Articles | Volume 22, issue 6
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The temporally varying roles of rainfall, snowmelt and soil moisture for debris flow initiation in a snow-dominated system
Institute of Mountain Risk Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
Institute of Mountain Risk Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
Institute of Mountain Risk Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
Water Resources Section, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
No articles found.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots, and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modelling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology, and therefore, has potential to improve climate predictions of for example droughts.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript under review for HESSShort summary
Overall, this study demonstrates that previously reported underestimations of water ages are most likely not the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and to instead adopting SAS-based or comparable model formulations.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986,Short summary
We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661,Short summary
This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 22, 1723–1742,Short summary
This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
Andrew Mitchell, Sophia Zubrycky, Scott McDougall, Jordan Aaron, Mylène Jacquemart, Johannes Hübl, Roland Kaitna, and Christoph Graf
Nat. Hazards Earth Syst. Sci., 22, 1627–1654,Short summary
Debris flows are complex, surging movements of sediment and water. Discharge observations from well-studied debris-flow channels were used as inputs for a numerical modelling study of the downstream effects of chaotic inflows. The results show that downstream impacts are sensitive to inflow conditions. Inflow conditions for predictive modelling are highly uncertain, and our method provides a means to estimate the potential variability in future events.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711,Short summary
We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318,Short summary
Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915,Short summary
Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743,Short summary
The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development and found improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453,Short summary
This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Artemis Roodari, Markus Hrachowitz, Farzad Hassanpour, and Mostafa Yaghoobzadeh
Hydrol. Earth Syst. Sci., 25, 1943–1967,Short summary
In a combined data analysis and modeling study in the transboundary Helmand River basin, we analyzed spatial patterns of drought and changes therein based on the drought indices as well as on absolute water deficits. Overall the results illustrate that flow deficits and the associated droughts clearly reflect the dynamic interplay between temporally varying regional differences in hydro-meteorological variables together with subtle and temporally varying effects linked to human intervention.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095,Short summary
We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982,Short summary
Satellite observations have increasingly been used for model calibration, while model structural developments largely rely on discharge data. For large river basins, this often results in poor representations of system internal processes. This study explores the combined use of satellite-based evaporation and total water storage data for model structural improvement and spatial–temporal model calibration for a large, semi-arid and data-scarce river system.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167,Short summary
This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Petra Hulsman, Hessel C. Winsemius, Claire I. Michailovsky, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 24, 3331–3359,Short summary
In the absence of discharge data in ungauged basins, remotely sensed river water level data, i.e. altimetry, may provide valuable information to calibrate hydrological models. This study illustrated that for large rivers in data-scarce regions, river altimetry data from multiple locations combined with GRACE data have the potential to fill this gap when combined with estimates of the river geometry, thereby allowing a step towards more reliable hydrological modelling in data-scarce regions.
Hongkai Gao, Christian Birkel, Markus Hrachowitz, Doerthe Tetzlaff, Chris Soulsby, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 23, 787–809,Short summary
Supported by large-sample ecological observations, a novel, simple and topography-driven runoff generation module (HSC-MCT) was created. The HSC-MCT is calibration-free, and therefore it can be used to predict in ungauged basins, and has great potential to be generalized at the global scale. Also, it allows us to reproduce the variation of saturation areas, which has great potential to be used for broader hydrological, ecological, climatological, and biogeochemical studies.
Laurène Bouaziz, Albrecht Weerts, Jaap Schellekens, Eric Sprokkereef, Jasper Stam, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 22, 6415–6434,Short summary
We quantify net intercatchment groundwater flows in the Meuse basin in a complementary three-step approach through (1) water budget accounting, (2) testing a set of conceptual hydrological models and (3) evaluating against remote sensing actual evaporation data. We show that net intercatchment groundwater flows can make up as much as 25 % of mean annual precipitation in the headwaters and should therefore be accounted for in conceptual models to prevent overestimating actual evaporation rates.
Markus Hrachowitz and Martyn P. Clark
Hydrol. Earth Syst. Sci., 21, 3953–3973,Short summary
Physically based and conceptual models in hydrology are the two endpoints in the spectrum of modelling strategies, mostly differing in their degree of detail in resolving the model domain. Given the limitations both modelling strategies face, we believe that to achieve progress in hydrological modelling, a convergence of these methods is necessary. This would allow us to exploit the respective advantages of the bottom-up and top-down models while limiting their respective uncertainties.
Catchments as meta-organisms – a new blueprint for hydrological modelling
Hubert H. G. Savenije and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 21, 1107–1116,Short summary
The natural environment that we live in is the result of evolution. This does not only apply to ecosystems, but also to the physical environment through which the water flows. This has resulted in the formation of flow patterns that obey sometimes surprisingly simple mathematical laws. Hydrological models should represent the physics of these patterns and should account for the fact that the ecosystem adjusts itself continuously to changing circumstances. Physics-based models are alive!
Remko Nijzink, Christopher Hutton, Ilias Pechlivanidis, René Capell, Berit Arheimer, Jim Freer, Dawei Han, Thorsten Wagener, Kevin McGuire, Hubert Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 4775–4799,Short summary
The core component of many hydrological systems, the moisture storage capacity available to vegetation, is typically treated as a calibration parameter in hydrological models and often considered to remain constant in time. In this paper we test the potential of a recently introduced method to robustly estimate catchment-scale root-zone storage capacities exclusively based on climate data to reproduce the temporal evolution of root-zone storage under change (deforestation).
Remko C. Nijzink, Luis Samaniego, Juliane Mai, Rohini Kumar, Stephan Thober, Matthias Zink, David Schäfer, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 20, 1151–1176,Short summary
The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
K. Schraml, B. Thomschitz, B. W. McArdell, C. Graf, and R. Kaitna
Nat. Hazards Earth Syst. Sci., 15, 1483–1492,Short summary
In this paper we used two different numerical simulation models to replicate two debris-flow events in Austria and compare the range and sensitivity of the model input parameters. We expect that our results contribute to a better application of simulation models for hazard and risk assessment in alpine regions.
S. Ceola, B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione, and T. Wagener
Hydrol. Earth Syst. Sci., 19, 2101–2117,Short summary
We present the outcomes of a collaborative hydrological experiment undertaken by five different international research groups in a virtual laboratory. Moving from the definition of accurate protocols, a rainfall-runoff model was independently applied by the research groups, which then engaged in a comparative discussion. The results revealed that sharing protocols and running the experiment within a controlled environment is fundamental for ensuring experiment repeatability and reproducibility.
O. Fovet, L. Ruiz, M. Hrachowitz, M. Faucheux, and C. Gascuel-Odoux
Hydrol. Earth Syst. Sci., 19, 105–123,Short summary
We studied the annual hysteretic patterns observed between stream flow and water storage in the saturated and unsaturated zones of a hillslope and a riparian zone. We described these signatures using a hysteresis index and then used this to assess conceptual hydrological models. This led us to identify four hydrological periods and a clearly distinct behaviour between riparian and hillslope groundwaters and to provide new information about the model performances.
