Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2439-2019
© Author(s) 2019. 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-23-2439-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 May 2019
Research article |
| 21 May 2019
| 21 May 2019
Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska
International Arctic Research Center, University of Alaska Fairbanks,
Fairbanks, Alaska, 99775, USA
Water and Environmental Research Center, University of Alaska
Fairbanks, Fairbanks, Alaska, 99775, USA
current address: Earth and Environmental Sciences, Los Alamos
National Lab, Los Alamos, NM, 87545, USA
Jessica E. Cherry
International Arctic Research Center, University of Alaska Fairbanks,
Fairbanks, Alaska, 99775, USA
Water and Environmental Research Center, University of Alaska
Fairbanks, Fairbanks, Alaska, 99775, USA
Alaska Pacific River Forecast Center, Anchorage, Alaska, 99502, USA
Ben Balk
Deltares USA, Silver Spring, Maryland, 20910, USA
Scott Lindsey
Alaska Pacific River Forecast Center, Anchorage, Alaska, 99502, USA
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Nathan Alec Conroy, Jeffrey M. Heikoop, Emma Lathrop, Dea Musa, Brent D. Newman, Chonggang Xu, Rachael E. McCaully, Carli A. Arendt, Verity G. Salmon, Amy Breen, Vladimir Romanovsky, Katrina E. Bennett, Cathy J. Wilson, and Stan D. Wullschleger
The Cryosphere, 17, 3987–4006, https://doi.org/10.5194/tc-17-3987-2023, https://doi.org/10.5194/tc-17-3987-2023, 2023
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This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
Ian Shirley, Sebastian Uhlemann, John Peterson, Katrina Bennett, Susan S. Hubbard, and Baptiste Dafflon
EGUsphere, https://doi.org/10.5194/egusphere-2023-968, https://doi.org/10.5194/egusphere-2023-968, 2023
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Snow depth has a strong impact on soil temperatures and carbon cycling in the arctic. Because of this, we want to understand why snow is deeper in some places than others. Using cameras mounted on a drone, we mapped snow depth, vegetation height, and elevation across a watershed in Alaska. In this paper, we develop novel techniques using image processing and machine learning to characterize the influence of topography and shrubs on snow depth in the watershed.
Xiang Huang, Charles J. Abolt, and Katrina E. Bennett
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-8, https://doi.org/10.5194/tc-2023-8, 2023
Manuscript not accepted for further review
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Near-surface humidity is a sensitive parameter for predicting snow depth. Greater values of the relative humidity are obtained if the saturation vapor pressure was calculated with over-ice correction compared to without during the winter. During the summer thawing period, the choice of whether or not to employ an over-ice correction corresponds to significant variability in simulated thaw depths.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
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In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Dylan R. Harp, Vitaly Zlotnik, Charles J. Abolt, Bob Busey, Sofia T. Avendaño, Brent D. Newman, Adam L. Atchley, Elchin Jafarov, Cathy J. Wilson, and Katrina E. Bennett
The Cryosphere, 15, 4005–4029, https://doi.org/10.5194/tc-15-4005-2021, https://doi.org/10.5194/tc-15-4005-2021, 2021
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Polygon-shaped landforms present in relatively flat Arctic tundra result in complex landscape-scale water drainage. The drainage pathways and the time to transition from inundated conditions to drained have important implications for heat and carbon transport. Using fundamental hydrologic principles, we investigate the drainage pathways and timing of individual polygons, providing insights into the effects of polygon geometry and preferential flow direction on drainage pathways and timing.
Katrina E. Bennett, Theodore J. Bohn, Kurt Solander, Nathan G. McDowell, Chonggang Xu, Enrique Vivoni, and Richard S. Middleton
Hydrol. Earth Syst. Sci., 22, 709–725, https://doi.org/10.5194/hess-22-709-2018, https://doi.org/10.5194/hess-22-709-2018, 2018
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We applied the Variable Infiltration Capacity hydrologic model to examine scenarios of change under climate and landscape disturbances in the San Juan River basin, a major sub-watershed of the Colorado River basin. Climate change coupled with landscape disturbance leads to reduced streamflow in the San Juan River basin. Disturbances are expected to be widespread in this region. Therefore, accounting for these changes within the context of climate change is imperative for water resource planning.
Randal D. Koster, Alan K. Betts, Paul A. Dirmeyer, Marc Bierkens, Katrina E. Bennett, Stephen J. Déry, Jason P. Evans, Rong Fu, Felipe Hernandez, L. Ruby Leung, Xu Liang, Muhammad Masood, Hubert Savenije, Guiling Wang, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 3777–3798, https://doi.org/10.5194/hess-21-3777-2017, https://doi.org/10.5194/hess-21-3777-2017, 2017
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Large-scale hydrological variability can affect society in profound ways; floods and droughts, for example, often cause major damage and hardship. A recent gathering of hydrologists at a symposium to honor the career of Professor Eric Wood motivates the present survey of recent research on this variability. The surveyed literature and the illustrative examples provided in the paper show that research into hydrological variability continues to be strong, vibrant, and multifaceted.
Martyn P. Clark, Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard
Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, https://doi.org/10.5194/hess-21-3427-2017, 2017
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The diversity in hydrologic models has led to controversy surrounding the “correct” approach to hydrologic modeling. In this paper we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs.
Nathan Alec Conroy, Jeffrey M. Heikoop, Emma Lathrop, Dea Musa, Brent D. Newman, Chonggang Xu, Rachael E. McCaully, Carli A. Arendt, Verity G. Salmon, Amy Breen, Vladimir Romanovsky, Katrina E. Bennett, Cathy J. Wilson, and Stan D. Wullschleger
The Cryosphere, 17, 3987–4006, https://doi.org/10.5194/tc-17-3987-2023, https://doi.org/10.5194/tc-17-3987-2023, 2023
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This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
Ian Shirley, Sebastian Uhlemann, John Peterson, Katrina Bennett, Susan S. Hubbard, and Baptiste Dafflon
EGUsphere, https://doi.org/10.5194/egusphere-2023-968, https://doi.org/10.5194/egusphere-2023-968, 2023
Preprint archived
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Snow depth has a strong impact on soil temperatures and carbon cycling in the arctic. Because of this, we want to understand why snow is deeper in some places than others. Using cameras mounted on a drone, we mapped snow depth, vegetation height, and elevation across a watershed in Alaska. In this paper, we develop novel techniques using image processing and machine learning to characterize the influence of topography and shrubs on snow depth in the watershed.
