Articles | Volume 26, issue 3
https://doi.org/10.5194/hess-26-589-2022
© 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-26-589-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Feb 2022
Research article |
| 07 Feb 2022
| 07 Feb 2022
Drivers of drought-induced shifts in the water balance through a Budyko approach
Blue Forest Conservation, Sacramento, CA, USA
Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA
Francesco Avanzi
CIMA Research Foundation, via Armando Magliotto 2, 17100, Savona, Italy
Steven D. Glaser
Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA
Roger C. Bales
Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA
Sierra Nevada Research Institute, University of California, Merced, CA, USA
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Francesco Avanzi, Joseph Rungee, Tessa Maurer, Roger Bales, Qin Ma, Steven Glaser, and Martha Conklin
Hydrol. Earth Syst. Sci., 24, 4317–4337, https://doi.org/10.5194/hess-24-4317-2020, https://doi.org/10.5194/hess-24-4317-2020, 2020
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Multi-year droughts in Mediterranean climates often see a lower fraction of precipitation allocated to runoff compared to non-drought years. By comparing observed water-balance components with simulations by a hydrologic model (PRMS), we reinterpret these shifts as a hysteretic response of the water budget to climate elasticity of evapotranspiration. Our results point to a general improvement in hydrologic predictions across drought and recovery cycles by including this mechanism.
Francesca Munerol, Francesco Avanzi, Eleonora Panizza, Marco Altamura, Simone Gabellani, Lara Polo, Marina Mantini, Barbara Alessandri, and Luca Ferraris
Geosci. Commun., 7, 1–15, https://doi.org/10.5194/gc-7-1-2024, https://doi.org/10.5194/gc-7-1-2024, 2024
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To contribute to advancing education in a warming climate and prepare the next generations to play their role in future societies, we designed “Water and Us”, a three-module initiative focusing on the natural and anthropogenic water cycle, climate change, and conflicts. This study aims to introduce the initiative's educational objectives, methods, and early results.
Giulia Blandini, Francesco Avanzi, Simone Gabellani, Denise Ponziani, Hervé Stevenin, Sara Ratto, Luca Ferraris, and Alberto Viglione
The Cryosphere, 17, 5317–5333, https://doi.org/10.5194/tc-17-5317-2023, https://doi.org/10.5194/tc-17-5317-2023, 2023
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Automatic snow depth data are a valuable source of information for hydrologists, but they also tend to be noisy. To maximize the value of these measurements for real-world applications, we developed an automatic procedure to differentiate snow cover from grass or bare ground data, as well as to detect random errors. This procedure can enhance snow data quality, thus providing more reliable data for snow models.
Junyan Ding, Polly Buotte, Roger Bales, Bradley Christoffersen, Rosie A. Fisher, Michael Goulden, Ryan Knox, Lara Kueppers, Jacquelyn Shuman, Chonggang Xu, and Charles D. Koven
Biogeosciences, 20, 4491–4510, https://doi.org/10.5194/bg-20-4491-2023, https://doi.org/10.5194/bg-20-4491-2023, 2023
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We used a vegetation model to investigate how the different combinations of plant rooting depths and the sensitivity of leaves and stems to drying lead to differential responses of a pine forest to drought conditions in California, USA. We found that rooting depths are the strongest control in that ecosystem. Deep roots allow trees to fully utilize the soil water during a normal year but result in prolonged depletion of soil moisture during a severe drought and hence a high tree mortality risk.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Giulia Bruno, Doris Duethmann, Francesco Avanzi, Lorenzo Alfieri, Andrea Libertino, and Simone Gabellani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-416, https://doi.org/10.5194/hess-2022-416, 2022
Manuscript not accepted for further review
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Hydrological models often have issues during droughts. We used the distributed Continuum model over the Po river basin and independent datasets of streamflow (Q), evapotranspiration (ET), and storage. Continuum simulated Q well during wet years and moderate droughts. Performances declined for a severe drought and we explained this drop with an increased uncertainty in ET anomalies in human-affected croplands. These findings provide guidelines for assessments of model robustness during droughts.
Lorenzo Alfieri, Francesco Avanzi, Fabio Delogu, Simone Gabellani, Giulia Bruno, Lorenzo Campo, Andrea Libertino, Christian Massari, Angelica Tarpanelli, Dominik Rains, Diego G. Miralles, Raphael Quast, Mariette Vreugdenhil, Huan Wu, and Luca Brocca
Hydrol. Earth Syst. Sci., 26, 3921–3939, https://doi.org/10.5194/hess-26-3921-2022, https://doi.org/10.5194/hess-26-3921-2022, 2022
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This work shows advances in high-resolution satellite data for hydrology. We performed hydrological simulations for the Po River basin using various satellite products, including precipitation, evaporation, soil moisture, and snow depth. Evaporation and snow depth improved a simulation based on high-quality ground observations. Interestingly, a model calibration relying on satellite data skillfully reproduces observed discharges, paving the way to satellite-driven hydrological applications.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
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Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Christian Massari, Francesco Avanzi, Giulia Bruno, Simone Gabellani, Daniele Penna, and Stefania Camici
Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, https://doi.org/10.5194/hess-26-1527-2022, 2022
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Droughts are a creeping disaster, meaning that their onset, duration and recovery are challenging to monitor and forecast. Here, we provide further evidence of an additional challenge of droughts, i.e. the fact that the deficit in water supply during droughts is generally much more than expected based on the observed decline in precipitation. At a European scale we explain this with enhanced evapotranspiration, sustained by higher atmospheric demand for moisture during such dry periods.
Francesco Avanzi, Giulia Ercolani, Simone Gabellani, Edoardo Cremonese, Paolo Pogliotti, Gianluca Filippa, Umberto Morra di Cella, Sara Ratto, Hervè Stevenin, Marco Cauduro, and Stefano Juglair
Hydrol. Earth Syst. Sci., 25, 2109–2131, https://doi.org/10.5194/hess-25-2109-2021, https://doi.org/10.5194/hess-25-2109-2021, 2021
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Precipitation tends to increase with elevation, but the magnitude and distribution of this enhancement remain poorly understood. By leveraging over 11 000 spatially distributed, manual measurements of snow depth (snow courses) upstream of two reservoirs in the western European Alps, we show that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improved modeling accuracy and, ultimately, our understanding of the water budget.
