Articles | Volume 369
https://doi.org/10.5194/piahs-369-25-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/piahs-369-25-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A Tri-National program for estimating the link between snow resources and hydrological droughts
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
T. Vitvar
Czech Technical University in Prague, Faculty of Civil, Engineering, Prague, Czech Republic
A. Rücker
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
G. Melikadze
Tbilisi State University, Institute of Geophysics, Tbilisi, Georgia
L. Bernhard
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
V. David
Czech Technical University in Prague, Faculty of Civil, Engineering, Prague, Czech Republic
M. Jans-Singh
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
N. Zhukova
Tbilisi State University, Institute of Geophysics, Tbilisi, Georgia
Czech Technical University in Prague, Faculty of Civil, Engineering, Prague, Czech Republic
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We generate operational forecasts of daily maximum stream water temperature for the next month at 54 stations in Switzerland with our best performing data-driven model. The average forecast error is 0.38 °C for 1 day ahead and increases to 0.90 °C for 1 month ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
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Recession models (RM) are crucial for observing the low flow behavior of a catchment. We developed two novel RM, which are designed to represent slowly draining catchment conditions. With a newly designed low flow prediction procedure we tested the prediction capability of these two models and three others from literature. One of our novel products delivered the best results, because it best represents the slowly draining catchment conditions.
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
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To predict timing and magnitude peak run-off, meteorological and calibrated hydrological models are commonly coupled. A flash-flood forecasting chain is presented based on a process-based run-off generation module with no need for calibration. This chain has been evaluated using data for the Emme catchment (Switzerland). The outcomes of this study show that operational flash predictions in ungauged basins can benefit from the use of information on run-off processes.
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high-flow situations.
Love Råman Vinnå, Alfred Wüest, Massimiliano Zappa, Gabriel Fink, and Damien Bouffard
Hydrol. Earth Syst. Sci., 22, 31–51, https://doi.org/10.5194/hess-22-31-2018, https://doi.org/10.5194/hess-22-31-2018, 2018
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Responses of inland waters to climate change vary on global and regional scales. Shifts in river discharge regimes act as positive and negative feedbacks in influencing water temperature. The extent of this effect on warming is controlled by the change in river discharge and lake hydraulic residence time. A shift of deep penetrating river intrusions from summer towards winter can potentially counteract the otherwise negative climate effects on deep-water oxygen content.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Manuel Antonetti, Rahel Buss, Simon Scherrer, Michael Margreth, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 20, 2929–2945, https://doi.org/10.5194/hess-20-2929-2016, https://doi.org/10.5194/hess-20-2929-2016, 2016
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We evaluated three automatic mapping approaches of dominant runoff processes (DRPs) with different complexity using similarity measures and synthetic runoff simulations. The most complex DRP maps were the most similar to the reference maps. Runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and rather coarse simplifications in the mapping criteria. It would thus be worthwhile trying to obtain DRP maps that are as realistic as possible.
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
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In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Michal Jenicek, Jan Seibert, Massimiliano Zappa, Maria Staudinger, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 859–874, https://doi.org/10.5194/hess-20-859-2016, https://doi.org/10.5194/hess-20-859-2016, 2016
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We quantified how long snowmelt affects runoff, and we estimated the sensitivity of catchments to changes in snowpack. This is relevant as the increase of air temperature might cause decreased snow storage. We used time series from 14 catchments in Switzerland. On average, a decrease of maximum snow storage by 10 % caused a decrease of minimum discharge in July by 2 to 9 %. The results showed a higher sensitivity of summer low flow to snow in alpine catchments compared to pre-alpine catchments.
M. Zappa, N. Andres, P. Kienzler, D. Näf-Huber, C. Marti, and M. Oplatka
Proc. IAHS, 370, 235–242, https://doi.org/10.5194/piahs-370-235-2015, https://doi.org/10.5194/piahs-370-235-2015, 2015
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The most severe threat for the city of Zürich (Switzerland) are flash-floods from the small Sihl river. An assessment using a rainfall-runoff model evaluated more than 40000 extreme flood scenarios. These scenarios identified deficits for the safety of Zürich. The combination of different structural and flood management measures can lead to an optimal safety also in case of unfavorable initial conditions. Pending questions concern the costs, political decisions and the environmental matters.
