Articles | Volume 19, issue 11
https://doi.org/10.5194/hess-19-4619-2015
© 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/hess-19-4619-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Nov 2015
Research article |
| 23 Nov 2015
From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution
M. Herrnegger
CORRESPONDING AUTHOR
Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
H. P. Nachtnebel
Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
K. Schulz
Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, Austria
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Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
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We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
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Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
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We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
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This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
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A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
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Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
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We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
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Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-272, https://doi.org/10.5194/hess-2024-272, 2024
Revised manuscript accepted for HESS
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Our study projects how climate change will affect drying of river segments and stream networks in Europe, using advanced modeling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent, intense and start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists in evaluating the ecological health of river ecosystem.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
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
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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.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
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An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-230, https://doi.org/10.5194/hess-2024-230, 2024
Revised manuscript accepted for HESS
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Water budget non-closure is a widespread phenomenon among multisource datasets, which undermines the robustness of hydrological inferences. This study proposes a Multisource Datasets Correction Framework grounded in Physical Hydrological Processes Modelling to enhance water budget closure, called PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset, and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Eduardo Acuna Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-2147, https://doi.org/10.5194/egusphere-2024-2147, 2024
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Data-driven techniques have shown the potential to outperform process-based models in rainfall-runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions we test their generalization capabilities for extreme hydrological events.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
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The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
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By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
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Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
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Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
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Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-1464, https://doi.org/10.5194/egusphere-2024-1464, 2024
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Our study conducted a detailed analysis of runoff component and future trend in the Yarlung Tsangpo River basin owing to the existed differences in the published results, and find that the contributions of snowmelt and glacier melt runoff to streamflow were limited, both for ~5 % which were much lower than previous results. The streamflow there will continuously increase in the future, but the overestimated contribution from glacier melt would lead to an underestimation on such increasing trend.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart Lane, and Francesco Comiti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1687, https://doi.org/10.5194/egusphere-2024-1687, 2024
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In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until an overparametrization limit is reached.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-169, https://doi.org/10.5194/hess-2024-169, 2024
Revised manuscript accepted for HESS
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Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine-learning models are increasingly being applied for flood forecasting. Such models are typically trained to large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets, that maximise the spatiotemproal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
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This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-118, https://doi.org/10.5194/hess-2024-118, 2024
Revised manuscript accepted for HESS
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This study develops an integrated framework based on the novel Driving index for changes in Precipitation-Runoff Relationships (DPRR) to explore the controls for changes in precipitation-runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation-runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2024-1030, https://doi.org/10.5194/egusphere-2024-1030, 2024
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Accurate early warning systems are crucial for reducing damages caused by flooding events. In this study, we demonstrate the potential of Long Short-Term Memory Networks for enhancing the forecast accuracy of hydrologic models employed in operational flood forecasting. The presented approach elevated the investigated hydrologic model’s forecast accuracy for further ahead predictions and at flood event runoff.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Cited articles
Ahrens, B., Jasper, K., and Gurtz, J.: On ALADIN precipitation modeling and validation in an Alpine watershed, Ann. Geophys., 21, 627–637, https://doi.org/10.5194/angeo-21-627-2003, 2003.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration: guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper No. 56, Rome, Italy, 1998.
Bergström, S.: The HBV model, in: Computer Models of Watershed Hydrology, edited by: Singh, V. P., Water Resources Publications, Highland Ranch, CO, USA, 443–476, 1995.
Bica, B., Herrnegger, M., Kann, A., and Nachtnebel, H. P.: HYDROCAST – Enhanced estimation of areal rainfallby combining a meteorological nowcasting system with a hydrological model, Final report, Austrian Academy of Science, Vienna, https://doi.org/10.1553/hydrocast2011, 2011.
BMLFUW: Hydrological Atlas of Austria, 3rd Edn., Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft, Vienna, Austria, ISBN: 3-85437-250-7, 2007.
BMLFUW: Hydrographical Yearbook of Austria, Abteilung VII 3 – Wasserhaushalt im Bundesministerium für Land und Forstwirtschaft, Umwelt und Wasserwirtschaft, Vienna, Austria, 2009.
