Articles | Volume 22, issue 8
https://doi.org/10.5194/hess-22-4565-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-4565-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Aug 2018
Research article |
| 29 Aug 2018
| 29 Aug 2018
Incremental model breakdown to assess the multi-hypotheses problem
Florian U. Jehn
CORRESPONDING AUTHOR
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig
University Giessen, Heinrich-Buff-Ring 26, 35390 Giessen, Germany
Lutz Breuer
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig
University Giessen, Heinrich-Buff-Ring 26, 35390 Giessen, Germany
Centre for International Development and Environmental Research
(ZEU), Justus Liebig University Giessen, Senckenbergstraße 3, 35392
Giessen, Germany
Tobias Houska
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig
University Giessen, Heinrich-Buff-Ring 26, 35390 Giessen, Germany
Konrad Bestian
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig
University Giessen, Heinrich-Buff-Ring 26, 35390 Giessen, Germany
Philipp Kraft
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig
University Giessen, Heinrich-Buff-Ring 26, 35390 Giessen, Germany
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We grouped 643 rivers from the United States into 10 behavioral groups based on their hydrological behavior (e.g., how much water they transport overall). Those groups are aligned with the ecoregions in the United States. Depending on the groups’ location and other characteristics, either snow, aridity or seasonality is most important for the behavior of the rivers in a group. We also find that very similar river behavior can be found in rivers far apart and with different characteristics.
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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.
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
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Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-6, https://doi.org/10.5194/hess-2024-6, 2024
Revised manuscript accepted for HESS
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Climate and land-surface conditions influence the availability of fresh water resources. Their impact is quantified with data of 71 catchments in Saxony/Germany, for which distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease 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.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Huy Dang and Yadu Pokhrel
EGUsphere, https://doi.org/10.5194/egusphere-2023-3158, https://doi.org/10.5194/egusphere-2023-3158, 2024
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By examining basin-wide simulations of the 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 Mekong’s flow regime and annual flooding patterns at major downstream areas in recent years. These findings could help rethink the planning of future dams and water resource management in the MRB.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
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Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Alberto Montanari, Bruno Merz, and Günter Blöschl
EGUsphere, https://doi.org/10.5194/egusphere-2023-2420, https://doi.org/10.5194/egusphere-2023-2420, 2023
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Floods often take communities by surprise, as they are often considered virtually “impossible”, yet 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.
Pamela E. Tetford and Joseph R. Desloges
Hydrol. Earth Syst. Sci., 27, 3977–3998, https://doi.org/10.5194/hess-27-3977-2023, https://doi.org/10.5194/hess-27-3977-2023, 2023
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An efficient regional flood frequency model relates drainage area to discharge, with a major assumption of similar basin conditions. In a landscape with variable glacial deposits and land use, we characterize varying hydrological function using 28 explanatory variables. We demonstrate that (1) a heterogeneous landscape requires objective model selection criteria to optimize the fit of flow data, and (2) incorporating land use as a predictor variable improves the drainage area to discharge model.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn E. Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-258, https://doi.org/10.5194/hess-2023-258, 2023
Revised manuscript accepted for HESS
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Wouldn't it be nice to have both the accuracy of neural networks (NNs) and the interpretability of process-based models (PBMs)? Differentiable modeling gives you the best of both worlds by connecting NNs with PBMs. However, there was previously a major issue that iterative solution schemes would run into memory use trouble. This paper presents an operator called adjoint, which liberates all the iterative solvers. This is the first time adjoint is applied to large-scale hydrologic modeling.
Ana Ramos Oliveira, Tiago Brito Ramos, Lígia Pinto, and Ramiro Neves
Hydrol. Earth Syst. Sci., 27, 3875–3893, https://doi.org/10.5194/hess-27-3875-2023, https://doi.org/10.5194/hess-27-3875-2023, 2023
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This paper intends to demonstrate the adequacy of a hybrid solution to overcome the difficulties related to the incorporation of human behavior when modeling hydrological processes. Two models were implemented, one to estimate the outflow of a reservoir and the other to simulate the hydrological processes of the watershed. With both models feeding each other, results show that the proposed approach significantly improved the streamflow estimation downstream of the reservoir.