P. Ronco, M. Bullo, S. Torresan, A. Critto, R. Olschewski, M. Zappa, and A. Marcomini
Hydrol. Earth Syst. Sci., 19, 1561–1576, https://doi.org/10.5194/hess-19-1561-2015, https://doi.org/10.5194/hess-19-1561-2015, 2015
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The aim of the paper is the application of the KULTURisk regional risk assessment (KR-RRA) methodology, presented in the companion paper (Part 1), to the Sihl River basin, in northern Switzerland. Flood-related risks have been assessed for different receptors lying in the Sihl river valley including the city of Zurich, which represents a typical case of river flooding in an urban area, by means of a calibration process of the methodology to the site-specific context and features.
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
K. Liechti, L. Panziera, U. Germann, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, https://doi.org/10.5194/hess-17-3853-2013, 2013
F. Fundel, S. Jörg-Hess, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 395–407, https://doi.org/10.5194/hess-17-395-2013, https://doi.org/10.5194/hess-17-395-2013, 2013
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2591, https://doi.org/10.5194/egusphere-2024-2591, 2024
Short summary
Short summary
We generate operational forecasts of daily maximum stream water temperature for the next month at 54 stations in Switzerland with our best performing data-driven model. The average forecast error is 0.38 °C for 1 day ahead and increases to 0.90 °C for 1 month ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Jiří Kocum, Jan Haidl, Ondřej Gebouský, Kristýna Falátková, Václav Šípek, Martin Šanda, Natalie Orlowski, and Lukáš Vlček
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-225, https://doi.org/10.5194/hess-2024-225, 2024
Revised manuscript under review for HESS
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We present a new method for extracting water from soil for stable isotope analysis. The reason for initiating the development was the need to easily and accurately extract sufficient amounts of water from soil samples. The developed apparatus for this method has a medium throughput, high accuracy and high precision. The method is suitable for experiments and studies where high precision is required to distinguish between different pools of water and where mere trend detection is not sufficient.
Michael Margreth, Florian Lustenberger, Dorothea Hug Peter, Fritz Schlunegger, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-78, https://doi.org/10.5194/nhess-2024-78, 2024
Preprint under review for NHESS
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Recession models (RM) are crucial for observing the low flow behavior of a catchment. We developed two novel RM, which are designed to represent slowly draining catchment conditions. With a newly designed low flow prediction procedure we tested the prediction capability of these two models and three others from literature. One of our novel products delivered the best results, because it best represents the slowly draining catchment conditions.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-993, https://doi.org/10.5194/egusphere-2024-993, 2024
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This study uses deep learning to predict spatially contiguous water runoff in Switzerland from 1962–2023. It outperforms traditional models, requiring less data and computational power. Key findings include increased dry years and summer water scarcity. This method offers significant advancements in water monitoring.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
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CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Elham Rouholahnejad Freund, Massimiliano Zappa, and James W. Kirchner
Hydrol. Earth Syst. Sci., 24, 5015–5025, https://doi.org/10.5194/hess-24-5015-2020, https://doi.org/10.5194/hess-24-5015-2020, 2020
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Evapotranspiration (ET) is the largest flux from the land to the atmosphere and thus contributes to Earth's energy and water balance. Due to its impact on atmospheric dynamics, ET is a key driver of droughts and heatwaves. In this paper, we demonstrate how averaging over land surface heterogeneity contributes to substantial overestimates of ET fluxes. We also demonstrate how one can correct for the effects of small-scale heterogeneity without explicitly representing it in land surface models.
