Articles | Volume 21, issue 2
Hydrol. Earth Syst. Sci., 21, 923–947, 2017
https://doi.org/10.5194/hess-21-923-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 923–947, 2017
https://doi.org/10.5194/hess-21-923-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
15 Feb 2017
Research article
| 15 Feb 2017
Examining regional groundwater–surface water dynamics using an integrated hydrologic model of the San Joaquin River basin
James M. Gilbert and Reed M. Maxwell
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Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Didier Voisin, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Jean-Gabriel Valay, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-639, https://doi.org/10.5194/hess-2021-639, 2022
Preprint under review for HESS
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Patchy snow cover is a common phenomenon in mountain landscapes. It leads to a longer period of snowmelt contribution to streams. Our study shows that surface variability of snow cover leads to differences in streamflow, evapotranspiration and snowmelt responses. We have used up-to-date hydrological tools strongly constrained with data collected from field and satellite images. The study finding will be helpful for the mountain hydrology community in the proper estimation of water resources.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Geosci. Model Dev., 14, 7545–7571, https://doi.org/10.5194/gmd-14-7545-2021, https://doi.org/10.5194/gmd-14-7545-2021, 2021
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
hiddenunderground and thus hard to measure. We suggest using multiple complementary strategies to assess the performance of a model (
model evaluation).
Mary M. F. O'Neill, Danielle T. Tijerina, Laura E. Condon, and Reed M. Maxwell
Geosci. Model Dev., 14, 7223–7254, https://doi.org/10.5194/gmd-14-7223-2021, https://doi.org/10.5194/gmd-14-7223-2021, 2021
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Modeling the hydrologic cycle at high resolution and at large spatial scales is an incredible opportunity and challenge for hydrologists. In this paper, we present the results of a high-resolution hydrologic simulation configured over the contiguous United States. We discuss simulated water fluxes through groundwater, soil, plants, and over land, and we compare model results to in situ observations and satellite products in order to build confidence and guide future model development.
Jun Zhang, Laura E. Condon, Hoang Tran, and Reed M. Maxwell
Earth Syst. Sci. Data, 13, 3263–3279, https://doi.org/10.5194/essd-13-3263-2021, https://doi.org/10.5194/essd-13-3263-2021, 2021
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Existing national topographic datasets for the US may not be compatible with gridded hydrologic models. A national topographic dataset developed to support physically based hydrologic models at 1 km and 250 m over the contiguous US is provided. We used a Priority Flood algorithm to ensure hydrologically consistent drainage networks and evaluated the performance with an integrated hydrologic model. Datasets and scripts are available for direct data usage or modification of processing as desired.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Stephen R. Maples, Laura Foglia, Graham E. Fogg, and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 24, 2437–2456, https://doi.org/10.5194/hess-24-2437-2020, https://doi.org/10.5194/hess-24-2437-2020, 2020
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In this study, we use a combination of local- and global-sensitivity analyses to evaluate the relative importance of (1) the configuration of subsurface alluvial geology and (2) the hydraulic properties of geologic facies on recharge processes. Results show that there is a large variation of recharge rates possible in a typical alluvial aquifer system and that the configuration proportion of sand and gravel deposits in the subsurface have a large impact on recharge rates.
Benjamin N. O. Kuffour, Nicholas B. Engdahl, Carol S. Woodward, Laura E. Condon, Stefan Kollet, and Reed M. Maxwell
Geosci. Model Dev., 13, 1373–1397, https://doi.org/10.5194/gmd-13-1373-2020, https://doi.org/10.5194/gmd-13-1373-2020, 2020
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Integrated hydrologic models (IHMs) were developed in order to allow for more accurate simulations of real-world ecohydrologic conditions. Many IHMs exist, and the literature can be dense, so it is often difficult to understand what a specific model can and cannot do. We provide a review of the current core capabilities, solution techniques, communication structure with other models, some limitations, and potential future improvements of one such open-source integrated model called ParFlow.
Annette Hein, Laura Condon, and Reed Maxwell
Hydrol. Earth Syst. Sci., 23, 1931–1950, https://doi.org/10.5194/hess-23-1931-2019, https://doi.org/10.5194/hess-23-1931-2019, 2019
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Drought is a natural disaster that can result from changes to temperature, precipitation and/or vegetation. Here we apply a
high-resolution computer model to explore the relative importance of each factor on the North American High Plains, one of the most important agricultural regions of the USA. Decreased precipitation caused larger changes in hydrologic variables (evapotranspiration, soil moisture, stream flow and water table levels) than increased temperature or disturbed vegetation did.