Xiang Huang, Charles J. Abolt, and Katrina E. Bennett
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-8, https://doi.org/10.5194/tc-2023-8, 2023
Manuscript not accepted for further review
Short summary
Short summary
Near-surface humidity is a sensitive parameter for predicting snow depth. Greater values of the relative humidity are obtained if the saturation vapor pressure was calculated with over-ice correction compared to without during the winter. During the summer thawing period, the choice of whether or not to employ an over-ice correction corresponds to significant variability in simulated thaw depths.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
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In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Dylan R. Harp, Vitaly Zlotnik, Charles J. Abolt, Bob Busey, Sofia T. Avendaño, Brent D. Newman, Adam L. Atchley, Elchin Jafarov, Cathy J. Wilson, and Katrina E. Bennett
The Cryosphere, 15, 4005–4029, https://doi.org/10.5194/tc-15-4005-2021, https://doi.org/10.5194/tc-15-4005-2021, 2021
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Polygon-shaped landforms present in relatively flat Arctic tundra result in complex landscape-scale water drainage. The drainage pathways and the time to transition from inundated conditions to drained have important implications for heat and carbon transport. Using fundamental hydrologic principles, we investigate the drainage pathways and timing of individual polygons, providing insights into the effects of polygon geometry and preferential flow direction on drainage pathways and timing.
Christopher D. Arp, Jessica E. Cherry, Dana R. N. Brown, Allen C. Bondurant, and Karen L. Endres
The Cryosphere, 14, 3595–3609, https://doi.org/10.5194/tc-14-3595-2020, https://doi.org/10.5194/tc-14-3595-2020, 2020
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River and lake ice thickens at varying rates geographically and from year to year. We took a closer look at ice growth across a large geographic region experiencing rapid climate change, the State of Alaska, USA. Slower ice growth was most pronounced in northern Alaskan lakes over the last 60 years. Western and interior Alaska ice showed more variability in thickness and safe travel duration. This analysis provides a comprehensive evaluation of changing freshwater ice in Alaska.
Katrina E. Bennett, Theodore J. Bohn, Kurt Solander, Nathan G. McDowell, Chonggang Xu, Enrique Vivoni, and Richard S. Middleton
Hydrol. Earth Syst. Sci., 22, 709–725, https://doi.org/10.5194/hess-22-709-2018, https://doi.org/10.5194/hess-22-709-2018, 2018
Short summary
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We applied the Variable Infiltration Capacity hydrologic model to examine scenarios of change under climate and landscape disturbances in the San Juan River basin, a major sub-watershed of the Colorado River basin. Climate change coupled with landscape disturbance leads to reduced streamflow in the San Juan River basin. Disturbances are expected to be widespread in this region. Therefore, accounting for these changes within the context of climate change is imperative for water resource planning.
Randal D. Koster, Alan K. Betts, Paul A. Dirmeyer, Marc Bierkens, Katrina E. Bennett, Stephen J. Déry, Jason P. Evans, Rong Fu, Felipe Hernandez, L. Ruby Leung, Xu Liang, Muhammad Masood, Hubert Savenije, Guiling Wang, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 3777–3798, https://doi.org/10.5194/hess-21-3777-2017, https://doi.org/10.5194/hess-21-3777-2017, 2017
Short summary
Short summary
Large-scale hydrological variability can affect society in profound ways; floods and droughts, for example, often cause major damage and hardship. A recent gathering of hydrologists at a symposium to honor the career of Professor Eric Wood motivates the present survey of recent research on this variability. The surveyed literature and the illustrative examples provided in the paper show that research into hydrological variability continues to be strong, vibrant, and multifaceted.
Martyn P. Clark, Marc F. P. Bierkens, Luis Samaniego, Ross A. Woods, Remko Uijlenhoet, Katrina E. Bennett, Valentijn R. N. Pauwels, Xitian Cai, Andrew W. Wood, and Christa D. Peters-Lidard
Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, https://doi.org/10.5194/hess-21-3427-2017, 2017
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The diversity in hydrologic models has led to controversy surrounding the “correct” approach to hydrologic modeling. In this paper we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, summarize modeling advances that address these challenges, and define outstanding research needs.
Jessica E. Cherry, Corrie Knapp, Sarah Trainor, Andrea J. Ray, Molly Tedesche, and Susan Walker
Hydrol. Earth Syst. Sci., 21, 133–151, https://doi.org/10.5194/hess-21-133-2017, https://doi.org/10.5194/hess-21-133-2017, 2017
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We know that climate is changing quickly in the Far North (the Arctic and sub-Arctic). Hydropower continues to grow in this region because water resources are perceived to be plentiful. However, with changes in glacier extent and permafrost, and more extreme events, will those resources prove reliable into the future? This study amasses the evidence that quantitative hydrology modeling and uncertainty assessment have matured to the point where they should be used in water resource planning.
Y. Y. Kontar, U. S. Bhatt, S. D. Lindsey, E. W. Plumb, and R. L. Thoman
Proc. IAHS, 369, 13–17, https://doi.org/10.5194/piahs-369-13-2015, https://doi.org/10.5194/piahs-369-13-2015, 2015
R. L. Herman, J. E. Cherry, J. Young, J. M. Welker, D. Noone, S. S. Kulawik, and J. Worden
Atmos. Meas. Tech., 7, 3127–3138, https://doi.org/10.5194/amt-7-3127-2014, https://doi.org/10.5194/amt-7-3127-2014, 2014
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Satellite data help estimate groundwater depletion, but earlier assessments missed mass loss from river sediment. In the Ganges–Brahmaputra–Meghna (GBM) river system, sediment accounts for 4 % of the depletion. Correcting for sediment in the GBM mountains reduces estimated depletion by 14 %. It's important to note that the Himalayas' uplift may offset some sediment-induced mass loss. This understanding is vital for accurate water storage trend assessments and sustainable groundwater management.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
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Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Eliot Sicaud, Daniel Fortier, Jean-Pierre Dedieu, and Jan Franssen
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Jingkai Xie, Yue-Ping Xu, Hongjie Yu, Yan Huang, and Yuxue Guo
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Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers around the world. In this study, we propose a new index incorporating satellite observations combined with meteorological data to monitor extreme flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The conclusions drawn from this study provide important implications for flood hazard prevention and water resource management over this region.
