Articles | Volume 26, issue 10
https://doi.org/10.5194/hess-26-2779-2022
© Author(s) 2022. 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-26-2779-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jun 2022
Research article |
| 01 Jun 2022
| 01 Jun 2022
Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
Department of Ecosystem Science and Sustainability, Colorado State
University, Fort Collins, CO, USA
Department of Geosciences, Idaho State University, Pocatello, ID, USA
Ernesto Trujillo
Department of Geosciences, Boise State University, Boise, ID,
USA
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Andrew Hedrick
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Scott Havens
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Katherine Hale
Department of Geography, University of Colorado, Boulder, CO, USA
Institute of Arctic and Alpine Research, University of Colorado,
Boulder, CO, USA
Mark Seyfried
Northwest Watershed Research Center, USDA Agricultural Research Service, Boise, ID, USA
Stephanie Kampf
Department of Ecosystem Science and Sustainability, Colorado State
University, Fort Collins, CO, USA
Sarah E. Godsey
Department of Geosciences, Idaho State University, Pocatello, ID, USA
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The sources of stream water are important, for instance, for predicting floods. The connectivity between streams and different (ground-)water sources can change during rain events, which affects the stream water composition. We investigated this for stream water sampled during four events and found that stream water came from different sources. The stream water composition changed gradually, and we showed that changes in solute concentrations could be partly linked to changes in connectivity.
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Related subject area
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Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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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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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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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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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.
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.
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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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.
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.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-237, https://doi.org/10.5194/hess-2023-237, 2023
Revised manuscript accepted for HESS
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It is challenging to incorporate the spatial distribution information of input variables when implementing LSTM models for streamflow prediction. This paper presents a novel hybrid modeling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise in predicting streamflow at large ungauged basin.
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.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-230, https://doi.org/10.5194/hess-2023-230, 2023
Revised manuscript accepted for HESS
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of water falls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow-rain transition (2,000–2,500m) and very vulnerable to shift in the snow-rain ratio.
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.
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.
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.
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.
Marcus Edmund Henry Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-138, https://doi.org/10.5194/hess-2023-138, 2023
Revised manuscript accepted for HESS
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in 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.
Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, https://doi.org/10.5194/hess-27-2149-2023, 2023
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We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943, https://doi.org/10.5194/hess-27-1929-2023, https://doi.org/10.5194/hess-27-1929-2023, 2023
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This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, Christoph Mayer, and Axel Bronstert
Hydrol. Earth Syst. Sci., 27, 1841–1863, https://doi.org/10.5194/hess-27-1841-2023, https://doi.org/10.5194/hess-27-1841-2023, 2023
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We present a suitable method to reconstruct sediment export from decadal records of hydroclimatic predictors (discharge, precipitation, temperature) and shorter suspended sediment measurements. This lets us fill the knowledge gap on how sediment export from glacierized high-alpine areas has responded to climate change. We find positive trends in sediment export from the two investigated nested catchments with step-like increases around 1981 which are linked to crucial changes in glacier melt.
Samantha Petch, Bo Dong, Tristan Quaife, Robert P. King, and Keith Haines
Hydrol. Earth Syst. Sci., 27, 1723–1744, https://doi.org/10.5194/hess-27-1723-2023, https://doi.org/10.5194/hess-27-1723-2023, 2023
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Gravitational measurements of water storage from GRACE (Gravity Recovery and Climate Experiment) can improve understanding of the water budget. We produce flux estimates over large river catchments based on observations that close the monthly water budget and ensure consistency with GRACE on short and long timescales. We use energy data to provide additional constraints and balance the long-term energy budget. These flux estimates are important for evaluating climate models.
Ting Su, Chiyuan Miao, Qingyun Duan, Jiaojiao Gou, Xiaoying Guo, and Xi Zhao
Hydrol. Earth Syst. Sci., 27, 1477–1492, https://doi.org/10.5194/hess-27-1477-2023, https://doi.org/10.5194/hess-27-1477-2023, 2023
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The Three-River Source Region (TRSR) plays an extremely important role in water resources security and ecological and environmental protection in China and even all of Southeast Asia. This study used the variable infiltration capacity (VIC) land surface hydrologic model linked with the degree-day factor algorithm to simulate the runoff change in the TRSR. These results will help to guide current and future regulation and management of water resources in the TRSR.