Francesco Avanzi, Joseph Rungee, Tessa Maurer, Roger Bales, Qin Ma, Steven Glaser, and Martha Conklin
Hydrol. Earth Syst. Sci., 24, 4317–4337, https://doi.org/10.5194/hess-24-4317-2020, https://doi.org/10.5194/hess-24-4317-2020, 2020
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Multi-year droughts in Mediterranean climates often see a lower fraction of precipitation allocated to runoff compared to non-drought years. By comparing observed water-balance components with simulations by a hydrologic model (PRMS), we reinterpret these shifts as a hysteretic response of the water budget to climate elasticity of evapotranspiration. Our results point to a general improvement in hydrologic predictions across drought and recovery cycles by including this mechanism.
James W. Roche, Robert Rice, Xiande Meng, Daniel R. Cayan, Michael D. Dettinger, Douglas Alden, Sarina C. Patel, Megan A. Mason, Martha H. Conklin, and Roger C. Bales
Earth Syst. Sci. Data, 11, 101–110, https://doi.org/10.5194/essd-11-101-2019, https://doi.org/10.5194/essd-11-101-2019, 2019
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This paper summarizes climate, snow, and soil moisture data for the Tuolumne and Merced river watersheds in California, USA, for water years 2010–2014. Climate data include hourly air temperature and relative humidity, precipitation, wind speed and direction, and solar radiation. Snow depth and soil moisture at three–six points per site are available at four locations. Snow depth and water content are available from instrumented snow pillow sites and manual snow survey locations.
Roger C. Bales, Erin M. Stacy, Xiande Meng, Martha H. Conklin, Peter B. Kirchner, and Zeshi Zheng
Earth Syst. Sci. Data, 10, 2115–2122, https://doi.org/10.5194/essd-10-2115-2018, https://doi.org/10.5194/essd-10-2115-2018, 2018
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This 2006–2016 record of snow depth, soil moisture and soil temperature, and meteorological data quantifies hydrologic inputs and storage in the mostly undeveloped Wolverton catchment (2180–2750 m) in Sequoia National Park. Two meteorological stations were installed, along with clustered sensors that recorded differences in snow and soil moisture across the landscape with regard to aspect and canopy cover at elevations of 2250 and 2625 m, just above the current rain–snow transition elevation.
Roger Bales, Erin Stacy, Mohammad Safeeq, Xiande Meng, Matthew Meadows, Carlos Oroza, Martha Conklin, Steven Glaser, and Joseph Wagenbrenner
Earth Syst. Sci. Data, 10, 1795–1805, https://doi.org/10.5194/essd-10-1795-2018, https://doi.org/10.5194/essd-10-1795-2018, 2018
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Strategically placed, spatially distributed sensors provide representative measures of changes in snowpack and subsurface water storage, plus the fluxes affecting these stores, in a set of nested headwater catchments. We present 8 years of hourly snow-depth, soil-moisture, and soil-temperature data from hundreds of sensors, as well as 14 years of streamflow and meteorological data that detail processes at the rain–snow transition at Providence Creek in the southern Sierra Nevada, California.
Susan L. Brantley, William H. McDowell, William E. Dietrich, Timothy S. White, Praveen Kumar, Suzanne P. Anderson, Jon Chorover, Kathleen Ann Lohse, Roger C. Bales, Daniel D. Richter, Gordon Grant, and Jérôme Gaillardet
Earth Surf. Dynam., 5, 841–860, https://doi.org/10.5194/esurf-5-841-2017, https://doi.org/10.5194/esurf-5-841-2017, 2017
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The layer known as the critical zone extends from the tree tops to the groundwater. This zone varies globally as a function of land use, climate, and geology. Energy and materials input from the land surface downward impact the subsurface landscape of water, gas, weathered material, and biota – at the same time that differences at depth also impact the superficial landscape. Scientists are designing observatories to understand the critical zone and how it will evolve in the future.
Hiroyuki Hirashima, Francesco Avanzi, and Satoru Yamaguchi
Hydrol. Earth Syst. Sci., 21, 5503–5515, https://doi.org/10.5194/hess-21-5503-2017, https://doi.org/10.5194/hess-21-5503-2017, 2017
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We reproduced the formation of capillary barriers and the development of preferential flow through snow using a multi-dimensional water transport model, which was then validated using laboratory experiments of liquid water infiltration into layered, initially dry snow. Simulation results showed that the model reconstructs some relevant features of capillary barriers and the timing of liquid water arrival at the snow base.
Francesco Avanzi, Alberto Bianchi, Alberto Cina, Carlo De Michele, Paolo Maschio, Diana Pagliari, Daniele Passoni, Livio Pinto, Marco Piras, and Lorenzo Rossi
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-57, https://doi.org/10.5194/tc-2017-57, 2017
Revised manuscript not accepted
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We compare three different instruments used to collect snow depth, i.e., photogrammetric surveys using Unmanned Aerial Systems (UAS), a 3D laser scanning, and manual probing. The relatively high density of manual data (135 pt over 6700 m2, i.e., 2 pt/100 m2) enables to assess the performance of UAS in capturing the marked spatial variability of snow. Results suggest that UAS represent a competitive choice among existing techniques for high-precision, high-resolution remote sensing of snow.
Francesco Avanzi, Hiroyuki Hirashima, Satoru Yamaguchi, Takafumi Katsushima, and Carlo De Michele
The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, https://doi.org/10.5194/tc-10-2013-2016, 2016
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We investigate capillary barriers and preferential flow in layered snow during nine cold laboratory experiments. The dynamics of each sample were replicated solving Richards equation within the 1-D multi-layer physically based SNOWPACK model. Results show that both processes affect the speed of water infiltration in stratified snow and are marked by a high degree of spatial variability at cm scale and complex 3-D patterns.