Laura E. Condon and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 21, 1117–1135, https://doi.org/10.5194/hess-21-1117-2017, https://doi.org/10.5194/hess-21-1117-2017, 2017
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We evaluate the impact of groundwater–surface water exchanges on the fraction of precipitation that leaves a watershed as either surface runoff or evapotranspiration. Results show that groundwater storage can systematically influence watershed behavior at the land surface. This is an important finding because most studies of tradeoffs between runoff and evapotranspiration assume that watersheds are in a steady-state condition where there are no net exchanges between the surface and subsurface.
Wolfgang Kurtz, Guowei He, Stefan J. Kollet, Reed M. Maxwell, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 9, 1341–1360, https://doi.org/10.5194/gmd-9-1341-2016, https://doi.org/10.5194/gmd-9-1341-2016, 2016
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This paper describes the development of a modular data assimilation (DA) system for the integrated Earth system model TerrSysMP with the help of the PDAF data assimilation library.
Currently, pressure and soil moisture data can be used to update model states and parameters in the subsurface compartment of TerrSysMP.
Results from an idealized twin experiment show that the developed DA system provides a good parallel performance and is also applicable for high-resolution modelling problems.
R. M. Maxwell, L. E. Condon, and S. J. Kollet
Geosci. Model Dev., 8, 923–937, https://doi.org/10.5194/gmd-8-923-2015, https://doi.org/10.5194/gmd-8-923-2015, 2015
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A model that simulates groundwater and surface water flow has been developed for the major river basins of the continental United States. Fundamental data sets provide input to the model resulting in a natural organization of stream networks and groundwater flow that is compared to observations of surface water and groundwater. Model results show relationships between flow and area that are moderated by aridity and represent an important step toward integrated hydrological prediction.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Effects of spatial and temporal variability in surface water inputs on streamflow generation and cessation in the rain–snow transition zone
Quantifying multi-year hydrological memory with Catchment Forgetting Curves
On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation
Influences of land use changes on the dynamics of water quantity and quality in the German lowland catchment of the Stör
Impact of spatial distribution information of rainfall in runoff simulation using deep learning method
Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco
The effects of spatial and temporal resolution of gridded meteorological forcing on watershed hydrological responses
Hydrological response of a peri-urban catchment exploiting conventional and unconventional rainfall observations: the case study of Lambro Catchment
Assessing hydrological sensitivity of grassland basins in the Canadian Prairies to climate using a basin classification-based virtual modelling approach
The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites
Storylines of UK drought based on the 2010–2012 event
Uncertainty estimation with deep learning for rainfall–runoff modeling
Applying non-parametric Bayesian networks to estimate maximum daily river discharge: potential and challenges
The Great Lakes Runoff Intercomparison Project Phase 4: The Great Lakes (GRIP-GL)
Contrasting changes in hydrological processes of the Volta River basin under global warming
A retrospective on hydrological catchment modelling based on half a century with the HBV model
Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters
Rainfall–runoff relationships at event scale in western Mediterranean ephemeral streams
Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
Simultaneous assimilation of water levels from river gauges and satellite flood maps for near-real-time flood mapping
Remote sensing-aided rainfall–runoff modeling in the tropics of Costa Rica
Drivers of drought-induced shifts in the water balance through a Budyko approach
Regionalization of hydrological model parameters using gradient boosting machine
Aquifer recharge in the Piedmont Alpine zone: historical trends and future scenarios
Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+
How well are we able to close the water budget at the global scale?
Bending of the concentration discharge relationship can inform about in-stream nitrate removal
Quantifying the impacts of land cover change on hydrological responses in the Mahanadi river basin in India
Identification of the contributing area to river discharge during low-flow periods
Simulating sediment discharge at water treatment plants under different land use scenarios using cascade modelling with an expert-based erosion-runoff model and a deep neural network
In-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based models
Can we use precipitation isotope outputs of isotopic general circulation models to improve hydrological modeling in large mountainous catchments on the Tibetan Plateau?
Small-scale topography explains patterns and dynamics of dissolved organic carbon exports from the riparian zone of a temperate, forested catchment
Revisiting parameter sensitivities in the Variable Infiltration Capacity model
Flood forecasting with machine learning models in an operational framework
Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca, Mexico
Benchmarking data-driven rainfall–runoff models in Great Britain: a comparison of long short-term memory (LSTM)-based models with four lumped conceptual models
Numerical daemons of hydrological models are summoned by extreme precipitation
How is Baseflow Index (BFI) impacted by water resource management practices?
