Articles | Volume 27, issue 3
https://doi.org/10.5194/hess-27-703-2023
© Author(s) 2023. 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-27-703-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Feb 2023
Research article |
| 09 Feb 2023
| 09 Feb 2023
Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning
Antoine Di Ciacca
CORRESPONDING AUTHOR
Environmental Research, Lincoln Agritech Ltd, Lincoln, New
Zealand
Scott Wilson
Environmental Research, Lincoln Agritech Ltd, Lincoln, New
Zealand
Jasmine Kang
National Institute of Water and Atmospheric Research (NIWA),
Christchurch, New Zealand
Thomas Wöhling
Environmental Research, Lincoln Agritech Ltd, Lincoln, New
Zealand
Chair of Hydrology, Technische Universität Dresden, Dresden,
Germany
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We show the results of the 2022 Groundwater Time Series Modelling Challenge; 15 teams applied data-driven models to simulate hydraulic heads, and three model groups were identified: lumped, machine learning, and deep learning. For all wells, reasonable performance was obtained by at least one team from each group. There was not one team that performed best for all wells. In conclusion, the challenge was a successful initiative to compare different models and learn from each other.
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Braided rivers are complex and dynamic systems that are difficult to understand. Here, we proposes a new model of how braided rivers work in the subsurface based on field observations in three braided rivers in New Zealand. We suggest that braided rivers create their own shallow aquifers by moving bed sediments during flood flows. This new conceptualisation considers braided rivers as whole “river systems” consisting of channels and a gravel aquifer, which is distinct from the regional aquifer.
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We show the results of the 2022 Groundwater Time Series Modelling Challenge; 15 teams applied data-driven models to simulate hydraulic heads, and three model groups were identified: lumped, machine learning, and deep learning. For all wells, reasonable performance was obtained by at least one team from each group. There was not one team that performed best for all wells. In conclusion, the challenge was a successful initiative to compare different models and learn from each other.
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Braided rivers are complex and dynamic systems that are difficult to understand. Here, we proposes a new model of how braided rivers work in the subsurface based on field observations in three braided rivers in New Zealand. We suggest that braided rivers create their own shallow aquifers by moving bed sediments during flood flows. This new conceptualisation considers braided rivers as whole “river systems” consisting of channels and a gravel aquifer, which is distinct from the regional aquifer.
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We compare seven meteorological drought indices that are commonly used to predict future droughts. Our goal is to assess the reliability of these indices to predict hydrological impacts of droughts under changing climatic conditions, using an integrated hydrological model. Drought indices are able to identify the timing of hydrological impacts of droughts in present and future climate. However, these indices can not estimate the severity of hydrological impacts of droughts in future climate.
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Anette Eltner, Hannes Sardemann, and Jens Grundmann
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Andreas Kääb, Bas Altena, and Joseph Mascaro
Hydrol. Earth Syst. Sci., 23, 4233–4247, https://doi.org/10.5194/hess-23-4233-2019, https://doi.org/10.5194/hess-23-4233-2019, 2019
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Knowledge of water surface velocities in rivers is useful for understanding a wide range of processes and systems, but is difficult to measure over large reaches. Here, we present a novel method to exploit near-simultaneous imagery produced by the Planet cubesat constellation to track river ice floes and estimate water surface velocities. We demonstrate the method for a 60 km long reach of the Amur River and a 200 km long reach of the Yukon River.
Najib Abou Karaki, Simone Fiaschi, Killian Paenen, Mohammad Al-Awabdeh, and Damien Closson
Hydrol. Earth Syst. Sci., 23, 2111–2127, https://doi.org/10.5194/hess-23-2111-2019, https://doi.org/10.5194/hess-23-2111-2019, 2019
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The Dead Sea shore is a unique salt karst system. Development began in the 1960s, when the water resources that used to feed the Dead Sea were diverted. The water level is falling at more than 1 m yr−1, causing a hydrostatic disequilibrium between the underground fresh water and the base level. Despite these conditions, tourism development projects have flourished. Here, we show that a 10 km long strip of coast that encompasses several resorts is exposed to subsidence, sinkholes and landslides.