S. Gharari, M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4839–4859,
S. Gharari, M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 4861–4870,
H. Gao, M. Hrachowitz, F. Fenicia, S. Gharari, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 18, 1895–1915,
T. Euser, H. C. Winsemius, M. Hrachowitz, F. Fenicia, S. Uhlenbrook, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 17, 1893–1912,
M. Hrachowitz, H. Savenije, T. A. Bogaard, D. Tetzlaff, and C. Soulsby
Hydrol. Earth Syst. Sci., 17, 533–564,
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approachesRevisiting the hydrological basis of the Budyko framework with the principle of hydrologically similar groupsReconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regressionWater and energy budgets over hydrological basins on short and long timescalesHydrological response to climate change and human activities in the Three-River Source RegionIncorporating experimentally derived streamflow contributions into model parameterization to improve discharge predictionMachine-learning- and deep-learning-based streamflow prediction in a hilly catchment for future scenarios using CMIP6 GCM dataRiver hydraulic modeling with ICESat-2 land and water surface elevationHydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece)Technical note: How physically based is hydrograph separation by recursive digital filtering?A comprehensive open-source course for teaching applied hydrological modelling in Central AsiaImpact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchmentTechnical note: Extending the SWAT model to transport chemicals through tile and groundwater flowLong-term reconstruction of satellite-based precipitation, soil moisture, and snow water equivalent in ChinaDisentangling scatter in long-term concentration–discharge relationships: the role of event typesSimulating the hydrological impacts of land use conversion from annual crop to perennial forage in the Canadian Prairies using the Cold Regions Hydrological Modelling platformHow can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?When best is the enemy of good – critical evaluation of performance criteria in hydrological modelsOn the value of satellite remote sensing to reduce uncertainties of regional simulations of the Colorado RiverAssessing runoff sensitivity of North American Prairie Pothole Region basins to wetland drainage using a basin classification-based virtual modelling approachA large-sample investigation into uncertain climate change impacts on high flows across Great BritainEffects of passive-storage conceptualization on modeling hydrological function and isotope dynamics in the flow system of a cockpit karst landscapeTechnical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networksAttribution of climate change and human activities to streamflow variations with a posterior distribution of hydrological simulationsA time-varying distributed unit hydrograph method considering soil moistureFlood patterns in a catchment with mixed bedrock geology and a hilly landscape: identification of flashy runoff contributions during storm eventsA graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusionImproving hydrologic models for predictions and process understanding using neural ODEsResponse of active catchment water storage capacity to a prolonged meteorological drought and asymptotic climate variationHESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologistsDevelopment of a national 7-day ensemble streamflow forecasting service for AustraliaFuture snow changes and their impact on the upstream runoff in SalweenTechnical note: Do different projections matter for the Budyko framework?Representation of seasonal land use dynamics in SWAT+ for improved assessment of blue and green water consumptionLarge-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological modelAn algorithm for deriving the topology of belowground urban stormwater networksProducing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observationsAssessing the influence of water sampling strategy on the performance of tracer-aided hydrological modeling in a mountainous basin on the Tibetan PlateauThe suitability of differentiable, learnable hydrologic models for ungauged regions and climate change impact assessmentFlood forecasting with machine learning models in an operational frameworkPrecipitation fate and transport in a Mediterranean catchment through models calibrated on plant and stream water isotope dataHigh-resolution satellite products improve hydrological modeling in northern ItalyAnalysis of high streamflow extremes in climate change studies: how do we calibrate hydrological models?A conceptual-model-based sediment connectivity assessment for patchy agricultural catchmentsThe Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)Spatial extrapolation of stream thermal peaks using heterogeneous time series at a national scaleRevisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradientDeep learning rainfall–runoff predictions of extreme eventsDiel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling doesTeaching hydrological modelling: illustrating model structure uncertainty with a ready-to-use computational exerciseEffects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943,Short summary
This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, Christoph Mayer, and Axel Bronstert
Hydrol. Earth Syst. Sci., 27, 1841–1863,Short summary
We present a suitable method to reconstruct sediment export from decadal records of hydroclimatic predictors (discharge, precipitation, temperature) and shorter suspended sediment measurements. This lets us fill the knowledge gap on how sediment export from glacierized high-alpine areas has responded to climate change. We find positive trends in sediment export from the two investigated nested catchments with step-like increases around 1981 which are linked to crucial changes in glacier melt.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744,Short summary
Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492,Short summary
The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable inﬁltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341,Short summary
We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Dharmaveer Singh, Manu Vardhan, Rakesh Sahu, Debrupa Chatterjee, Pankaj Chauhan, and Shiyin Liu
Hydrol. Earth Syst. Sci., 27, 1047–1075,Short summary
This study examines, for the first time, the potential of various machine learning models in streamflow prediction over the Sutlej River basin (rainfall-dominated zone) in western Himalaya during the period 2041–2070 (2050s) and 2071–2100 (2080s) and its relationship to climate variability. The mean ensemble of the model results shows that the mean annual streamflow of the Sutlej River is expected to rise between the 2050s and 2080s by 0.79 to 1.43 % for SSP585 and by 0.87 to 1.10 % for SSP245.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032,Short summary
This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
Evgenia Koltsida, Nikos Mamassis, and Andreas Kallioras
Hydrol. Earth Syst. Sci., 27, 917–931,Short summary
Daily and hourly rainfall observations were inputted to a Soil and Water Assessment Tool (SWAT) hydrological model to investigate the impacts of rainfall temporal resolution on a discharge simulation. Results indicated that groundwater flow parameters were more sensitive to daily time intervals, and channel routing parameters were more influential for hourly time intervals. This study suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin.
Hydrol. Earth Syst. Sci., 27, 495–499,Short summary
An important hydrological issue is to identify components of streamflow that react to precipitation with different degrees of attenuation and delay. From the multitude of methods that have been developed for this so-called hydrograph separation, a specific, frequently used one is singled out here. It is shown to be derived from plausible physical principles. This increases confidence in its results.
Beatrice Sabine Marti, Aidar Zhumabaev, and Tobias Siegfried
Hydrol. Earth Syst. Sci., 27, 319–330,Short summary
Numerical modelling is often used for climate impact studies in water resources management. It is, however, not yet highly accessible to many students of hydrology in Central Asia. One big hurdle for new learners is the preparation of relevant data prior to the actual modelling. We present a robust, open-source workflow and comprehensive teaching material that can be used by teachers and by students for self study.
Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Reed Maxwell, Jean-Gabriel Valay, and Didier Voisin
Hydrol. Earth Syst. Sci., 27, 191–212,Short summary
Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Hendrik Rathjens, Jens Kiesel, Michael Winchell, Jeffrey Arnold, and Robin Sur
Hydrol. Earth Syst. Sci., 27, 159–167,Short summary
The SWAT model can simulate the transport of water-soluble chemicals through the landscape but neglects the transport through groundwater or agricultural tile drains. These transport pathways are, however, important to assess the amount of chemicals in streams. We added this capability to the model, which significantly improved the simulation. The representation of all transport pathways in the model enables watershed managers to develop robust strategies for reducing chemicals in streams.
Wencong Yang, Hanbo Yang, Changming Li, Taihua Wang, Ziwei Liu, Qingfang Hu, and Dawen Yang
Hydrol. Earth Syst. Sci., 26, 6427–6441,Short summary
We produced a daily 0.1° dataset of precipitation, soil moisture, and snow water equivalent in 1981–2017 across China via reconstructions. The dataset used global background data and local on-site data as forcing input and satellite-based data as reconstruction benchmarks. This long-term high-resolution national hydrological dataset is valuable for national investigations of hydrological processes.
Felipe A. Saavedra, Andreas Musolff, Jana von Freyberg, Ralf Merz, Stefano Basso, and Larisa Tarasova
Hydrol. Earth Syst. Sci., 26, 6227–6245,Short summary
Nitrate contamination of rivers from agricultural sources is a challenge for water quality management. During runoff events, different transport paths within the catchment might be activated, generating a variety of responses in nitrate concentration in stream water. Using nitrate samples from 184 German catchments and a runoff event classification, we show that hydrologic connectivity during runoff events is a key control of nitrate transport from catchments to streams in our study domain.
