Evaluation of pedotransfer functions to estimate some of soil hydraulic characteristics in North Africa: a case study from Morocco

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dc.contributor.authorBeniaich, Adnane
dc.contributor.authorOtten, Wilfred
dc.contributor.authorShin, Ho-Chul
dc.contributor.authorCooper, Hannah
dc.contributor.authorRickson, R. Jane
dc.contributor.authorSoulaimani, Azia
dc.contributor.authorEl Gharous, Mohamed
dc.date.accessioned2023-02-15T11:02:36Z
dc.date.available2023-02-15T11:02:36Z
dc.date.issued2023-02-08
dc.description.abstractSoil hydraulic properties are an important factor to optimize and adapt water management for a given crop. Pedotransfer functions (PTFs) present a solution to predict soil variables such as hydraulic properties, using fundamental soil properties. In this research, we compared two sources of soil information: iSDAsoil data and field data, in four regions in Morocco. We then used this data to evaluate published data and developed new PTFs using soil information to estimate soil gravimetric moisture content at saturation (w0), field capacity (w330) and permanent wilting point (w15000). A total of 331 samples were collected from four regions: Doukkala, Gharb-Loukous, Moulouya and Tadla. The data was divided into calibration and validation datasets. For development of different PTFs, we used simple linear regression, multiple linear regression, regression tree, Cubist algorithm, and random forest approaches. PTFs developed by Dijkerman (Geoderma, 1988, 42, 29–49) presented the best performance, showing lower RMSE, Bias and MAE compared to other PTFs. Using multiple linear regression to develop PTFs, models based on clay, silt and soil organic matter as input variables showed the best performance after calibration (R2 of 0.590, 0.785, 0.786 for w0, w330, and w15000, respectively). Regarding the techniques based on machine learning, random forest showed the best performance after calibration compared with other algorithms (R2 of 0.930, 0.955, 0.954 for w0, w330, and w15000, respectively). PTFs represent a low cost and easy technique to estimate soil hydraulic properties, to improve water management efficiency for the farmers.en_UK
dc.identifier.citationBeniaich A, Otten W, Shin HC, et al., (2023) Evaluation of pedotransfer functions to estimate some of soil hydraulic characteristics in North Africa: a case study from Morocco. Frontiers in Environmental Science, Volume 11, February 2023, Article number 1090688en_UK
dc.identifier.eissn2296-665X
dc.identifier.urihttps://doi.org/10.3389/fenvs.2023.1090688
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19193
dc.language.isoenen_UK
dc.publisherFrontiersen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectsoil hydraulic propertiesen_UK
dc.subjectwilting pointen_UK
dc.subjectfield capacityen_UK
dc.subjectmultiple linear regressionen_UK
dc.subjectregression treeen_UK
dc.subjectcubist algorithmen_UK
dc.subjectrandom foresten_UK
dc.subjectensemble classifieren_UK
dc.titleEvaluation of pedotransfer functions to estimate some of soil hydraulic characteristics in North Africa: a case study from Moroccoen_UK
dc.typeArticleen_UK

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