Andreas Hartmann, Jean-Lionel Payeur-Poirier, and Luisa Hopp
Hydrol. Earth Syst. Sci., 27, 1325–1341, https://doi.org/10.5194/hess-27-1325-2023, https://doi.org/10.5194/hess-27-1325-2023, 2023
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We advance our understanding of including information derived from environmental tracers into hydrological modeling. We present a simple approach that integrates streamflow observations and tracer-derived streamflow contributions for model parameter estimation. We consider multiple observed streamflow components and their variation over time to quantify the impact of their inclusion for streamflow prediction at the catchment scale.
Dharmaveer Singh, Manu Vardhan, Rakesh Sahu, Debrupa Chatterjee, Pankaj Chauhan, and Shiyin Liu
Hydrol. Earth Syst. Sci., 27, 1047–1075, https://doi.org/10.5194/hess-27-1047-2023, https://doi.org/10.5194/hess-27-1047-2023, 2023
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This study examines, for the first time, the potential of various machine learning models in streamflow prediction over the Sutlej River basin (rainfall-dominated zone) in western Himalaya during the period 2041–2070 (2050s) and 2071–2100 (2080s) and its relationship to climate variability. The mean ensemble of the model results shows that the mean annual streamflow of the Sutlej River is expected to rise between the 2050s and 2080s by 0.79 to 1.43 % for SSP585 and by 0.87 to 1.10 % for SSP245.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023, https://doi.org/10.5194/hess-27-1011-2023, 2023
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This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
Evgenia Koltsida, Nikos Mamassis, and Andreas Kallioras
Hydrol. Earth Syst. Sci., 27, 917–931, https://doi.org/10.5194/hess-27-917-2023, https://doi.org/10.5194/hess-27-917-2023, 2023
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Daily and hourly rainfall observations were inputted to a Soil and Water Assessment Tool (SWAT) hydrological model to investigate the impacts of rainfall temporal resolution on a discharge simulation. Results indicated that groundwater flow parameters were more sensitive to daily time intervals, and channel routing parameters were more influential for hourly time intervals. This study suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin.
Cited articles
Baker, D. B., Richards, R. P., Loftus, T. T., and Kramer, J. W.: A New
Flashiness Index: Characteristics and Applications to Midwestern Rivers and
Streams, J. Am. Water Resources Assoc., 40, 503–522,
https://doi.org/10.1111/j.1752-1688.2004.tb01046.x, 2004.
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a
warming climate on water availability in snow-dominated regions, Nature,
438, 303–309, https://doi.org/10.1038/nature04141, 2005.
Bavay, M., Grünewald, T., and Lehning, M.: Response of snow cover and
runoff to climate change in high Alpine catchments of Eastern Switzerland,
Adv. Water Resour., 55, 4–16,
https://doi.org/10.1016/j.advwatres.2012.12.009, 2013.
Beniston, M., Keller, F., Koffi, B., and Goyette, S.: Estimates of snow
accumulation and volume in the Swiss Alps under changing climatic
conditions, Theor. Appl. Climatol., 76, 125–140,
https://doi.org/10.1007/s00704-003-0016-5, 2003.
Berghuijs, W. R., Woods, R. A., and Hrachowitz, M.: A precipitation shift
from snow towards rain leads to a decrease in streamflow, Nat. Clim.
Change, 4, 583–586, https://doi.org/10.1038/nclimate2246, 2014.
Bilish, S. P., Callow, J. N., and McGowan, H. A.: Streamflow variability and
the role of snowmelt in a marginal snow environment, Arct. Antarct. Alp.
Res., 52, 161–176, https://doi.org/10.1080/15230430.2020.1746517, 2020.
Chauvin, G. M., Flerchinger, G. N., Link, T. E., Marks, D., Winstral, A. H.,
and Seyfried, M. S.: Long-term water balance and conceptual model of a
semi-arid mountainous catchment, J. Hydrol., 400, 133–143,
https://doi.org/10.1016/j.jhydrol.2011.01.031, 2011.