Carlo De Michele, Francesco Avanzi, Daniele Passoni, Riccardo Barzaghi, Livio Pinto, Paolo Dosso, Antonio Ghezzi, Roberto Gianatti, and Giacomo Della Vedova
The Cryosphere, 10, 511–522, https://doi.org/10.5194/tc-10-511-2016, https://doi.org/10.5194/tc-10-511-2016, 2016
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We investigate snow depth distribution at peak accumulation over a small Alpine area using photogrammetry-based surveys with a fixed wing unmanned aerial system. Results reveal that UAS estimations of point snow depth present an average difference with reference to manual measurements equal to -0.073 m. Moreover, in this case study snow depth standard deviation (hence coefficient of variation) increases with decreasing cell size, but it stabilizes for resolutions smaller than 1 m.
Z. Zheng, P. B. Kirchner, and R. C. Bales
The Cryosphere, 10, 257–269, https://doi.org/10.5194/tc-10-257-2016, https://doi.org/10.5194/tc-10-257-2016, 2016
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By analyzing high-resolution lidar products and using statistical methods, we quantified the snow depth dependency on elevation, slope and aspect of the terrain and also the surrounding vegetation in four catchment size sites in the southern Sierra Nevada during snow peak season. The relative importance of topographic and vegetation attributes varies with elevation and canopy, but all these attributes were found significant in affecting snow distribution in mountain basins.
P. B. Kirchner, R. C. Bales, N. P. Molotch, J. Flanagan, and Q. Guo
Hydrol. Earth Syst. Sci., 18, 4261–4275, https://doi.org/10.5194/hess-18-4261-2014, https://doi.org/10.5194/hess-18-4261-2014, 2014
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In this study we present results from LiDAR snow depth measurements made over 53 sq km and a 1600 m elevation gradient. We found a lapse rate of 15 cm accumulated snow depth and 6 cm SWE per 100 m in elevation until 3300 m, where depth sharply decreased. Residuals from this trend revealed the role of aspect and highlighted the importance of solar radiation and wind for snow distribution. Lastly, we compared LiDAR SWE estimations with four model estimates of SWE and total precipitation.
S. Masclin, M. M. Frey, W. F. Rogge, and R. C. Bales
Atmos. Chem. Phys., 13, 8857–8877, https://doi.org/10.5194/acp-13-8857-2013, https://doi.org/10.5194/acp-13-8857-2013, 2013
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Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
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Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
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Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
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On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
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Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression
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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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Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
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We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
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Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
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Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
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.
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.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-252, https://doi.org/10.5194/hess-2023-252, 2023
Revised manuscript accepted for HESS
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Long Short-Term Memory (LSTM) is a widely used machine learning model in hydrology. However, 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.
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.
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.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-143, https://doi.org/10.5194/hess-2023-143, 2023
Revised manuscript accepted for HESS
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Calibrating hydrological models with multiple objective functions enhances model robustness. By integrating spatially distributed snow information into the calibration process, the overall performance of the model can be enhanced without compromising the model outputs. In this study, HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (SPAtial Efficiency metric) alongside NSE and RMSE, with the aim of identifying the optimal calibration strategy.
Ricardo Mantilla, Morgan Fonley, and Nicolas Velasquez
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-187, https://doi.org/10.5194/hess-2023-187, 2023
Revised manuscript accepted for HESS
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle, however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator that a correct description of the small-scale runoff processes.
Fabio Ciulla and Charuleka Varadharajan
EGUsphere, https://doi.org/10.5194/egusphere-2023-1675, https://doi.org/10.5194/egusphere-2023-1675, 2023
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When studying the behavior of rivers, like their tendency to flood, it is useful to group them using the characteristics of their surrounding areas like geology, climate, land use and human influence. We developed a method that, in addition to this classification, also returns the relevant characteristics of each group and associates them to particular behaviors. In this way we better understand how rivers interact with the environment and can try to improve the predictions of future behaviors.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-186, https://doi.org/10.5194/hess-2023-186, 2023
Revised manuscript accepted for HESS
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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.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
EGUsphere, https://doi.org/10.5194/egusphere-2023-1322, https://doi.org/10.5194/egusphere-2023-1322, 2023
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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 is 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.
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.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-166, https://doi.org/10.5194/hess-2023-166, 2023
Revised manuscript accepted for HESS
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
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.
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.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-124, https://doi.org/10.5194/hess-2023-124, 2023
Revised manuscript accepted for HESS
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Are machine learning models able to produce reliable rainfall-runoff predictions and add enough benefits that justify the effort to implement these methods? This study covers a large set of Australian catchments (almost 500) comparing deep learning and traditional model results. The deep learning model matched or exceeded conceptual model performance for more than two-thirds of the study catchments, indicating the general viability of these models in a variety of catchments conditions.
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.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
EGUsphere, https://doi.org/10.5194/egusphere-2023-569, https://doi.org/10.5194/egusphere-2023-569, 2023
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling frameworks tested.
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.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-428, https://doi.org/10.5194/hess-2022-428, 2023
Revised manuscript accepted for HESS
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This study used the relationship between river water and air temperature to understand processes causing stream warming and predict how streams might respond to future climate warming. We found that the air-water relationship was diverse across sites and controlled largely by geology and snowmelt. Our findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate insensitive areas of the basin that should be preserved and protected.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-25, https://doi.org/10.5194/hess-2023-25, 2023
Revised manuscript accepted for HESS
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The study determines the value of water towards ecosystem services production in an agricultural watershed in Ontario, Canada. It uses a computer model and an economic valuation approach to determine how subsurface and surface water affect ecosystem services supply. The results show that subsurface water plays a critical role in maintaining ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Klaus Eckhardt
Hydrol. Earth Syst. Sci., 27, 495–499, https://doi.org/10.5194/hess-27-495-2023, https://doi.org/10.5194/hess-27-495-2023, 2023
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An important hydrological issue is to identify components of streamflow that react to precipitation with different degrees of attenuation and delay. From the multitude of methods that have been developed for this so-called hydrograph separation, a specific, frequently used one is singled out here. It is shown to be derived from plausible physical principles. This increases confidence in its results.
Beatrice Sabine Marti, Aidar Zhumabaev, and Tobias Siegfried
Hydrol. Earth Syst. Sci., 27, 319–330, https://doi.org/10.5194/hess-27-319-2023, https://doi.org/10.5194/hess-27-319-2023, 2023
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Numerical modelling is often used for climate impact studies in water resources management. It is, however, not yet highly accessible to many students of hydrology in Central Asia. One big hurdle for new learners is the preparation of relevant data prior to the actual modelling. We present a robust, open-source workflow and comprehensive teaching material that can be used by teachers and by students for self study.