Johannes Larson, William Lidberg, Anneli M. Ågren, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 26, 4837–4851, https://doi.org/10.5194/hess-26-4837-2022, https://doi.org/10.5194/hess-26-4837-2022, 2022
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Terrain indices constitute a good candidate for modelling the spatial variation of soil moisture conditions in many landscapes. In this study, we evaluate nine terrain indices on varying DEM resolution and user-defined thresholds with validation using an extensive field soil moisture class inventory. We demonstrate the importance of field validation for selecting the appropriate DEM resolution and user-defined thresholds and that failing to do so can result in ambiguous and incorrect results.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
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This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
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Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
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This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Gopal Penny, Zubair A. Dar, and Marc F. Müller
Hydrol. Earth Syst. Sci., 26, 375–395, https://doi.org/10.5194/hess-26-375-2022, https://doi.org/10.5194/hess-26-375-2022, 2022
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We develop an empirical approach to attribute declining streamflow in the Upper Jhelum watershed, a key subwatershed of the transboundary Indus basin. We find that a loss of streamflow since the year 2000 resulted primarily due to interactions among vegetation and groundwater in response to climate rather than local changes in land use, revealing the climate sensitivity of this Himalayan watershed.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 2021
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Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
Ulrike Falk and Adrián Silva-Busso
Hydrol. Earth Syst. Sci., 25, 3227–3244, https://doi.org/10.5194/hess-25-3227-2021, https://doi.org/10.5194/hess-25-3227-2021, 2021
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This paper focuses on the groundwater flow aspects of a small hydrological catchment at the northern tip of the Antarctic Peninsula. This region has experienced drastic climatological changes in the recent past. The basin is representative for the rugged coastline of the peninsula. It is discussed as a case study for possible future evolution of similar basins further south. Results include a quantitative analysis of glacial and groundwater contribution to total discharge into coastal waters.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
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We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Mo Zhang, Wenjiao Shi, and Ziwei Xu
Hydrol. Earth Syst. Sci., 24, 2505–2526, https://doi.org/10.5194/hess-24-2505-2020, https://doi.org/10.5194/hess-24-2505-2020, 2020
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We systematically compared 45 models for direct and indirect soil texture classification and soil particle size fraction interpolation based on 5 machine-learning models and 3 log-ratio transformation methods. Random forest showed powerful performance in both classification of imbalanced data and regression assessment. Extreme gradient boosting is more meaningful and computationally efficient when dealing with large data sets. The indirect classification and log-ratio methods are recommended.
Florian U. Jehn, Konrad Bestian, Lutz Breuer, Philipp Kraft, and Tobias Houska
Hydrol. Earth Syst. Sci., 24, 1081–1100, https://doi.org/10.5194/hess-24-1081-2020, https://doi.org/10.5194/hess-24-1081-2020, 2020
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We grouped 643 rivers from the United States into 10 behavioral groups based on their hydrological behavior (e.g., how much water they transport overall). Those groups are aligned with the ecoregions in the United States. Depending on the groups’ location and other characteristics, either snow, aridity or seasonality is most important for the behavior of the rivers in a group. We also find that very similar river behavior can be found in rivers far apart and with different characteristics.
Cecile M. M. Kittel, Karina Nielsen, Christian Tøttrup, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 22, 1453–1472, https://doi.org/10.5194/hess-22-1453-2018, https://doi.org/10.5194/hess-22-1453-2018, 2018
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In this study, we integrate free, global Earth observations in a user-friendly and flexible model to reliably characterize an otherwise unmonitored river basin. The proposed model is the best baseline characterization of the Ogooué basin in light of available observations. Furthermore, the study shows the potential of using new, publicly available Earth observations and a suitable model structure to obtain new information in poorly monitored or remote areas and to support user requirements.
Gopal Penny, Veena Srinivasan, Iryna Dronova, Sharachchandra Lele, and Sally Thompson
Hydrol. Earth Syst. Sci., 22, 595–610, https://doi.org/10.5194/hess-22-595-2018, https://doi.org/10.5194/hess-22-595-2018, 2018
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Water resources in the Arkavathy watershed in southern India are changing due to human modification of the landscape, including changing agricultural practices and urbanization. We analyze surface water resources in man-made lakes in satellite imagery over a period of 4 decades and find drying in the northern part of the watershed (characterized by heavy agriculture) and wetting downstream of urban areas. Drying in the watershed is associated with groundwater-irrigated agriculture.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
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The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
Henning Oppel and Andreas Schumann
Hydrol. Earth Syst. Sci., 21, 4259–4282, https://doi.org/10.5194/hess-21-4259-2017, https://doi.org/10.5194/hess-21-4259-2017, 2017
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How can we evaluate the heterogeneity of natural watersheds and how can we assess its spatial organization? How can we make use of this information for hydrological models and is it beneficial to our models? We propose a method display and assess the interaction of catchment characteristics with the flow path which we defined as the ordering scheme within a basin. A newly implemented algorithm brings this information to the set-up of a model and our results show an increase in model performance.
Lu Zhuo and Dawei Han
Hydrol. Earth Syst. Sci., 21, 3267–3285, https://doi.org/10.5194/hess-21-3267-2017, https://doi.org/10.5194/hess-21-3267-2017, 2017
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Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from remote sensing and land surface modelling. The result shows a significant improvement of the soil moisture state accuracy; the method can be easily applied in other catchments.
Mauricio Zambrano-Bigiarini, Alexandra Nauditt, Christian Birkel, Koen Verbist, and Lars Ribbe
Hydrol. Earth Syst. Sci., 21, 1295–1320, https://doi.org/10.5194/hess-21-1295-2017, https://doi.org/10.5194/hess-21-1295-2017, 2017
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This work exhaustively evaluates – for the first time – the suitability of seven state-of-the-art satellite-based rainfall estimates (SREs) over the complex topography and diverse climatic gradients of Chile.
Several indices of performance are used for different timescales and elevation zones. Our analysis reveals what SREs are in closer agreement to ground-based observations and what indices allow for understanding mismatches in shape, magnitude, variability and intensity of precipitation.
Yun Yang, Martha C. Anderson, Feng Gao, Christopher R. Hain, Kathryn A. Semmens, William P. Kustas, Asko Noormets, Randolph H. Wynne, Valerie A. Thomas, and Ge Sun
Hydrol. Earth Syst. Sci., 21, 1017–1037, https://doi.org/10.5194/hess-21-1017-2017, https://doi.org/10.5194/hess-21-1017-2017, 2017
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This work explores the utility of a thermal remote sensing based MODIS/Landsat ET data fusion procedure over a mixed forested/agricultural landscape in North Carolina, USA. The daily ET retrieved at 30 m resolution agreed well with measured fluxes in a clear-cut and a mature pine stand. An accounting of consumptive water use by land cover classes is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components.
Domenico Guida, Albina Cuomo, and Vincenzo Palmieri
Hydrol. Earth Syst. Sci., 20, 3493–3509, https://doi.org/10.5194/hess-20-3493-2016, https://doi.org/10.5194/hess-20-3493-2016, 2016
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The authors apply an object-based geomorphometric procedure to define the runoff contribution areas. The results enabled us to identify the contribution area related to the different runoff components activated during the storm events through an advanced hydro-chemical analysis. This kind of approach could be useful applied to similar, rainfall-dominated, forested and no-karst Mediterranean catchments.
Nutchanart Sriwongsitanon, Hongkai Gao, Hubert H. G. Savenije, Ekkarin Maekan, Sirikanya Saengsawang, and Sansarith Thianpopirug
Hydrol. Earth Syst. Sci., 20, 3361–3377, https://doi.org/10.5194/hess-20-3361-2016, https://doi.org/10.5194/hess-20-3361-2016, 2016
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We demonstrated that the readily available NDII remote sensing product is a very useful proxy for moisture storage in the root zone of vegetation. We compared the temporal variation of the NDII with the root zone storage in a hydrological model of eight catchments in the Upper Ping River in Thailand, yielding very good results. Having a reliable NDII product that can help us to estimate the actual moisture storage in catchments is a major contribution to prediction in ungauged basins.