Technical note: RAT – a robustness assessment test for calibrated and uncalibrated hydrological models
Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment
Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models
Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling
Deep learning rainfall-runoff predictions of extreme events
Hydrologically informed machine learning for rainfall–runoff modelling: towards distributed modelling
Development and evaluation of 0.05° terrestrial water storage estimates using Community Atmosphere Biosphere Land Exchange (CABLE) land surface model and assimilation of GRACE data
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective
A new fractal-theory-based criterion for hydrological model calibration
The value of water isotope data on improving process understanding in a glacierized catchment on the Tibetan Plateau
Leonie Kiewiet, Ernesto Trujillo, Andrew Hedrick, Scott Havens, Katherine Hale, Mark Seyfried, Stephanie Kampf, and Sarah E. Godsey
Hydrol. Earth Syst. Sci., 26, 2779–2796, https://doi.org/10.5194/hess-26-2779-2022, https://doi.org/10.5194/hess-26-2779-2022, 2022
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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.
Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, and Berit Arheimer
Hydrol. Earth Syst. Sci., 26, 2715–2732, https://doi.org/10.5194/hess-26-2715-2022, https://doi.org/10.5194/hess-26-2715-2022, 2022
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A watershed remembers the past to some extent, and this memory influences its behavior. This memory is defined by the ability to store past rainfall for several years. By releasing this water into the river or the atmosphere, it tends to forget. We describe how this memory fades over time in France and Sweden. A few watersheds show a multi-year memory. It increases with the influence of groundwater or dry conditions. After 3 or 4 years, they behave independently of the past.
Antoine Pelletier and Vazken Andréassian
Hydrol. Earth Syst. Sci., 26, 2733–2758, https://doi.org/10.5194/hess-26-2733-2022, https://doi.org/10.5194/hess-26-2733-2022, 2022
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A large part of the water cycle takes place underground. In many places, the soil stores water during the wet periods and can release it all year long, which is particularly visible when the river level is low. Modelling tools that are used to simulate and forecast the behaviour of the river struggle to represent this. We improved an existing model to take underground water into account using measurements of the soil water content. Results allow us make recommendations for model users.
Chaogui Lei, Paul D. Wagner, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 26, 2561–2582, https://doi.org/10.5194/hess-26-2561-2022, https://doi.org/10.5194/hess-26-2561-2022, 2022
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We presented an integrated approach to hydrologic modeling and partial least squares regression quantifying land use change impacts on water and nutrient balance over 3 decades. Results highlight that most variations (70 %–80 %) in water quantity and quality variables are explained by changes in land use class-specific areas and landscape metrics. Arable land influences water quantity and quality the most. The study provides insights on water resources management in rural lowland catchments.
Yang Wang and Hassan A. Karimi
Hydrol. Earth Syst. Sci., 26, 2387–2403, https://doi.org/10.5194/hess-26-2387-2022, https://doi.org/10.5194/hess-26-2387-2022, 2022
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We found that rainfall data with spatial information can improve the model's performance, especially when simulating the future multi-day discharges. We did not observe that regional LSTM as a regional model achieved better results than LSTM as individual model. This conclusion applies to both one-day and multi-day simulations. However, we found that using spatially distributed rainfall data can reduce the difference between individual LSTM and regional LSTM.
Wanshu Nie, Sujay V. Kumar, Kristi R. Arsenault, Christa D. Peters-Lidard, Iliana E. Mladenova, Karim Bergaoui, Abheera Hazra, Benjamin F. Zaitchik, Sarith P. Mahanama, Rachael McDonnell, David M. Mocko, and Mahdi Navari
Hydrol. Earth Syst. Sci., 26, 2365–2386, https://doi.org/10.5194/hess-26-2365-2022, https://doi.org/10.5194/hess-26-2365-2022, 2022
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The MENA (Middle East and North Africa) region faces significant food and water insecurity and hydrological hazards. Here we investigate the value of assimilating remote sensing data sets into an Earth system model to help build an effective drought monitoring system and support risk mitigation and management by countries in the region. We highlight incorporating satellite-informed vegetation conditions into the model as being one of the key processes for a successful application for the region.
Pin Shuai, Xingyuan Chen, Utkarsh Mital, Ethan T. Coon, and Dipankar Dwivedi
Hydrol. Earth Syst. Sci., 26, 2245–2276, https://doi.org/10.5194/hess-26-2245-2022, https://doi.org/10.5194/hess-26-2245-2022, 2022
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Using an integrated watershed model, we compared simulated watershed hydrologic variables driven by three publicly available gridded meteorological forcings (GMFs) at various spatial and temporal resolutions. Our results demonstrated that spatially distributed variables are sensitive to the spatial resolution of the GMF. The temporal resolution of the GMF impacts the dynamics of watershed responses. The choice of GMF depends on the quantity of interest and its spatial and temporal scales.
