Prediction of Water Retention of Soils from the Humid Tropics by the Nonparametric <i>k</i>‐Nearest Neighbor Approach

Botula, Yves-Dady; Nemes, Attila; Mafuka, Paul; Ranst, Éric Van; Cornelis, Wim

doi:10.2136/vzj2012.0123

Cited by 61 publications

(36 citation statements)

References 70 publications

(126 reference statements)

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“…Working with extensive soil database in the temperate regions, Nemes et al (2006a) have derived regression equations between the k and p term and training data set size. Botula et al (2013) then tested this relation for soils in the humid tropics and obtained similar results. Therefore in this study, we use the proposed formula of Nemes et al (2006a) for determining the designed parameters k and p. More methodological and calculation details on the whole procedure can be found in the works of Botula et al (2013), Nemes et al (2006a,b).…”

Section: K-nearest Neighbors (Knn)mentioning

confidence: 85%

“…Botula et al (2013) then tested this relation for soils in the humid tropics and obtained similar results. Therefore in this study, we use the proposed formula of Nemes et al (2006a) for determining the designed parameters k and p. More methodological and calculation details on the whole procedure can be found in the works of Botula et al (2013), Nemes et al (2006a,b). The kNN algorithm used in this study was adapted from the variants developed by Nemes et al (2006a) and Botula et al (2013).…”

Section: K-nearest Neighbors (Knn)mentioning

confidence: 85%

“…Therefore in this study, we use the proposed formula of Nemes et al (2006a) for determining the designed parameters k and p. More methodological and calculation details on the whole procedure can be found in the works of Botula et al (2013), Nemes et al (2006a,b). The kNN algorithm used in this study was adapted from the variants developed by Nemes et al (2006a) and Botula et al (2013). The implementation of the kNN algorithm was done in the MATLAB R2014a environment (the MathWorks).…”

Section: K-nearest Neighbors (Knn)mentioning

confidence: 99%

See 2 more Smart Citations

Impact of regression methods on improved effects of soil structure on soil water retention estimates

Nguyen

Pue

et al. 2015

Journal of Hydrology

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Section: K-nearest Neighbors (Knn)mentioning

confidence: 85%

Section: K-nearest Neighbors (Knn)mentioning

confidence: 85%

Section: K-nearest Neighbors (Knn)mentioning

confidence: 99%

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Impact of regression methods on improved effects of soil structure on soil water retention estimates

Nguyen

Pue

et al. 2015

Journal of Hydrology

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“…Recently, Patil et al (2012) used the k-NN software developed by Nemes et al (2008) to estimate water content at -33 and -1500 kPa of 157 shrinkswell soils in India to derive their AWC. The ability of the k-NN approach to estimate water content at different matric potentials of highly weathered soils in the humid tropics was tested for the first time by Botula et al (2013). They applied a variant of the k-NN technique to predict soil water retention in a humid tropical region of Central Africa with high accuracy.…”

Section: K-nearest Neighbormentioning

confidence: 99%

Pedotransfer functions to predict water retention for soils of the humid tropics: a review