Cheng-Zhi Qin, Xue-Wei Wu, Jing-Chao Jiang, and A-Xing Zhu
Hydrol. Earth Syst. Sci., 20, 3379–3392, https://doi.org/10.5194/hess-20-3379-2016, https://doi.org/10.5194/hess-20-3379-2016, 2016
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Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge. However, the DTA knowledge has not been formalized well to be available for inference in automatic tools. We propose a case-based methodology to solve this problem. This methodology can also be applied to other domains of geographical modeling with a similar situation.
Patricia López López, Niko Wanders, Jaap Schellekens, Luigi J. Renzullo, Edwin H. Sutanudjaja, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 20, 3059–3076, https://doi.org/10.5194/hess-20-3059-2016, https://doi.org/10.5194/hess-20-3059-2016, 2016
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We perform a joint assimilation experiment of high-resolution satellite soil moisture and discharge observations in the Murrumbidgee River basin with a large-scale hydrological model. Additionally, we study the impact of high- and low-resolution meteorological forcing on the model performance. We show that the assimilation of high-resolution satellite soil moisture and discharge observations has a significant impact on discharge simulations and can bring them closer to locally calibrated models.
Zhi Wei Li, Guo An Yu, Gary Brierley, and Zhao Yin Wang
Hydrol. Earth Syst. Sci., 20, 3013–3025, https://doi.org/10.5194/hess-20-3013-2016, https://doi.org/10.5194/hess-20-3013-2016, 2016
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Influence of vegetation upon bedload transport and channel morphodynamics is examined along a channel stability gradient ranging from meandering to anabranching to anabranching–braided to fully braided planform conditions along trunk and tributary reaches of the Yellow River source zone in western China. This innovative work reveals complex interactions between channel planform, bedload transport capacity, sediment supply in the flood season, and the hydraulic role of vegetation.
W. Qi, C. Zhang, G. Fu, C. Sweetapple, and H. Zhou
Hydrol. Earth Syst. Sci., 20, 903–920, https://doi.org/10.5194/hess-20-903-2016, https://doi.org/10.5194/hess-20-903-2016, 2016
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Six precipitation products, including TRMM3B42, TRMM3B42RT, GLDAS/Noah, APHRODITE, PERSIANN, and GSMAP-MVK+, are investigated in the usually neglected area of NE China, and a framework is developed to quantify the contributions of uncertainties from precipitation products, hydrological models, and their interactions to uncertainty in simulated discharges. It is found that interactions between hydrological models and precipitation products contribute significantly to uncertainty in discharge.
A. Molina, V. Vanacker, E. Brisson, D. Mora, and V. Balthazar
Hydrol. Earth Syst. Sci., 19, 4201–4213, https://doi.org/10.5194/hess-19-4201-2015, https://doi.org/10.5194/hess-19-4201-2015, 2015
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Andean catchments play a key role in the provision of freshwater resources. The development of megacities in the inter-Andean valleys raises severe concerns about growing water scarcity. This study is one of the first long-term (1970s-now) analyses of the role of land cover and climate change on provision and regulation of streamflow in the tropical Andes. Forest conversion had the largest impact on streamflow, leading to a 10 % net decrease in streamflow over the last 40 years.
D. Shen, J. Wang, X. Cheng, Y. Rui, and S. Ye
Hydrol. Earth Syst. Sci., 19, 3605–3616, https://doi.org/10.5194/hess-19-3605-2015, https://doi.org/10.5194/hess-19-3605-2015, 2015
M. A. Matin and C. P.-A. Bourque
Hydrol. Earth Syst. Sci., 19, 3387–3403, https://doi.org/10.5194/hess-19-3387-2015, https://doi.org/10.5194/hess-19-3387-2015, 2015
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This paper describes a methodology in analysing the interdependencies between components of the hydrological cycle and vegetation characteristics at different elevation zones of two endorheic river basins in an arid-mountainous region of NW China. The analysis shows that oasis vegetation has an important function in sustaining the water cycle in the river basins and oasis vegetation is dependent on surface and shallow subsurface water flow from mountain sources.
L. Hao, G. Sun, Y. Liu, J. Wan, M. Qin, H. Qian, C. Liu, J. Zheng, R. John, P. Fan, and J. Chen
Hydrol. Earth Syst. Sci., 19, 3319–3331, https://doi.org/10.5194/hess-19-3319-2015, https://doi.org/10.5194/hess-19-3319-2015, 2015
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The role of land cover in affecting hydrologic and environmental changes in the humid region in southern China is not well studied. We found that high flows and low flows increased and evapotranspiration decreased due to urbanization in the Qinhuai River basin. Urbanization masked climate warming effects in a rice-paddy-dominated watershed in altering long-term hydrology. Flooding risks and heat island effects are expected to rise due to urbanization.
E. A. Sproles, S. G. Leibowitz, J. T. Reager, P. J. Wigington Jr, J. S. Famiglietti, and S. D. Patil
Hydrol. Earth Syst. Sci., 19, 3253–3272, https://doi.org/10.5194/hess-19-3253-2015, https://doi.org/10.5194/hess-19-3253-2015, 2015
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The paper demonstrates how data from the Gravity Recovery and Climate Experiment (GRACE) can be used to describe the relationship between water stored at the regional scale and stream flow. Additionally, we employ GRACE as a regional-scale indicator to successfully predict stream flow later in the water year. Our work focuses on the Columbia River Basin (North America), but is widely applicable across the globe, and could prove to be particularly useful in regions with limited hydrological data.
A. Rouillard, G. Skrzypek, S. Dogramaci, C. Turney, and P. F. Grierson
Hydrol. Earth Syst. Sci., 19, 2057–2078, https://doi.org/10.5194/hess-19-2057-2015, https://doi.org/10.5194/hess-19-2057-2015, 2015
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We reconstructed a 100-year monthly history of flooding and drought of a large wetland in arid northwest Australia, using hydroclimatic data calibrated against 25 years of satellite images. Severe and intense regional rainfall, as well as the sequence of events, determined surface water expression on the floodplain. While inter-annual variability was high, changes to the flood regime over the last 20 years suggest the wetland may become more persistent in response to the observed rainfall trend.
B. Müller, M. Bernhardt, and K. Schulz
Hydrol. Earth Syst. Sci., 18, 5345–5359, https://doi.org/10.5194/hess-18-5345-2014, https://doi.org/10.5194/hess-18-5345-2014, 2014
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We present a method to define hydrological landscape units by a time series of thermal infrared satellite data. Land surface temperature is calculated for 28 images in 12 years for a catchment in Luxembourg. Pattern measures show spatio-temporal persistency; principle component analysis extracts relevant patterns. Functional units represent similar behaving entities based on a representative set of images. Resulting classification and patterns are discussed regarding potential applications.