Marcos R. C. Cordeiro, Kang Liang, Henry F. Wilson, Jason Vanrobaeys, David A. Lobb, Xing Fang, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 26, 5917–5931,Short summary
This study addresses the issue of increasing interest in the hydrological impacts of converting cropland to perennial forage cover in the Canadian Prairies. By developing customized models using the Cold Regions Hydrological Modelling (CRHM) platform, this long-term (1992–2013) modelling study is expected to provide stakeholders with science-based information regarding the hydrological impacts of land use conversion from annual crop to perennial forage cover in the Canadian Prairies.
Reyhaneh Hashemi, Pierre Brigode, Pierre-André Garambois, and Pierre Javelle
Hydrol. Earth Syst. Sci., 26, 5793–5816,Short summary
Hydrologists have long dreamed of a tool that could adequately predict runoff in catchments. Data-driven long short-term memory (LSTM) models appear very promising to the hydrology community in this respect. Here, we have sought to benefit from traditional practices in hydrology to improve the effectiveness of LSTM models. We discovered that one LSTM parameter has a hydrologic interpretation and that there is a need to increase the data and to tune two parameters, thereby improving predictions.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
The Kling-Gupta Efficiency (KGE) is a performance criterion extensively used to evaluate hydrological models. We conduct a critical study on the KGE and its variant to examine counterbalancing errors. Results show that, assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without being associated to an increase in model relevance. We suggest to carefully choose performance criteria and to use scaling factors.
Mu Xiao, Giuseppe Mascaro, Zhaocheng Wang, Kristen M. Whitney, and Enrique R. Vivoni
Hydrol. Earth Syst. Sci., 26, 5627–5646,Short summary
As the major water resource in the southwestern United States, the Colorado River is experiencing decreases in naturalized streamflow and is predicted to face severe challenges under future climate scenarios. Here, we demonstrate the value of Earth observing satellites to improve and build confidence in the spatiotemporal simulations from regional hydrologic models for assessing the sensitivity of the Colorado River to climate change and supporting regional water managers.
Christopher Spence, Zhihua He, Kevin R. Shook, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 5555–5575,Short summary
We learnt how streamflow from small creeks could be altered by wetland removal in the Canadian Prairies, where this practice is pervasive. Every creek basin in the region was placed into one of seven groups. We selected one of these groups and used its traits to simulate streamflow. The model worked well enough so that we could trust the results even if we removed the wetlands. Wetland removal did not change low flow amounts very much, but it doubled high flow and tripled average flow.
Rosanna A. Lane, Gemma Coxon, Jim Freer, Jan Seibert, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 26, 5535–5554,Short summary
This study modelled the impact of climate change on river high flows across Great Britain (GB). Generally, results indicated an increase in the magnitude and frequency of high flows along the west coast of GB by 2050–2075. In contrast, average flows decreased across GB. All flow projections contained large uncertainties; the climate projections were the largest source of uncertainty overall but hydrological modelling uncertainties were considerable in some regions.
Guangxuan Li, Xi Chen, Zhicai Zhang, Lichun Wang, and Chris Soulsby
Hydrol. Earth Syst. Sci., 26, 5515–5534,Short summary
We developed a coupled flow–tracer model to understand the effects of passive storage on modeling hydrological function and isotope dynamics in a karst flow system. Models with passive storages show improvement in matching isotope dynamics performance, and the improved performance also strongly depends on the number and location of passive storages. Our results also suggested that the solute transport is primarily controlled by advection and hydrodynamic dispersion in the steep hillslope unit.
Grey S. Nearing, Daniel Klotz, Jonathan M. Frame, Martin Gauch, Oren Gilon, Frederik Kratzert, Alden Keefe Sampson, Guy Shalev, and Sella Nevo
Hydrol. Earth Syst. Sci., 26, 5493–5513,Short summary
When designing flood forecasting models, it is necessary to use all available data to achieve the most accurate predictions possible. This manuscript explores two basic ways of ingesting near-real-time streamflow data into machine learning streamflow models. The point we want to make is that when working in the context of machine learning (instead of traditional hydrology models that are based on bio-geophysics), it is not necessary to use complex statistical methods for injecting sparse data.
Xiongpeng Tang, Guobin Fu, Silong Zhang, Chao Gao, Guoqing Wang, Zhenxin Bao, Yanli Liu, Cuishan Liu, and Junliang Jin
Hydrol. Earth Syst. Sci., 26, 5315–5339,Short summary
In this study, we proposed a new framework that considered the uncertainties of model simulations in quantifying the contribution rate of climate change and human activities to streamflow changes. Then, the Lancang River basin was selected for the case study. The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was mainly human activities.
Bin Yi, Lu Chen, Hansong Zhang, Vijay P. Singh, Ping Jiang, Yizhuo Liu, Hexiang Guo, and Hongya Qiu
Hydrol. Earth Syst. Sci., 26, 5269–5289,Short summary
An improved GIS-derived distributed unit hydrograph routing method considering time-varying soil moisture was proposed for flow routing. The method considered the changes of time-varying soil moisture and rainfall intensity. The response of underlying surface to the soil moisture content was considered an important factor in this study. The SUH, DUH, TDUH and proposed routing methods (TDUH-MC) were used for flood forecasts, and the simulated results were compared and discussed.
Audrey Douinot, Jean François Iffly, Cyrille Tailliez, Claude Meisch, and Laurent Pfister
Hydrol. Earth Syst. Sci., 26, 5185–5206,Short summary
The objective of the paper is to highlight the seasonal and singular shift of the transfer time distributions of two catchments (≅10 km2). Based on 2 years of rainfall and discharge observations, we compare variations in the properties of TTDs with the physiographic characteristics of catchment areas and the eco-hydrological cycle. The paper eventually aims to deduce several factors conducive to particularly rapid and concentrated water transfers, which leads to flash floods.
Alexander Y. Sun, Peishi Jiang, Zong-Liang Yang, Yangxinyu Xie, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 26, 5163–5184,Short summary
High-resolution river modeling is of great interest to local governments and stakeholders for flood-hazard mitigation. This work presents a physics-guided, machine learning (ML) framework for combining the strengths of high-resolution process-based river network models with a graph-based ML model capable of modeling spatiotemporal processes. Results show that the ML model can approximate the dynamics of the process model with high fidelity, and data fusion further improves the forecasting skill.
Marvin Höge, Andreas Scheidegger, Marco Baity-Jesi, Carlo Albert, and Fabrizio Fenicia
Hydrol. Earth Syst. Sci., 26, 5085–5102,Short summary
Neural ODEs fuse physics-based models with deep learning: neural networks substitute terms in differential equations that represent the mechanistic structure of the system. The approach combines the flexibility of machine learning with physical constraints for inter- and extrapolation. We demonstrate that neural ODE models achieve state-of-the-art predictive performance while keeping full interpretability of model states and processes in hydrologic modelling over multiple catchments.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874,Short summary
Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Riccardo Rigon, Giuseppe Formetta, Marialaura Bancheri, Niccolò Tubini, Concetta D'Amato, Olaf David, and Christian Massari
Hydrol. Earth Syst. Sci., 26, 4773–4800,Short summary
Digital Earth(DE) metaphor is very useful for both end users and hydrological modelers. We analyse different categories of models, with the view of making them part of a Digital eARth Twin Hydrology system (called DARTH). We also stress the idea that DARTHs are not models in and of themselves, rather they need to be built on an appropriate information technology infrastructure. It is remarked that DARTHs have to, by construction, support the open-science movement and its ideas.
