Articles | Volume 11, issue 3
https://doi.org/10.5194/esd-11-755-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-755-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Groundwater storage dynamics in the world's large aquifer systems from GRACE: uncertainty and role of extreme precipitation
Mohammad Shamsudduha
CORRESPONDING AUTHOR
Department of Geography, University College London, London, UK
Department of Geography, University of Sussex, Falmer, Brighton, UK
Richard G. Taylor
Department of Geography, University College London, London, UK
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This study advances groundwater research using a high-resolution random forest model, revealing new recharge areas and spatial variability, mainly in humid regions. Limited data in rainy zones is a constraint for the model. Our findings underscore the promise of machine learning for large-scale groundwater modelling while further emphasizing the importance of data collection for robust results.
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Knowledge of the relationship between climate and groundwater is limited and typically undermined by the scale, duration and accessibility of observations. Using monthly satellite measurements newly compiled over 14 years in the tropics and sub-tropics, we show that the imprint of precipitation history on groundwater, i.e. hydraulic memory, is longer in drylands than humid environments with important implications for the understanding and management of groundwater resources under climate change.
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This study tests the phase and amplitude of GRACE TWS signals in the Upper Nile Basin from five commonly used gridded products (NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS) using in situ data and soil moisture from the Global Land Data Assimilation System. Resolution of changes in groundwater storage (ΔGWS) from GRACE is greatly constrained by the uncertain simulated soil moisture storage and the low amplitude in ΔGWS observed in deeply weathered crystalline rocks in the Upper Nile Basin.
Anna Pazola, Mohammad Shamsudduha, Jon French, Alan M. MacDonald, Tamiru Abiye, Ibrahim Baba Goni, and Richard G. Taylor
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This study advances groundwater research using a high-resolution random forest model, revealing new recharge areas and spatial variability, mainly in humid regions. Limited data in rainy zones is a constraint for the model. Our findings underscore the promise of machine learning for large-scale groundwater modelling while further emphasizing the importance of data collection for robust results.
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Groundwater is increasingly being included in large-scale (continental to global) land surface and hydrologic simulations. However, it is challenging to evaluate these simulations because groundwater is
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Simon Opie, Richard G. Taylor, Chris M. Brierley, Mohammad Shamsudduha, and Mark O. Cuthbert
Earth Syst. Dynam., 11, 775–791, https://doi.org/10.5194/esd-11-775-2020, https://doi.org/10.5194/esd-11-775-2020, 2020
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Knowledge of the relationship between climate and groundwater is limited and typically undermined by the scale, duration and accessibility of observations. Using monthly satellite measurements newly compiled over 14 years in the tropics and sub-tropics, we show that the imprint of precipitation history on groundwater, i.e. hydraulic memory, is longer in drylands than humid environments with important implications for the understanding and management of groundwater resources under climate change.
Tom Gleeson, Thorsten Wagener, Petra Döll, Samuel C. Zipper, Charles West, Yoshihide Wada, Richard Taylor, Bridget Scanlon, Rafael Rosolem, Shams Rahman, Nurudeen Oshinlaja, Reed Maxwell, Min-Hui Lo, Hyungjun Kim, Mary Hill, Andreas Hartmann, Graham Fogg, James S. Famiglietti, Agnès Ducharne, Inge de Graaf, Mark Cuthbert, Laura Condon, Etienne Bresciani, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-378, https://doi.org/10.5194/hess-2020-378, 2020
Revised manuscript not accepted
Seshagiri Rao Kolusu, Mohammad Shamsudduha, Martin C. Todd, Richard G. Taylor, David Seddon, Japhet J. Kashaigili, Girma Y. Ebrahim, Mark O. Cuthbert, James P. R. Sorensen, Karen G. Villholth, Alan M. MacDonald, and Dave A. MacLeod
Hydrol. Earth Syst. Sci., 23, 1751–1762, https://doi.org/10.5194/hess-23-1751-2019, https://doi.org/10.5194/hess-23-1751-2019, 2019
Mohammad Shamsudduha, Richard G. Taylor, Darren Jones, Laurent Longuevergne, Michael Owor, and Callist Tindimugaya
Hydrol. Earth Syst. Sci., 21, 4533–4549, https://doi.org/10.5194/hess-21-4533-2017, https://doi.org/10.5194/hess-21-4533-2017, 2017
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This study tests the phase and amplitude of GRACE TWS signals in the Upper Nile Basin from five commonly used gridded products (NASA's GRCTellus: CSR, JPL, GFZ; JPL-Mascons; GRGS) using in situ data and soil moisture from the Global Land Data Assimilation System. Resolution of changes in groundwater storage (ΔGWS) from GRACE is greatly constrained by the uncertain simulated soil moisture storage and the low amplitude in ΔGWS observed in deeply weathered crystalline rocks in the Upper Nile Basin.
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S. P. K. Bowring, L. M. Miller, L. Ganzeveld, and A. Kleidon
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Short summary
Recent assessments of the sustainability of global groundwater resources using the Gravity Recovery and Climate Experiment (GRACE) satellites assume that the underlying trends are linear. Here, we assess recent changes in groundwater storage (ΔGWS) in the world’s large aquifer systems using an ensemble of GRACE datasets and show that trends are mostly non-linear. Non-linearity in ΔGWS derives, in part, from the episodic nature of groundwater replenishment associated with extreme precipitation.
Recent assessments of the sustainability of global groundwater resources using the Gravity...
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