Greta Cazzaniga, Carlo De Michele, Michele D'Amico, Cristina Deidda, Antonio Ghezzi, and Roberto Nebuloni
Hydrol. Earth Syst. Sci., 26, 2093–2111, https://doi.org/10.5194/hess-26-2093-2022, https://doi.org/10.5194/hess-26-2093-2022, 2022
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Rainfall estimates are usually obtained from rain gauges, weather radars, or satellites. An alternative is the measurement of the signal loss induced by rainfall on commercial microwave links (CMLs). In this work, we assess the hydrologic response of Lambro Basin when CML-retrieved rainfall is used as model input. CML estimates agree with rain gauge data. CML-driven discharge simulations show performance comparable to that from rain gauges if a CML-based calibration of the model is undertaken.
Christopher Spence, Zhihua He, Kevin R. Shook, Balew A. Mekonnen, John W. Pomeroy, Colin J. Whitfield, and Jared D. Wolfe
Hydrol. Earth Syst. Sci., 26, 1801–1819, https://doi.org/10.5194/hess-26-1801-2022, https://doi.org/10.5194/hess-26-1801-2022, 2022
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We determined how snow and flow in small creeks change with temperature and precipitation in the Canadian Prairie, a region where water resources are often under stress. We tried something new. Every watershed in the region was placed in one of seven groups based on their landscape traits. We selected one of these groups and used its traits to build a model of snow and streamflow. It worked well, and by the 2040s there may be 20 %–40 % less snow and 30 % less streamflow than the 1980s.
Rui Tong, Juraj Parajka, Borbála Széles, Isabella Greimeister-Pfeil, Mariette Vreugdenhil, Jürgen Komma, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, https://doi.org/10.5194/hess-26-1779-2022, 2022
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The role and impact of using additional data (other than runoff) for the prediction of daily hydrographs in ungauged basins are not well understood. In this study, we assessed the model performance in terms of runoff, soil moisture, and snow cover predictions with the existing regionalization approaches. Results show that the best transfer methods are the similarity and the kriging approaches. The performance of the transfer methods differs between lowland and alpine catchments.
Wilson C. H. Chan, Theodore G. Shepherd, Katie Facer-Childs, Geoff Darch, and Nigel W. Arnell
Hydrol. Earth Syst. Sci., 26, 1755–1777, https://doi.org/10.5194/hess-26-1755-2022, https://doi.org/10.5194/hess-26-1755-2022, 2022
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We select the 2010–2012 UK drought and investigate an alternative unfolding of the drought from changes to its attributes. We created storylines of drier preconditions, alternative seasonal contributions, a third dry winter, and climate change. Storylines of the 2010–2012 drought show alternative situations that could have resulted in worse conditions than observed. Event-based storylines exploring plausible situations are used that may lead to high impacts and help stress test existing systems.
Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Johannes Brandstetter, Günter Klambauer, Sepp Hochreiter, and Grey Nearing
Hydrol. Earth Syst. Sci., 26, 1673–1693, https://doi.org/10.5194/hess-26-1673-2022, https://doi.org/10.5194/hess-26-1673-2022, 2022
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This contribution evaluates distributional runoff predictions from deep-learning-based approaches. We propose a benchmarking setup and establish four strong baselines. The results show that accurate, precise, and reliable uncertainty estimation can be achieved with deep learning.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-113, https://doi.org/10.5194/hess-2022-113, 2022
Revised manuscript accepted for HESS
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Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse models setup using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Moctar Dembélé, Mathieu Vrac, Natalie Ceperley, Sander J. Zwart, Josh Larsen, Simon J. Dadson, Grégoire Mariéthoz, and Bettina Schaefli
Hydrol. Earth Syst. Sci., 26, 1481–1506, https://doi.org/10.5194/hess-26-1481-2022, https://doi.org/10.5194/hess-26-1481-2022, 2022
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Climate change impacts on water resources in the Volta River basin are investigated under various global warming scenarios. Results reveal contrasting changes in future hydrological processes and water availability, depending on greenhouse gas emission scenarios, with implications for floods and drought occurrence over the 21st century. These findings provide insights for the elaboration of regional adaptation and mitigation strategies for climate change.
Jan Seibert and Sten Bergström
Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, https://doi.org/10.5194/hess-26-1371-2022, 2022
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Hydrological catchment models are commonly used as the basis for water resource management planning. The HBV model, which is a typical example of such a model, was first applied about 50 years ago in Sweden. We describe and reflect on the model development and applications. The aim is to provide an understanding of the background of model development and a basis for addressing the balance between model complexity and data availability that will continue to face hydrologists in the future.
Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
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Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Roberto Serrano-Notivoli, Alberto Martínez-Salvador, Rafael García-Lorenzo, David Espín-Sánchez, and Carmelo Conesa-García
Hydrol. Earth Syst. Sci., 26, 1243–1260, https://doi.org/10.5194/hess-26-1243-2022, https://doi.org/10.5194/hess-26-1243-2022, 2022
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Ephemeral streams in the western Mediterranean area are driven by the duration, magnitude, and intensity of rainfall events (REs). A detailed statistical analysis showed that the average RE (1.2 d and 1.5 mm) is not enough to generate new flow, which is only guaranteed by events occurring in return periods from 2 to > 50 years. REs explain near to 75 % of new flow, meaning that terrain and lithological characteristics play a fundamental role.
Adam P. Schreiner-McGraw and Hoori Ajami
Hydrol. Earth Syst. Sci., 26, 1145–1164, https://doi.org/10.5194/hess-26-1145-2022, https://doi.org/10.5194/hess-26-1145-2022, 2022
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We assess the impact of uncertainty in measurements of precipitation and air temperature on simulated groundwater processes in a mountainous watershed. We illustrate the role of topography in controlling how uncertainty in the input datasets propagates through the soil and into the groundwater. While the focus of previous investigations has been on the impact of precipitation uncertainty, we show that air temperature uncertainty is equally important in controlling the groundwater recharge.
Antonio Annis, Fernando Nardi, and Fabio Castelli
Hydrol. Earth Syst. Sci., 26, 1019–1041, https://doi.org/10.5194/hess-26-1019-2022, https://doi.org/10.5194/hess-26-1019-2022, 2022
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In this work, we proposed a multi-source data assimilation framework for near-real-time flood mapping. We used a quasi-2D hydraulic model to update model states by injecting both stage gauge observations and satellite-derived flood extents. Results showed improvements in terms of water level prediction and reduction of flood extent uncertainty when assimilating both stage gauges and satellite images with respect to the disjoint assimilation of both observations.
Saúl Arciniega-Esparza, Christian Birkel, Andrés Chavarría-Palma, Berit Arheimer, and José Agustín Breña-Naranjo
Hydrol. Earth Syst. Sci., 26, 975–999, https://doi.org/10.5194/hess-26-975-2022, https://doi.org/10.5194/hess-26-975-2022, 2022
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In the humid tropics, a notoriously data-scarce region, we need to find alternatives in order to reasonably apply hydrological models. Here, we tested remotely sensed rainfall data in order to drive a model for Costa Rica, and we evaluated the simulations against evapotranspiration satellite products. We found that our model was able to reasonably simulate the water balance and streamflow dynamics of over 600 catchments where the satellite data helped to reduce the model uncertainties.
Tessa Maurer, Francesco Avanzi, Steven D. Glaser, and Roger C. Bales
Hydrol. Earth Syst. Sci., 26, 589–607, https://doi.org/10.5194/hess-26-589-2022, https://doi.org/10.5194/hess-26-589-2022, 2022
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Predicting how much water will end up in rivers is more difficult during droughts because the relationship between precipitation and streamflow can change in unexpected ways. We differentiate between changes that are predictable based on the weather patterns and those harder to predict because they depend on the land and vegetation of a particular region. This work helps clarify why models are less accurate during droughts and helps predict how much water will be available for human use.
Zhihong Song, Jun Xia, Gangsheng Wang, Dunxian She, Chen Hu, and Si Hong
Hydrol. Earth Syst. Sci., 26, 505–524, https://doi.org/10.5194/hess-26-505-2022, https://doi.org/10.5194/hess-26-505-2022, 2022
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We performed a machine learning approach to regionalize the parameters of a China-wide hydrological model by linking six model parameters with 10 physical attributes (terrain and soil properties). The results show the superiority of machine-learning-based regionalization approach compared with the traditional linear regression method in ungauged regions. We also obtained the relative importance of attributes against model parameters.
Elisa Brussolo, Elisa Palazzi, Jost von Hardenberg, Giulio Masetti, Gianna Vivaldo, Maurizio Previati, Davide Canone, Davide Gisolo, Ivan Bevilacqua, Antonello Provenzale, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 26, 407–427, https://doi.org/10.5194/hess-26-407-2022, https://doi.org/10.5194/hess-26-407-2022, 2022
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In this study, we evaluate the past, present and future quantity of groundwater potentially available for drinking purposes in the metropolitan area of Turin, north-western Italy. In order to effectively manage water resources, a knowledge of the water cycle components is necessary, including precipitation, evapotranspiration and subsurface reservoirs. All these components have been carefully evaluated in this paper, using observational datasets and modelling approaches.