Christensen, N. S., Wood, A. W., Voisin, N., Lettenmaier, D. P., and Palmer,
R. N.: The Effects of Climate Change on the Hydrology and Water Resources of
the Colorado River Basin, Climat. Change, 62, 337–363,
https://doi.org/10.1023/B:CLIM.0000013684.13621.1f, 2004.
Datry, T., Larned, S. T., and Tockner, K.: Intermittent Rivers: A Challenge
for Freshwater Ecology, BioScience, 64, 229–235,
https://doi.org/10.1093/biosci/bit027, 2014.
Deems, J. S., Painter, T. H., and Finnegan, D. C.: Lidar measurement of snow
depth: a review, J. Glaciol., 59, 467–479,
https://doi.org/10.3189/2013JoG12J154, 2013.
Elder, K., Dozier, J., and Michaelsen, J.: Snow accumulation and
distribution in an Alpine Watershed, Water Resour. Res., 27, 1541–1552,
https://doi.org/10.1029/91WR00506, 1991.
Esri Inc.: ArcMap (version 10.7.1), Environmental Systems Research Institute, Redlands, CA, https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview (last access: 11 March 2021), 2020.
Fang, X. and Pomeroy, J. W.: Modelling blowing snow redistribution to
prairie wetlands, Hydrol. Process., 23, 2557–2569,
https://doi.org/10.1002/hyp.7348, 2009.
Flerchinger, G. N. and Cooley, K. R.: A ten-year water balance of a
mountainous semi-arid watershed, J. Hydrol., 237, 86–99,
https://doi.org/10.1016/S0022-1694(00)00299-7, 2000.
Flerchinger, G. N., Cooley, K. R., and Ralston, D. R.: Groundwater response
to snowmelt in a mountainous watershed, J. Hydrol., 133, 293–311,
https://doi.org/10.1016/0022-1694(93)90146-Z, 1992.
Godsey, S. E., Marks, D., Kormos, P. R., Seyfried, M. S., Enslin, C. L., Winstral, A. H., McNamara, J. P., and Link, T. E.: Eleven years of mountain weather, snow, soil moisture and streamflow data from the rain–snow transition zone – the Johnston Draw catchment, Reynolds Creek Experimental Watershed and Critical Zone Observatory, USA, Earth Syst. Sci. Data, 10, 1207–1216, https://doi.org/10.5194/essd-10-1207-2018, 2018a.
Godsey, S. E., Marks, D. G., Kormos, P. R., Seyfried, M. S., Enslin, C. L., McNamara, J. P., and Link, T. E.: Data from: Eleven years of mountain weather, snow, soil moisture and stream flow data from the rain-snow transition zone – the Johnston Draw catchment, Reynolds Creek Experimental Watershed and Critical Zone Observatory, USA, v1.1. Ag Data Commons, USDA [data set], https://doi.org/10.15482/USDA.ADC/1402076, 2018b.
Grünewald, T., Bühler, Y., and Lehning, M.: Elevation dependency of mountain snow depth, The Cryosphere, 8, 2381–2394, https://doi.org/10.5194/tc-8-2381-2014, 2014.
Hammond, J. C., Harpold, A. A., Weiss, S., and Kampf, S. K.: Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties, Hydrol. Earth Syst. Sci., 23, 3553–3570, https://doi.org/10.5194/hess-23-3553-2019, 2019.
Hartman, M. D., Baron, J. S., Lammers, R. B., Cline, D. W., Band, L. E.,
Liston, G. E., and Tague, C.: Simulations of snow distribution and hydrology
in a mountain basin, Water Resour. Res., 35, 1587–1603,
https://doi.org/10.1029/1998WR900096, 1999.
Havens, S., Marks, D., Kormos, P., and Hedrick, A.: Spatial Modeling for
Resources Framework (SMRF): A modular framework for developing spatial
forcing data for snow modeling in mountain basins, Comput. Geosci., 109,
295–304, https://doi.org/10.1016/j.cageo.2017.08.016, 2017.