Hapu Arachchige Prasantha Hapuarachchi, Mohammed Abdul Bari, Aynul Kabir, Mohammad Mahadi Hasan, Fitsum Markos Woldemeskel, Nilantha Gamage, Patrick Daniel Sunter, Xiaoyong Sophie Zhang, David Ewen Robertson, James Clement Bennett, and Paul Martinus Feikema
Hydrol. Earth Syst. Sci., 26, 4801–4821,Short summary
Methodology for developing an operational 7-day ensemble streamflow forecasting service for Australia is presented. The methodology is tested for 100 catchments to learn the characteristics of different NWP rainfall forecasts, the effect of post-processing, and the optimal ensemble size and bootstrapping parameters. Forecasts are generated using NWP rainfall products post-processed by the CHyPP model, the GR4H hydrologic model, and the ERRIS streamflow post-processor inbuilt in the SWIFT package
Chenhao Chai, Lei Wang, Deliang Chen, Jing Zhou, Hu Liu, Jingtian Zhang, Yuanwei Wang, Tao Chen, and Ruishun Liu
Hydrol. Earth Syst. Sci., 26, 4657–4683,Short summary
This work quantifies future snow changes and their impacts on hydrology in the upper Salween River (USR) under SSP126 and SSP585 using a cryosphere–hydrology model. Future warm–wet climate is not conducive to the development of snow. The rain–snow-dominated pattern of runoff will shift to a rain-dominated pattern after the 2040s under SSP585 but is unchanged under SSP126. The findings improve our understanding of cryosphere–hydrology processes and can assist water resource management in the USR.
Remko C. Nijzink and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 4575–4585,Short summary
Most catchments plot close to the empirical Budyko curve, which allows for the estimation of the long-term mean annual evaporation and runoff. The Budyko curve can be defined as a function of a wetness index or a dryness index. We found that differences can occur and that there is an uncertainty due to the different formulations.
Anna Msigwa, Celray James Chawanda, Hans C. Komakech, Albert Nkwasa, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 4447–4468,Short summary
Studies using agro-hydrological models, like the Soil and Water Assessment Tool (SWAT), to map evapotranspiration (ET) do not account for cropping seasons. A comparison between the default SWAT+ set-up (with static land use representation) and a dynamic SWAT+ model set-up (with seasonal land use representation) is made by spatial mapping of the ET. The results show that ET with seasonal representation is closer to remote sensing estimates, giving better performance than ET with static land use.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430,Short summary
In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
Taher Chegini and Hong-Yi Li
Hydrol. Earth Syst. Sci., 26, 4279–4300,Short summary
Belowground urban stormwater networks (BUSNs) play a critical and irreplaceable role in preventing or mitigating urban floods. However, they are often not available for urban flood modeling at regional or larger scales. We develop a novel algorithm to estimate existing BUSNs using ubiquitously available aboveground data at large scales based on graph theory. The algorithm has been validated in different urban areas; thus, it is well transferable.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. The proposed approach supports the participation of end-users in interpreting the impact of climate change on water resources.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167,Short summary
Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript accepted for HESSShort summary
Hybrid models (we call δ models) that embrace the fundamental learning capability of AI but can explain all the physical processes can be powerful. In this paper we assess how they perform when applied in regions not in the training data. δ models rivaled the accuracy of state-of-the-art AI models under the data-dense scenario and even surpassed them for the data-sparse one. They generalize well due to the physical structure. δ models could be ideal candidates for global hydrologic assessments.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032,Short summary
Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Matthias Sprenger, Pilar Llorens, Francesc Gallart, Paolo Benettin, Scott T. Allen, and Jérôme Latron
Hydrol. Earth Syst. Sci., 26, 4093–4107,Short summary
Our catchment-scale transit time modeling study shows that including stable isotope data on evapotranspiration in addition to the commonly used stream water isotopes helps constrain the model parametrization and reveals that the water taken up by plants has resided longer in the catchment storage than the water leaving the catchment as stream discharge. This finding is important for our understanding of how water is stored and released, which impacts the water availability for plants and humans.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939,Short summary
This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Bruno Majone, Diego Avesani, Patrick Zulian, Aldo Fiori, and Alberto Bellin
Hydrol. Earth Syst. Sci., 26, 3863–3883,Short summary
In this work, we introduce a methodology for devising reliable future high streamflow scenarios from climate change simulations. The calibration of a hydrological model is carried out to maximize the probability that the modeled and observed high flow extremes belong to the same statistical population. Application to the Adige River catchment (southeastern Alps, Italy) showed that this procedure produces reliable quantiles of the annual maximum streamflow for use in assessment studies.
Pedro V. G. Batista, Peter Fiener, Simon Scheper, and Christine Alewell
Hydrol. Earth Syst. Sci., 26, 3753–3770,Short summary
Patchy agricultural landscapes have a large number of small fields, which are separated by linear features such as roads and field borders. When eroded sediments are transported out of the agricultural fields by surface runoff, these features can influence sediment connectivity. By use of measured data and a simulation model, we demonstrate how a dense road network (and its drainage system) facilitates sediment transport from fields to water courses in a patchy Swiss agricultural catchment.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572,Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Aurélien Beaufort, Jacob S. Diamond, Eric Sauquet, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 3477–3495,Short summary
We developed one of the largest stream temperature databases to calculate a simple, ecologically relevant metric – the thermal peak – that captures the magnitude of summer thermal extremes. Using statistical models, we extrapolated the thermal peak to nearly every stream in France, finding the hottest thermal peaks along large rivers without forested riparian zones and groundwater inputs. Air temperature was a poor proxy for the thermal peak, highlighting the need to grow monitoring networks.
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445,Short summary
This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly used macroscale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
Jonathan M. Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shalev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 26, 3377–3392,Short summary
The most accurate rainfall–runoff predictions are currently based on deep learning. There is a concern among hydrologists that deep learning models may not be reliable in extrapolation or for predicting extreme events. This study tests that hypothesis. The deep learning models remained relatively accurate in predicting extreme events compared with traditional models, even when extreme events were not included in the training set.
Sebastian A. Krogh, Lucia Scaff, James W. Kirchner, Beatrice Gordon, Gary Sterle, and Adrian Harpold
Hydrol. Earth Syst. Sci., 26, 3393–3417,Short summary
We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder rather than in warmer places, which is then contrasted with land surface simulations.
Wouter J. M. Knoben and Diana Spieler
Hydrol. Earth Syst. Sci., 26, 3299–3314,Short summary
This paper introduces educational materials that can be used to teach students about model structure uncertainty in hydrological modelling. There are many different hydrological models and differences between these models impact their usefulness in different places. Such models are often used to support decision making about water resources and to perform hydrological science, and it is thus important for students to understand that model choice matters.
Leonie Kiewiet, Ernesto Trujillo, Andrew Hedrick, Scott Havens, Katherine Hale, Mark Seyfried, Stephanie Kampf, and Sarah E. Godsey
Hydrol. Earth Syst. Sci., 26, 2779–2796,Short summary
Climate change affects precipitation phase, which can propagate into changes in streamflow timing and magnitude. This study examines how variations in rainfall and snowmelt affect discharge. We found that annual discharge and stream cessation depended on the magnitude and timing of rainfall and snowmelt and on the snowpack melt-out date. This highlights the importance of precipitation timing and emphasizes the need for spatiotemporally distributed simulations of snowpack and rainfall dynamics.
