Journal article
Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges
Nans Addor, Hong X Do, Camila Alvarez-Garreton, Gemma Coxon, Keirnan Fowler, Pablo A Mendoza
Hydrological Sciences Journal | Taylor & Francis | Published : 2020
Abstract
Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities, yet they are also limited by their lack of comparability, uncertainty estimates and characterization of human impacts. This article (i) underscores the key role of LSH datasets in hydrological studies, (ii) provides a review of currently available LSH datasets, (iii) highlights current li..
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Grants
Awarded by Swiss National Science Foundation
Awarded by Australia Awards Scholarship
Awarded by University of Michigan Research Fellowship
Awarded by FONDECYT
Awarded by Center for Climate and Resilience Research (CR2)
Awarded by NERC MaRIUS: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity
Awarded by Bureau of Meteorology, Australia
Awarded by Australian Research Council
Awarded by CONICYT-PIA Project
Funding Acknowledgements
NA is supported by the Swiss National Science Foundation (fellowships P2ZHP2_161963 and P400P2_180791). HXD acknowledges support from the Australia Awards Scholarship (ST000HKE6), the University of Adelaide D R Stranks Fellowship and the University of Michigan Research Fellowship (grant number U064474). CAG is funded by FONDECYT postdoctoral grant no. 3170428 and the Center for Climate and Resilience Research (CR2, CONICYT/FONDAP/15110009). GC is supported by NERC MaRIUS: Managing the Risks, Impacts and Uncertainties of droughts and water Scarcity (grant NE/L010399/1). KF acknowledges the support of the Bureau of Meteorology, Australia (TP705654) and the Australian Research Council (LP170100598). PAM acknowledges support from FONDECYT postdoctoral grant No. 3170079 and CONICYT-PIA Project AFB180004.