Havens, S., Marks, D., Sandusky, M., Hedrick, A., Johnson, M., Robertson,
M., and Trujillo, E.: Automated Water Supply Model (AWSM): Streamlining and
standardizing application of a physically based snow model for water
resources and reproducible science, Comput. Geosci., 144, 104571,
https://doi.org/10.1016/j.cageo.2020.104571, 2020.
Hedrick, A. R., Marks, D., Marshall, H., McNamara, J., Havens, S., Trujillo,
E., Sandusky, M., Robertson, M., Johnson, M., Bormann, K. J., and Painter,
T. H.: From Drought to Flood: A Water Balance Analysis of the Tuolumne River
Basin during Extreme Conditions (2015–2017), Hydrol. Process., 34,
hyp.13749, https://doi.org/10.1002/hyp.13749, 2020.
Jasechko, S., Birks, S. J., Gleeson, T., Wada, Y., Fawcett, P. J., Sharp, Z.
D., McDonnell, J. J., and Welker, J. M.: The pronounced seasonality of
global groundwater recharge, Water Resour. Res., 50, 8845–8867,
https://doi.org/10.1002/2014WR015809, 2014.
Johnson, G. L. and Hanson, C. L.: Topographic and atmospheric influences on
precipitation variability over a mountainous watershed, J. Appl. Meteor.,
34, 68–86, 1995.
Kelleners, T. J., Chandler, D. G., McNamara, J. P., Gribb, M. M., and
Seyfried, M. S.: Modeling Runoff Generation in a Small Snow-Dominated
Mountainous Catchment, Vadose Zone J., 9, 517–527,
https://doi.org/10.2136/vzj2009.0033, 2010.
Klos, P. Z., Link, T. E., and Abatzoglou, J. T.: Extent of the rain-snow
transition zone in the western U.S. under historic and projected climate:
Climatic rain-snow transition zone, Geophys. Res. Lett., 41, 4560–4568,
https://doi.org/10.1002/2014GL060500, 2014.
Kormos, P. R., Marks, D., McNamara, J. P., Marshall, H. P., Winstral, A.,
and Flores, A. N.: Snow distribution, melt and surface water inputs to the
soil in the mountain rain–snow transition zone, J. Hydrol., 519, 190–204,
https://doi.org/10.1016/j.jhydrol.2014.06.051, 2014.
Kormos, P. R., Luce, C. H., Wenger, S. J., and Berghuijs, W. R.: Trends and
sensitivities of low streamflow extremes to discharge timing and magnitude
in Pacific Northwest mountain streams, Water Resour. Res., 52, 4990–5007,
https://doi.org/10.1002/2015WR018125, 2016.
Kretchun, A. M., Scheller, R. M., Shinneman, D. J., Soderquist, B., Maguire,
K., Link, T. E., and Strand, E. K.: Long term persistence of aspen in
snowdrift-dependent ecosystems, For. Ecol. Manag., 462, 118005,
https://doi.org/10.1016/j.foreco.2020.118005, 2020.
Leung, L. R., Qian, Y., Bian, X., Washington, W. M., Han, J., and Roads, J.
O.: Mid-Century Ensemble Regional Climate Change Scenarios for the Western
United States, Clim. Change, 62, 75–113,
https://doi.org/10.1023/B:CLIM.0000013692.50640.55, 2004.
López-Moreno, J. I. and Stähli, M.: Statistical analysis of the snow
cover variability in a subalpine watershed: Assessing the role of topography
and forest interactions, J. Hydrol., 348, 379–394,
https://doi.org/10.1016/j.jhydrol.2007.10.018, 2008.
Luce, C. H. and Holden, Z. A.: Declining annual streamflow distributions in
the Pacific Northwest United States, 1948–2006, Geophys. Res. Lett., 36,
L16401, https://doi.org/10.1029/2009GL039407, 2009.
MacNeille, R. B., Lohse, K. A., Godsey, S. E., Perdrial, J. N., and Baxter,
C. N.: Influence of drying and wildfire on longitudinal chemistry patterns
and processes of intermittent streams, Front. Water, ISSN 2624-9375,
https://doi.org/10.3389/frwa.2020.563841, 2020.
Marks, D., Domingo, J., Susong, D., Link, T., and Garen, D.: A spatially
distributed energy balance snowmelt model for application in mountain
basins, Hydrol. Process., 13, 1935–1959, 1999.