Conrad Jackisch, Kai Germer, Thomas Graeff, Ines Andrä, Katrin Schulz, Marcus Schiedung, Jaqueline Haller-Jans, Jonas Schneider, Julia Jaquemotte, Philipp Helmer, Leander Lotz, Andreas Bauer, Irene Hahn, Martin Šanda, Monika Kumpan, Johann Dorner, Gerrit de Rooij, Stefan Wessel-Bothe, Lorenz Kottmann, Siegfried Schittenhelm, and Wolfgang Durner
Earth Syst. Sci. Data, 12, 683–697, https://doi.org/10.5194/essd-12-683-2020, https://doi.org/10.5194/essd-12-683-2020, 2020
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Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for field monitoring exist. In a field experiment under idealised conditions we compared 15 systems for soil moisture and 14 systems for matric potential. The individual records of one system agree well with the others. Most records are also plausible. However, the absolute values of the different measuring systems span a very large range of possible truths.
Marco Dal Molin, Mario Schirmer, Massimiliano Zappa, and Fabrizio Fenicia
Hydrol. Earth Syst. Sci., 24, 1319–1345, https://doi.org/10.5194/hess-24-1319-2020, https://doi.org/10.5194/hess-24-1319-2020, 2020
Matthias J. R. Speich, Massimiliano Zappa, Marc Scherstjanoi, and Heike Lischke
Geosci. Model Dev., 13, 537–564, https://doi.org/10.5194/gmd-13-537-2020, https://doi.org/10.5194/gmd-13-537-2020, 2020
Short summary
Short summary
Climate change is expected to substantially affect natural processes, and simulation models are a valuable tool to anticipate these changes. In this study, we combine two existing models that each describe one aspect of the environment: forest dynamics and the terrestrial water cycle. The coupled model better described observed patterns in vegetation structure. We also found that including the effect of water availability on tree height and rooting depth improved the model.
Manuela I. Brunner, Daniel Farinotti, Harry Zekollari, Matthias Huss, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019, https://doi.org/10.5194/hess-23-4471-2019, 2019
Short summary
Short summary
River flow regimes are expected to change and so are extreme flow regimes. We propose two methods for estimating extreme flow regimes and show on a data set from Switzerland how these extreme regimes are expected to change. Our results show that changes in low- and high-flow regimes are distinct for rainfall- and melt-dominated regions. Our findings provide guidance in water resource planning and management.
Manuela I. Brunner, Katharina Liechti, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci., 19, 2311–2323, https://doi.org/10.5194/nhess-19-2311-2019, https://doi.org/10.5194/nhess-19-2311-2019, 2019
Short summary
Short summary
The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The return period estimates depended on the region, variable, and return period considered.
Andrea Rücker, Stefan Boss, James W. Kirchner, and Jana von Freyberg
Hydrol. Earth Syst. Sci., 23, 2983–3005, https://doi.org/10.5194/hess-23-2983-2019, https://doi.org/10.5194/hess-23-2983-2019, 2019
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To better understand how rain-on-snow (ROS) events affect snowpack outflow volumes and streamflow generation, we measured snowpack outflow volumes and isotopic composition during 10 ROS events with automated snowmelt lysimeters at three locations in a pre-Alpine catchment. We quantified the spatio-temporal variability of snowpack outflow and its relative contribution to streamflow, and identified rainfall characteristics and initial snow depth as major controls on snow hydrological processes.
Samuel Monhart, Massimiliano Zappa, Christoph Spirig, Christoph Schär, and Konrad Bogner
Hydrol. Earth Syst. Sci., 23, 493–513, https://doi.org/10.5194/hess-23-493-2019, https://doi.org/10.5194/hess-23-493-2019, 2019
Short summary
Short summary
Subseasonal streamflow forecasts have received increasing attention during the past decade, but their performance in alpine catchments is still largely unknown. We analyse the effect of a statistical correction technique applied to the driving meteorological forecasts on the performance of the resulting streamflow forecasts. The study shows the benefits of such hydrometeorological ensemble prediction systems and highlights the importance of snow-related processes for subseasonal predictions.