Nicolás Alamos, Camila Alvarez-Garreton, Ariel Muñoz, and Alvaro González-Reyes
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-246, https://doi.org/10.5194/hess-2023-246, 2023
Revised manuscript accepted for HESS
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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 three 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.
Zhihua He, Kevin Shook, Christopher Spence, John W. Pomeroy, and Colin Whitfield
Hydrol. Earth Syst. Sci., 27, 3525–3546, https://doi.org/10.5194/hess-27-3525-2023, https://doi.org/10.5194/hess-27-3525-2023, 2023
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This study evaluated the impacts of climate change on snowmelt, soil moisture, and streamflow over the Canadian Prairies. The entire prairie region was divided into seven basin types. We found strong variations of hydrological sensitivity to precipitation and temperature changes in different land covers and basins, which suggests that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the prairies.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
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This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Dung Trung Vu, Thanh Duc Dang, Francesca Pianosi, and Stefano Galelli
Hydrol. Earth Syst. Sci., 27, 3485–3504, https://doi.org/10.5194/hess-27-3485-2023, https://doi.org/10.5194/hess-27-3485-2023, 2023
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The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
Francesco Fatone, Bartosz Szeląg, Przemysław Kowal, Arthur McGarity, Adam Kiczko, Grzegorz Wałek, Ewa Wojciechowska, Michał Stachura, and Nicolas Caradot
Hydrol. Earth Syst. Sci., 27, 3329–3349, https://doi.org/10.5194/hess-27-3329-2023, https://doi.org/10.5194/hess-27-3329-2023, 2023
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A novel methodology for the development of a stormwater network performance simulator including advanced risk assessment was proposed. The applied tool enables the analysis of the influence of spatial variability in catchment and stormwater network characteristics on the relation between (SWMM) model parameters and specific flood volume, as an alternative approach to mechanistic models. The proposed method can be used at the stage of catchment model development and spatial planning management.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2023-1980, https://doi.org/10.5194/egusphere-2023-1980, 2023
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Hydrological hybrid models 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 LSTM networks. We explored this method to evaluate if the flexibility given by LSTM overwrites the interpretability of the process-based part. We showed that if a well-tested model architecture is combined with an LSTM, the latter can learn to operate the process-based model consistently.
Olivier Delaigue, Pierre Brigode, Guillaume Thirel, and Laurent Coron
Hydrol. Earth Syst. Sci., 27, 3293–3327, https://doi.org/10.5194/hess-27-3293-2023, https://doi.org/10.5194/hess-27-3293-2023, 2023
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Teaching hydrological modeling is an important, but difficult, matter. It requires appropriate tools and teaching material. In this article, we present the airGRteaching package, which is an open-source software tool relying on widely used hydrological models. This tool proposes an interface and numerous hydrological modeling exercises representing a wide range of hydrological applications. We show how this tool can be applied to simple but real-life cases.