F. F. Worku, M. Werner, N. Wright, P. van der Zaag, and S. S. Demissie
Hydrol. Earth Syst. Sci., 18, 3837–3853, https://doi.org/10.5194/hess-18-3837-2014, https://doi.org/10.5194/hess-18-3837-2014, 2014
A. M. Ågren, W. Lidberg, M. Strömgren, J. Ogilvie, and P. A. Arp
Hydrol. Earth Syst. Sci., 18, 3623–3634, https://doi.org/10.5194/hess-18-3623-2014, https://doi.org/10.5194/hess-18-3623-2014, 2014
N. Wanders, D. Karssenberg, A. de Roo, S. M. de Jong, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 18, 2343–2357, https://doi.org/10.5194/hess-18-2343-2014, https://doi.org/10.5194/hess-18-2343-2014, 2014
J. K. Kiptala, M. L. Mul, Y. A. Mohamed, and P. van der Zaag
Hydrol. Earth Syst. Sci., 18, 2287–2303, https://doi.org/10.5194/hess-18-2287-2014, https://doi.org/10.5194/hess-18-2287-2014, 2014
C. I. Michailovsky and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 18, 997–1007, https://doi.org/10.5194/hess-18-997-2014, https://doi.org/10.5194/hess-18-997-2014, 2014
T. Conradt, F. Wechsung, and A. Bronstert
Hydrol. Earth Syst. Sci., 17, 2947–2966, https://doi.org/10.5194/hess-17-2947-2013, https://doi.org/10.5194/hess-17-2947-2013, 2013
M. El Bastawesy, R. Ramadan Ali, A. Faid, and M. El Osta
Hydrol. Earth Syst. Sci., 17, 1493–1501, https://doi.org/10.5194/hess-17-1493-2013, https://doi.org/10.5194/hess-17-1493-2013, 2013
A. C. V. Getirana and C. Peters-Lidard
Hydrol. Earth Syst. Sci., 17, 923–933, https://doi.org/10.5194/hess-17-923-2013, https://doi.org/10.5194/hess-17-923-2013, 2013
Y. Tramblay, R. Bouaicha, L. Brocca, W. Dorigo, C. Bouvier, S. Camici, and E. Servat
Hydrol. Earth Syst. Sci., 16, 4375–4386, https://doi.org/10.5194/hess-16-4375-2012, https://doi.org/10.5194/hess-16-4375-2012, 2012
J. Parajka, L. Holko, Z. Kostka, and G. Blöschl
Hydrol. Earth Syst. Sci., 16, 2365–2377, https://doi.org/10.5194/hess-16-2365-2012, https://doi.org/10.5194/hess-16-2365-2012, 2012
S. Peischl, J. P. Walker, C. Rüdiger, N. Ye, Y. H. Kerr, E. Kim, R. Bandara, and M. Allahmoradi
Hydrol. Earth Syst. Sci., 16, 1697–1708, https://doi.org/10.5194/hess-16-1697-2012, https://doi.org/10.5194/hess-16-1697-2012, 2012
S. Bircher, N. Skou, K. H. Jensen, J. P. Walker, and L. Rasmussen
Hydrol. Earth Syst. Sci., 16, 1445–1463, https://doi.org/10.5194/hess-16-1445-2012, https://doi.org/10.5194/hess-16-1445-2012, 2012
J.-M. Kileshye Onema, A. E. Taigbenu, and J. Ndiritu
Hydrol. Earth Syst. Sci., 16, 1435–1443, https://doi.org/10.5194/hess-16-1435-2012, https://doi.org/10.5194/hess-16-1435-2012, 2012
S. Manfreda, T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli
Hydrol. Earth Syst. Sci., 15, 2839–2852, https://doi.org/10.5194/hess-15-2839-2011, https://doi.org/10.5194/hess-15-2839-2011, 2011
M. Salvia, F. Grings, P. Ferrazzoli, V. Barraza, V. Douna, P. Perna, C. Bruscantini, and H. Karszenbaum
Hydrol. Earth Syst. Sci., 15, 2679–2692, https://doi.org/10.5194/hess-15-2679-2011, https://doi.org/10.5194/hess-15-2679-2011, 2011
Cited articles
Arsenault, K. R., Houser, P. R., and De Lannoy, G. J.: Evaluation of the MODIS snow cover fraction product, Hydrol. Process., 28, 980–998, 2014.
Anderson, E. A.: A point energy and mass balance model of a snow
cover, NOAA Tech. Rep. NWS 19, Office of Hydrology, National Weather
Service, Silver Spring, MD, 150 pp., 1976.
Anderson, E. A.: Calibration of conceptual hydrologic models for use in river
forecasting, Office of Hydrologic Development, US National Weather Service,
Silver Spring, MD, 372 pp., available at: https://www.nws.noaa.gov/oh/hrl/modelcalibration/1. Calibration Process/1_Anderson_CalbManual.pdf
(last access: 8 May 2019), 2002.
Anderson, E. A.: Snow Accumulation and Ablation Model – SNOW-17, Nat. Weather Serv. NOAA,
44 pp., available at: http://www.nws.noaa.gov/oh/hrl/nwsrfs/users_manual/part2/_pdf/22snow17.pdf (last
access: 17 August 2018), 2006.
Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow
observations into a macroscale hydrology model, Adv. Water Res., 29,
872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006.
Bennett, K. E. and Walsh, J.: Spatial and temporal changes in indices of
extreme precipitation and temperature for Alaska, Int. J. Climatol., 35,
1434–1452, https://doi.org/10.1002/joc.4067, 2015.
Bennett, K. E., Cannon, A. J., and Hinzman, L.: Historical trends and
extremes in boreal Alaska river basins, J. Hydrol., 527, 590–607,
https://doi.org/10.1016/j.jhydrol.2015.04.065, 2015.
Burnash, R. J. E., Ferral, R. L., and McGuire, R. A.: A generalized
streamflow simulation system, Joint Federal-State River Forecast Center,
Sacramento, CA, 204 pp., 1973.
Cherry, J. E., Tremblay, L. B., Déry, S. J., and Stieglitz, M.:.
Reconstructing solid precipitation from snow depth measurements and a land
surface model, Water Resour. Res., 41, 1–15,
https://doi.org/10.1029/2005WR003965, 2005.
Cherry, J. E., Tremblay, L. B., Stieglitz, M., Gong, G., and Déry, S.
J.: Development of the pan-arctic snowfall reconstruction: new land-based
solid precipitation estimates for 1940-99, J. Hydrometeorol., 8, 1243–1263,
https://doi.org/10.1175/2007JHM765.1, 2007.