Aleotti, P.: A warning system for rainfall-induced shallow failures, Eng. Geol., 73, 247–265, https://doi.org/10.1016/j.enggeo.2004.01.007, 2004.
Anagnostopoulos, G. G., Fatichi, S., and Burlando, P.: An advanced process-based distributed model for the investigation of rainfall-induced landslides: The effect of process representation and boundary conditions, Water Resour. Res., 51, 7501–7523, https://doi.org/10.1002/2015WR016909, 2015.
Auer, I., Böhm, R., Jurkovic, A., Lipa, W., Orlik, A., Potzmann, R., Schöner, W., Ungersböck, M., Matulla, C., Briffa, K., Jones, P. D., Efthymiadis, D., Brunetti, M., Nanni, T., Maugeri, M., Mercalli, L., Mestre, O., Moisselin, J.-M., Begert, M., Müller-Westermeier, G., Kveton, V., Bochnicek, O., Stastny, P., Lapin, M., Szalai, S., Szentimrey, T., Cegnar, T., Dolinar, M., Gajic-Capka, M., Zaninovic, K., Majstorovic, Z., and Nieplova, E.: HISTALP – historical instrumental climatological surface time series of the Greater Alpine Region, Int. J. Climatol., 27, 17–46, https://doi.org/10.1002/joc.1377, 2007.
Austrian Glacier Inventory: Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck, available at: http://acinn.uibk.ac.at/research/ice-and-climate/projects/agi, last access: 2 February 2016.
Baum, R. L. and Godt, J. W.: Early warning of rainfall-induced shallow landslides and debris flows in the USA, Landslides, 7, 259–272, https://doi.org/10.1007/s10346-009-0177-0, 2010.
Berenguer, M., Sempere-Torres, D., and Hürlimann, M.: Debris-flow forecasting at regional scale by combining susceptibility mapping and radar rainfall, Nat. Hazards Earth Syst. Sci., 15, 587–602, https://doi.org/10.5194/nhess-15-587-2015, 2015.
Berghuijs, W. R., Sivapalan, M., Woods, R. A., and Savenije, H. H.: Patterns of similarity of seasonal water balances: A window into streamflow variability over a range of time scales, Water Resour. Res., 50, 5638–5661, https://doi.org/10.1002/2014WR015692, 2014.
Berti, M. and Simoni, A.: Experimental evidences and numerical modelling of debris flow initiated by channel runoff, Landslides, 2, 171–182, https://doi.org/10.1007/s10346-005-0062-4, 2005.
Berti, M., Genevois, R., Simoni, A., and Tecca, P. R.: Field observations of a debris flow event in the Dolomites, Geomorphology 29, 265–274, https://doi.org/10.1016/S0169-555X(99)00018-5, 1999.
Berti, M., Martina, M. L. V., Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.: Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res., 117, F04006, https://doi.org/10.1029/2012JF002367, 2012.
Beven, K.: Changing ideas in hydrology – the case of physically based models, J. Hydrol., 105, 157–172, 1989.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006a.
Beven, K.: Searching for the Holy Grail of scientific hydrology: as closure, Hydrol. Earth Syst. Sci., 10, 609–618, https://doi.org/10.5194/hess-10-609-2006, 2006b.
Beven, K. J.: Rainfall-Runoff Modelling: The Primer, 2nd Edn., John Wiley & Sons Inc., Chichester, UK, ISBN: 978-0-470-71459-1, 2012.
Beven, K. J., Almeida, S., Aspinall, W. P., Bates, P. D., Blazkova, S., Borgomeo, E., Goda, K., Hall, J. W., Phillips, J. C., Simpson, M., Smith, P. J., Stephenson, D. B., Wagener, T., Watson, M., and Wilkins, K. L.: Epistemic uncertainties and natural hazard risk assessment. 1. A review of different natural hazard areas, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-250, in review, 2017a.
Beven, K. J., Aspinall, W. P., Bates, P. D., Borgomeo, E., Goda, K., Hall, J. W., Page, T., Phillips, J. C., Simpson, M., Smith, P. J., Wagener, T., and Watson, M.: Epistemic uncertainties and natural hazard risk assessment. 2. What should constitute good practice?, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-251, in review, 2017b.
Bíl, M., Andrášik, R., Zahradníček, P., Kubeček, J., Sedoník, J., and Štěpánek, P.: Total water content thresholds for shallow landslides, Outer Western Carpathians, Landslides, 13, 337–347, https://doi.org/10.1007/s10346-015-0570-9, 2015.
Birkel, C., Soulsby, C., and Tetzlaff, D.: Conceptual modelling to assess how the interplay of hydrological connectivity, catchment storage and tracer dynamics controls nonstationary water age estimates, Hydrol. Process., 29, 2956–2969, https://doi.org/10.1002/hyp.10414, 2015.
Bogaard, T. and Greco, R.: Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat. Hazards Earth Syst. Sci., 18, 31–39, https://doi.org/10.5194/nhess-18-31-2018, 2018.
Bogaard, T. A. and Greco, R.: Landslide hydrology: from hydrology to pore pressure, WIREs Water, 3, 439–459, https://doi.org/10.1002/wat2.1126, 2016.
Böhm, R., Schöner, W., Auer, I., Hynek, B., Kroisleitner, C., Weyss, G., and Jurkovic, A.: Gletscher und Abflussverhalten, Bericht zu Zielvereinbarung 2008/31, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Austria, 2007.
Borga, M., Stoffel, M., Marchi, L., Marra, F., and Jakob, M.: Hydrogeomorphic response to extreme rainfall in headwater systems: flash floods and debris flows, J. Hydrol., 518, 194–205, https://doi.org/10.1016/j.jhydrol.2014.05.022, 2014.
Braun, M. and Kaitna, R.: Analysis of meteorological trigger conditions for debris flows on a daily time scale, in: Debris flows: risks, forecast, protection: Materials of IV International Conference (Russia, Irkutsk – Arshan village (The Republic of Buriatia), edited by: Makarov, S. A., Atutova, J. V., and Shekhovtsov, A. I., Publishing House of Sochava Institute of Geography SB RAS, Irkutsk, ISBN: 978-5-94797-273-3, 2016.
BMLFUW: Austrian Federal Ministry of Agriculture, Forestry, Environment and Water Management, inventory of documented mass movements in Austria, last access: December 2015.
Chitu, Z., Bogaard, T. A., Busuioc, A., Burcea, S., Sandric, I., and Adler, M. J.: Identifying hydrological pre-conditions and rainfall triggers of slope failures at catchment scale for 2014 storm events in the Ialomita Subcarpathians, Romania, Landslides, 14, 419–434, https://doi.org/10.1007/s10346-016-0740-4, 2017.
Church, M. and Miles, M. J.: Meteorological antecedents to debris flow in southwestern British Columbia: some case studies, in: Debris flows/avalanches: Process, Recognition and Mitigation, edited by: Costa, J. E. and Wieczorek, G. F., Reviews in Engineering Geology, 7, 63–80, Geological Society of America, Boulder, Colorado, https://doi.org/10.1130/REG7-p63, 1987.
Ciavolella, M., Bogaard, T. A., Gargano, R., and Greco, R.: Is there predictive power in hydrological catchment information for regional landslides hazard assessment?, Proced. Earth Plan. Sc., 16, 195–203, https://doi.org/10.1016/j.proeps.2016.10.021, 2016.