Brent, R. P.: Algorithms for Minimization without Derivatives, Prentice-Hall, Englewood Cliffs, NJ, USA, 1973.
de Jong, C., List, F., and Ergenzinger, C.: Experimental hydrological analyses in the Dischma based on daily and seasonal evaporation, Nord. Hydrol., 33, 1–14, 2002.
di Baldassarre, G. and Montanari, A.: Uncertainty in river discharge observations: a quantitative analysis, Hydrol. Earth Syst. Sci., 13, 913–921, https://doi.org/10.5194/hess-13-913-2009, 2009.
Duan, Q., Sorooshian, S., and Gupta, V. K.: Effective and efficient global optimization for conceptual rainfall–runoff models, Water Resour. Res., 28, 1015–1031, 1992.
Eder, G., Fuchs, M., Nachtnebel, H. P., and Loibl, W.: Semi-distributed modelling of the monthly water balance in an alpine catchment, Hydrol. Process., 19, 2339–2360, 2005.
Elias, V., Tesar, M., and Buchtele, J.: Occult precipitation: sampling, chemical analysis and process modeling in the Sumava Mts. (Czech Republic) and in the Taunus Mts. (Germany), J. Hydrol., 166, 409–420, 1995.
Fekete, B. M., Vorosmarty, C. J., Roads, J. O., and Willmot, C. J.: Uncertainties in precipitation and their impacts on runoff estimates, J. Climate, 17, 294–304, 2004.
Goodison, B. E., Louie, P. Y. T., and Yang, D.: WMO solid precipitation measurement intercomparison, Instruments and Observing Methods Rep. 67 (WMO/TD 872), World Meteorological Organization, Geneva, Switzerland, 318 pp., 1998.
Groetsch, C.: Inverse Problems in Mathematical Sciences, Vieweg Mathematics for Scientists and Engineers, Wiesbaden, 1993.
Haiden, T. and Pistotnik, G.: Intensity-dependent parameterization of elevation effects in precipitation analysis, Adv. Geosci., 20, 33–38, https://doi.org/10.5194/adgeo-20-33-2009, 2009.
Haiden, T., Kann, A., Wittman, C., Pistotnik, G., Bica, B., and Gruber, C.: The Integrated Nowcasting through Comprehensive Analysis (INCA) system and its validation over the Eastern Alpine region, Weather Forecast., 26, 166–183, https://doi.org/10.1175/2010WAF2222451.1, 2011.
Hargreaves, G. H. and Samani, Z. A.: Estimating potential evapotranspiration, J. Irr. Drain. Div.-ASCE, 108, 225–230, 1982.
Herrnegger, M.: Zeitlich hochaufgelöste inverse Modellierung von Gebietsniederschlägen aus Abflussmessungen, PhD thesis, Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, Austria, 2013.
Herrnegger, M., Nachtnebel, H. P., and Haiden, T.: Evapotranspiration in high alpine catchments – an important part of the water balance!, Hydrol. Res., 43, 460–475, 2012.
Hino, M. and Hasabe, M.: Analysis of hydrologic characteristics from runoff data – a hydrologic inverse problem, J. Hydrol., 49, 287–313, 1981.
Jacobs, A. F. G., Heusinkveld, B. G., and Wichink Kruit, R. J.: Contribution of dew to the water budget of a grassland area in the Netherlands, Water Resour. Res., 42, W03415, https://doi.org/10.1029/2005WR004055, 2006.
Jasper, K. and Kaufmann, P.: Coupled runoff simulations as validation tools for atmospheric models at the regional scale, Q. J. Roy. Meteorol. Soc., 129, 673–692, 2007.
Jasper, K., Gurtz, J., and Lang, H.: Advanced flood forecasting in Alpine watersheds by coupling meteorological observations and forecasts with a distributed hydrological model, J. Hydrol., 267, 40–52, 2002.
Kirchner, J. W.: Catchments as simple dynamical systems: catchment characterization, rainfall–runoff modeling, and doing hydrology backward, Water Resour. Res., 45, W02429, https://doi.org/10.1029/2008WR006912, 2009.
Klemm, O. and Wrzesinski, T.: Fog deposition fluxes of water and ions to a mountainous site in Central Europe, Tellus, 59, 705–714, 2007.
Kling, H.: Spatio-temporal modelling of the water balance of Austria, Dissertation, University of Natural Resources and Applied Life Sciences, 234 pp., available at: http://iwhw.boku.ac.at/dissertationen/kling.pdf (last access: 7 October 2014), 2006.