Cherry, J. E., Knapp, C., Trainor, S., Ray, A. J., Tedesche, M., and Walker, S.: Planning for climate change impacts on hydropower
in the Far North, Hydrol. Earth Syst. Sci., 21, 133–151, https://doi.org/10.5194/hess-21-133-2017, 2017.
Clark, M. P., Slater, A. G., Barrett, A. P., Hay, L. E., McCabe, G. J.,
Rajagopalan, B., and Leavesley, G. H.: Assimilation of snow covered area
information into hydrologic and land-surface models, Adv. Water Res., 29,
1209–1221, https://doi.org/10.1016/j.advwatres.2005.10.001,
2006.
Clark, M. P., Hendrikx, J., Slater, A. G., Kavetski, D., Anderson, B.,
Cullen, N. J., Kerr, T., Hreinsson, E. Ö., and Woods, R. A: Representing
spatial variability of snow water equivalent in hydrologic and land-surface
models: A review, Water Resour. Res., 47, 1–23,
https://doi.org/10.1029/2011WR010745, 2011.
Clark, M. P., Bierkens, M. F. P., Samaniego, L., Woods, R. A., Uijlenhoet, R., Bennett, K. E., Pauwels, V. R. N., Cai, X., Wood, A. W.,
and Peters-Lidard, C. D.: The evolution of process-based hydrologic models: historical challenges and the collective quest for
physical realism, Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, 2017.
Cohen, J. L., Furtado, J. C., Barlow, M. A., Alexeev, V. A., and Cherry, J.
E.: Arctic warming, increasing snow cover and widespread boreal winter
cooling, Environ. Res. Lett., 7, 014007,
https://doi.org/10.1088/1748-9326/7/1/014007, 2012.
Cooley, S. W. and Pavelsky, T. M.: Spatial and temporal patterns in Arctic
river ice breakup revealed by automated ice detection from MODIS imagery,
Remote Sens. Environ., 175, 310–322,
https://doi.org/10.1016/j.rse.2016.01.004, 2016.
Déry, S. J., Salomonson, V. V., Stieglitz, M., Hall, D. K., and Appel,
I.: An approach to using snow areal depletion curves inferred from MODIS and
its application to land surface modelling in Alaska, Hydrol. Process., 19,
2755–2774, https://doi.org/10.1002/hyp.5784, 2005.
Dozier, J., Painter, T. H., Rittger, K., and Frew, J. E.: Time-space
continuity of daily maps of fractional snow cover and albedo from MODIS,
Adv. Water Res., 31, 1515–1526,
https://doi.org/10.1016/j.advwatres.2008.08.011, 2008.
Duethmann, D., Peters, J., Blume, T., Vorogushyn, S., and Güntner, A.:
The value of satellite-derived snow cover images for calibrating a
hydrological model in snow-dominated catchments in Central Asia, Water
Resour. Res., 50, 2002–2021, https://doi.org/10.1002/2013WR014382. 2014.
Durand, M., Molotch, N. P., and Margulis, S. A.: Merging complementary remote
sensing datasets in the context of snow water equivalent reconstruction,
Remote Sens. Environ., 112, 1212–1225,
https://doi.org/10.1016/j.rse.2007.08.010, 2008.
Dwyer, J. and Schmidt, G.: The MODIS reprojection tool, in: Earth Science
Satellite Remote Sensing, Springer, Berlin, Heidelberg, Germany, 162–177,
2006.
Euskirchen, E., McGuire, A., Chapin III, F., Yi, S., and Thompson, C.:
Changes in vegetation in northern Alaska under scenarios of climate change,
2003–2100: implications for climate feedbacks, Ecol. Appl., 19, 1022–1043,
https://doi.org/10.1890/08-0806.1, 2009.
Franz, K. J. and Karsten, L. R.: Calibration of a distributed snow model
using MODIS snow covered area data, J. Hydrol., 494, 160–175,
https://doi.org/10.1016/j.jhydrol.2013.04.026, 2013.
Franz, K. J., Hogue, T. S., and Sorooshian, S.: Operational snow modeling:
Addressing the challenges of an energy balance model for National Weather
Service forecasts, J. Hydrol., 360, 48–66,
https://doi.org/10.1016/j.jhydrol.2008.07.013, 2008.
Gesch, D., Oimoen, M., Greenlee, S., Nelson, C., Steuck, M., and Tyler, D.:
The National Elevation Dataset, Photogramm. Eng. Rem. S., 68, 5–11,
2002.
Groisman, P. Y., Bogdanova, E., Alexeev, V., Cherry, J., and Bulygina, O.:
Impact of snowfall measurement deficiencies on quantification of
precipitation and its trends over northern Eurasia, Ice Snow, 54, 29–43,
https://doi.org/10.15356/2076-6734-2014-2-29-43, 2014.
Hall, D. K. and Riggs, G. A.: Accuracy assessment of the MODIS snow
product, Hydrol. Process., 21, 1534–1547,
https://doi.org/10.1002/hyp.6715, 2007.
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6, Snow Cover, Boulder, Colorado USA,
NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/MODIS/MOD10A1.006, 2016.
Hall, D. K., Riggs, G. A., Salomonson, V. V., DiGirolamo, N. E., and Bayr,
K. J.: MODIS snow-cover products, Remote Sens. Environ., 83, 181–194,
https://doi.org/10.1016/S0034-4257(02)00095-0, 2002.
Hall, D. K., Riggs, G. A., and Salomonson, V. V.: MODIS/Terra Snow Cover
Daily L3 Global 500m Grid V005, 2000-Daily Updates, National Snow and Ice
Data Center, Boulder, Colorado USA, 2006.
He, M., Hogue, T. S., Franz, K. J., Margulis, S. A., and Vrugt, J. A.:
Characterizing parameter sensitivity and uncertainty for a snow model across
hydroclimatic regimes, Adv. Water Res., 34, 114–127,
https://doi.org/10.1016/j.advwatres.2010.10.002, 2011.
Hinzman, L. D., Bettez, N. D., Bolton, W. R., Chapin, F. S., Dyurgerov, M.
B., Fastie, C. L., Griffith, B., Hollister, R. D., Hope, A., Huntinton, H.
P., Jensen, A. M., Jia, G. J., Jorgenson, T., Kane, D. L., Klein, D. R.,
Kofinas, G., Lynch, A. H., Lloyd, A. H., McGuire, A. D., Nelson, F. E.,
Oechel, W. C., Osterkamp, T. E., Racine, C. H., Romanovsky, V. E., Stone, R.
S., Stow, D. A., Sturm, M. D., Walker, D. A., Webber, P. J., Welker, J. M.,
Winker, K. S., and Yoshikawa, K.: Evidence and implications of recent
climate change in northern Alaska and other Arctic regions, Climate Change,
72, 251–298, https://doi.org/10.1007/s10584-005-5352-2, 2005.
