Data from: Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity

Parametric and nonparametric supervised machine learning techniques were used to estimate saturated and near saturated hydraulic conductivities (Ks, K10) from easily measurable soil properties including name of pedological horizon (HOR), soil texture (sand, silt & clay), organic matter (OM), bul...

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Bibliographische Detailangaben

Hauptverfasser:	Kotlar, Ali Mehmandoost, Iversen, Bo V., De Jong Van Lier, Quirijn
Format:	Dataset
Sprache:	eng
Online-Zugang:	Volltext bestellen
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