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Hydrological modelling of karst catchment using lumped conceptual and data mining models

https://doi.org/10.1016/j.jhydrol.2019.06.036

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Karst water resources in a changing world: Review of hydrological modeling approaches

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Evaluation of the ability of an artificial neural network model to simulate the input-output responses of a large karstic aquifer: the La Rochefoucauld aquifer (Charente, France)

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Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting

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Karst spring catchment: an example from Dinaric karst

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Hydrological stream flow modelling using soil and water assessment tool (SWAT) and neural networks (NNs) for the Limkheda watershed, Gujarat, India

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River flow forecasting through conceptual models part I — A discussion of principles

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Prediction of flow rate of karstic springs using support vector machines

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Characterisation of selected karst springs in Slovenia by means of a time series analysis

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airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 1.7.6

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inferredcites →https://doi.org/10.5860/choice.45-3808openalex-snapshot

Karst hydrogeology and geomorphology

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Reply on RC1

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Comment on hess-2021-403

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Étude de la vulnérabilité et de la réactivité des hydrosystèmes alluviaux face aux changements globaux. Exemple de la rivière Allier et de sa nappe alluviale.

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