Florian Willkofer, Raul Roger Wood, and Ralf Ludwig
EGUsphere, https://doi.org/10.5194/egusphere-2023-2019, https://doi.org/10.5194/egusphere-2023-2019, 2023
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Severe flood events pose threat to riverine areas, yet robust estimates about the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses and benefits from data from a RCM SMILE to drive a high-resolution hydrological model for 98 catchments of the Hydrological Bavaria to exploit 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.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
EGUsphere, https://doi.org/10.5194/egusphere-2023-1969, https://doi.org/10.5194/egusphere-2023-1969, 2023
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Due to climate change, flooding is expected to become more frequent globally in the coming decades. Locally, storm-induced channel geometry changes can drastically affect flood hazards, yet rivers are mostly treated as static elements in flood studies. This study tried to gain an understanding of the effects of major storm events on future flood hazards, promoting a framework for incorporating channel conveyance adjustments into flood hazard assessment.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
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This study shows that previously reported underestimations of water ages are most likely not due to 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 instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
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We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023, https://doi.org/10.5194/hess-27-2973-2023, 2023
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Mediterranean floods are causing major damage, and recent studies have shown that, despite the increase in intense rainfall, there has been no increase in river floods. This study reveals that the seasonality of floods changed in the Mediterranean Basin during 1959–2021. There was also an increased frequency of floods linked to short episodes of intense rain, associated with a decrease in soil moisture. These changes need to be taken into consideration to adapt flood warning systems.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-168, https://doi.org/10.5194/hess-2023-168, 2023
Revised manuscript accepted for HESS
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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.
Yanfeng Wu, Jingxuan Sun, Boting Hu, Y. Jun Xu, Alain N. Rousseau, and Guangxin Zhang
Hydrol. Earth Syst. Sci., 27, 2725–2745, https://doi.org/10.5194/hess-27-2725-2023, https://doi.org/10.5194/hess-27-2725-2023, 2023
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Reservoirs and wetlands are important regulators of watershed hydrology, which should be considered when projecting floods and droughts. We first coupled wetlands and reservoir operations into a semi-spatially-explicit hydrological model and then applied it in a case study involving a large river basin in northeast China. We found that, overall, the risk of future floods and droughts will increase further even under the combined influence of reservoirs and wetlands.
Peishi Jiang, Pin Shuai, Alexander Sun, Maruti K. Mudunuru, and Xingyuan Chen
Hydrol. Earth Syst. Sci., 27, 2621–2644, https://doi.org/10.5194/hess-27-2621-2023, https://doi.org/10.5194/hess-27-2621-2023, 2023
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We developed a novel deep learning approach to estimate the parameters of a computationally expensive hydrological model on only a few hundred realizations. Our approach leverages the knowledge obtained by data-driven analysis to guide the design of the deep learning model used for parameter estimation. We demonstrate this approach by calibrating a state-of-the-art hydrological model against streamflow and evapotranspiration observations at a snow-dominated watershed in Colorado.
Guillaume Cinkus, Naomi Mazzilli, Hervé Jourde, Andreas Wunsch, Tanja Liesch, Nataša Ravbar, Zhao Chen, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 27, 2397–2411, https://doi.org/10.5194/hess-27-2397-2023, https://doi.org/10.5194/hess-27-2397-2023, 2023
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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, when assessing a simulation, concurrent over- and underestimation of discharge can lead to an overall higher criterion score without an associated increase in model relevance. We suggest that one carefully choose performance criteria and use scaling factors.
Dapeng Feng, Hylke Beck, Kathryn Lawson, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 27, 2357–2373, https://doi.org/10.5194/hess-27-2357-2023, https://doi.org/10.5194/hess-27-2357-2023, 2023
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Powerful hybrid models (called δ or delta models) embrace the fundamental learning capability of AI and can also explain the physical processes. Here we test their performance when applied to 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 included. δ models could be ideal candidates for global hydrologic assessment.
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil
Hydrol. Earth Syst. Sci., 27, 2375–2395, https://doi.org/10.5194/hess-27-2375-2023, https://doi.org/10.5194/hess-27-2375-2023, 2023
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A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. Results confirm that 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.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-106, https://doi.org/10.5194/hess-2023-106, 2023
Revised manuscript accepted for HESS
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (HUP) with the Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method to reduce 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.
Cited articles
Ambroise, B.: Variable “active” versus “contributing” areas or periods: a
necessary distinction, Hydrol. Process., 18, 1149–1155,
https://doi.org/10.1002/hyp.5536, 2004.