Marks, D., Winstral, A., and Seyfried, M.: Simulation of terrain and forest
shelter effects on patterns of snow deposition, snowmelt and runoff over a
semi-arid mountain catchment, Hydrol. Process., 16, 3605–3626,
https://doi.org/10.1002/hyp.1237, 2002.
Marks, D., Winstral, A., Reba, M., Pomeroy, J., and Kumar, M.: An evaluation
of methods for determining during-storm precipitation phase and the
rain/snow transition elevation at the surface in a mountain basin, Adv.
Water Resour., 55, 98–110, https://doi.org/10.1016/j.advwatres.2012.11.012,
2013.
Marshall, A. M., Link, T. E., Abatzoglou, J. T., Flerchinger, G. N., Marks,
D. G., and Tedrow, L.: Warming Alters Hydrologic Heterogeneity: Simulated
Climate Sensitivity of Hydrology-Based Microrefugia in the Snow-to-Rain
Transition Zone, Water Resour. Res., 55, 2122–2141,
https://doi.org/10.1029/2018WR023063, 2019.
McCabe, G. J. and Clark, M. P.: Trends and Variability in Snowmelt Runoff in
the Western United States, J. Hydromet., 6, 476–482,
https://doi.org/10.1175/JHM428.1, 2005.
McCabe, G. J., Wolock, D. M., Pederson, G. T., Woodhouse, C. A., and McAfee,
S.: Evidence that Recent Warming is Reducing Upper Colorado River Flows,
Earth Interact., 21, 1–14, https://doi.org/10.1175/EI-D-17-0007.1, 2017.
McNamara, J. P., Chandler, D., Seyfried, M., and Achet, S.: Soil moisture
states, lateral flow, and streamflow generation in a semi-arid,
snowmelt-driven catchment, Hydrol. Process., 19, 4023–4038,
https://doi.org/10.1002/hyp.5869, 2005.
Milly, P. C. D. and Dunne, K. A.: Colorado River flow dwindles as
warming-driven loss of reflective snow energizes evaporation, Science, 367,
1252–1255, https://doi.org/10.1126/science.aay9187, 2020.
Molotch, N. P., Brooks, P. D., Burns, S. P., Litvak, M., Monson, R. K.,
McConnell, J. R., and Musselman, K.: Ecohydrological controls on snowmelt
partitioning in mixed-conifer sub-alpine forests, Ecohydrol., 2, 129–142,
https://doi.org/10.1002/eco.48, 2009.
Mott, R., Vionnet, V., and Grünewald, T.: The Seasonal Snow Cover
Dynamics: Review on Wind-Driven Coupling Processes, Front. Earth Sci., 6,
197, https://doi.org/10.3389/feart.2018.00197, 2018.
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.
Nayak, A., Marks, D., Chandler, D. G., and Seyfried, M.: Long-term snow,
climate, and streamflow trends at the Reynolds Creek Experimental Watershed,
Owyhee Mountains, Idaho, United States, Water Resour. Res., 46, W06519,
https://doi.org/10.1029/2008WR007525, 2010.
Naz, B. S., Kao, S.-C., Ashfaq, M., Rastogi, D., Mei, R., and Bowling, L.
C.: Regional hydrologic response to climate change in the conterminous
United States using high-resolution hydroclimate simulations, Glob. Planet.
Change, 143, 100–117, https://doi.org/10.1016/j.gloplacha.2016.06.003,
2016.
Nolin, A. W. and Daly, C.: Mapping “At Risk” Snow in the Pacific
Northwest, J. Hydromet., 7, 1164–1171, https://doi.org/10.1175/JHM543.1,
2006.
Parr, C., Sturm, M., and Larsen, C.: Snowdrift Landscape Patterns: An Arctic
Investigation, Water Resour. Res., 56, e2020WR027823, https://doi.org/10.1029/2020WR027823, 2020.
Patton, N. R., Lohse, K. A., Seyfried, M. S., Godsey, S. E., and Parsons, S.
