Data for the article: "Root zone soil moisture estimation with Random Forests"

The dataset contains information on soil moisture, meteorological conditions, land cover, and soil hydrological groups for the soil moisture stations installed within the Raam soil moisture network. The network has a total of 15 stations within the Raam catchment, located in the southeastern portion of the Netherlands. The datasets covers the periods from April 2016 to December 2018. It was used for predicting root zone soil moisture using a Random Forest model and a 1-dimensional process-based model. For each station, daily in situ measurements of surface soil moisture (SSM) at 5 cm and zone weighted depth-averaged root zone soil moisture (RZSM) are given. The meteorological conditions are obtained from daily datasets available from KNMI. First, the measurements from KNMI meteorological stations are interpolated in order to get spatially distributed values covering the study sites. The values from the interpolated maps were extracted for each point in the Raam network. The vegetation characteristics are represented by leaf area index (LAI) obtained from MODIS. The crops at each station for each year are obtained from fieldwork data. The BOdemFysische Eenheden Kaart (BOFEK2012, Wosten et al., 2013), which is a map of soil hydro-physical properties for the Netherlands, was the basis for the information on the soil groups at the study sites.

Bibliographic Details

Main Authors:	Carranza, Coleen, Nolet, Corjan, Pezij, Michiel, van der Ploeg, Martine
Format:	Dataset biblioteca
Published:	Wageningen University & Research
Subjects:	Random Forests modeling approach, soil moisture contents,
Online Access:	https://research.wur.nl/en/datasets/data-for-the-article-root-zone-soil-moisture-estimation-with-rand
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