Tim Busker, Ad de Roo, Emiliano Gelati, Christian Schwatke, Marko Adamovic, Berny Bisselink, Jean-Francois Pekel, and Andrew Cottam
Hydrol. Earth Syst. Sci., 23, 669–690, https://doi.org/10.5194/hess-23-669-2019, https://doi.org/10.5194/hess-23-669-2019, 2019
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This paper estimates lake and reservoir volume variations over all continents from 1984 to 2015 using remote sensing alone. This study improves on previous methodologies by using the Global Surface Water dataset developed by the Joint Research Centre, which allowed for volume calculations on a global scale, a high resolution (30 m) and back to 1984 using very detailed lake area dynamics. Using 18 in situ volume time series as validation, our volume estimates showed a high accuracy.
Andrew Ogilvie, Gilles Belaud, Sylvain Massuel, Mark Mulligan, Patrick Le Goulven, and Roger Calvez
Hydrol. Earth Syst. Sci., 22, 4349–4380, https://doi.org/10.5194/hess-22-4349-2018, https://doi.org/10.5194/hess-22-4349-2018, 2018
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Accurate monitoring of surface water extent is essential for hydrological investigation of small lakes (1–10 ha), which supports millions of smallholder farmers. Landsat monitoring of long-term surface water dynamics is shown to be suited to lakes over 3 ha based on extensive hydrometric data from seven field sites over 15 years. MNDWI water classification optimized here for the specificities of small water bodies reduced mean surface area errors by 57 % compared to published global datasets.
Filippo Bandini, Daniel Olesen, Jakob Jakobsen, Cecile Marie Margaretha Kittel, Sheng Wang, Monica Garcia, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 22, 4165–4181, https://doi.org/10.5194/hess-22-4165-2018, https://doi.org/10.5194/hess-22-4165-2018, 2018
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Water depth observations are essential data to forecast flood hazard, predict sediment transport, or monitor in-stream habitats. We retrieved bathymetry with a sonar wired to a drone. This system can improve the speed and spatial scale at which water depth observations are retrieved. Observations can be retrieved also in unnavigable or inaccessible rivers. Water depth observations showed an accuracy of ca. 2.1 % of actual depth, without being affected by water turbidity or bed material.
Kiana Zolfaghari, Claude R. Duguay, and Homa Kheyrollah Pour
Hydrol. Earth Syst. Sci., 21, 377–391, https://doi.org/10.5194/hess-21-377-2017, https://doi.org/10.5194/hess-21-377-2017, 2017
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A remotely-sensed water clarity value (Kd) was applied to improve FLake model simulations of Lake Erie thermal structure using a time-invariant (constant) annual value as well as monthly values of Kd. The sensitivity of FLake model to Kd values was studied. It was shown that the model is very sensitive to variations in Kd when the value is less than 0.5 m-1.
Tomasz Niedzielski, Matylda Witek, and Waldemar Spallek
Hydrol. Earth Syst. Sci., 20, 3193–3205, https://doi.org/10.5194/hess-20-3193-2016, https://doi.org/10.5194/hess-20-3193-2016, 2016
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We study detectability of changes in water surface areas on orthophotomaps. We use unmanned aerial vehicles to acquire visible light photographs. We offer a new method for detecting changes in water surface areas and river stages. The approach is based on the application of the Student's t test, in asymptotic and bootstrapped versions. We test our approach on aerial photos taken during 3-year observational campaign. We detect transitions between all characteristic river stages using drone data.
E. Lalot, F. Curie, V. Wawrzyniak, F. Baratelli, S. Schomburgk, N. Flipo, H. Piegay, and F. Moatar
Hydrol. Earth Syst. Sci., 19, 4479–4492, https://doi.org/10.5194/hess-19-4479-2015, https://doi.org/10.5194/hess-19-4479-2015, 2015
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This work shows that satellite thermal infrared images (LANDSAT) can be used to locate and quantify groundwater discharge into a large river (Loire River, France - 100 to 300 m wide). Groundwater discharge rate is found to be highly variable with time and space and maximum during flow recession periods and in winter. The main identified groundwater discharge area into the Loire River corresponds to a known discharge area of the Beauce aquifer.
M. D. Wilson, M. Durand, H. C. Jung, and D. Alsdorf
Hydrol. Earth Syst. Sci., 19, 1943–1959, https://doi.org/10.5194/hess-19-1943-2015, https://doi.org/10.5194/hess-19-1943-2015, 2015
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We use a virtual mission analysis on a ca. 260km reach of the central Amazon River to assess the hydraulic implications of potential measurement errors in swath-altimetry imagery from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission. We estimated water surface slope from imagery of water heights and then derived channel discharge. Errors in estimated discharge were lowest when using longer reach lengths and channel cross-sectional averaging to estimate water slopes.