Manuel Antonetti, Christoph Horat, Ioannis V. Sideris, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci., 19, 19–40, https://doi.org/10.5194/nhess-19-19-2019, https://doi.org/10.5194/nhess-19-19-2019, 2019
Short summary
Short summary
To predict timing and magnitude peak run-off, meteorological and calibrated hydrological models are commonly coupled. A flash-flood forecasting chain is presented based on a process-based run-off generation module with no need for calibration. This chain has been evaluated using data for the Emme catchment (Switzerland). The outcomes of this study show that operational flash predictions in ungauged basins can benefit from the use of information on run-off processes.
Peter Stucki, Moritz Bandhauer, Ulla Heikkilä, Ole Rössler, Massimiliano Zappa, Lucas Pfister, Melanie Salvisberg, Paul Froidevaux, Olivia Martius, Luca Panziera, and Stefan Brönnimann
Nat. Hazards Earth Syst. Sci., 18, 2717–2739, https://doi.org/10.5194/nhess-18-2717-2018, https://doi.org/10.5194/nhess-18-2717-2018, 2018
Short summary
Short summary
A catastrophic flood south of the Alps in 1868 is assessed using documents and the earliest example of high-resolution weather simulation. Simulated weather dynamics agree well with observations and damage reports. Simulated peak water levels are biased. Low forest cover did not cause the flood, but such a paradigm was used to justify afforestation. Supported by historical methods, such numerical simulations allow weather events from past centuries to be used for modern hazard and risk analyses.
Manuel Antonetti and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 22, 4425–4447, https://doi.org/10.5194/hess-22-4425-2018, https://doi.org/10.5194/hess-22-4425-2018, 2018
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We developed 60 modelling chain combinations based on either experimentalists' (bottom-up) or modellers' (top-down) thinking and forced them with data of increasing accuracy. Results showed that the differences in performance arising from the forcing data were due to compensation effects. We also found that modellers' and experimentalists' concept of
model realismdiffers, and the level of detail a model should have to reproduce the processes expected must be agreed in advance.
Matthias J. R. Speich, Heike Lischke, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 22, 4097–4124, https://doi.org/10.5194/hess-22-4097-2018, https://doi.org/10.5194/hess-22-4097-2018, 2018
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To simulate the water balance of, e.g., a forest plot, it is important to estimate the maximum volume of water available to plants. This depends on soil properties and the average depth of roots. Rooting depth has proven challenging to estimate. Here, we applied a model assuming that plants dimension their roots to optimize their carbon budget. We compared its results with values obtained by calibrating a dynamic water balance model. In most cases, there is good agreement between both methods.
Christoph Horat, Manuel Antonetti, Katharina Liechti, Pirmin Kaufmann, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-119, https://doi.org/10.5194/nhess-2018-119, 2018
Publication in NHESS not foreseen
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Two forecasting chains are forced by information from numerical weather predictions. The framework presented in the companion paper by Antonetti et al. has been set up for the Swiss Verzasca basin. The forecasts obtained with the uncalibrated RGM-PRO model are compared to forecasts yielded by the calibrated PREVAH-HRU model. Results shows that the uncalibrated model is able to compete with the calibrated operational prediction system and was consistently superior for
high-flow situations.
