2024
DOI: 10.1016/j.ejrh.2024.101718
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Suitability of ERA5-Land reanalysis dataset for hydrological modelling in the Alpine region

Daniele Dalla Torre,
Nicola Di Marco,
Andrea Menapace
et al.
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Cited by 7 publications
(1 citation statement)
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“…Bias correction of meteorological and hydrometric datasets is crucial in hydrology because of input uncertainty, such as measurement errors, model uncertainty, and parametric uncertainty [21,22]. Nowadays, bias correction has become a compulsory process when integrating hydrological models with climate change datasets, which inherently contain biases from systematic and random errors derived by the climate models [23].…”
Section: Introductionmentioning
confidence: 99%
“…Bias correction of meteorological and hydrometric datasets is crucial in hydrology because of input uncertainty, such as measurement errors, model uncertainty, and parametric uncertainty [21,22]. Nowadays, bias correction has become a compulsory process when integrating hydrological models with climate change datasets, which inherently contain biases from systematic and random errors derived by the climate models [23].…”
Section: Introductionmentioning
confidence: 99%