Botula

Ranst

Cornelis

2014

Rev. Bras. Ciênc. Solo

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SUMMARYOver the past three decades, pedotransfer functions (PTFs) have been widely used by soil scientists to estimate soils properties in temperate regions in response to the lack of soil data for these regions. Several authors indicated that little effort has been dedicated to the prediction of soil properties in the humid tropics, where the need for soil property information is of even greater priority. The aim of this paper is to provide an up-to-date repository of past and recently published articles as well as papers from proceedings of events dealing with water-retention PTFs for soils of the humid tropics. Of the 35 publications found in the literature on PTFs for prediction of water retention of soils of the humid tropics, 91 % of the PTFs are based on an empirical approach, and only 9 % are based on a semiphysical approach. Of the empirical PTFs, 97 % are continuous, and 3 % (one) is a class PTF; of the empirical PTFs, 97 % are based on multiple linear and polynomial regression of n th order techniques, and 3 % (one) is based on the k-Nearest Neighbor approach; 84 % of the continuous PTFs are point-based, and 16 % are parameter-based; 97 % of the continuous PTFs are equation-based PTFs, and 3 % (one) is based on pattern recognition. Additionally, it was found that 26 % of the tropical water-retention PTFs were developed for soils in Brazil, 26 % for soils in India, 11 % for soils in other countries in America, and 11 % for soils in other countries in Africa.Index terms: physical soil properties, soil hydraulic properties, tropical soils, data-mining techniques.( Durante as últimas três décadas, as funções de pedotransferência (FPTs) foram amplamente utilizadas pelos cientistas para estimar propriedades de solos em regiões temperadas para responder à falta de banco de dados deles. Diferentes autores indicaram que poucos esforços foram dedicados à estimação de propriedades de solo nos trópicos úmidos, onde a necessidade de informações sobre as propriedades dos solos é ainda mais prioritária. Este artigo buscou proporcionar um inventário atualizado dos artigos, assim como trabalhos publicados recentemente em anais de congressos sobre FPTs com retenção de água para solos nos trópicos úmidos. Entre 35 publicações encontradas na literatura sobre as FPTs para a estimação da retenção de água dos solos nos trópicos úmidos, 91 % dos FPTs estão com base num enfoque empírico e somente 9 %, num enfoque semifísico. Das FPTs empíricas, 97 % são contínuas e 3 % (uma) é uma classe. Das FPTs empíricas, 97 % são com base em regressão multilinear e polinomial de n técnicas de ordenamento e 3 % (uma), no método k-NN; 84 % das FPTs contínuas são com base em pontos e 16 %, em parâmetros; 97 % das FPTs contínuas são baseadas em equação e 3 % (uma), no reconhecimento padrão. Adicionalmente, foi encontrado que 26 % das FPTs da retenção de água "tropical" foram desenvolvidas para solos no Brasil; 26 % , na Índia; 11 %, em outros países na América; e 11 %, em outros países na África.Termos de indexação: meteorização de solos, sol...

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“…The most important topics in building and developing PTFs to estimate the water retention of soils are the determination of the role of additional soil properties on water retention (eg more detailed information about PSD, soil structural information, and morphological properties) (Vereeckeen et al, 2010), and the development of new data handling techniques, such as artificial neural networks, regression trees, or inference systems (Botula et al, 2013;Minasny et al, 2004). Even though the promising new statistical techniques might offer higher prediction ability, MLR has the advantage of simple operation with sufficient accuracy to estimate soil water retention characteristic (SWRC) (Minasny et al, 1999;Vereecken et al, 1989).…”

Section: Introductionmentioning

confidence: 99%

Preliminary investigation to estimate soil NAPL retention using parametric pedotransfer functions

Hernádi¹,

Makó²

2014

International Agrophysics

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A b s t r a c t. Organic liquid retention of soils is a primary input variable for modelling the nonaqueous phase liquid transport and behaviour in the subsurface. In environmental and soil physical practice, it is mainly determined by scaling based on the water retention of soils or with charts of average empirical values of organic liquid retention or the fitting parameters of hydraulic functions. Predicting the fitting parameters of organic liquid retention curves with pedotransfer functions might be a promising alternative method, but this topic has only been researched to a limited extent. Thus we investigated the applicability of different hydraulic functions (3-and 4-parameter form of the van Genuchten equation and Brutsaert equation) for fitting organic liquid retention characteristics. Multivariate linear regression was used to build and develop pedotransfer functions, modelling relations between original and transformed values of basic soil properties and organic liquid retention. We attempted to generate parametric pedotransfer functions. According to our results, the applicability of hydraulic functions for fitting nonaqueous phase liquid retention curves to the experimental data was proven. The investigations gave promising results for the possibility to estimate soil nonaqueous phase liquid retention with parametric pedotransfer functions.

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Prediction of Water Retention of Soils from the Humid Tropics by the Nonparametric k‐Nearest Neighbor Approach

Cited by 61 publications

References 70 publications

Impact of regression methods on improved effects of soil structure on soil water retention estimates

Impact of regression methods on improved effects of soil structure on soil water retention estimates

Pedotransfer functions to predict water retention for soils of the humid tropics: a review

Preliminary investigation to estimate soil NAPL retention using parametric pedotransfer functions

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