B.: Topographic controls of soil organic carbon on soil-mantled landscapes,
Sci. Rep., 9, 6390, https://doi.org/10.1038/s41598-019-42556-5, 2019.
Pflug, J. M. and Lundquist, J. D.: Inferring Distributed Snow Depth by
Leveraging Snow Pattern Repeatability: Investigation Using 47 Lidar
Observations in the Tuolumne Watershed, Sierra Nevada, California, Water
Resour. Res., 56, e2020WR027243, https://doi.org/10.1029/2020WR027243, 2020.
Pierson, F. B. and Cram, Z. K.: Reynolds Creek Experimental Watershed Runoff and Sediment Data Collection Field Manual, Rep. NWRC 98-2, Northwest Watershed Res. Center, USDA-ARS, Boise, Idaho, 30, 1998.
Pierson, F. B., Slaughter, C. W., and Cram, Z. K.: Long-term stream discharge and suspended-sediment database, Reynolds Creek Experimental Watershed, Idaho, Water Resour. Res., 37, 2857–2861, https://doi.org/10.1029/2001WR000420, 2001.
Planet Application Program Interface: In Space for Life on Earth, San Francisco, CA, https://www.planet.com/ (last access: 12 November 2020), 2017.
Pomeroy, J. W., Toth, B., Granger, R. J., Hedstrom, N. R., and Essery, R. L.
H.: Variation in Surface Energetics during Snowmelt in a Subarctic Mountain
Catchment, J. Hydromet., 4, 702–719, https://doi.org/10.1175/1525-7541(2003)004<0702:VISEDS>2.0.CO;2, 2003.
Regonda, S. K., Rajagopalan, B., Clark, M., and Pitlick, J.: Seasonal Cycle
Shifts in Hydroclimatology over the Western United States, J. Climate, 18,
372–384, https://doi.org/10.1175/JCLI-3272.1, 2005.
Schirmer, M., Wirz, V., Clifton, A., and Lehning, M.: Persistence in
intra-annual snow depth distribution: 1. Measurements and topographic
control, Water Resour. Res., 47, W09516, https://doi.org/10.1029/2010WR009426, 2011.
Schweizer, J., Jamieson, J. B., and Schneebeli, M.: Snow avalanche
formation, Rev. Geophys., 41, 1016, https://doi.org/10.1029/2002RG000123,
2003.
Seager, R., Naik, N., and Vogel, L.: Does Global Warming Cause Intensified
Interannual Hydroclimate Variability?, J. Climate, 25, 3355–3372,
https://doi.org/10.1175/JCLI-D-11-00363.1, 2012.
Seyfried, M., Chandler, D., and Marks, D.: Long-Term Soil Water Trends
across a 1000 m Elevation Gradient, Vadose Zone J., 10, 1276–1286,
https://doi.org/10.2136/vzj2011.0014, 2011.
Seyfried, M., Flerchinger, G., Bryden, S., Link, T., Marks, D., and
McNamara, J.: Slope/Aspect Controls on Soil Climate: Field Documentation and
Implications for Large-Scale Simulation of Critical Zone Processes, Vadose
Zone J., e20158, https://doi.org/10.1002/vzj2.20158, 2021.
Seyfried, M. S., Grant, L. E., Marks, D., Winstral, A., and McNamara, J.:
Simulated soil water storage effects on streamflow generation in a
mountainous snowmelt environment, Idaho, USA, Hydrol. Process., 23,
858–873, https://doi.org/10.1002/hyp.7211, 2009.
Shrestha, R. and Glenn, N. F.: 2007 Lidar-Derived Digital Elevation Model,
Canopy Height Model and Vegetation Cover Model Data Sets for Reynolds Creek
Experimental Watershed, Southwestern Idaho [data set],
https://doi.org/10.18122/B27C77, 2016.
Somers, L. D. and McKenzie, J. M.: A review of groundwater in high mountain
environments, WIREs Water, 7, e1475, https://doi.org/10.1002/wat2.1475, 2020.
Stephenson, G. R.: Soil-Geology-vegetation Inventories for
Reynolds Creek Watershed, Agric. Exp. Stn. Univ. Idaho Coll. Agric., http://cinergi.sdsc.edu/geoportal/rest/metadata/item/3a885851a7704879a7e4034065a8a98c/html
(last access: 6 May 2022), 1970.