Albert Nkwasa, Celray James Chawanda, Jonas Jägermeyr, and Ann van Griensven
Hydrol. Earth Syst. Sci., 26, 71–89, https://doi.org/10.5194/hess-26-71-2022, https://doi.org/10.5194/hess-26-71-2022, 2022
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We present an approach on how to incorporate crop phenology in a regional hydrological model using decision tables and global datasets of rainfed and irrigated cropland with the associated cropping calendar and management practices. Results indicate improved temporal patterns of leaf area index (LAI) and evapotranspiration (ET) simulations in comparison with remote sensing data. In addition, the improvement of the cropping season also helps to improve soil erosion estimates in cultivated areas.
Fanny Lehmann, Bramha Dutt Vishwakarma, and Jonathan Bamber
Hydrol. Earth Syst. Sci., 26, 35–54, https://doi.org/10.5194/hess-26-35-2022, https://doi.org/10.5194/hess-26-35-2022, 2022
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Many data sources are available to evaluate components of the water cycle (precipitation, evapotranspiration, runoff, and terrestrial water storage). Despite this variety, it remains unclear how different combinations of datasets satisfy the conservation of mass. We conducted the most comprehensive analysis of water budget closure on a global scale to date. Our results can serve as a basis to select appropriate datasets for regional hydrological studies.
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463, https://doi.org/10.5194/hess-25-6437-2021, https://doi.org/10.5194/hess-25-6437-2021, 2021
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Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Shaini Naha, Miguel Angel Rico-Ramirez, and Rafael Rosolem
Hydrol. Earth Syst. Sci., 25, 6339–6357, https://doi.org/10.5194/hess-25-6339-2021, https://doi.org/10.5194/hess-25-6339-2021, 2021
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Rapid growth in population in developing countries leads to an increase in food demand, and as a consequence, percentages of land are being converted to cropland which alters river flow processes. This study describes how the hydrology of a flood-prone river basin in India would respond to the current and future changes in land cover. Our findings indicate that the recurrent flood events occurring in the basin might be influenced by these changes in land cover at the catchment scale.
Maxime Gillet, Corinne Le Gal La Salle, Pierre Alain Ayral, Somar Khaska, Philippe Martin, and Patrick Verdoux
Hydrol. Earth Syst. Sci., 25, 6261–6281, https://doi.org/10.5194/hess-25-6261-2021, https://doi.org/10.5194/hess-25-6261-2021, 2021
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This paper aims at identifying the key reservoirs sustaining river low flow during dry summer. The reservoirs are discriminated based on the geological nature of the formations and the geochemical signature of groundwater. Results show the increasing importance to low-flow support of a specific reservoir, showing only a limited outcrop area and becoming preponderant in the heart of the dry season. This finding will contribute to improving the protective measures for preserving low flows.
Edouard Patault, Valentin Landemaine, Jérôme Ledun, Arnaud Soulignac, Matthieu Fournier, Jean-François Ouvry, Olivier Cerdan, and Benoit Laignel
Hydrol. Earth Syst. Sci., 25, 6223–6238, https://doi.org/10.5194/hess-25-6223-2021, https://doi.org/10.5194/hess-25-6223-2021, 2021
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The goal of this study was to assess the sediment discharge variability at a water treatment plant (Normandy, France) according to multiple realistic land use scenarios. We developed a new cascade modelling approach and simulations suggested that coupling eco-engineering and best farming practices can significantly reduce the sediment discharge (up to 80 %).
Ather Abbas, Sangsoo Baek, Norbert Silvera, Bounsamay Soulileuth, Yakov Pachepsky, Olivier Ribolzi, Laurie Boithias, and Kyung Hwa Cho
Hydrol. Earth Syst. Sci., 25, 6185–6202, https://doi.org/10.5194/hess-25-6185-2021, https://doi.org/10.5194/hess-25-6185-2021, 2021
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Correct estimation of fecal indicator bacteria in surface waters is critical for public health. Process-driven models and recently data-driven models have been applied for water quality modeling; however, a systematic comparison for simulation of E. coli is missing in the literature. We compared performance of process-driven (HSPF) and data-driven (LSTM) models for E. coli simulation. We show that LSTM can be an alternative to process-driven models for estimation of E. coli in surface waters.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 25, 6151–6172, https://doi.org/10.5194/hess-25-6151-2021, https://doi.org/10.5194/hess-25-6151-2021, 2021
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Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Benedikt J. Werner, Oliver J. Lechtenfeld, Andreas Musolff, Gerrit H. de Rooij, Jie Yang, Ralf Gründling, Ulrike Werban, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 25, 6067–6086, https://doi.org/10.5194/hess-25-6067-2021, https://doi.org/10.5194/hess-25-6067-2021, 2021
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Export of dissolved organic carbon (DOC) from riparian zones (RZs) is an important yet poorly understood component of the catchment carbon budget. This study chemically and spatially classifies DOC source zones within a RZ of a small catchment to assess DOC export patterns. Results highlight that DOC export from only a small fraction of the RZ with distinct DOC composition dominates overall DOC export. The application of a spatial, topographic proxy can be used to improve DOC export models.