Bai, Y., Wagener, T., and Reed, P.: A top-down framework for watershed model
evaluation and selection under uncertainty, Environ. Modell. Softw., 24,
901–916, https://doi.org/10.1016/j.envsoft.2008.12.012, 2009.
Bergström, S.: Principles and Confidence in Hydrological Modelling,
Hydrol. Res., 22, 123–136, https://doi.org/10.2166/nh.1991.0009, 1991.
Bergström, S. and Graham, L. P.: On the scale problem in hydrological
modelling, J. Hydrol., 211, 253–265,
https://doi.org/10.1016/S0022-1694(98)00248-0, 1998.
Beven, K.: Towards integrated environmental models of everywhere:
uncertainty, data and modelling as a learning process, Hydrol. Earth Syst.
Sci., 11, 460–467, https://doi.org/10.5194/hess-11-460-2007, 2007.
Beven, K. and Binley, A.: The future of distributed models: Model
calibration and uncertainty prediction, Hydrol. Process., 6, 279–298,
https://doi.org/10.1002/hyp.3360060305, 1992.
Beven, K. J.: Uniqueness of place and process representations in hydrological
modelling, Hydrol. Earth Syst. Sci., 4, 203–213,
https://doi.org/10.5194/hess-4-203-2000, 2000.
Beven, K. J.: On hypothesis testing in hydrology, Hydrol. Process., 15,
1655–1657, https://doi.org/10.1002/hyp.436, 2001.
Beven, K. J.: Towards an alternative blueprint for a physically based
digitally simulated hydrologic response modelling system, Hydrol. Process.,
16, 189–206, https://doi.org/10.1002/hyp.343, 2002.
Beven, K. J.: A manifesto for the equifinality thesis, J. Hydrol., 320,
18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Beven, K. J.: Facets of uncertainty: epistemic uncertainty, non-stationarity,
likelihood, hypothesis testing, and communication, Hydrolog. Sci. J., 61,
1652–1665, https://doi.org/10.1080/02626667.2015.1031761, 2016.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology/Un modèle à base physique de zone
d'appel variable de l'hydrologie du bassin versant, Hydrol. Sci. B., 24,
43–69, https://doi.org/10.1080/02626667909491834, 1979.
Blume, H.-P., Brümmer, G. W., Horn, R., Kandeler, E., Kögel-Knabner,
I., Kretzschmar, R., Stahr, K., Wilke, B.-M., Scheffer, F., and
Schachtschabel, P.: Scheffer/Schachtschabel Lehrbuch der Bodenkunde, 16.
Auflage, (Nachdruck), Springer Spektrum, Berlin, Heidelberg, 2016.
Bosch, D. D., Sheridan, J. M., Batten, H. L., and Arnold, J. G.: Evaluation
of the SWAT model on a coastal plain agricultural watershed, T. ASAE, 47,
1493–1506, https://doi.org/10.13031/2013.17629, 2004.
Breuer, L., Eckhardt, K., and Frede, H.-G.: Plant parameter values for models
in temperate climates, Ecol. Model., 169, 237–293,
https://doi.org/10.1016/S0304-3800(03)00274-6, 2003.
Breuer, L., Huisman, J. A., Willems, P., Bormann, H., Bronstert, A., Croke,
B. F. W., Frede, H.-G., Gräff, T., Hubrechts, L., Jakeman, A. J., Kite,
G., Lanini, J., Leavesley, G., Lettenmaier, D. P., Lindström, G.,
Seibert, J., Sivapalan, M., and Viney, N. R.: Assessing the impact of land
use change on hydrology by ensemble modeling (LUCHEM). I: Model
intercomparison with current land use, Adv. Water Resour., 32, 129–146,
https://doi.org/10.1016/j.advwatres.2008.10.003, 2009.
Buytaert, W., Reusser, D., Krause, S., and Renaud, J.-P.: Why can't we do
better than Topmodel?, Hydrol. Process., 22, 4175–4179,
https://doi.org/10.1002/hyp.7125, 2008.
