Articles | Volume 17, issue 10
https://doi.org/10.5194/hess-17-4143-2013
© Author(s) 2013. 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-17-4143-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Oct 2013
Research article |
| 24 Oct 2013
Distributed hydrologic modeling of a sparsely monitored basin in Sardinia, Italy, through hydrometeorological downscaling
G. Mascaro
Consorzio Interuniversitario Nazionale per la Fisica delle Atmosfere e delle Idrosfere, Tolentino, Italy
Dipartimento di Ingegneria Civile, Ambientale ed Architettura, Università degli Studi di Cagliari, Cagliari, Italy
School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA
M. Piras
Consorzio Interuniversitario Nazionale per la Fisica delle Atmosfere e delle Idrosfere, Tolentino, Italy
Dipartimento di Ingegneria Civile, Ambientale ed Architettura, Università degli Studi di Cagliari, Cagliari, Italy
R. Deidda
Consorzio Interuniversitario Nazionale per la Fisica delle Atmosfere e delle Idrosfere, Tolentino, Italy
Dipartimento di Ingegneria Civile, Ambientale ed Architettura, Università degli Studi di Cagliari, Cagliari, Italy
E. R. Vivoni
School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, USA
School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA
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Naika Meili, Gabriele Manoli, Paolo Burlando, Elie Bou-Zeid, Winston T. L. Chow, Andrew M. Coutts, Edoardo Daly, Kerry A. Nice, Matthias Roth, Nigel J. Tapper, Erik Velasco, Enrique R. Vivoni, and Simone Fatichi
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A. P. Schreiner-McGraw, E. R. Vivoni, G. Mascaro, and T. E. Franz
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Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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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
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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
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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
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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.
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.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emilio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
EGUsphere, https://doi.org/10.5194/egusphere-2023-1755, https://doi.org/10.5194/egusphere-2023-1755, 2023
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The authors compared different regionalization methods for river flow prediction in watersheds with few data. We collected data on precipitation, evapotranspiration, river flow, and geographical and climatic factors for 126 catchments in the Paraná state, Brazil. The regionalization method based on physiographic-climatic similarity showed to be the most robust for predicting daily and Q95 reference flow. We also found patterns in data, grouping locations based on similarities.
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.
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.
Cited articles
Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S., and Yang, H.: Assessing the impact of climate change on water resources in Iran, Water Resour. Res., 45, W10434, https://doi.org/10.1029/2008WR007615, 2009.
Allen, R. G., Jensen, M. E., Wright, J. L., and Burman, R.D.: Operational estimates of reference evapotranspiration, Agron. J., 81, 650–662, 1989.
Allen, R. G., Pruitt, W. O., Wright, J. L., Howell, T. A., Ventura, F., Snyder, R., Itenfisu, D., Steduto, P., Berengena, J., Yrisarry, J. B., Smith, M., Pereira, L. S., Raes, D., Perrier, A., Alves I., Walter, I., and Elliott, R.: A recommendation on standardized surface resistance for hourly calculation of reference ET0 by the FAO56 Penman-Monteith method, Agr. Water Manage., 81, 1–22, https://doi.org/10.1016/j.agwat.2005.03.007, 2006.
Aru, A., Baldaccini, P., and Vacca, A.: Carta dei suoli della Sardegna 1:250,000. Regione Autonoma della Sardegna, Assessorato Programmazione, Bilancio ed Assetto del Territorio, 1992.
Badas, M. G., Deidda, R., and Piga, E.: Modulation of homogeneous space-time rainfall cascades to account for orographic influences, Nat. Hazards Earth Syst. Sci., 6, 427–437, https://doi.org/10.5194/nhess-6-427-2006, 2006.
Beven, K.: Runoff generation in semi-arid areas, in: Dryland Rivers, edited by: Bull, L. J. and Kirkby, M. J., J. Wiley & Sons, 57–105, 2002.
Cabral, M. C., Garrote, L., Bras, R. L., and Entekhabi, D.: A kinematic model of infiltration and runoff generation in layered and sloped soils, Adv. Water Resour., 15, 311–324, 1992.
Camporese, M., Paniconi, C., Putti, M., and Orlandini, S.: Surface-subsurface flow modeling with path-based runoff routing, boundary condition-based coupling, and assimilation of multisource observation data, Water Resour. Res., 46, W02512, https://doi.org/10.1029/2008WR007536, 2010.
Cayan, D. R., Dasa, T., Piercea, D. W., Barnetta, T. P., Tyreea, M., and Gershunova, A.: Future dryness in the southwest US and the hydrology of the early 21st century drought, P. Natl. Acad. Sci. USA, 107, 21271–21276. https://doi.org/10.1073/pnas.0912391107, 2010.