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta, H. V., Wagener, T., and Hay, L. E.: Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models, Water Resour. Res., 44, W00B02, https://doi.org/10.1029/2007WR006735, 2008.
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resour. Res., 47, W09301, https://doi.org/10.1029/2010WR009827, 2011.
Clark, M. P., Bierkens, M. F. P., Samaniego, L., Woods, R. A., Uijlenhoet, R., Bennett, K. E., Pauwels, V. R. N., Cai, X., Wood, A. W., and Peters-Lidard, C. D.: The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism, Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, 2017.
Coe, J. A., Kinner, D. A., and Godt, J. W.: Initiation conditions for debris flows generated by runoff at Chalk Cliffs, central Colorado, Geomorphology 96, 270–297, https://doi.org/10.1016/j.geomorph.2007.03.017, 2008.
Cohen, J., Ye, H., and Jones, J.: Trends and variability in rain-on-snow events, Geophys. Res. Lett., 42, 7115–7122, https://doi.org/10.1002/2015GL065320, 2015.
Conway, H. and Raymond, C. F.: Snow stability during rain, J. Glaciol., 39, 635–642, 1993.
CORINE Land cover: European Environment Agency, European Union, available at: http://eea.europa.eu/data-and-maps/data/corine-land-cover-1990-raster-3, last access: 2 February 2016a.
CORINE Land cover: European Environment Agency, European Union, available at: http://eea.europa.eu/data-and-maps/data/corine-land-cover-2000-raster-2,, last access: 2 February 2016b.
CORINE Land cover: European Environment Agency, European Union, available at: http://eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-3, last access: 2 February 2016c.
Criss, R. E. and Winston, W. E.: Do Nash values have value? Discussion and alternate proposals, Hydrol. Process., 22, 2723–2725, https://doi.org/10.1002/hyp.7072, 2008.
Crozier, M. J.: Prediction of rainfall-triggered landslides: a test of the antecedent water status model, Earth Surf. Proc. Land., 24, 825–833, https://doi.org/10.1002/(SICI)1096-9837(199908)24:9<825::AID-ESP14>3.0.CO;2-M, 1999.
Data.gv.at: Digital Elevation Model (DEM) “b5de6975-417b-4320-afdb-eb2a9e2a1dbf”, available at: http://data.gv.at/katalog/dataset/b5de6975-417b-4320-afdb-eb2a9e2a1dbf, last access: 2 February 2016.
Decaulne, A., Sæmundsson, Þ., and Pétursson, O.: Debris flow triggered by rapid snowmelt: a case study in the Gleiðarhjalli area, northwestern Iceland, Geogr. Ann. A, 87, 487–500, https://doi.org/10.1111/j.0435-3676.2005.00273.x, 2005.
Deganutti, A. M., Marchi, L., and Arattano, M.: Rainfall and debris-flow occurrence in the Moscardo basin (Italian Alps), in: Debris-flow Hazards Mitigation: Mechanics, Prediction and Assessment, edited by: Wieczorek, G. F. and Naeser, N. D., Proceedings of the second international conference on debris flow hazards mitigation, Taipei, Taiwan, 62–72, 16–18 August 2000.
Dhakal, A. S. and Sidle, R. C.: Distributed simulations of landslides for different rainfall conditions, Hydrol. Process., 18, 757–776, https://doi.org/10.1002/hyp.1365, 2004.
Dooge, J. C.: Looking for hydrologic laws, Water Resour. Res., 22, 46–58, https://doi.org/10.1029/WR022i09Sp0046S, 1986.
Euser, T., Winsemius, H. C., Hrachowitz, M., Fenicia, F., Uhlenbrook, S., and Savenije, H. H. G.: A framework to assess the realism of model structures using hydrological signatures, Hydrol. Earth Syst. Sci., 17, 1893–1912, https://doi.org/10.5194/hess-17-1893-2013, 2013.
Euser, T., Hrachowitz, M., Winsemius, H. C., and Savenije, H. H. G.: The effect of forcing and landscape distribution on performance and consistency of model structures: Distribution of forcing and model structures, Hydrol. Process., 29, 3727–3743, https://doi.org/10.1002/hyp.10445, 2015.
Fan, L., Lehmann, P., and Or, D.: Effects of soil spatial variability at the hillslope and catchment scales on characteristics of rainfall-induced landslides, Water Resour. Res., 52, 1781–1799, https://doi.org/10.1002/2015WR017758, 2016.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resour. Res., 47, W11510, https://doi.org/10.1029/2010WR010174, 2011.
Fenicia, F., Kavetski, D., Savenije, H. H. G., Clark, M. P., Schoups, G., Pfister, L., and Freer, J.: Catchment properties, function, and conceptual model representation: is there a correspondence?, Hydrol. Process., 28, 2451–2467, https://doi.org/10.1002/hyp.9726, 2014.
Fenicia, F., Kavetski, D., Savenije, H. H. G., and Pfister, L.: From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions, Water Resour. Res., 52, 954–989, https://doi.org/10.1002/2015WR017398, 2016.
Fovet, O., Ruiz, L., Hrachowitz, M., Faucheux, M., and Gascuel-Odoux, C.: Hydrological hysteresis and its value for assessing process consistency in catchment conceptual models, Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, 2015.
Gao, H., Ding, Y., Zhao, Q., Hrachowitz, M., and Savenije, H. H. G.: The importance of aspect for modelling the hydrological response in a glacier catchment in Central Asia, Hydrol. Process., 31, 2842–2859, https://doi.org/10.1002/hyp.11224, 2017.
Gharari, S., Hrachowitz, M., Fenicia, F., Gao, H., and Savenije, H. H. G.: Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrol. Earth Syst. Sci., 18, 4839–4859, https://doi.org/10.5194/hess-18-4839-2014, 2014.
Glade, T.: Modelling landslide-triggering rainfalls in different regions of New Zealand – the soil water status model, Z. Geomorphol., 122, 63–84, 2000.
Glade, T., Crozier, M., and Smith, P.: Applying Probability Determination to Refine Landslide-triggering Rainfall Thresholds Using an “Empirical Antecedent Daily Rainfall Model”, Pure Appl. Geophys., 157, 1059–1079, https://doi.org/10.1007/s000240050017, 2000.
Gregoretti, C. and Fontana, G. D.: The triggering of debris flow due to channel-bed failure in some alpine headwater basins of the Dolomites: analyses of critical runoff, Hydrol. Process., 22, 2248–2263, https://doi.org/10.1002/hyp.6821, 2008.
Gupta, H. V., Wagener, T., and Liu, Y.: Reconciling theory with observations: Elements of a diagnostic approach to model evaluation, Hydrol. Process., 22, 3802–3813, https://doi.org/10.1002/hyp.6989, 2008.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol. Atmos. Phys., 98, 239–267, https://doi.org/10.1007/s00703-007-0262-7, 2007.
Guzzetti, F., Peruccacci, S., Rossi, M., and Stark, C. P.: The rainfall intensity–duration control of shallow landslides and debris flows: an update, Landslides, 5, 3–17, https://doi.org/10.1007/s10346-007-0112-1, 2008.
Hargreaves, G. H. and Samani, Z. A.: Reference crop evapotranspiration from temperature, Appl. Eng. Agric., 1, 96–99, https://doi.org/10.13031/2013.26773, 1985.
Harr, R. D.: Some characteristics and consequences of snowmelt during rainfall in Western Oregon, J. Hydrol., 53, 277–304, 1981.
