Identifying Covariates to Assess the Spatial Variability of Saturated Soil Hydraulic Conductivity Using Robust Cokriging
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ORIGINAL PAPER
Identifying Covariates to Assess the Spatial Variability of Saturated Soil Hydraulic Conductivity Using Robust Cokriging at the Watershed Scale Mauricio Fornalski Soares 1 & Luana Nunes Centeno 2 & Luís Carlos Timm 3 Douglas Rodrigo Kaiser 5 & Samuel Beskow 1
&
Carlos Rogério Mello 4 &
Received: 30 September 2019 / Accepted: 11 March 2020 # Sociedad Chilena de la Ciencia del Suelo 2020
Abstract The mapping of saturated soil hydraulic conductivity (KSat) is essential to understanding soil water dynamics and is a sensitive input in hydrological modeling. The objectives of this study were to provide a reference for the selection of soil hydrology and other environmental attributes that can be used as covariates for estimating KSat and to compare the efficiency of univariate ordinary kriging versus ordinary robust cokriging, using selected soil hydrology and environmental attributes. Data sets were obtained from a sample grid of 179 points established in the Ellert creek watershed (ECW), located in Rio Grande do Sul state, Southern Brazil. KSat, macroporosity, microporosity, total porosity, and bulk density were determined from soil sampled at each point. Data of land use and elevation were also applied. All data sets were firstly submitted to classical statistics. Boxplot graphics were constructed to evaluate the relationship between KSat and land uses. Spearman coefficient of correlation between KSat and the other attributes was also assessed. For the assortment of covariates, cluster analysis was applied. Classical and robust estimators were applied to calculate the auto and cross-semivariograms and hereafter the ordinary kriging and cokriging. The Spearman coefficient showed some inconsistencies among the applied variables, suggesting that the multivariate method was more appropriate. All cross-semivariograms, except for land use, showed results with better accuracy than the auto-semivariograms. From the methods applied, the best estimates of KSat were obtained using the robust cokriging method, using macroporosity and soil bulk density as covariates. Keywords Cross-semivariogram . Robust estimation . Covariate
* Luís Carlos Timm [email protected] Mauricio Fornalski Soares [email protected] Luana Nunes Centeno [email protected]
1
Center of Technological Development, Federal University of Pelotas, Campus Porto, Rua Gomes Carneiro, n. 01, Pelotas, Rio Grande do Sul 96010-610, Brazil
2
Center of Technological Development, Federal University of Pelotas, Pelotas, Rio Grande do Sul, Brazil
3
Department of Rural Engineering, Faculty of Agronomy, Federal University of Pelotas, Campus Universitário s/n, Capao do Leao, Rio Grande do Sul 96010-900, Brazil
4
Water Resources Department, Federal University of Lavras, Lavras, Minas Gerais, Brazil
5
Federal University of Fronteira Sul, Cerro Largo, RS, Brazil
Carlos Rogério Mello [email protected] Douglas Rodrigo Kaiser [email protected] Samuel Beskow [email protected]
J Soil Sci Plant Nutr
1 Introduction
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