Chessa, P. A., Cesari, D., and Delitala, A. M. S.: Mesoscale precipitation and temperature regimes in Sardinia (Italy) and their related synoptic circulation, Theor. Appl. Climatol., 63, 195–221, 1999.
Chessa, P. A., Ficca, G., Marrocu, M., and Buizza, R.: Application of a limited-area short-range ensemble forecast system to a case of heavy rainfall in the Mediterranean region, Weather Forecast., 19, 566–581, 2004.
Deidda, R.: Rainfall downscaling in a space-time multifractal framework, Water Resour. Res., 36, 1779–1784, 2000.
Deidda, R., Benzi, R., and Siccardi, F.: Multifractal modeling of anomalous scaling laws in rainfall, Water Resour. Res., 35, 1853–1867, 1999.
Deidda, R., Badas, M. G., and Piga, E.: Space-time scaling in high-intensity Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment TOGA-COARE storms, Water Resour. Res., 40, W02506, https://doi.org/10.1029/2003WR002574, 2004.
Deidda, R., Badas, M. G., and Piga, E.: Space-time Multifractality of Remotely Sensed Rainfall Fields, J. Hydrol., 322, 2–13, 2006.
Delrieu, G., Nicol, J., Yates, E., Kirstetter, P.-E., Creutin, J.-D., Anquetin, S., Obled, C., and Saulnier, G.-M.: The catastrophic flash-flood event of 8–9 September 2002 in the Gard region, France: a first case study for the Cévennes–Vivarais Mediterranean hydrometeorological observatory, J. Hydrometeorol., 6, 34–52, 2005.
Forman, B. A., Vivoni, E. R., and Margulis, S. A.: Evaluation of ensemble-based distributed hydrologic model response with disaggregated precipitation products, Water Resour. Res., 44, 1–18, https://doi.org/10.1029/2008WR006827, 2008.
Frei, C., Schöll, R., Fukutome, S., Schmidli, J., and Vidale, P. L.: Future change of precipitation extremes in Europe: intercomparison of scenarios from regional climate models, J. Geophys. Res., 111, D06105, https://doi.org/10.1029/2005JD005965, 2006.
Gallart, F., Llorens, P., Latron, J., and Regüés, D.: Hydrological processes and their seasonal controls in a small Mediterranean mountain catchment in the Pyrenees, Hydrol. Earth Syst. Sci., 6, 527–537, https://doi.org/10.5194/hess-6-527-2002, 2002.
Gebremichael, M., Over, T. M., and Krajewski, W. F.: Comparison of the scaling properties of rainfall derived from space- and surface-based radars, J. Hydrometeor., 7, 1277–1294, 2006.
Giorgi, F.: Climate change hot-spots, Geophys. Res. Lett., 33, L08707, https://doi.org/10.1029/2006GL025734, 2006.
Hargreaves, G. H.: Defining and using reference evapotranspiration, J. Irrig. Drain. E.-ASCE, 120, 1132–1139, 1994.
Hargreaves, G. H. and Allen, R. G.: History and evaluation of Hargreaves Evapotraspiration equation, J. Irrig. Drain. E.-ASCE, 129, 53–63, 2003.
IPCC (Intergovernmental Panel on Climate Change): Climate Change 2007: impacts, adaptation and vulnerability, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, 976, 2007.
IPCC (Intergovernmental Panel on Climate Change): Climate Change and Water, Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat, Geneva, 210, 2008.
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Catchment hydrologic response with a fully-distributed triangulated irregular network model, Water Resour. Res., 40, 1–23, https://doi.org/10.1029/2004WR003218, 2004a.
Ivanov, V. Y., Vivoni, E. R., Bras, R. L., and Entekhabi, D.: Preserving high-resolution surface and rainfall data in operational-scale basin hydrology: A fully-distributed physically-based approach, J. Hydrol., 298, 80–111, https://doi.org/10.1016/j.jhydrol.2004.03.041, 2004b.
Langousis, A., Veneziano, D., Furcolo, P., and Lepore, C.: Multifractal rainfall extremes: Theoretical analysis and practical estimation, Chaos Soliton. Fract., 39, 1182–1194, https://doi.org/10.1016/j.chaos.2007.06.004, 2009.
Langousis, A., Carsteanu, A. A., and Deidda, R.: A simple approximation to multifractal rainfall maxima using a generalized extreme value distribution model, Stoch. Environ. Res. Risk Assess., 27, 1525–1531, https://doi.org/10.1007/s00477-013-0687-0, 2013.
Liuzzo, L., Noto, L. V., Vivoni, E. R., and La Loggia, G.: Basin-scale water resources assessment in Oklahoma under synthetic climate change scenarios using a fully distributed hydrological model, J. Hydrol. Eng., 15, 107–122, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000166, 2010.