Hinzman, L. D., Deal, C. J., McGuire, A. D., Mernild, S. H., Polyakov, I.
V., and Walsh, J. E.: Trajectory of the Arctic as an integrated system,
Ecol. Appl., 23, 1837–1868, https://doi.org/10.1890/11-1498.1, 2013.
Hock, R.: Temperature index melt modelling in mountain areas, J. Hydrol.,
282, 104–115, https://doi.org/10.1016/S0022-1694(03)00257-9,
2003.
Huntington, T. G.: Evidence for intensification of the global water cycle:
review and synthesis, J. Hydrol., 319, 83–95,
https://doi.org/10.1016/j.jhydrol.2005.07.003, 2006.
Instanes, A., Kokorev, V., Janowicz, R., Bruland, O., Sand, K., and Prowse,
T.: Changes to freshwater systems affecting Arctic infrastructure and
natural resources, J. Geophys. Res.-Biogeo., 121, 567–585,
https://doi.org/10.1002/2015JG003125, 2016.
Jones, J. B. and Rinehart, A. J.: The long-term response of stream flow to
climatic warming in headwater streams of interior Alaska, Can. J. Forest
Res., 40, 1210–1218, 2010.
Kane, V. R., Gillespie, A. R., McGaughey, R., Lutz, J. A., Ceder, K., and
Franklin, J. F.: Interpretation and topographic compensation of conifer
canopy self-shadowing, Remote Sens. Environ., 112, 3820–3832,
https://doi.org/10.1016/j.rse.2008.06.001, 2008.
Karl, T. R., Melillo, J. M., Peterson, T. C., and Hassol, S. J. (Eds.): Global climate change impacts in the United States, Cambridge University Press, 2009.
Koven C. D., Riley W. J., and Stern, A.: Analysis of permafrost thermal
dynamics and response to climate change in the CMIP5 Earth system models, J.
Climate, 26, 1877–900,
https://doi.org/10.1175/JCLI-D-12-00228.1, 2013.
Lesack, L. F. W., Marsh, P., Hicks, F. E., and Forbes, D. L.: Local spring
warming drives earlier river-ice breakup in a large Arctic delta, Geophys.
Res. Lett., 41, 1560–1567, https://doi.org/10.1002/2013GL058761, 2014.
Liu, J., Melloh, R. A., Woodcock, C. E., Davis, R. E., and Ochs, E. S.: The
effect of viewing geometry and topography on viewable gap fractions through
forest canopies, Hydrol. Process., 18, 3595–3607,
https://doi.org/10.1002/hyp.5802, 2004.
Liu, J., Woodcock, C. E., Melloh, R. A., Davis, R. E., McKenzie, C., and
Painter, T. H.: Modeling the view angle dependence of gap fractions in forest
canopies: Implications for mapping fractional snow cover using optical
remote sensing, J. Hydrometeorol., 9, 1005–1019,
https://doi.org/10.1175/2008JHM866.1, 2008.
Liu, Y., Peters-Lidard, C. D., Kumar, S., Foster, J. L., Shaw, M., Tian, Y.,
and Fall, G. M.: Assimilating satellite-based snow depth and snow cover
products for improving snow predictions in Alaska, Adv. Water Res., 54,
208–227, https://doi.org/10.1016/j.advwatres.2013.02.005, 2013.
Magnusson, J., Wever, N., Essery, R., Helbig, N., Winstral, A., and Jonas,
T.: Evaluating snow models with varying process representations for
hydrological applications, Water Resour. Res., 51, 2707–2723,
https://doi.org/10.1002/2014WR016498, 2015.
McGuire, M., Wood, A. W., Hamlet, A. F., and Lettenmaier, D. P.: Use of
satellite data for streamflow and reservoir storage forecasts in the Snake
River Basin, J. Water Resour. Plan. Man., 132, 97–1109,
https://doi.org/10.1061/(ASCE)0733-9496(2006)132:2(97), 2006.
Molotch, N. P. and Bales, R. C.: Scaling snow observation from the point to
the grid element: Implications for observation network design, Water Resour.
Res., 41, 1–16, https://doi.org/10.1029/2005WR004229, 2005.
Molotch, N. P. and Margulis, S. A.: Estimating the distribution of snow
water equivalent using remotely sensed snow cover data and a spatially
distributed snowmelt model: A multi-resolution, multi-sensor comparison,
Adv. Water Res., 31, 1503–1514,
https://doi.org/10.1016/j.advwatres.2008.07.017, 2008.
Morriss, B. F., Ochs, E., Deeb, E. J., Newman, S. D., Daly, S. F., and
Gagnon, J. J.: Persistence-based temporal filtering for MODIS snow products,
Remote Sens. Environ., 175, 130–137,
https://doi.org/10.1016/j.rse.2015.12.030, 2016.
Muhammad, P., Duguay, C., and Kang, K.-K.: Monitoring ice break-up on the Mackenzie River using MODIS data,
The Cryosphere, 10, 569–584, https://doi.org/10.5194/tc-10-569-2016, 2016.
National Resources Conservation Service:
Snow Water Equivalent (SWE) and Snow Depth Products, https://www.wcc.nrcs.usda.gov/snow/snotel-wereports.html, last access 16 May 2019.
NOAA: NOAA National Water Model: Improving NOAA's Water Prediction
Services, 2 pp., available at: https://water.noaa.gov/documents/wrn-national-water-model.pdf (last
access: 1 December 2018), 2017.
NWS: Overview of the Hydrologic Ensemble Forecast Service (HEFS), Office of Hydrologic Development, 34 pp.,
available at:
http://www.nws.noaa.gov/os/water/RFC_support/HEFS_doc/HEFS_Overview_0.1.2.pdf (last access: 1 December 2018), 2012.
Painter, T. H., Rittger, K., McKenzie, C., Slaughter, P., Davis, R. E., and
Dozier, J.: Retrieval of subpixel snow covered area, grain size, and albedo
from MODIS, Remote Sens. Environ., 113, 868–879,
https://doi.org/10.1016/j.rse.2009.01.001, 2009.
Parajka, J. and Blöschl, G.: The value of MODIS snow cover data in
validating and calibrating conceptual hydrologic models, J. Hydrol., 358,
240–258, https://doi.org/10.1016/j.jhydrol.2008.06.006, 2008.
Prowse, T., Bring, A., Mård, J., Carmack, E., Holland, M., Instanes, A.,
Vihma, T., and Wrona, F.: Arctic Freshwater Synthesis: Summary of key
emerging issues, J. Geophys. Res.-Biogeo., 120, 1887–1893,
https://doi.org/10.1002/2015JG003128, 2015.