HD Tirol: Hydrographischer Dienst Tirol (Hydrographic Service Tyrol), Sachgebiet Hydrographie und Hydrologie, Amt der Tiroler Landesregierung, available at: http://tirol.gv.at, last access: 25 August 2015.
Hrachowitz, M. and Clark, M. P.: HESS Opinions: The complementary merits of competing modelling philosophies in hydrology, Hydrol. Earth Syst. Sci., 21, 3953–3973, https://doi.org/10.5194/hess-21-3953-2017, 2017.
Hrachowitz, M. and Weiler, M.: Uncertainty of Precipitation Estimates Caused by Sparse Gauging Networks in a Small, Mountainous Watershed, J. Hydrol. Eng., 16, 460–471, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000331, 2011.
Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R., Freer, J., Savenije, H. H. G., and Gascuel-Odoux, C.: Process consistency in models: The importance of system signatures, expert knowledge, and process complexity, Water Resour. Res., 50, 7445–7469, https://doi.org/10.1002/2014WR015484, 2014.
Hrachowitz, M., Fovet, O., Ruiz, L., and Savenije, H. H.: Transit time distributions, legacy contamination and variability in biogeochemical 1/fα scaling: how are hydrological response dynamics linked to water quality at the catchment scale?, Hydrol. Process., 29, 5241–5256, https://doi.org/10.1002/hyp.10546, 2015.
Hübl, J., Totschnig, R., Sitter, F., Mayer, B., and Schneider, A.: Historische Ereignisse – Band 2: Auswertung von Wildbach Schadereignissen in Westösterreich auf Grundlage der Wildbachaufnahmeblätter, IAN Report 111, Band 2, University of Natural Resources and Life Sciences, Vienna, 2008.
Hungr, O., Leroueil, S., and Picarelli, L.: The Varnes classification of landslide types: an update, Landslides 11, 167–194, https://doi.org/10.1007/s10346-013-0436-y, 2014.
Iverson, R. M.: Landslide triggering by rain infiltration, Water Resour. Res., 36, 1897–1910, https://doi.org/10.1007/3-540-27129-5_1, 2000.
Jakeman, A. J. and Hornberger, G. M.: How much complexity is warranted in a rainfall-runoff model?, Water Resour. Res., 29, 2637–2649, 1993.
Johnson, K. and Sitar, N.: Hydrologic conditions leading to debris-flow initiation, Can. Geotech. J., 27, 789–801, https://doi.org/10.1139/t90-092, 1990.
Kean, J. W., McCoy, S. W., Tucker, G. E., Staley, D. M., and Coe, J. A.: Runoff-generated debris flows: Observations and modeling of surge initiation, magnitude, and frequency, J. Geophys. Res.-Earth, 118, 2190–2207, https://doi.org/10.1002/jgrf.20148, 2013.
Kienholz, H.: Gefahrenbeurteilung und -bewertung – auf dem Weg zu einem Gesamtkonzept, Schweizerische Zeitschrift für Forstwesen, 146, 701–725, 1995.
Lambrecht, A. and Kuhn, M.: Glacier changes in the Austrian Alps during the last three decades, derived from the new Austrian glacier inventory, Ann. Glaciol., 46, 177–184, 2007.
Leavesley, G. H., Markstrom, S. L., Brewer, M. S., and Viger, R. J.: The modular modeling system (MMS) – The physical process modeling component of a database-centered decision support system for water and power management, in: Clean Water: Factors that Influence Its Availability, Quality and Its Use, edited by: Chow, W., Brocksen, R. W., and Wisniewski, J., Springer the Netherlands, 303–311, 1996.
Lehmann, P. and Or, D.: Hydromechanical triggering of landslides: From progressive local failures to mass release, Water Resour. Res., 48, W03535, https://doi.org/10.1029/2011WR010947, 2012.
Mader, H., Steidl, T., and Wimmer, R.: Abflussregime Österreichischer Fließgewässer: Beitrag zu einer bundesweiten Fließgewassertypologie, Umweltbundesamt, Monographien, Vol. 82, Wien, ISBN: 3-85457-336-7, 1996.
Mancarella, D., Doglioni, A., and Simeone, V.: On capillary barrier effects and debris slide triggering in unsaturated layered covers, Eng. Geol., 147–148, 14–27, https://doi.org/10.1016/j.enggeo.2012.07.003, 2012.
Marchi, L., Arattano, M., and Deganutti, A. M.: Ten years of debris-flow monitoring in the Moscardo Torrent (Italian Alps), Geomorphology, 46, 1–17, https://doi.org/10.1016/S0169-555X(01)00162-3, 2002.
Marra, F., Destro, E., Nikolopoulos, E. I., Zoccatelli, D., Creutin, J. D., Guzzetti, F., and Borga, M.: Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds, Hydrol. Earth Syst. Sci., 21, 4525–4532, https://doi.org/10.5194/hess-21-4525-2017, 2017.
McArdell, B. W., Bartelt, P., and Kowalski, J.: Field observations of basal forces and fluid pore pressure in a debris flow, Geophys. Res. Lett., 34, L07406, https://doi.org/10.1029/2006GL029183, 2007.
McCoy, S. W., Kean, J. W., Coe, J. A., Tucker, G. E., Staley, D. M., and Wasklewicz, T. A.: Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment, J. Geophys. Res.-Earth, 117, F03016, https://doi.org/10.1029/2011JF002278, 2012.
McDonnell, J. J., Sivapalan, M., Vaché, K., Dunn, S., Grant, G., Haggerty, R., Hinz, C., Hooper, R., Kirchner, J., Roderick, M. L., Selker, J., and Weiler, M.: Moving beyond heterogeneity and process complexity: A new vision for watershed hydrology, Water Resour. Res., 43, W07301, https://doi.org/10.1029/2006WR005467, 2007.
Mergili, M. and Kerschner, H.: Gridded precipitation mapping in mountainous terrain combining GRASS and R, Norsk Geogr. Tidsskr., 69, 2–17, https://doi.org/10.1080/00291951.2014.992807, 2015.
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the topographic control on shallow landsliding, Water Resour. Res., 30, 1153–1171, https://doi.org/10.1029/93WR02979, 1994.
Montgomery, D. R., Schmidt, K. M., Dietrich, W. E., and McKean, J.: Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability, J. Geophys. Res.-Earth, 114, F01031, https://doi.org/10.1029/2008JF001078, 2009.
Moser, M. and Hohensinn, F.: Geotechnical aspects of soil slips in Alpine regions, Eng. Geol., 19, 185–211, https://doi.org/10.1016/0013-7952(83)90003-0, 1983.
Nandi, A. and Shakoor, A.: Application of logistic regression model for slope instability prediction in Cuyahoga River Watershed, Ohio, USA, Georisk, 2, 16–27, https://doi.org/10.1080/17499510701842221, 2008.
Napolitano, E., Fusco, F., Baum, R. L., Godt, J. W., and De Vita, P.: Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy), Landslides, 13, 967–983, https://doi.org/10.1007/s10346-015-0647-5, 2016.
Nash, J. E. and Sutcliffe, J. V.: 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.
Nijzink, R. C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M., Schäfer, D., Savenije, H. H. G., and Hrachowitz, M.: The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models, Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, 2016a.
Nijzink, R., Hutton, C., Pechlivanidis, I., Capell, R., Arheimer, B., Freer, J., Han, D., Wagener, T., McGuire, K., Savenije, H., and Hrachowitz, M.: The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?, Hydrol. Earth Syst. Sci., 20, 4775–4799, https://doi.org/10.5194/hess-20-4775-2016, 2016b.