Ludwig, R., Soddu, A., Duttmann, R., Baghdadi, N., Benabdallah, S., Deidda, R., Marrocu, M., Strunz, G., Wendland, F., Engin, G., Paniconi, C., Prettenthaler, F., Lajeunesse, I., Afifi, S., Cassiani, G., Bellin, A., Mabrouk, B., Bach, H., and Ammerl, T.: Climate-induced changes on the hydrology of Mediterranean basins – A research concept to reduce uncertainty and quantify risk, Fresen. Environ. Bull., 19, 2379–2384, 2010.
Mahfouf, J. F. and Noilhan, J.: Comparative study of various formulations from bare soil using in situ data, J. Appl. Meteorol., 30, 1354–1365, 1991.
Mascaro, G., Vivoni, E. R., and Deidda, R.: Implications of ensemble quantitative precipitation forecast errors on distributed streamflow forecasting, J. Hydrometeorol., 11, 69–86, https://doi.org/10.1175/2009JHM1144.1, 2010.
Mascaro, G., Deidda, R., and Hellies, M.: On the nature of rainfall intermittency as revealed by different metrics and sampling approaches, Hydrol, Earth Syst. Sci., 17, 355–369, https://doi.org/10.5194/hess-17-355-2013, 2013.
Menabde, M., Harris, D., Seed, A,. Austin, G., and Stow, D.: Multiscaling properties of rainfall and bounded random cascades, Wat. Resour. Res., 33, 2823–2830, 1997.
Montaldo, N., Albertson, J. D., and Mancini, M.: Vegetation dynamics and soil water balance in a water-limited Mediterranean ecosystem on Sardinia, Italy, Hydrol. Earth Syst. Sci., 12, 1257–1271, https://doi.org/10.5194/hess-12-1257-2008, 2008.
Monteith, J. L.: Evaporation and environment, Sym. Soc. Exp. Biol., 19, 205–234, 1965.
Montenegro, S. and Ragab, R.,: Impact of possible climate and land use changes in the semi arid regions: a case study from North Eastern Brazil, J. Hydrol., 434-435, 55–68, https://doi.org/10.1016/j.jhydrol.2012.02.036, 2012.
Moussa, R., Chahinian, N., and Bocquillon, C.: Distributed hydrological modeling of a Mediterranean mountainous catchment – model construction and multi-site validation. J. Hydrol., 337, 35–51, https://doi.org/10.1016/j.jhydrol.2007.01.028, 2007.
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.
Nikolopoulus, E. I., Anagnostou, E. N., Borga, M., Vivoni, E. R., and Papadopoulus, A.: Sensitivity of a mountain basin flash flood to initial wetness condition and rainfall variability, J. Hydrol., 402, 165–178, https://doi.org/10.1016/j.jhydrol.2010.12.020, 2011.
Noto, L. V., Ivanov, V. Y., Bras, R. L., and Vivoni, E. R.: Effects of initialization on response of a fully-distributed hydrologic model, J. Hydrol., 352, 107–125, https://doi.org/10.1016/j.jhydrol.2007.12.031, 2008.
Olesen, J. E. and Bindi, M.: Consequences of climate change for European agricultural productivity, land use and policy, Eur. J. Agron., 16, 239–262, 2002.
Over, T. M. and Gupta, V. K.: A space-time theory of mesoscale rainfall using random cascades, J. Geophys. Res., 101, 26319–26331, 1996.
Penman, H. L.: Natural evaporation from open water, bare soil and grass, P. R. Soc. London, Ser.-A, 193, 120–145, 1948.
Perica, S. and Foufoula-Georgiou, E.: Model for multiscale disaggregation of spatial rainfall based on coupling meteorological and scaling descriptions, J. Geophys. Res., 101, 26347–26361, 1996.
Piñol, J., Beven, K., and Freer, J.: Modelling the hydrological response of Mediterranean catchments, Prades, Catalonia. The use of distributed models as aids to hypothesis formulation, Hydrol. Process., 11, 1287–1306, 1997.
Pulina, M. A.: L'Evapotraspirazione potenziale in Sardegna in funzione dello studio del regime idrico dei suoli. Studi sassaresi: organo ufficiale della Società sassarese di Scienze mediche e naturali. Sez. 3: Annali della Facoltà di Agraria dell'Università di Sassari, Vol. 32, 96–109, ISSN 0562-2662, 1986.
Rawls, W. J., Brakensiek, D. L., and Saxton, K. E.: Estimation of soil properties, T. ASAE, 1316–1328, 1982.
Robles-Morua, A., Vivoni, E. R., and Mayer, A. S.: Distributed hydrologic modeling in Northwest Mexico reveals the links between runoff mechanisms and evapotranspiration, J. Hydrometeor., 13, 785–807, https://doi.org/10.1175/JHM-D-11-0112.1, 2012.