Aniket Gupta, Alix Reverdy, Jean-Martial Cohard, Basile Hector, Marc Descloitres, Jean-Pierre Vandervaere, Catherine Coulaud, Romain Biron, Lucie Liger, Reed Maxwell, Jean-Gabriel Valay, and Didier Voisin
Hydrol. Earth Syst. Sci., 27, 191–212, https://doi.org/10.5194/hess-27-191-2023, https://doi.org/10.5194/hess-27-191-2023, 2023
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Patchy snow cover during spring impacts mountainous ecosystems on a large range of spatio-temporal scales. A hydrological model simulated such snow patchiness at 10 m resolution. Slope and orientation controls precipitation, radiation, and wind generate differences in snowmelt, subsurface storage, streamflow, and evapotranspiration. The snow patchiness increases the duration of the snowmelt to stream and subsurface storage, which sustains the plants and streamflow later in the summer.
Hendrik Rathjens, Jens Kiesel, Michael Winchell, Jeffrey Arnold, and Robin Sur
Hydrol. Earth Syst. Sci., 27, 159–167, https://doi.org/10.5194/hess-27-159-2023, https://doi.org/10.5194/hess-27-159-2023, 2023
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The SWAT model can simulate the transport of water-soluble chemicals through the landscape but neglects the transport through groundwater or agricultural tile drains. These transport pathways are, however, important to assess the amount of chemicals in streams. We added this capability to the model, which significantly improved the simulation. The representation of all transport pathways in the model enables watershed managers to develop robust strategies for reducing chemicals in streams.
Cited articles
Abatzoglou, J. T., Redmond, K. T., and Edwards, L. M.: Classification of
regional climate variability in the state of California, J. Appl. Meteorol. Clim., 48, 1527–1541, https://doi.org/10.1175/2009JAMC2062.1, 2009. a
Ackerly, D. D., Loarie, S. R., Cornwell, W. K., Weiss, S. B., Hamilton, H.,
Branciforte, R., and Kraft, N. J.: The geography of climate change:
Implications for conservation biogeography, Div. Distrib., 16, 476–487, https://doi.org/10.1111/j.1472-4642.2010.00654.x, 2010. a
Allerup, P., Madsen, H., and Vejen, F.: Correction of precipitation based on
off-site weather information, Atmos. Res., 53, 231–250,
https://doi.org/10.1016/S0169-8095(99)00051-4, 2000. a
Alvarez-Garreton, C., Pablo Boisier, J., Garreaud, R., Seibert, J., and Vis,
M.: Progressive water deficits during multiyear droughts in basins with long
hydrological memory in Chile, Hydrol. Earth Syst. Sci., 25, 429–446, https://doi.org/10.5194/hess-25-429-2021, 2021. a
Avanzi, F., Rungee, J., Maurer, T., Bales, R., Ma, Q., Glaser, S., and Conklin, M.: Climate elasticity of evapotranspiration shifts the water balance of Mediterranean climates during multi-year droughts, Hydrol. Earth Syst. Sci., 24, 4317–4337, https://doi.org/10.5194/hess-24-4317-2020, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t
Avanzi, F., Ercolani, G., Gabellani, S., Cremonese, E., Pogliotti, P., Filippa, G., Morra Di Cella, U., Ratto, S., Stevenin, H., Cauduro, M., and Juglair, S.: Learning about precipitation lapse rates from snow course data improves water balance modeling, Hydrol. Earth Syst. Sci., 25, 2109–2131,
https://doi.org/10.5194/hess-25-2109-2021, 2021. a, b
Bales, R. C., Guo, Q., Shen, D., McConnell, J. R., Du, G., Burkhart, J. F.,
Spikes, V. B., Hanna, E., and Cappelen, J.: Annual accumulation for
Greenland updated using ice core data developed during 2000–2006 and analysis of daily coastal meteorological data, J. Geophys. Res.-Atmos., 114, D06116, https://doi.org/10.1029/2008JD011208, 2009. a
Bales, R. C., Goulden, M. L., Hunsaker, C. T., Conklin, M. H., Hartsough, P. C., O'Geen, A. T., Hopmans, J. W., and Safeeq, M.: Mechanisms controlling
the impact of multi-year drought on mountain hydrology, Scient. Rep., 8, 1–8, https://doi.org/10.1038/s41598-017-19007-0, 2018. a, b, c, d, e, f, g, h
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. a, b, c
Bolger, B. L., Park, Y. J., Unger, A. J., and Sudicky, E. A.: Simulating the
pre-development hydrologic conditions in the San Joaquin Valley, California,
J. Hydrol., 411, 322–330, https://doi.org/10.1016/j.jhydrol.2011.10.013, 2011. a
Brown, L. R. and Bauer, M. L.: Effects of hydrologic infrastructure on flow
regimes of California's Central Valley rivers: Implications for fish populations, River Res. Appl., 26, 751–765, https://doi.org/10.1002/rra.1293, 2010. a
Chen, X., Alimohammadi, N., and Wang, D.: Modeling interannual variability of
seasonal evaporation and storage change based on the extended Budyko framework, Water Resour. Res., 49, 6067–6078, https://doi.org/10.1002/wrcr.20493, 2013. a
Coron, L., Andréassian, V., Perrin, C., Lerat, J., Vaze, J., Bourqui, M.,
and Hendrickx, F.: Crash testing hydrological models in contrasted climate
conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, 1–17, https://doi.org/10.1029/2011WR011721, 2012. a
Dai, A.: Increasing drought under global warming in observations and models, Nat. Clim. Change, 3, 52–58, https://doi.org/10.1038/nclimate1633, 2013. a
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor,
G. H., Curtis, J., and Pasteris, P. P.: Physiographically sensitive mapping