Rawlins, M. A., Steele, M., Holland, M. M., Adam, J. C., Cherry, J. E., Francis, J. A., Groisman, P. Y., Hinzman, L. D., Huntington, T. G.,
Kane, D. L., Kimball, J. S., Kwok, R., Lammers, R. B., Lee, C. M., Lettenmaier, D. P., McDonald, K. C., Podest, E.,
Pundsack, J. W., Rudels, B., Serreze, M. C., Shiklomanov, A., Skagseth, Ø., Troy, T. J., Vörösmarty, C. J., Wensnahan, M.,
Wood, E. F., Woodgate, R., Yang, D., Zhang, K., and Zhang, T.: Analysis of the Arctic System for Freshwater Cycle Intensification:
Observations and Expectations, J. Climate, 23, 5715–5737, https://doi.org/10.1175/2010JCLI3421.1, 2010.
Raleigh, M. S., Rittger, K., Moore, C. E., Henn, B., Lutz, J. A., and
Lundquist, J. D.: Ground-based testing of MODIS fractional snow cover in
subalpine meadows and forests of the Sierra Nevada, Remote Sens. Environ.,
128, 44–57, https://doi.org/10.1016/j.rse.2012.09.016, 2013.
Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., and Seo, D.-J.:
Overall distributed model intercomparison project results, J. Hydrol., 298,
27–60, https://doi.org/10.1016/j.jhydrol.2004.03.031, 2004.
Riggs, G. A., Hall, D. K., and Salomonson, V. V.: MODIS Snow Products User
Guide to Collection 5, 80 pp., available at: https://modis-snow-ice.gsfc.nasa.gov/?c=userguides
(last access: 1 December 2018), 2006.
Rittger, K., Painter, T. H., and Dozier, J.: Assessment of methods for
mapping snow cover from MODIS, Adv. Water Res., 51, 367–380,
https://doi.org/10.1016/j.advwatres.2012.03.002, 2013.
Rodell, M., Houser, P., Jambor, U., Gottschalck, J., Mitchell, K., Meng,
C.-J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin,
J. K., Walker, J. P., Lohmann, D., and Toll, D.: The global land data
assimilation system, B. Am. Meteorol. Soc., 85, 381–394,
https://doi.org/10.1175/BAMS-85-3-381, 2004.
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic
amplification: A research synthesis, Global Planet. Change, 77, 85–96,
https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011.
Shamir, E. and Georgakakos, K. P.: Estimating snow depletion curves for
American River basins using distributed snow modeling, J. Hydrol., 334,
162–173, https://doi.org/10.1016/j.jhydrol.2006.10.007, 2007.
Stahl, K., Moore, R. D., Floyer, J. A., Asplin, M. G., and McKendry, I. G.:
Comparison of approaches for spatial interpolation of daily air temperature
in a large region with complex topography and highly variable station
density, Agr. Forest Meteorol., 139, 224–236,
https://doi.org/10.1016/j.agrformet.2006.07.004, 2006.
Stewart, B. C., Kunkel, K. E., Stevens, L. E., and Sun, L.: Regional climate trends and scenarios
for the U.S. National Climate Assessment,
Part 7. Climate of Alaska, NOAA technical Report NESDIS 142–147, 60 pp., 2013.
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K.,
Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.: Climate
Change 2013: The physical science basis, Intergovernmental Panel on Climate
Change, Working Group I Contribution to the IPCC Fifth Assessment Report
(AR5), Cambridge Univ Press, New York, available at: https://www.ipcc.ch/report/ar5/wg1/ (last access: 1 December 2018), 2013.
Stuefer, S. L., Arp, C. D., Kane, D. L., and Liljedahl, A. K.: Recent
extreme runoff observations from Coastal Arctic watersheds in Alaska, Water
Resour. Res., 53, 9145–9163, https://doi.org/10.1002/2017WR020567, 2017.
Sturm, M., Goldstein, M. A., and Parr, C.: Water and life from snow: A
trillion dollar science question, Water Resour. Res., 53, 3534–3544,
https://doi.org/10.1002/2017WR020840, 2017.
Sun, C., Walker, J. P., and Houser, P. R.: A methodology for snow data
assimilation in a land surface model, J. Geophys. Res.-Atmos., 109, D08108,
https://doi.org/10.1029/2003JD003765 2004.
Tan, B., Woodcock, C. E., Hu, J., Zhang, P., Ozdogan, M., Huang, D., Yang,
W., Knyazikhin, Y., and Myneni, R. B.: The impact of gridding artifacts on
the local spatial properties of MODIS data: Implications for validation,
compositing, and band-to-band registration across resolutions, Remote Sens.
Environ., 105, 98–114,
https://doi.org/10.1016/j.rse.2006.06.008, 2006.
Thirel, G., Salamon, P., Burek, P., and Kalas, M.: Assimilation of MODIS
snow cover area data in a distributed hydrological model using the particle
filter, Remote Sens., 5, 5825–5850, https://doi.org/10.3390/rs5115825, 2013.
U.S. Geological Survey: National Water Information System data available on the World Wide Web
(USGS Water Data for the Nation), https://waterdata.usgs.gov/nwis/rt, last access: 16 May 2019.
Udnæs, H., Alfnes, E., and Andreassen, L. M.: Improving runoff modelling
using satellite-derived snow covered area?, Hydrol. Res., 38, 21–32,
https://doi.org/10.2166/nh.2007.032, 2007.
Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O.,
and Heynert, K.: The Delft-FEWS flow forecasting system, Environ. Model.
Softw., 40, 65–77, https://doi.org/10.1016/j.envsoft.2012.07.010 2013.
Woo, M. K., Thorne, R., Szeto, K., and Yang, D.: Streamflow hydrology in the
boreal region under the influences of climate and human interference,
Philos. T. R. Soc. B, 363, 2249–2258, https://doi.org/10.1098/rstb.2007.2197, 2008.
Wrona, F. J., Johansson, M., Culp, J. M., Jenkins, A., Mård, J.,
Myers-Smith, I. H., Prowse, T. D., Vincent, W. F., and Wookey, P. A.:
Transitions in Arctic ecosystems: Ecological implications of a changing
hydrological regime, J. Geophys. Res.-Biogeo., 121, 650–674,
https://doi.org/10.1002/2015JG003133, 2016.
Zaitchik, B. and Rodell, M.: Forward-looking assimilation of MODIS-derived
snow-covered area into a land surface model, J. Hydrometeorol., 10,
130–148, https://doi.org/10.1175/2008JHM1042.1, 2009.
Short summary
Remotely sensed snow observations may improve operational streamflow forecasting in remote regions, such as Alaska. In this study, we insert remotely sensed observations of snow extent into the operational framework employed by the US National Weather Service’s Alaska Pacific River Forecast Center. Our work indicates that the snow observations can improve snow estimates and streamflow forecasting. This work provides direction for forecasters to implement remote sensing in their operations.
Remotely sensed snow observations may improve operational streamflow forecasting in remote...