Ulises Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-550, https://doi.org/10.5194/hess-2021-550, 2021
Revised manuscript accepted for HESS
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This paper characterizes parameter sensitivities across > 5,500 grid cells for a commonly used macro-scale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-554, https://doi.org/10.5194/hess-2021-554, 2021
Revised manuscript accepted for HESS
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Early flood warnings are one of the most effective tools to save lives and goods. Machine learning models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses machine learning models for forecasting river stage and flood inundation maps, and discusses the models’ performances. In 2021 more than 100M flood alerts were sent to people near rivers over an area of 287,000 km2.
Sergio Naranjo, Francelino A. Rodrigues Jr., Georg Cadisch, Santiago Lopez-Ridaura, Mariela Fuentes Ponce, and Carsten Marohn
Hydrol. Earth Syst. Sci., 25, 5561–5588, https://doi.org/10.5194/hess-25-5561-2021, https://doi.org/10.5194/hess-25-5561-2021, 2021
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We integrate a spatially explicit soil erosion model with plot- and watershed-scale characterization and high-resolution drone imagery to assess the effect of spatial resolution digital terrain models (DTMs) on discharge and soil loss. Results showed reduction in slope due to resampling down of DTM. Higher resolution translates to higher slope, denser fluvial system, and extremer values of soil loss, reducing concentration time and increasing soil loss at the outlet. The best resolution was 4 m.
Thomas Lees, Marcus Buechel, Bailey Anderson, Louise Slater, Steven Reece, Gemma Coxon, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 25, 5517–5534, https://doi.org/10.5194/hess-25-5517-2021, https://doi.org/10.5194/hess-25-5517-2021, 2021
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We used deep learning (DL) models to simulate the amount of water moving through a river channel (discharge) based on the rainfall, temperature and potential evaporation in the previous days. We tested the DL models on catchments across Great Britain finding that the model can accurately simulate hydrological systems across a variety of catchment conditions. Ultimately, the model struggled most in areas where there is chalky bedrock and where human influence on the catchment is large.
Peter T. La Follette, Adriaan J. Teuling, Nans Addor, Martyn Clark, Koen Jansen, and Lieke A. Melsen
Hydrol. Earth Syst. Sci., 25, 5425–5446, https://doi.org/10.5194/hess-25-5425-2021, https://doi.org/10.5194/hess-25-5425-2021, 2021
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Hydrological models are useful tools that allow us to predict distributions and movement of water. A variety of numerical methods are used by these models. We demonstrate which numerical methods yield large errors when subject to extreme precipitation. As the climate is changing such that extreme precipitation is more common, we find that some numerical methods are better suited for use in hydrological models. Also, we find that many current hydrological models use relatively inaccurate methods.
John P. Bloomfield, Mengyi Gong, Benjamin P. Marchant, Gemma Coxon, and Nans Addor
Hydrol. Earth Syst. Sci., 25, 5355–5379, https://doi.org/10.5194/hess-25-5355-2021, https://doi.org/10.5194/hess-25-5355-2021, 2021
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Groundwater provides flow, known as baseflow, to surface streams and rivers. It is important as it sustains the flow of many rivers at times of water stress. However, it may be affected by water management practices. Statistical models have been used to show that abstraction of groundwater may influence baseflow. Consequently, it is recommended that information on groundwater abstraction is included in future assessments and predictions of baseflow.
Pierre Nicolle, Vazken Andréassian, Paul Royer-Gaspard, Charles Perrin, Guillaume Thirel, Laurent Coron, and Léonard Santos
Hydrol. Earth Syst. Sci., 25, 5013–5027, https://doi.org/10.5194/hess-25-5013-2021, https://doi.org/10.5194/hess-25-5013-2021, 2021
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In this note, a new method (RAT) is proposed to assess the robustness of hydrological models. The RAT method is particularly interesting because it does not require multiple calibrations (it is therefore applicable to uncalibrated models), and it can be used to determine whether a hydrological model may be safely used for climate change impact studies. Success at the robustness assessment test is a necessary (but not sufficient) condition of model robustness.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Etienne Guilpart, Vahid Espanmanesh, Amaury Tilmant, and François Anctil
Hydrol. Earth Syst. Sci., 25, 4611–4629, https://doi.org/10.5194/hess-25-4611-2021, https://doi.org/10.5194/hess-25-4611-2021, 2021
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The stationary assumption in hydrology has become obsolete because of climate changes. In that context, it is crucial to assess the performance of a hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. We illustrate the method on the Senegal River.
