of the Southwestern United States, J. Hydrol., 529, Part 1, 340–353, https://doi.org/10.1016/j.jhydrol.2015.07.043, 2015.
St-Hilaire, A., Morin, G., El-Jabi, N., and Caissie, D.: Water temperature modelling in a small forested stream: implication of forest canopy and soil temperature, Can. J. Civil Eng., 27, 1095–1108, https://doi.org/10.1139/l00-021, 2000.
Sullivan, K., Tooley, J., Doughty, K., Caldwell, J., and Knudsen, P.: Evaluation of prediction models and characterization of stream temperature regimes in Washington, Tech. Rep. Timber/Fish/Wildlife Rep. No. TFW-WQ3-90-006, Washington Dept. Nat. Resources, Olympia, Washington, 1990.
Sun, N., Yearsley, J., Voisin, N., and Lettenmaier, D. P.: A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds, Hydrol. Process., 29, 2331–2345, https://doi.org/10.1002/hyp.10363, 2015.
Tang, X., Knight, D. W., and Samuels, P. G.: Variable parameter Muskingum-Cunge method for flood routing in a compound channel, J. Hydraul. Res., 37, 591–614, https://doi.org/10.1080/00221689909498519, 1999.
Tarboton, D. G.: A new method for the determination of flow directions and upslope areas in grid digital elevation models, Water Resour. Res., 33, 309–319, https://doi.org/10.1029/96WR03137, 1997.
Toffolon, M. and Piccolroaz, S.: A hybrid model for river water temperature as a function of air temperature and discharge, Environ. Res. Lett., 10, 114011, https://doi.org/10.1088/1748-9326/10/11/114011, 2015.
Tung, C.-P., Lee, T.-Y., Huang, J.-C., Perng, P.-W., Kao, S.-J., and Liao, L.-Y.: The development of stream temperature model in a mountainous river of Taiwan, Environ. Monit. Assess., 186, 7489–7503, https://doi.org/10.1007/s10661-014-3942-z, 2014.
van Beek, L. P. H., Eikelboom, T., van Vliet, M. T. H., and Bierkens, M. F. P.: A physically based model of global freshwater surface temperature, Water Resour. Res., 48, W09530, https://doi.org/10.1029/2012WR011819, 2012.
van Heesch, D.: Doxygen: Source code documentation generator tool, available at: http://www.doxygen.org/ (last access: 24 February 2014), 2008.
van Vliet, M. T. H., Yearsley, J. R., Franssen, W. H. P., Ludwig, F., Haddeland, I., Lettenmaier, D. P., and Kabat, P.: Coupled daily streamflow and water temperature modelling in large river basins, Hydrol. Earth Syst. Sci., 16, 4303–4321, https://doi.org/10.5194/hess-16-4303-2012, 2012.
Viviroli, D., Archer, D. R., Buytaert, W., Fowler, H. J., Greenwood, G. B., Hamlet, A. F., Huang, Y., Koboltschnig, G., Litaor, M. I., López-Moreno, J. I., Lorentz, S., Schädler, B., Schreier, H., Schwaiger, K., Vuille, M., and Woods, R.: Climate change and mountain water resources: overview and recommendations for research, management and policy, Hydrol. Earth Syst. Sci., 15, 471–504, https://doi.org/10.5194/hess-15-471-2011, 2011.
Voegeli, C., Lehning, M., Wever, N., and Bavay, M.: Scaling precipitation input to distributed hydrological models by measured snow distribution, Front. Earth Sci., in preparation, 2016.
Vrugt, J. A. and Ter Braak, C. J. F.: DREAM(D): an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems, Hydrol. Earth Syst. Sci., 15, 3701–3713, https://doi.org/10.5194/hess-15-3701-2011, 2011.
Webb, B. W. and Zhang, Y.: Spatial and seasonal variability in the components of the river heat budget, Hydrol. Process., 11, 79–101, https://doi.org/10.1002/(SICI)1099-1085(199701)11:1<79::AID-HYP404>3.0.CO;2-N, 1997.
Wehrly, K. E., Wang, L., and Mitro, M.: Field-Based Estimates of Thermal Tolerance Limits for Trout: Incorporating Exposure Time and Temperature Fluctuation, T. Am. Fish. Soc., 136, 365–374, https://doi.org/10.1577/T06-163.1, 2007.
Weijs, S. V., Mutzner, R., and Parlange, M. B.: Could electrical conductivity replace water level in rating curves for alpine streams?, Water Resour. Res., 49, 343–351, https://doi.org/10.1029/2012WR012181, 2013.
Westhoff, M. C., Savenije, H. H. G., Luxemburg, W. M. J., Stelling, G. S., van de Giesen, N. C., Selker, J. S., Pfister, L., and Uhlenbrook, S.: A distributed stream temperature model using high resolution temperature observations, Hydrol. Earth Syst. Sci., 11, 1469–1480, https://doi.org/10.5194/hess-11-1469-2007, 2007.
Wever, N., Fierz, C., Mitterer, C., Hirashima, H., and Lehning, M.: Solving Richards Equation for snow improves snowpack meltwater runoff estimations in detailed multi-layer snowpack model, The Cryosphere, 8, 257–274, https://doi.org/10.5194/tc-8-257-2014, 2014.
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M.: Verification of the multi-layer SNOWPACK model with different water transport schemes, The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, 2015.
Wilhelm, L., Besemer, K., Fragner, L., Peter, H., Weckwerth, W., and Battin, T.: Altitudinal patterns of diversity and functional traits of metabolically active microorganisms in stream biofilms, ISME Journal, 9, 2454–2464, https://doi.org/10.1038/ismej.2015.56, 2015.
Zappa, M., Pos, F., Strasser, U., Warmerdam, P., and Gurtz, J.: Seasonal Water Balance of an Alpine Catchment as Evaluated by Different Methods for Spatially Distributed Snowmelt Modelling, Hydrol. Res., 34, 179–202, 2003.
Zeng, X.: A general approach to enhance slope limiters on non-uniform rectilinear grids, arXiv:1301.0967, available at: http://arxiv.org/abs/1301.0967, 2013.
Short summary
This paper presents the improvements brought to an existing model for discharge and temperature prediction in Alpine streams. Compared to the original model version, it is now possible to choose between various alternatives to simulate certain parts of the water cycle, such as the technique used to transfer water along the stream network. The paper includes an example of application of the model over an Alpine catchment in Switzerland.
This paper presents the improvements brought to an existing model for discharge and temperature...