Clark, M. P. and Kavetski, D.: Ancient numerical daemons of conceptual
hydrological modeling: 1. Fidelity and efficiency of time stepping schemes:
Numerical daemons of hydrological modeling, 1, Water Resour. Res., 46,
W10510, https://doi.org/10.1029/2009WR008894, 2010.
Clark, M. P., Kavetski, D., and Fenicia, F.: Pursuing the method of multiple
working hypotheses for hydrological modeling: Hypothesis testing in
hydrology, Water Resour. Res., 47, W09301, https://doi.org/10.1029/2010WR009827, 2011.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E.,
Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D.,
Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for
process-based hydrologic modeling: 1. Modeling concept: A unified approach
for process-based hydrologic modeling, Water Resour. Res., 51, 2498–2514,
https://doi.org/10.1002/2015WR017198, 2015a.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E.,
Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Gochis, D. J.,
Rasmussen, R. M., Tarboton, D. G., Mahat, V., Flerchinger, G. N., and Marks,
D. G.: A unified approach for process-based hydrologic modeling: 2. Model
implementation and case studies: A unified approach for process-based
hydrologic modeling, Water Resour. Res., 51, 2515–2542,
https://doi.org/10.1002/2015WR017200, 2015b.
Clark, M. P., Schaefli, B., Schymanski, S. J., Samaniego, L., Luce, C. H.,
Jackson, B. M., Freer, J. E., Arnold, J. R., Moore, R. D., Istanbulluoglu,
E., and Ceola, S.: Improving the theoretical underpinnings of process-based
hydrologic models: Narrowing the gap between hydrologic theory and models,
Water Resour. Res., 52, 2350–2365, https://doi.org/10.1002/2015WR017910, 2016.
CMF: Catchment Modelling Framework Website, available at:
http://fb09-pasig.umwelt.uni-giessen.de/cmf, last access:
12 February 2017.
Djabelkhir, K., Lauvernet, C., Kraft, P., and Carluer, N.: Development of a
dual permeability model within a hydrological catchment modeling framework:
1D application, Sci. Total Environ., 575, 1429–1437,
https://doi.org/10.1016/j.scitotenv.2016.10.012, 2017.
Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective
calibration approaches in hydrological modelling: a review, Hydrolog. Sci.
J., 55, 58–78, https://doi.org/10.1080/02626660903526292, 2010.
Elliott, K.: Error as Means to Discovery, Philos. Sci., 71, 174–197,
https://doi.org/10.1086/383010, 2004.
Fenicia, F., Savenije, H. H. G., Matgen, P., and Pfister, L.: Understanding
catchment behavior through stepwise model concept improvement, Water Resour.
Res., 44, W01402, https://doi.org/10.1029/2006WR005563, 2008.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible
approach for conceptual hydrological modeling: 1. Motivation and theoretical
development: Flexible framework for hydrological modeling, 1, 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.
Ficchì, A., Perrin, C., and Andréassian, V.: Impact of temporal
resolution of inputs on hydrological model performance: An analysis based on
2400 flood events, J. Hydrol., 538, 454–470,
https://doi.org/10.1016/j.jhydrol.2016.04.016, 2016.
Fink, G. S. M. and Koch, M.: Climate change effects on the water balance in
the Fulda catchment, Germany, during the 21st centruy, conference paper at
Symposium on sustainable water ressource management and climate change
adaption, Nakon Pathom., 2010.
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.
Gupta, H. V. and Nearing, G. S.: Debates-the future of hydrological sciences:
A (common) path forward? Using models and data to learn: A systems theoretic
perspective on the future of hydrological science, Water Resour. Res., 50,
5351–5359, https://doi.org/10.1002/2013WR015096, 2014.