Kling, H. and Nachtnebel, H. P.: A method for the regional estimation of runoff separation parameters for hydrological modelling, J. Hydrol., 364, 163–174, 2009.
Kling, H., Stanzel, P., Fuchs, M., and Nachtnebel, H. P.: Performance of the COSERO precipitation-runoff model under non-stationary conditions in basins with different climates, Hydrolog. Sci. J., 60, 1374–1393, https://doi.org/10.1080/02626667.2014.959956, 2015.
Krajewski, W. F. and Smith, J. A.: Radar hydrology: rainfall estimation, Adv. Water Resour., 25, 1387–13, 2002.
Krajewski, W. F., Villarini, G., and Smith, J. A.: RADAR-rainfall uncertainties, B. Am. Meteorol. Soc., 91, 87–94, https://doi.org/10.1175/2009BAMS2747.1, 2010.
Krier, R., Matgen, P., Goergen, K., Pfister, L., Hoffmann, L., Kirchner, J. W., Uhlenbrook, S., and Savenije, H. H. G.: Inferring catchment precipitation by doing hydrology backward: a test in 24 small and mesoscale catchments in Luxembourg, Water Resour. Res., 48, W10525, https://doi.org/10.1029/2011WR010657, 2012.
Kuczera, G., Kavetski, D., Franks, S., and Thyer, M.: Towards a Bayesian total error analysis of conceptual rainfall–runoff models: characterising model error using storm-dependent parameters, J. Hydrol., 331, 161–177, 2006.
Kunstmann, H. and Stadler, C.: High resolution distributed atmospheric-hydrological modeling for Alpine catchments, J. Hydrol., 314, 105–124, 2005.
Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H.-J., Kumar, S., Moradkhani, H., Seo, D.-J., Schwanenberg, D., Smith, P., van Dijk, A. I. J. M., van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., and Restrepo, P.: Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, 2012.
McLaughlin, D.: An integrated approach to hydrologic data assimilation: interpolation, smoothing and filtering, Adv. Water Resour., 25, 1275–1286, 2002.
McMillan, H., Freer, J., Pappenberger, F., Krueger, T., and Clark, M.: Impacts of uncertain river flow data on rainfall–runoff model calibration and discharge predictions, Hydrol. Process., 24, 1270–1284, https://doi.org/10.1002/Hyp.7587, 2010.
Nachtnebel, H. P., Baumung, S., and Lettl, W.: Abflussprognosemodell für das Einzugsgebiet der Enns und Steyr, report, Institute of Water Management, Hydology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Vienna, Austria, 1993.
Nachtnebel, H. P., Haberl, U., Stanzel, Ph., Kahl, B., Holzmann, H., and Pfaffenwimmer, Th.: Hydrologische Abflussmodellierung – Teil 3, in: Amt der Salzburger Landesregierung: HydrisII Hydrologisches Informationssystem zur Hochwasservorhersage im Land Salzburg, Amt der Salzburger Landesregierung, Salzburg, Austria, 341 pp., 2009a.
Nachtnebel, H. P., Senoner, T., Stanzel, P., Kahl, B., Hernegger, M., Haberl, U. and Pfaffenwimmer, T.: Inflow prediction system for the Hydropower Plant Gabčíkovo, Part 3 – Hydrologic Modelling, Slovenské elektrárne, a.s. Bratislava, Slovakia, 139 pp., 2009b.
Nachtnebel, H. P., Herrnegger, M., Kahl, B., and Hepp, G.: Meteorologisch-hydrologisches Warnsystem Steyr: Endbericht und Technische Dokumentation – Teil 3: Hydrologische Abflussmodellierung, Amt der OÖ Landesregierung, Abteilung Wasserwirtschaft, Schutzwasserwirtschaft und Hydrographie, Innsbruck, Austria, 197 pp., 2010a.
Nachtnebel, H. P., Senoner, T., Kahl, B., Apperl, B., and Waldhör, B.: Hochwasserprognosesystem Ybbs – Hydrologische Abflussmodellierung, Amt der NÖ Landesregierung, St. Pölten, Austria, 176 pp., 2010b.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models, Part I: A discussion of principles, J. Hydrol., 10, 282–290, 1970.