Love Råman Vinnå, Alfred Wüest, Massimiliano Zappa, Gabriel Fink, and Damien Bouffard
Hydrol. Earth Syst. Sci., 22, 31–51, https://doi.org/10.5194/hess-22-31-2018, https://doi.org/10.5194/hess-22-31-2018, 2018
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Responses of inland waters to climate change vary on global and regional scales. Shifts in river discharge regimes act as positive and negative feedbacks in influencing water temperature. The extent of this effect on warming is controlled by the change in river discharge and lake hydraulic residence time. A shift of deep penetrating river intrusions from summer towards winter can potentially counteract the otherwise negative climate effects on deep-water oxygen content.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Manuel Antonetti, Rahel Buss, Simon Scherrer, Michael Margreth, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 20, 2929–2945, https://doi.org/10.5194/hess-20-2929-2016, https://doi.org/10.5194/hess-20-2929-2016, 2016
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We evaluated three automatic mapping approaches of dominant runoff processes (DRPs) with different complexity using similarity measures and synthetic runoff simulations. The most complex DRP maps were the most similar to the reference maps. Runoff simulations derived from the simpler DRP maps were more uncertain due to inaccuracies in the input data and rather coarse simplifications in the mapping criteria. It would thus be worthwhile trying to obtain DRP maps that are as realistic as possible.
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
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In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Michal Jenicek, Jan Seibert, Massimiliano Zappa, Maria Staudinger, and Tobias Jonas
Hydrol. Earth Syst. Sci., 20, 859–874, https://doi.org/10.5194/hess-20-859-2016, https://doi.org/10.5194/hess-20-859-2016, 2016
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We quantified how long snowmelt affects runoff, and we estimated the sensitivity of catchments to changes in snowpack. This is relevant as the increase of air temperature might cause decreased snow storage. We used time series from 14 catchments in Switzerland. On average, a decrease of maximum snow storage by 10 % caused a decrease of minimum discharge in July by 2 to 9 %. The results showed a higher sensitivity of summer low flow to snow in alpine catchments compared to pre-alpine catchments.
M. Zappa, N. Andres, P. Kienzler, D. Näf-Huber, C. Marti, and M. Oplatka
Proc. IAHS, 370, 235–242, https://doi.org/10.5194/piahs-370-235-2015, https://doi.org/10.5194/piahs-370-235-2015, 2015
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The most severe threat for the city of Zürich (Switzerland) are flash-floods from the small Sihl river. An assessment using a rainfall-runoff model evaluated more than 40000 extreme flood scenarios. These scenarios identified deficits for the safety of Zürich. The combination of different structural and flood management measures can lead to an optimal safety also in case of unfavorable initial conditions. Pending questions concern the costs, political decisions and the environmental matters.
P. Ronco, M. Bullo, S. Torresan, A. Critto, R. Olschewski, M. Zappa, and A. Marcomini
Hydrol. Earth Syst. Sci., 19, 1561–1576, https://doi.org/10.5194/hess-19-1561-2015, https://doi.org/10.5194/hess-19-1561-2015, 2015
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The aim of the paper is the application of the KULTURisk regional risk assessment (KR-RRA) methodology, presented in the companion paper (Part 1), to the Sihl River basin, in northern Switzerland. Flood-related risks have been assessed for different receptors lying in the Sihl river valley including the city of Zurich, which represents a typical case of river flooding in an urban area, by means of a calibration process of the methodology to the site-specific context and features.
V. David and T. Davidova
Nat. Hazards Earth Syst. Sci., 14, 2655–2669, https://doi.org/10.5194/nhess-14-2655-2014, https://doi.org/10.5194/nhess-14-2655-2014, 2014
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
K. Liechti, L. Panziera, U. Germann, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, https://doi.org/10.5194/hess-17-3853-2013, 2013
F. Fundel, S. Jörg-Hess, and M. Zappa
Hydrol. Earth Syst. Sci., 17, 395–407, https://doi.org/10.5194/hess-17-395-2013, https://doi.org/10.5194/hess-17-395-2013, 2013
Cited articles
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Short summary
A research effort involving Switzerland, Georgia and the Czech Republic has been launched to evaluate the relation between snowpack and summer low flows. Two rainfall-runoff models will simulate over 10 years of snow hydrology and runoff in nested streams. Processes involved will be also evaluated by mean by means of high frequency sampling of the environmental isotopes 18O and 2H. The paper presents first analysis of available datasets of 18O, 2H, discharge, snowpack and modelling experiments.
A research effort involving Switzerland, Georgia and the Czech Republic has been launched to...