Haas, E., Klatt, S., Fröhlich, A., Kraft, P., Werner, C., Kiese, R.,
Grote, R., Breuer, L., and Butterbach-Bahl, K.: LandscapeDNDC: a process
model for simulation of biosphere–atmosphere–hydrosphere exchange processes
at site and regional scale, Landscape Ecol., 28, 615–636,
https://doi.org/10.1007/s10980-012-9772-x, 2013.
Hindmarsh, A. C., Brown, P., Grant, K. E., Lee, S. L., Serban, R., Shumaker,
D. E., and Woodward, C. S.: SUNDIALS: Suite of nonlinear and
differential/algebraic equation solvers, ACM T. Math. Software, 31, 363–396,
2005.
Holländer, H. M., Blume, T., Bormann, H., Buytaert, W., Chirico, G. B.,
Exbrayat, J.-F., Gustafsson, D., Hölzel, H., Kraft, P., Stamm, C., Stoll,
S., Blöschl, G., and Flühler, H.: Comparative predictions of
discharge from an artificial catchment (Chicken Creek) using sparse data,
Hydrol. Earth Syst. Sci., 13, 2069–2094,
https://doi.org/10.5194/hess-13-2069-2009, 2009.
Houska, T., Multsch, S., Kraft, P., Frede, H.-G., and Breuer, L.: Monte
Carlo-based calibration and uncertainty analysis of a coupled plant growth
and hydrological model, Biogeosciences, 11, 2069–2082,
https://doi.org/10.5194/bg-11-2069-2014, 2014.
Houska, T., Kraft, P., Chamorro-Chavez, A., and Breuer, L.: SPOTting Model
Parameters Using a Ready-Made Python Package, PLOS ONE, 10, e0145180,
https://doi.org/10.1371/journal.pone.0145180, 2015.
Houska, T., Kraft, P., Liebermann, R., Klatt, S., Kraus, D., Haas, E.,
Santabarbara, I., Kiese, R., Butterbach-Bahl, K., Müller, C., and Breuer,
L.: Rejecting hydro-biogeochemical model structures by multi-criteria
evaluation, Environ. Modell. Softw., 93, 1–12,
https://doi.org/10.1016/j.envsoft.2017.03.005, 2017.
Hublart, P., Ruelland, D., Dezetter, A., and Jourde, H.: Reducing structural
uncertainty in conceptual hydrological modelling in the semi-arid Andes,
Hydrol. Earth Syst. Sci., 19, 2295–2314,
https://doi.org/10.5194/hess-19-2295-2015, 2015.
Hudson, G. and Wackernagel, H.: Mapping temperature using kriging with
external drift: Theory and an example from scotland, Int. J. Climatol., 14,
77–91, https://doi.org/10.1002/joc.3370140107, 1994.
Jehn, F.: Zutn/Incremental_Breakdown: Reupload,
https://doi.org/10.5281/zenodo.1067939, 2017.
Jehn, F.: Zutn/Fluxogram: First Public Version Of The Fluxogram,
https://doi.org/10.5281/zenodo.1137703, 2018.
Kavetski, D. and Clark, M. P.: Numerical troubles in conceptual hydrology:
Approximations, absurdities and impact on hypothesis testing, Hydrol.
Process., 25, 661–670, https://doi.org/10.1002/hyp.7899, 2011.
Kavetski, D. and Fenicia, F.: Elements of a flexible approach for conceptual
hydrological modeling: 2. Application and experimental insights: Flexible
framework for hydrological modeling, 2, Water Resour. Res., 47, W11511,
https://doi.org/10.1029/2011WR010748, 2011.
Kavetski, D., Fenicia, F., and Clark, M. P.: Impact of temporal data
resolution on parameter inference and model identification in conceptual
hydrological modeling: Insights from an experimental catchment, Water Resour.
Res., 47, W05501, https://doi.org/10.1029/2010WR009525, 2011.