Nikolopoulos, E. I., Crema, S., Marchi, L., Marra, F., Guzzetti, F., and Borga, M.: Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence, Geomorphology, 221, 286–297, https://doi.org/10.1016/j.geomorph.2014.06.015, 2014.
Oudin, L., Andréassian, V., Perrin, C., and Anctil, F.: Locating the sources of low-pass behavior within rainfall-runoff models, Water Resour. Res., 40, W11101, https://doi.org/10.1029/2004WR003291, 2004.
Papa, M. N., Medina, V., Ciervo, F., and Bateman, A.: Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems, Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, 2013.
Prancevic, J. P., Lamb, M. P., and Fuller, B. M.: Incipient sediment motion across the river to debris-flow transition, Geology, 42, 191–194, https://doi.org/10.1130/G34927.1, 2014.
Reichenbach, P., Mondini, A. C., and Rossi, M.: The influence of land use change on landslide susceptibility zonation: the Briga catchment test site (Messina, Italy), Environ. Manage., 54, 1372–1384, 2014.
Rickenmann, D. and Zimmermann, M.: The 1987 debris flows in Switzerland: documentation and analysis, Geomorphology, 8, 175–189, 1993.
Savenije, H. H. G. and Hrachowitz, M.: HESS Opinions “Catchments as meta-organisms – a new blueprint for hydrological modelling”, Hydrol. Earth Syst. Sci., 21, 1107–1116, https://doi.org/10.5194/hess-21-1107-2017, 2017.
Schimpf, H.: Untersuchung über das Auftreten beachtlicher Niederschläge in Österreich, Österreichische Wasserwirtschaft, 22, 121–127, 1970.
Schoups, G., Hopmans, J. W., Young, C. A., Vrugt, J. A., and Wallender, W. W.: Multi-criteria optimization of a regional spatially-distributed subsurface water flow model, J. Hydrol., 311, 20–48, https://doi.org/10.1016/j.jhydrol.2005.01.001, 2005.
Seibert, J.: Regionalisation of parameters for a conceptual rainfall-runoff model, Agr. Forest Meteorol., 98, 279–293, 1999.
Seibert, J. and Beven, K. J.: Gauging the ungauged basin: how many discharge measurements are needed?, Hydrol. Earth Syst. Sci., 13, 883–892, https://doi.org/10.5194/hess-13-883-2009, 2009.
Sidle, R. C. and Ziegler, A. D.: The canopy interception-landslide initiation conundrum: insight from a tropical secondary forest in northern Thailand, Hydrol. Earth Syst. Sci., 21, 651–667, https://doi.org/10.5194/hess-21-651-2017, 2017.
Simoni, S., Zanotti, F., Bertoldi, G., and Rigon, R.: Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process., 22, 532–545, https://doi.org/10.1002/hyp.6886, 2008.
Sivapalan, M.: Pattern, process and function: Elements of a new unified theory of hydrologic at the catchment scale, in: Encyclopedia of Hydrological Sciences, edited by: Anderson, M. G., John Wiley & Sons Australia Ltd, UK, 1, 193–220, 2005.
Stoffel, M., Bollschweiler, M., and Beniston, M.: Rainfall characteristics for periglacial debris flows in the Swiss Alps: past incidences–potential future evolutions, Climatic Change, 105, 263–280, https://doi.org/10.1007/s10584-011-0036-6, 2011.
Takahashi, T.: Estimation of potential debris flows and their hazardous zones: Soft countermeasures for a disaster, Natural Disaster science, 3, 57–89, 1981.
TIRIS: Tiroler Rauminformationssystem, State of Tyrol, available at: http://tirol.gv.at/data/datenkatalog, last access: 29 July 2015.
TIWAG: Tiroler Wasserkraft AG (Tyrolean Hydropower Corporation), available at: http://tiwag.at, last access: 11 September 2015.
Turkington, T., Remaître, A., Ettema, J., Hussin, H., and Westen, C.: Assessing debris flow activity in a changing climate, Climatic Change, 1, 1–13, https://doi.org/10.1007/s10584-016-1657-6, 2016.
Valéry, A., Andréssian, V., and Perrin, C.: Regionalization of precipitation and air temperature over high-altitude catchments – learning from outliers, Hydrolog. Sci. J., 55, 928–940, https://doi.org/10.1080/02626667.2010.504676, 2010.
van den Heuvel, F., Goyette, S., Rahman, K., and Stoffel, M.: Circulation patterns related to debris-flow triggering in the Zermatt valley in current and future climates, Geomorphology, 272, 127–136, https://doi.org/10.1016/j.geomorph.2015.12.010, 2016.
von Ruette, J., Papritz, A., Lehmann, P., Rickli, C., and Or, D.: Spatial statistical modeling of shallow landslides – Validating predictions for different landslide inventories and rainfall events, Geomorphology, 133, 11–22, https://doi.org/10.1016/j.geomorph.2011.06.010, 2011.
von Ruette, J., Lehmann, P., and Or, D.: Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization, Water Resour. Res., 49, 6266–6285, https://doi.org/10.1002/wrcr.20418, 2013.
Wagener, T., Boyle, D. P., Lees, M. J., Wheater, H. S., Gupta, H. V., and Sorooshian, S.: A framework for development and application of hydrological models, Hydrol. Earth Syst. Sci., 5, 13–26, https://doi.org/10.5194/hess-5-13-2001, 2001.
WGMS: Fluctuations of Glaciers Database, World Glacier Monitoring Service, Zurich, Switzerland, https://doi.org/10.5904/wgms-fog-2017-06, 2017.
Wieczorek, G. F. and Glade, T.: Climatic factors influencing occurrence of debris flows, in: Debris-flow Hazards and Related Phenomena, edited by: Jakob, M., and Hungr, O., Springer, Berlin, Heidelberg, 325–362, https://doi.org/10.1007/3-540-27129-5_14, 2005.
ZAMG: Zentralanstalt für Meteorologie und Geodynamik, Central Institute for Meteorology and Geodynamics, available at: http://zamg.ac.at, last access: 6 October 2015.
Zehe, E., Elsenbeer, H., Lindenmaier, F., Schulz, K., and Blöschl, G.: Patterns of predictability in hydrological threshold systems, Water Resour. Res., 43, W07434, https://doi.org/10.1029/2006WR005589, 2007.
Zehe, E., Ehret, U., Pfister, L., Blume, T., Schröder, B., Westhoff, M., Jackisch, C., Schymanski, S. J., Weiler, M., Schulz, K., Allroggen, N., Tronicke, J., van Schaik, L., Dietrich, P., Scherer, U., Eccard, J., Wulfmeyer, V., and Kleidon, A.: HESS Opinions: From response units to functional units: a thermodynamic reinterpretation of the HRU concept to link spatial organization and functioning of intermediate scale catchments, Hydrol. Earth Syst. Sci., 18, 4635–4655, https://doi.org/10.5194/hess-18-4635-2014, 2014.
- Full-text XML
Debris flows represent a severe hazard in mountain regions and so far remain difficult to predict. We applied a hydrological model to link not only precipitation, but also snowmelt, antecedent soil moisture, etc. with debris flow initiation in an Alpine watershed in Austria. Our results highlight the value of this more holistic perspective for developing a better understanding of debris flow initiation.
Debris flows represent a severe hazard in mountain regions and so far remain difficult to...