of climatological temperature and precipitation across the conterminous
United States, Int. J. Climatol., 28, 2031–2064, https://doi.org/10.1002/joc.1688, 2008. a, b
Dettinger, M. D. and Cayan, D. R.: Interseasonal covariability of Sierra Nevada streamflow and San Francisco Bay salinity, J. Hydrol., 277, 164–181, https://doi.org/10.1016/S0022-1694(03)00078-7, 2003. a
Ejeta, M. Z.: Validation of predicted meteorological drought in California
using analogous orbital geometries, Hydrol. Process., 28, 3703–3713, 2013. a
Ejeta, M. Z., Arora, S. K., Kadir, T., and Yin, H.: California Central Valley
Unimpaired Flow Data, Tech. rep., California Department of Water Resources,
Sacramento, CA, available at:
https://www.waterboards.ca.gov/waterrights/water_issues/programs/bay_delta/bay_delta_plan/water_quality_control_planning/docs/sjrf_spprtinfo/dwr_2007a.pdf
(last access: 16 July 2021), 2007. a, b
EROS Data Center: National Elevatoin Dataset, available at:
https://www.usgs.gov/core-science-systems/national-geospatial-program/national-map (last access: 17 July 2021), 1999. a
Fu, B.: On the Calculation of the Evaporation from Land Surface, Chinese J. Atmos. Sci., 5, 23–31, 1981. a
Gnann, S. J., Woods, R. A., and Howden, N. J.: Is There a Baseflow Budyko
Curve?, Water Resour. Res., 55, 2838–2855, https://doi.org/10.1029/2018WR024464, 2019. a
Goulden, M. L. and Bales, R. C.: Mountain runoff vulnerability to increased
evapotranspiration with vegetation expansion, P. Natl. Acad. Sci. USA, 111, 14071–14075, https://doi.org/10.1073/pnas.1319316111, 2014. a
Goulden, M. L. and Bales, R. C.: California forest die-off linked to multi-year deep soil drying in 2012–2015 drought, Nat. Geosci., 12, 632–637, https://doi.org/10.1038/s41561-019-0388-5, 2019. a, b, c, d
Goulden, M. L., Anderson, R. G., Bales, R. C., Kelly, A. E., Meadows, M., and
Winston, G. C.: Evapotranspiration along an elevation gradient in California's Sierra Nevada, J. Geophys. Res.-Biogeo., 117, 1–13, https://doi.org/10.1029/2012JG002027, 2012. a, b
Graf, A., Klosterhalfen, A., Arriga, N., Bernhofer, C., Bogena, H., Bornet, F., Brüggemann, N., Brümmer, C., Buchmann, N., Chi, J., Chipeaux, C.,
Cremonese, E., Cuntz, M., Dušek, J., El-Madany, T. S., Fares, S., Fischer, M., Foltýnová, L., Gharun, M., Ghiasi, S., Gielen, B.,
Gottschalk, P., Grünwald, T., Heinemann, G., Heinesch, B., Heliasz, M.,
Holst, J., Hörtnagl, L., Ibrom, A., Ingwersen, J., Jurasinski, G., Klatt, J., Knohl, A., Koebsch, F., Konopka, J., Korkiakoski, M., Kowalska, N., Kremer, P., Kruijt, B., Lafont, S., Léonard, J., De Ligne, A., Longdoz, B., Loustau, D., Magliulo, V., Mammarella, I., Manca, G., Mauder, M., Migliavacca, M., Mölder, M., Neirynck, J., Ney, P., Nilsson, M., Paul-Limoges, E., Peichl, M., Pitacco, A., Poyda, A., Rebmann, C., Roland,
M., Sachs, T., Schmidt, M., Schrader, F., Siebicke, L., Šigut, L., Tuittila, E. S., Varlagin, A., Vendrame, N., Vincke, C., Völksch, I., Weber, S., Wille, C., Wizemann, H. D., Zeeman, M., and Vereecken, H.: Altered energy partitioning across terrestrial ecosystems in the European drought year 2018: Energy partitioning in the drought 2018, Philos. T. Roy. Soc. B, 375, 1810, https://doi.org/10.1098/rstb.2019.0524, 2020. a
Greve, P., Gudmundsson, L., Orlowsky, B., and Seneviratne, S. I.: A
two-parameter Budyko function to represent conditions under which
evapotranspiration exceeds precipitation, Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, 2016. a
Groeneveld, D. P., Baugh, W. M., Sanderson, J. S., and Cooper, D. J.: Annual
groundwater evapotranspiration mapped from single satellite scenes, J. Hydrol., 344, 146–156, https://doi.org/10.1016/j.jhydrol.2007.07.002, 2007. a
Guan, B., Waliser, D. E., Ralph, F. M., Fetzer, E. J., and Neiman, P. J.:
Hydrometeorological characteristics of rain-on-snow events associated with
atmospheric rivers, Geophys. Res. Lett., 43, 2964–2973, https://doi.org/10.1002/2016GL067978, 2016. a
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of
the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
Hahm, W. J., Dralle, D. N., Rempe, D. M., Bryk, A. B., Thompson, S. E., Dawson, T. E., and Dietrich, W. E.: Low Subsurface Water Storage Capacity Relative to Annual Rainfall Decouples Mediterranean Plant Productivity and Water Use From Rainfall Variability, Geophys. Res. Lett., 46, 6544–6553, https://doi.org/10.1029/2019GL083294, 2019a. a
Hahm, W. J., Rempe, D. M., Dralle, D. N., Dawson, T. E., Lovill, S. M., Bryk,
A. B., Bish, D. L., Schieber, J., and Dietrich, W. E.: Lithologically
Controlled Subsurface Critical Zone Thickness and Water Storage Capacity
Determine Regional Plant Community Composition, Water Resour. Res., 55, 3028–3055, https://doi.org/10.1029/2018WR023760, 2019b. a
Hamon, W.: Computation of direct runoff amounts from storm rainfall, Int. Assoc. Hydrolog. Sci. Publ., 63, 52–62, 1963. a
He, M., Russo, M., and Anderson, M.: Hydroclimatic characteristics of the
2012–2015 California drought from an operational perspective, Climate, 5,
1987–1992, https://doi.org/10.3390/cli5010005, 2017. a, b
Hofste, R. W., Reig, P., and Schleifer, L.: 17 Countries, Home to One-Quarter
of the World's Population, Face Extremely High Water Stress, Tech. rep.,
World Resources Institute, Washington, DC, available at:
https://www.wri.org/blog/2019/08/17-countries-home-one-quarter-world-population-face-
extremely-high-water-stress (last access: 13 October 2020), 2019. a
Hrachowitz, M. and Clark, M. P.: The complementary merits of competing modelling philosophies in hydrology, Hydrol. Earth Syst. Sci., 21, 3953–3973, https://doi.org/10.5194/hess-21-3953-2017, 2017. a
Huang, G. and Kadir, T.: Estimates of Natural and Unimpaired Flows for the
Central Valley of California: Water Years 1922–2014, Tech. rep., California
Department of Water Resources, Sacramento, CA, available at:
https://www.waterboards.ca.gov/waterrights/water_issues/programs/bay_delta/california_waterfix/exhibits/docs/petitioners_exhibit/dwr/part2_rebuttal/dwr_1384.pdf
(last access: 16 July 2021), 2016. a, b
Huang, S., Li, P., Huang, Q., Leng, G., Hou, B., and Ma, L.: The propagation
from meteorological to hydrological drought and its potential influence factors, J. Hydrol., 547, 184–195, https://doi.org/10.1016/j.jhydrol.2017.01.041, 2017. a
Ishida, K., Gorguner, M., Ercan, A., Trinh, T., and Kavvas, M. L.: Trend
analysis of watershed-scale precipitation over Northern California by means of dynamically-downscaled CMIP5 future climate projections, Sci. Total Environ., 592, 12–24, https://doi.org/10.1016/j.scitotenv.2017.03.086, 2017. a
Jaramillo, F., Cory, N., Arheimer, B., Laudon, H., Van Der Velde, Y., Hasper,
T. B., Teutschbein, C., and Uddling, J.: Dominant effect of increasing forest biomass on evapotranspiration: Interpretations of movement in Budyko space, Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, 2018. a, b, c, d
Kirchner, J. W.: Catchments as simple dynamical systems: Catchment
characterization, rainfall-runoff modeling, and doing hydrology backward,
Water Resour. Res., 45, 2429, https://doi.org/10.1029/2008WR006912, 2009. a
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube
basin under an ensemble of climate change scenarios, J. Hydrol., 424–425, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012. a
Li, D., Pan, M., Cong, Z., Zhang, L., and Wood, E.: Vegetation control on water and energy balance within the Budyko framework, Water Resour. Res., 49, 969–976, https://doi.org/10.1002/wrcr.20107, 2013. a, b
Li, Y., Liu, C., Yu, W., Tian, D., and Bai, P.: Response of streamflow to
environmental changes: A Budyko-type analysis based on 144 river basins over
China, Sci. Total Environ., 664, 824–833, https://doi.org/10.1016/j.scitotenv.2019.02.011, 2019. a
Liu, J., Zhang, Q., Singh, V. P., and Shi, P.: Contribution of multiple
climatic variables and human activities to streamflow changes across China,
J. Hydrol., 545, 145–162, https://doi.org/10.1016/j.jhydrol.2016.12.016, 2017. a
Lundquist, J. D., Hughes, M., Henn, B., Gutmann, E. D., Livneh, B., Dozier, J., and Neiman, P.: High-elevation precipitation patterns: Using snow
measurements to assess daily gridded datasets across the Sierra Nevada, California, J. Hydrometeorol., 16, 1773–1792, https://doi.org/10.1175/JHM-D-15-0019.1, 2015. a
Ma, Y., Zhang, Y., Yang, D., and Farhan, S. B.: Precipitation bias variability versus various gauges under different climatic conditions over the Third Pole Environment (TPE) region, Int. J. Climatol., 35, 1201–1211, https://doi.org/10.1002/joc.4045, 2015. a
Masih, I., Maskey, S., Mussá, F. E., and Trambauer, P.: A review of droughts on the African continent: A geospatial and long-term perspective, Hydrol. Earth Syst. Sci., 18, 3635–3649, https://doi.org/10.5194/hess-18-3635-2014, 2014. a
Maskey, S. and Trambauer, P.: Hydrological Modeling for Drought Assessment,
Elsevier Inc., Delft, the Netherlands, https://doi.org/10.1016/B978-0-12-394846-5.00010-2, 2015. a
Mastrotheodoros, T., Pappas, C., Molnar, P., Burlando, P., Manoli, G., Parajka, J., Rigon, R., Szeles, B., Bottazzi, M., Hadjidoukas, P., and Fatichi, S.: More green and less blue water in the Alps during warmer summers, Nat. Clim. Change, 10, 155–161, https://doi.org/10.1038/s41558-019-0676-5, 2020. a, b
McVicar, T. R., Roderick, M. L., Donohue, R. J., and Van Niel, T. G.: Less
bluster ahead? ecohydrological implications of global trends of terrestrial
near-surface wind speeds, Ecohydrology, 5, 381–388, https://doi.org/10.1002/eco.1298,
2012. a
Mernild, S. H., Hanna, E., McConnell, J. R., Sigl, M., Beckerman, A. P., Yde,
J. C., Cappelen, J., Malmros, J. K., and Steffen, K.: Greenland precipitation trends in a long-term instrumental climate context (1890–2012): evaluation of coastal and ice core records, Int. J. Climatol., 35, 303–320, https://doi.org/10.1002/joc.3986, 2015. a
Moussa, R. and Lhomme, J. P.: The Budyko functions under non-steady-state
conditions, Hydrol. Earth Syst. Sci., 20, 4867–4879,
https://doi.org/10.5194/hess-20-4867-2016, 2016. a
Ning, T., Li, Z., and Liu, W.: Vegetation dynamics and climate seasonality
jointly control the interannual catchment water balance in the Loess Plateau
under the Budyko framework, Hydrol. Earth Syst. Sci., 21, 1515–1526, https://doi.org/10.5194/hess-21-1515-2017, 2017. a
Ning, T., Zhou, S., Chang, F., Shen, H., Li, Z., and Liu, W.: Interaction of
vegetation, climate and topography on evapotranspiration modelling at different time scales within the Budyko framework, Agr. Forest Meteorol., 275, 59–68, https://doi.org/10.1016/j.agrformet.2019.05.001, 2019. a, b, c, d, e