Kellner, J., Multsch, S., Houska, T., Kraft, P., Müller, C., and Breuer,
L.: A coupled hydrological-plant growth model for simulating the effect of
elevated CO 2 on a temperate grassland, Agr. Forest Meteorol., 246, 42–50,
https://doi.org/10.1016/j.agrformet.2017.05.017, 2017.
Kraft, P., Multsch, S., Vaché, K. B., Frede, H.-G., and Breuer, L.: Using
Python as a coupling platform for integrated catchment models, Adv. Geosci.,
27, 51–56, https://doi.org/10.5194/adgeo-27-51-2010, 2010.
Kraft, P., Vaché, K. B., Frede, H.-G., and Breuer, L.: CMF: A
Hydrological Programming Language Extension For Integrated Catchment Models,
Environ. Modell. Softw., 26, 828–830, https://doi.org/10.1016/j.envsoft.2010.12.009,
2011.
Ley, R., Hellebrand, H., Casper, M., and Fenicia, F.: Is Catchment
Classification Possible by Means of Multiple Model Structures? A Case Study
Based on 99 Catchments in Germany, Hydrology, 3, 22,
https://doi.org/10.3390/hydrology3020022, 2016.
Link, T. E., Unsworth, M., and Marks, D.: The dynamics of rainfall
interception by a seasonal temperate rainforest, Agr. Forest Meteorol., 124,
171–191, https://doi.org/10.1016/j.agrformet.2004.01.010, 2004.
Maier, N., Breuer, L., and Kraft, P.: Prediction and uncertainty analysis of
a parsimonious floodplain surface water-groundwater interaction model, Water
Resour. Res., 53 , 7678–7695, https://doi.org/10.1002/2017WR020749, 2017.
McKay, M. D., Beckman, R. J., and Conover, W. J.: A Comparison of Three
Methods for Selecting Values of Input Variables in the Analysis of Output
from a Computer Code, Technometrics, 21, 239–245, https://doi.org/10.2307/1268522,
1979.
Moriasi, D. N., Arnold, J. G., Liew, M. W. V., Bingner, R. L., Harmel, R. D.,
and Veith, T. L.: Model Evaluation Guidelines for Systematic Quantification
of Accuracy in Watershed Simulations, T. ASABE, 50, 885–900,
https://doi.org/10.13031/2013.23153, 2007.
Orlowski, N., Kraft, P., Pferdmenges, J., and Breuer, L.: Exploring water
cycle dynamics by sampling multiple stable water isotope pools in a developed
landscape in Germany, Hydrol. Earth Syst. Sci., 20, 3873–3894,
https://doi.org/10.5194/hess-20-3873-2016, 2016.
Plesca, I., Timbe, E., Exbrayat, J.-F., Windhorst, D., Kraft, P., Crespo, P.,
Vaché, K. B., Frede, H.-G., and Breuer, L.: Model intercomparison to
explore catchment functioning: Results from a remote montane tropical
rainforest, Ecol. Model., 239, 3–13, https://doi.org/10.1016/j.ecolmodel.2011.05.005,
2012.
Rawlins, M. A., Willmott, C. J., Shiklomanov, A., Linder, E., Frolking, S.,
Lammers, R. B., and Vörösmarty, C. J.: Evaluation of trends in
derived snowfall and rainfall across Eurasia and linkages with discharge to
the Arctic Ocean, Geophys. Res. Lett., 33, L07403,
https://doi.org/10.1029/2005GL025231, 2006.
Rhönenergie Fulda GmbH: Trinkwassergewinnung im Fulda Einzugsgebiet,
available at: https://re-fd.de/trinkwasser/der-weg-des-trinkwassers,
last access: 12 January 2017.
Ritter, A. and Muñoz-Carpena, R.: Performance evaluation of hydrological
models: Statistical significance for reducing subjectivity in
goodness-of-fit assessments, J. Hydrol., 480, 33–45,
https://doi.org/10.1016/j.jhydrol.2012.12.004, 2013.