Sebastian A. Krogh, Lucia Scaff, Gary Sterle, James Kirchner, Beatrice Gordon, and Adrian Harpold
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-437, https://doi.org/10.5194/hess-2021-437, 2021
Revised manuscript accepted for HESS
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We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder than in warmer places, which is then contrasted with land-surface simulations.
Jonathan Frame, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shelev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-423, https://doi.org/10.5194/hess-2021-423, 2021
Revised manuscript accepted for HESS
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The most accurate rainfall-runoff predictions are currently based on deep learning. There is a concern among hydrologists that deep learning models may not be reliable in extrapolation or for predicting extreme events. This study tests that hypothesis. The deep learning models remained relatively accurate in predicting extreme events compared traditional models, even when extreme events are not included in the training set.
Herath Mudiyanselage Viraj Vidura Herath, Jayashree Chadalawada, and Vladan Babovic
Hydrol. Earth Syst. Sci., 25, 4373–4401, https://doi.org/10.5194/hess-25-4373-2021, https://doi.org/10.5194/hess-25-4373-2021, 2021
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Existing hydrological knowledge has been integrated with genetic programming based on a machine learning algorithm (MIKA-SHA) to induce readily interpretable distributed rainfall–runoff models. At present, the model building components of two flexible modelling frameworks (FUSE and SUPERFLEX) represent the elements of hydrological knowledge. The proposed toolkit captures spatial variabilities and automatically induces semi-distributed rainfall–runoff models without any explicit user selections.
Natthachet Tangdamrongsub, Michael F. Jasinski, and Peter J. Shellito
Hydrol. Earth Syst. Sci., 25, 4185–4208, https://doi.org/10.5194/hess-25-4185-2021, https://doi.org/10.5194/hess-25-4185-2021, 2021
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Accurate estimation of terrestrial water storage (TWS) is essential for reliable water resource assessments. TWS can be estimated from the Community Atmosphere–Biosphere Land Exchange model (CABLE), but the resolution is limited to 0.5°. We reconfigure CABLE to improve TWS spatial details from 0.5° to 0.05°. GRACE satellite data are assimilated into CABLE to improve TWS accuracy. Our workflow relies only on publicly accessible data, allowing reproduction of 0.05° TWS in any region.
Seán Donegan, Conor Murphy, Shaun Harrigan, Ciaran Broderick, Dáire Foran Quinn, Saeed Golian, Jeff Knight, Tom Matthews, Christel Prudhomme, Adam A. Scaife, Nicky Stringer, and Robert L. Wilby
Hydrol. Earth Syst. Sci., 25, 4159–4183, https://doi.org/10.5194/hess-25-4159-2021, https://doi.org/10.5194/hess-25-4159-2021, 2021
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We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.
Paul C. Astagneau, Guillaume Thirel, Olivier Delaigue, Joseph H. A. Guillaume, Juraj Parajka, Claudia C. Brauer, Alberto Viglione, Wouter Buytaert, and Keith J. Beven
Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, https://doi.org/10.5194/hess-25-3937-2021, 2021
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The R programming language has become an important tool for many applications in hydrology. In this study, we provide an analysis of some of the R tools providing hydrological models. In total, two aspects are uniformly investigated, namely the conceptualisation of the models and the practicality of their implementation for end-users. These comparisons aim at easing the choice of R tools for users and at improving their usability for hydrology modelling to support more transferable research.
Zhixu Bai, Yao Wu, Di Ma, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 25, 3675–3690, https://doi.org/10.5194/hess-25-3675-2021, https://doi.org/10.5194/hess-25-3675-2021, 2021
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To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.
Yi Nan, Lide Tian, Zhihua He, Fuqiang Tian, and Lili Shao
Hydrol. Earth Syst. Sci., 25, 3653–3673, https://doi.org/10.5194/hess-25-3653-2021, https://doi.org/10.5194/hess-25-3653-2021, 2021
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This study integrated a water isotope module into the hydrological model THREW. The isotope-aided model was subsequently applied for process understanding in the glacierized watershed of Karuxung river on the Tibetan Plateau. The model was used to quantify the contribution of runoff component and estimate the water travel time in the catchment. Model uncertainties were significantly constrained by using additional isotopic data, improving the process understanding in the catchment.
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Short summary
Understanding how groundwater and streamflow interact over large areas is a challenge. In this study we use a computer simulation that calculates water movement and storage at the land surface and in the subsurface within California's San Joaquin River basin to analyze different parts of the watershed. Results show that the mountains may be an important source of groundwater to the Central Valley while differences in relative speed of groundwater and river flow affect their connection patterns.
Understanding how groundwater and streamflow interact over large areas is a challenge. In this...