Schertzer, D. and Lovejoy, S.: Physical modeling and analysis of rain and clouds by anisotropic scaling of multiplicative processes, J. Geophys. Res., 92, 9693–9714, 1987.
Schröter, D., Cramer, W., Leemans, R., Prentice, I. C., Araújo, M. B., Arnell, N. W., Bondeau, A., Bugmann, H., Carter, T. R., Gracia, C. A., de la Vega-Leinert, A. C., Erhard, M., Ewert, F., Glendining, M., House, J. I., Kankaanpää, S., Klein, R. J. T., Lavorel, S., Lindner, M., Metzger, M. J., Meyer, J., Mitchell, T. D., Reginster, I., Rounsevell, M., Sabaté, S., Sitch, S., Smith, B., Smith, J., Smith, P., Sykes, M. T., Thonicke, K., Thuiller, W., Tuck, G., Zaehle, S., and Zierl, B.: Ecosystem service supply and vulnerability to global change in Europe, Science, 310, 1333–1337, 2005.
Silvestro, F., Gabellani, S., Giannoni, F., Parodi, A., Rebora, N., Rudari, R., and Siccardi, F.: A hydrological analysis of the 4 November 2011 event in Genoa, Nat. Hazards Earth Syst. Sci., 12, 2743–2752, https://doi.org/10.5194/nhess-12-2743-2012, 2012.
Sulis, M., Paniconi, C., Rivard, C., Harvey, R., and Chaumont, D.: Assessment of climate change impacts at the catchment scale with a detailed hydrological model of surface-subsurface interactions and comparison with a land surface model, Water Resour. Res., 47, W01513, https://doi.org/10.1029/2010WR009167, 2011.
VanderKwaak, J. E. and Loague, K.: Hydrologic-response simulations for the R-5 catchment with a comprehensive physics-based model, Water Resour. Res., 37, 999–1013, 2001.
Veneziano, D. and and Langousis, A.: The areal reduction factor a multifractal analysis, Wat. Resour. Res., 41, W07008, https://doi.org/10.1029/2004WR003765, 2005.
Veneziano, D. and Langousis, A.: Scaling and fractals in hydrology, in: Advances in Data-based Approaches for Hydrologic Modeling and Forecasting, edited by: B. Sivakumar and R. Berndtsson, World Scientific, 145 pp., 2010.
Veneziano, D., Furcolo, P., and Iacobellis, V.: Imperfect scaling of time and space-time rainfall, J. Hydrol., 322, 105–119, 2006.
Vivoni, E. R., Ivanov, V. Y., Bras, R. L., and Entekhabi, D.: Generation of triangulated irregular networks based on hydrological similarity, J. Hydrol. Eng., 9, 288–302, https://doi.org/10.1061/(ASCE)1084-0699(2004)9:4(288), 2004.
Vivoni, E. R., Ivanov, V. Y., Bras, R. L., and Entekhabi, D.: On the effects of triangulated terrain resolution on distributed hydrologic model response, Hydrol. Process., 19, 2101–2122, https://doi.org/10.1002/hyp.5671, 2005.
Vivoni, E. R., Entekhabi, D., Bras, R. L., Ivanov, V. Y., Van Horne, M. P., Grassotti, C., and Hoffman, R. N.: Extending the predictability of hydrometeorological flood events using radar rainfall nowcasting, J. Hydrometeorol., 7, 660–677, 2006.
Vivoni, E. R., Entekhabi, D., Bras, R. L., and Ivanov, V. Y.: Controls on runoff generation and scale-dependence in a distributed hydrologic model, Hydrol. Earth Syst. Sci., 11, 1683–1701, https://doi.org/10.5194/hess-11-1683-2007, 2007.
Vivoni, E. R., Tai, K., and Gochis, D. J.: Effects of initial soil moisture on rainfall generation and subsequent hydrologic response during the North American monsoon, J. Hydrometeorol., 10, 644–664, https://doi.org/10.1175/2008JHM1069.1, 2009.
Vivoni, E. R., Rodriguez, J. C., and Watts, C. J.: On the spatiotemporal variability of soil moisture and evapotranspiration in a mountainous basin within the North American monsoon region, Water Resour. Res., 46, W02509, https://doi.org/10.1029/2009WR008240, 2010.
Vivoni, E. R., Mascaro, G., Mniszewski, S., Fasel, P., Springer, E. P., Ivanov, V. Y., and Bras, R. L.: Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment, J. Hydrol., 409, 483–496, https://doi.org/10.1016/j.jhydrol.2011.08.053, 2011.
Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs, Clim. Change, 62, 189–216, 2004.