Rutter, A. J. and Morton, A. J.: A Predictive Model of Rainfall Interception
in Forests. III. Sensitivity of The Model to Stand Parameters and
Meteorological Variables, J. Appl. Ecol., 14, 567–588,
https://doi.org/10.2307/2402568, 1977.
Samani, Z.: Estimating solar radiation and evapotranspiration using minimum
climatological data, J. Irrig. Drain. Eng., 126, 265–267, 2000.
Seibert, J. and Vis, M. J. P.: Teaching hydrological modeling with a
user-friendly catchment-runoff-model software package, Hydrol. Earth Syst.
Sci., 16, 3315–3325, https://doi.org/10.5194/hess-16-3315-2012, 2012.
Sikorska, A. E. and Seibert, J.: Appropriate temporal resolution of
precipitation data for discharge modelling in pre-alpine catchments,
Hydrolog. Sci. J., 63, 1–16, https://doi.org/10.1080/02626667.2017.1410279, 2018.
Singh, V. P.: Is hydrology kinematic?, Hydrol. Process., 16, 667–716,
https://doi.org/10.1002/hyp.306, 2002.
Son, K. and Sivapalan, M.: Improving model structure and reducing parameter
uncertainty in conceptual water balance models through the use of auxiliary
data: Improving model structure through auxiliary data, Water Resour. Res.,
43, W01415, https://doi.org/10.1029/2006WR005032, 2007.
Todini, E.: Hydrological catchment modelling: past, present and future,
Hydrol. Earth Syst. Sci., 11, 468–482,
https://doi.org/10.5194/hess-11-468-2007, 2007.
van Esse, W. R., Perrin, C., Booij, M. J., Augustijn, D. C. M., Fenicia, F.,
Kavetski, D., and Lobligeois, F.: The influence of conceptual model structure
on model performance: a comparative study for 237 French catchments, Hydrol.
Earth Syst. Sci., 17, 4227–4239, https://doi.org/10.5194/hess-17-4227-2013,
2013.
Wendland, F., Berthold, G., Fritsche, J.-G., Herrmann, F., Kunkel, R., Voigt,
H.-J., and Vereecken, H.: Konzeptionelles hydrogeologisches Modell zur
Analyse und Bewertung von Verweilzeiten in Hessen, Grundwasser, 16, 163–176,
https://doi.org/10.1007/s00767-011-0169-6, 2011.
Westerberg, I. K. and Birkel, C.: Observational uncertainties in hypothesis
testing: investigating the hydrological functioning of a tropical catchment:
Observational Uncertainties in Hypothesis Testing, Hydrol. Process., 29,
4863–4879, https://doi.org/10.1002/hyp.10533, 2015.
Windhorst, D., Kraft, P., Timbe, E., Frede, H.-G., and Breuer, L.: Stable
water isotope tracing through hydrological models for disentangling runoff
generation processes at the hillslope scale, Hydrol. Earth Syst. Sci., 18,
4113–4127, https://doi.org/10.5194/hess-18-4113-2014, 2014.
Wittmann, S.: Tritiumgestützte Wasserbilanzierung im Einzugsgebiet von
Fulda und Werra, available at:
http://www.hydrology.uni-freiburg.de/abschluss/Wittmann_S_2002_DA.pdf
(last access: 4 January 2017), Diploma-Thesis at the Institut for Hydrology,
Albert-Ludwigs-University Freiburg, 2002.
Short summary
By realizing that hydrological models are not one single hypothesis, but an assemblage of many hypotheses, new ways to scrutinize hydrological models are needed. Up until now, studies concentrate on comparing existing models or built models incrementally. This approach here tries to tackle the problem the other way around. We construct a complex model, containing all processes important for the catchment, and deconstruct it step by step to understand the influence of single processes.
By realizing that hydrological models are not one single hypothesis, but an assemblage of many...