Stewart, I. T.: Changes in snowpack and snowmelt runoff for key mountain
regions, Hydrol. Process., 23, 78–94, https://doi.org/10.1002/hyp.7128,
2009.
Stewart, I. T., Cayan, D. R., and Dettinger, M. D.: Changes toward Earlier
Streamflow Timing across Western North America, J. Climate, 18, 1136–1155,
https://doi.org/10.1175/JCLI3321.1, 2005.
Sturm, M.: White water: Fifty years of snow research in WRR and the outlook
for the future, Water Resour. Res., 51, 4948–4965,
https://doi.org/10.1002/2015WR017242, 2015.
Sturm, M. and Wagener, A. M.: Using repeated patterns in snow distribution
modeling: An Arctic example, Water Resour. Res., 46, W12549,
https://doi.org/10.1029/2010WR009434, 2010.
Tennant, C. J., Harpold, A. A., Lohse, K. A., Godsey, S. E., Crosby, B. T.,
Larsen, L. G., Brooks, P. D., Van Kirk, R. W., and Glenn, N. F.: Regional
sensitivities of seasonal snowpack to elevation, aspect, and vegetation
cover in western North America, Water Resour. Res., 53, 6908–6926,
https://doi.org/10.1002/2016WR019374, 2017.
Trujillo, E., Ramírez, J. A., and Elder, K. J.: Topographic,
meteorologic, and canopy controls on the scaling characteristics of the
spatial distribution of snow depth fields: spatial scaling of snow depth,
Water Resour. Res., 43, W07409, https://doi.org/10.1029/2006WR005317, 2007.
Trujillo, E., Havens, S., Hedrick, A. R., Johnson, M., Robertson, M.,
Pierson, F. B., and Marks, D. G.: Utilizing spatially resolved SWE to inform
snowfall interpolation across a headwater catchment in the Sierra Nevada –
AGU Fall meeting, December 9-13, C33B-1579, 2019.
Viviroli, D., Dürr, H. H., Messerli, B., Meybeck, M., and Weingartner,
R.: Mountains of the world, water towers for humanity: Typology, mapping,
and global significance, Water Resour. Res., 43, W07447,
https://doi.org/10.1029/2006WR005653, 2007.
Vögeli, C., Lehning, M., Wever, N., and Bavay, M.: Scaling Precipitation
Input to Spatially Distributed Hydrological Models by Measured Snow
Distribution, Front. Earth Sci., 4, 108, https://doi.org/10.3389/feart.2016.00108, 2016.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., and Swetnam, T. W.: Warming
and Earlier Spring Increase Western U.S. Forest Wildfire Activity, Science,
313, 940–943, https://doi.org/10.1126/science.1128834, 2006.
Williams, C. J., McNamara, J. P., and Chandler, D. G.: Controls on the temporal and spatial variability of soil moisture in a mountainous landscape: the signature of snow and complex terrain, Hydrol. Earth Syst. Sci., 13, 1325–1336, https://doi.org/10.5194/hess-13-1325-2009, 2009.
Winstral, A. and Marks, D.: Simulating wind fields and snow redistribution
using terrain-based parameters to model snow accumulation and melt over a
semi-arid mountain catchment, Hydrol. Process., 16, 3585–3603,
https://doi.org/10.1002/hyp.1238, 2002.
Winstral, A. and Marks, D.: Long-term snow distribution observations in a
mountain catchment: Assessing variability, time stability, and the
representativeness of an index site, Water Resour. Res., 50, 293–305,
https://doi.org/10.1002/2012WR013038, 2014.
Short summary
Climate change affects precipitation phase, which can propagate into changes in streamflow timing and magnitude. This study examines how variations in rainfall and snowmelt affect discharge. We found that annual discharge and stream cessation depended on the magnitude and timing of rainfall and snowmelt and on the snowpack melt-out date. This highlights the importance of precipitation timing and emphasizes the need for spatiotemporally distributed simulations of snowpack and rainfall dynamics.
Climate change affects precipitation phase, which can propagate into changes in streamflow...