Ning, T., Li, Z., Feng, Q., Chen, W., and Li, Z.: Effects of forest cover change on catchment evapotranspiration variation in China, Hydrol. Process., 34, 2219–2228, https://doi.org/10.1002/hyp.13719, 2020. a
O'Grady, A. P., Carter, J. L., and Bruce, J.: Can we predict groundwater
discharge from terrestrial ecosystems using existing eco-hydrological concepts?, Hydrol. Earth Syst. Sci., 15, 3731–3739, https://doi.org/10.5194/hess-15-3731-2011, 2011. a
Oroza, C. A., Bales, R. C., Stacy, E. M., Zheng, Z., and Glaser, S. D.:
Long-Term Variability of Soil Moisture in the Southern Sierra: Measurement
and Prediction, Vadose Zone J., 17, 170178, https://doi.org/10.2136/vzj2017.10.0178, 2018. a, b
Oudin, L., Andréassian, V., Lerat, J., and Michel, C.: Has land cover a
significant impact on mean annual streamflow? An international assessment
using 1508 catchments, J. Hydrol., 357, 303–316, https://doi.org/10.1016/j.jhydrol.2008.05.021, 2008. a
Peterson, T. J., Saft, M., Peel, M., and John, A.: Watersheds may not recover
from drought, Science, 372, 745–749, https://doi.org/10.1126/science.abd5085, 2021. a
Petheram, C., Potter, N., Vaze, J., Chiew, F., and Zhang, L.: Towards better
understanding of changes in rainfall-runoff relationships during the recent
drought in south-eastern Australia, in: MODSIM 2011 – 19th International
Congress on Modelling and Simulation – Sustaining Our Future: Understanding
and Living with Uncertainty, December 2011, 3622–3628, available at: https://www.mssanz.org.au/modsim2011/I6/petheram.pdf (last access: 9 October 2020), 2011. a, b
Pike, J. G.: The estimation of annual run-off from meteorological data in a
tropical climate, J. Hydrol., 2, 116–123, https://doi.org/10.1016/0022-1694(64)90022-8, 1964. a, b
Potter, N. J., Petheram, C., and Zhang, L.: Sensitivity of streamflow to
rainfall and temperature in south-eastern Australia during the Millennium
drought, in: MODSIM 2011 – 19th International Congress on Modelling and
Simulation – Sustaining Our Future: Understanding and Living with Uncertainty, November 2014, 3636–3642, available at: https://www.mssanz.org.au/modsim2011/I6/potter.pdf (last access: 10 October 2020), 2011. a, b
Raleigh, M. S. and Lundquist, J. D.: Comparing and combining SWE estimates
from the SNOW-17 model using PRISM and SWE reconstruction, Water Resour. Res., 48, 1–16, https://doi.org/10.1029/2011WR010542, 2012. a
Rana, G. and Katerji, N.: Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: A review, Eur. J. Agron., 13, 125–153, https://doi.org/10.1016/S1161-0301(00)00070-8, 2000. a
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S., Fischer,
A. P., Black, J., Thériault, J. M., Kucera, P., Gochis, D., Smith, C.,
Nitu, R., Hall, M., Ikeda, K., and Gutmann, E.: How well are we measuring
snow: The NOAA/FAA/NCAR winter precipitation test bed, B. Am. Meteorol. Soc., 93, 811–829, https://doi.org/10.1175/BAMS-D-11-00052.1, 2012. a, b
Roche, J. W., Goulden, M. L., and Bales, R. C.: Estimating evapotranspiration
change due to forest treatment and fire at the basin scale in the Sierra
Nevada, California, Ecohydrology, 11, e1978, https://doi.org/10.1002/eco.1978, 2018. a
Roderick, M. L. and Farquhar, G. D.: A simple framework for relating
variations in runoff to variations in climatic conditions and catchment
properties, Water Resour. Res., 47, 1–11, https://doi.org/10.1029/2010WR009826, 2011. a
Shao, Q., Traylen, A., and Zhang, L.: Nonparametric method for estimating the
effects of climatic and catchment characteristics on mean annual
evapotranspiration, Water Resour. Res., 48, 1–13, https://doi.org/10.1029/2010WR009610, 2012. a
Shen, Q., Cong, Z., and Lei, H.: Evaluating the impact of climate and
underlying surface change on runoff within the Budyko framework: A study
across 224 catchments in China, J. Hydrol., 554, 251–262,
https://doi.org/10.1016/j.jhydrol.2017.09.023, 2017. a, b
Tague, C. and Grant, G. E.: Groundwater dynamics mediate low-flow response to
global warming in snow-dominated alpine regions, Water Resour. Res., 45, 1–12, https://doi.org/10.1029/2008WR007179, 2009. a
Teuling, A. J., Van Loon, A. F., Seneviratne, S. I., Lehner, I., Aubinet, M.,
Heinesch, B., Bernhofer, C., Grünwald, T., Prasse, H., and Spank, U.:
Evapotranspiration amplifies European summer drought, Geophys. Res. Lett., 40, 2071–2075, https://doi.org/10.1002/grl.50495, 2013. a, b, c
Thomas, H. A.: Improved methods for national water assessment, water resources contract: WR15249270, Tech. rep., US Geological Survey,
https://doi.org/10.3133/70046351, 1981. a, b
Trenberth, K. E., Dai, A., van der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., and Sheffield, J.: Global warming and changes in drought,
Nat. Clim. Change, 4, 17–22, https://doi.org/10.1038/nclimate2067, 2014. a
Troch, P. A., Lahmers, T., Meira, A., Mukherjee, R., Pedersen, J. W., Roy, T., and Valdés-Pineda, R.: Catchment coevolution: A useful framework for
improving predictions of hydrological change?, Water Resour. Res., 51,
4903–4922, https://doi.org/10.1002/2015WR017032, 2015. a, b
Van Loon, A. F.: Hydrological drought explained, Wiley Interdisciplin. Rev.: Water, 2, 359–392, https://doi.org/10.1002/wat2.1085, 2015. a