Y. B. Sulistioadi, K.-H. Tseng, C. K. Shum, H. Hidayat, M. Sumaryono, A. Suhardiman, F. Setiawan, and S. Sunarso
Hydrol. Earth Syst. Sci., 19, 341–359, https://doi.org/10.5194/hess-19-341-2015, https://doi.org/10.5194/hess-19-341-2015, 2015
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This paper investigates the possibility of monitoring small water bodies through Envisat altimetry observation. A novel approach is introduced to identify qualified and non-qualified altimetry measurements by assessing the waveform shapes for each returned radar signal. This research indicates that small lakes (extent < 100 km2) and medium-sized rivers (e.g., 200--800 m in width) can be successfully monitored by satellite altimetry.
Z. F. Miller, T. M. Pavelsky, and G. H. Allen
Hydrol. Earth Syst. Sci., 18, 4883–4895, https://doi.org/10.5194/hess-18-4883-2014, https://doi.org/10.5194/hess-18-4883-2014, 2014
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Many previous studies have used stream gauge data to estimate patterns of river width and depth based on variations in river discharge. However, these relationships may not capture all of the actual variability in width and depth. We have instead mapped the widths of all of the rivers wider than 100 m (and many narrower) in the Mississippi Basin and then used them to also improve estimates of depth as well. Our results show width and depth variations not captured by power-law relationships.
A. Kääb, M. Lamare, and M. Abrams
Hydrol. Earth Syst. Sci., 17, 4671–4683, https://doi.org/10.5194/hess-17-4671-2013, https://doi.org/10.5194/hess-17-4671-2013, 2013
V. H. Phan, R. C. Lindenbergh, and M. Menenti
Hydrol. Earth Syst. Sci., 17, 4061–4077, https://doi.org/10.5194/hess-17-4061-2013, https://doi.org/10.5194/hess-17-4061-2013, 2013
N. M. Velpuri and G. B. Senay
Hydrol. Earth Syst. Sci., 16, 3561–3578, https://doi.org/10.5194/hess-16-3561-2012, https://doi.org/10.5194/hess-16-3561-2012, 2012
C. I. Michailovsky, S. McEnnis, P. A. M. Berry, R. Smith, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 16, 2181–2192, https://doi.org/10.5194/hess-16-2181-2012, https://doi.org/10.5194/hess-16-2181-2012, 2012
H. Hidayat, D. H. Hoekman, M. A. M. Vissers, and A. J. F. Hoitink
Hydrol. Earth Syst. Sci., 16, 1805–1816, https://doi.org/10.5194/hess-16-1805-2012, https://doi.org/10.5194/hess-16-1805-2012, 2012
M. Potes, M. J. Costa, and R. Salgado
Hydrol. Earth Syst. Sci., 16, 1623–1633, https://doi.org/10.5194/hess-16-1623-2012, https://doi.org/10.5194/hess-16-1623-2012, 2012
A. T. Assireu, E. Alcântara, E. M. L. M. Novo, F. Roland, F. S. Pacheco, J. L. Stech, and J. A. Lorenzzetti
Hydrol. Earth Syst. Sci., 15, 3689–3700, https://doi.org/10.5194/hess-15-3689-2011, https://doi.org/10.5194/hess-15-3689-2011, 2011
C. H. Grohmann, C. Riccomini, and M. A. C. Chamani
Hydrol. Earth Syst. Sci., 15, 1493–1504, https://doi.org/10.5194/hess-15-1493-2011, https://doi.org/10.5194/hess-15-1493-2011, 2011
C. C. Abon, C. P. C. David, and N. E. B. Pellejera
Hydrol. Earth Syst. Sci., 15, 1283–1289, https://doi.org/10.5194/hess-15-1283-2011, https://doi.org/10.5194/hess-15-1283-2011, 2011
S. Trevisani, M. Cavalli, and L. Marchi
Hydrol. Earth Syst. Sci., 14, 393–405, https://doi.org/10.5194/hess-14-393-2010, https://doi.org/10.5194/hess-14-393-2010, 2010
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Short summary
We present a novel framework to estimate how much water is lost by ephemeral rivers using satellite imagery and machine learning. This framework proved to be an efficient approach, requiring less fieldwork and generating more data than traditional methods, at a similar accuracy. Furthermore, applying this framework improved our understanding of the water transfer at our study site. Our framework is easily transferable to other ephemeral rivers and could be applied to long time series.
We present a novel framework to estimate how much water is lost by ephemeral rivers using...