Pappenberger, F., Matgen, P., Beven, K. J., Henry, J. B., Pfister, L., and de Fraipont, P.: Influence of uncertain boundary conditions and model structure on flood inundation predictions, Adv. Water Resour., 29, 1430–1449, 2006.
Pelletier, M. P.: Uncertainties in the determination of river discharge: a literature review, Can. J. Civil Eng., 15, 834–850, 1987.
Perrin, C., Michel, C., and Andréassian, V.: Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments, J. Hydrol., 242, 275–301, 2001.
Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.: Numerical Recipes in FORTRAN, The Art of Scientific Computing, Cambridge Univ. Press, New York, 965 pp., 1992.
Seibert, J.: Reliability of model predictions outside calibration conditions, Nord. Hydrol., 34, 477–492, 2003.
Seibert, J. and Morén, A.-S.: Reducing systematic errors in rainfall measurements using a new type of gauge, Agr. Forest Meteorol., 98–99, 341–348, 1999.
Sevruk, B.: Methodische Untersuchungen des systematischen Messfehlers der Hellmann-Regenmesser im Sommerhalbjahr in der Schweiz, dissertation, Eidgenöss. Techn. Hochsch. Zürich, Zürich, Switzerland, 1981.
Sevruk, B.: Correction of precipitation measurements. Proc. Workshop on the Correction of Precipitation Measurements, in: Zürcher Geographische Schriften, ETH Zurich, Zurich, Switzerland, p. 289, 1986.
Sevruk, B. and Nespor, V.: Empirical and theoretical assessment of the wind induced error of rain measurement, Water Sci. Technol., 37, 171–178, 1998.
Simoni, S., Padoan, S., Nadeau, D. F., Diebold, M., Porporato, A., Barrenetxea, G., Ingelrest, F., Vetterli, M., and Parlange, M. B.: Hydrologic response of an alpine watershed: application of a meteorological wireless sensor network to understand streamflow generation, Water Resour. Res., 47, W10524, https://doi.org/10.1029/2011WR010730, 2011.
Stanzel, P., Kahl, B., Haberl, U., Herrnegger, M., and Nachtnebel, H. P.: Continuous hydrological modeling in the context of real time flood forecasting in alpine Danube tributary catchments, IOP Conf. Ser., 4, 012005, https://doi.org/10.1088/1755-1307/4/1/012005, 2008.
Sugawara, M.: On the weights of precipitation stations, in: Advances in Theoretical Hydrology, edited by: O'Kane, J. P., Elsevier Science Publishers, Amsterdam, 59–74, 1992.
Tarantola, A.: Inverse Problem Theory and Methods for Model Parameter Estimation, Society for Industrial and Applied Mathematics, Philadelphia, 352 pp., 2005.
Valéry, A., Andréassian, V., and Perrin, C.: Inverting the hydrological cycle: when streamflow measurements help assess altitudinal precipitation gradients in mountain areas, in: New Approaches to Hydrological Prediction in Data-sparse Regions, IAHS Publ., 333, 281–286, 2009.
Valéry, A., Andréassian, V., and Perrin, C.: Regionalisation of rainfall and air temperature over high-altitude catchments – learning from outliers, Hydrolog. Sci. J., 55, 928–940, 2010.
van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Vrugt, J. A., ter Braak, C. J. F., Clark, M. P., Hyman, J. M., and Robinson, B. A.: Treatment of input uncertainty in hydrologic modeling: doing hydrology backward with Markov chain Monte Carlo simulation, Water Resour. Res., 44, W00B09, https://doi.org/10.1029/2007WR006720, 2008.
Wood, S. J., Jones, D. A., and Moore, R. J.: Accuracy of rainfall measurement for scales of hydrological interest, Hydrol. Earth Syst. Sci., 4, 531–543, https://doi.org/10.5194/hess-4-531-2000, 2000.
Short summary
Especially in alpine catchments, areal rainfall estimates often exhibit large errors. Runoff measurements are, on the other hand, one of the most robust observations within the hydrological cycle. We therefore calculate mean catchment rainfall by inverting an HBV-type rainfall-runoff model, using runoff observations as input. The inverse model may e.g. be used to analyse rainfall conditions of extreme flood events or estimation of snowmelt contribution.
Especially in alpine catchments, areal rainfall estimates often exhibit large errors. Runoff...