Vaze, J., Post, D. A., Chiew, F. H. S., Perraud, J.-M., Viney, N. R., and Teng, J.: Climate non-stationarity – Validity of calibrated rainfall–runoff
models for use in climate change studies, J. Hydrol., 394, 447–457, https://doi.org/10.1016/j.jhydrol.2010.09.018, 2010. a
Wang, D.: Evaluating interannual water storage changes at watersheds in
Illinois based on long-term soil moisture and groundwater level data, Water
Resour. Res., 48, 1–12, https://doi.org/10.1029/2011WR010759, 2012. a
Wang, D. and Alimohammadi, N.: Responses of annual runoff, evaporation, and
storage change to climate variability at the watershed scale, Water Resour. Res., 48, W05546, https://doi.org/10.1029/2011WR011444, 2012. a
Wang, D. and Hejazi, M.: Quantifying the relative contribution of the climate
and direct human impacts on mean annual streamflow in the contiguous United
States, Water Resour. Res., 47, W00J12, https://doi.org/10.1029/2010WR010283, 2011. a
Wang, D. and Tang, Y.: A one-parameter Budyko model for water balance captures emergent behavior in darwinian hydrologic models, Geophys. Res. Lett., 41, 4569–4577, https://doi.org/10.1002/2014GL060509, 2014. a
Wang, S., Pan, M., Mu, Q., Shi, X., Mao, J., Brümmer, C., Jassal, R. S.,
Krishnan, P., Li, J., and Andrew Black, T.: Comparing evapotranspiration
from eddy covariance measurements, water budgets, remote sensing, and land
surface models over Canada, J. Hydrometeorol., 16, 1540–1560,
https://doi.org/10.1175/JHM-D-14-0189.1, 2015. a
Williams, C. A., Reichstein, M., Buchmann, N., Baldocchi, D., Beer, C.,
Schwalm, C., Wohlfahrt, G., Hasler, N., Bernhofer, C., Foken, T., Papale, D.,
Schymanski, S., and Schaefer, K.: Climate and vegetation controls on the
surface water balance: Synthesis of evapotranspiration measured across a
global network of flux towers, Water Resour. Res., 48, 1–13, https://doi.org/10.1029/2011WR011586, 2012. a
Wilson, K. B. and Baldocchi, D. D.: Seasonal and interannual variability of
energy fluxes over a broadleaved temperate deciduous forest in North America, Agr. Forest Meteorol., 100, 1–18, https://doi.org/10.1016/S0168-1923(99)00088-X, 2000. a
Woodhouse, C. A., Meko, D. M., MacDonald, G. M., Stahle, D. W., and Cook, E. R.: A 1,200-year perspective of 21st century drought in southwestern North America, P. Natl. Acad. Sci. USA, 107, 21283–21288, https://doi.org/10.1073/pnas.0911197107, 2010. a, b
Yang, D., Ishida, S., Goodison, B. E., and Gunther, T.: Bias correction of
daily precipitation measurements for Greenland, J. Geophys. Res., 104, 6171–6181, https://doi.org/10.1029/1998JD200110, 1999. a
Yang, D., Sun, F., Liu, Z., Cong, Z., Ni, G., and Lei, Z.: Analyzing spatial
and temporal variability of annual water-energy balance in nonhumid regions
of China using the Budyko hypothesis, Water Resour. Res., 43, 1–12,
https://doi.org/10.1029/2006WR005224, 2007. a, b, c
Yang, D., Shao, W., Yeh, P. J., Yang, H., Kanae, S., and Oki, T.: Impact of
vegetation coverage on regional water balance in the nonhumid regions of China, Water Resour. Res., 45, 1–13, https://doi.org/10.1029/2008WR006948, 2009. a, b
Zeff, H. B., Hamilton, A. L., Malek, K., Herman, J. D., Cohen, J. S.,
Medellin-Azuara, J., Reed, P. M., and Characklis, G. W.: California's
food-energy-water system: An open source simulation model of adaptive surface
and groundwater management in the Central Valley, Environ. Model. Softw., 141, 105052, https://doi.org/10.1016/j.envsoft.2021.105052, 2021.
a
Zhang, L., Dawes, W. R., and Walker, G. R.: Response of mean annual
evapotranspiration to vegetation changes at catchment scale, Water Resour. Res., 37, 701–708, https://doi.org/10.1029/2000WR900325, 2001. a, b, c
Zhang, L., Hickel, K., Dawes, W. R., Chiew, F. H., Western, A. W., and Briggs, P. R.: A rational function approach for estimating mean annual
evapotranspiration, Water Resour. Res., 40, 1–14, https://doi.org/10.1029/2003WR002710, 2004. a, b
Zhang, L., Potter, N., Hickel, K., Zhang, Y., and Shao, Q.: Water balance
modeling over variable time scales based on the Budyko framework – Model
development and testing, J. Hydrol., 360, 117–131, https://doi.org/10.1016/j.jhydrol.2008.07.021, 2008. a, b
Zhang, S., Yang, H., Yang, D., and Jayawardena, A. W.: Quantifying the effect
of vegetation change on the regional water balance within the Budyko framework, Geophys. Res. Lett., 43, 1140–1148, https://doi.org/10.1002/2015GL066952, 2016. a, b
Zhang, X., Dong, Q., Cheng, L., and Xia, J.: A Budyko-based framework for
quantifying the impacts of aridity index and other factors on annual runoff,
J. Hydrol., 579, 124224, https://doi.org/10.1016/J.JHYDROL.2019.124224, 2019. a
Zhang, Z., Glaser, S., Bales, R., Conklin, M., Rice, R., and Marks, D.: Insights into mountain precipitation and snowpack from a basin-scale
wireless-sensor network, Water Resour. Res., 53, 6626–6641,
https://doi.org/10.1002/2016WR018825, 2017. a
Zhou, J., Wang, Y., Su, B., Wang, A., Tao, H., Zhai, J., Kundzewicz, Z. W., and Jiang, T.: Choice of potential evapotranspiration formulas influences
drought assessment: A case study in China, Atmos. Res., 242, 104979, https://doi.org/10.1016/j.atmosres.2020.104979, 2020. a
Short summary
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.
Predicting how much water will end up in rivers is more difficult during droughts because the...
