Nonlinear mixed effect modelling for improved estimation of water retention and infiltration parameters

Omuto, T.C.; Minasny, Budiman; McBratney, Alex B.; Biamah, E.K

doi:10.1016/j.jhydrol.2006.05.006

Cited by 16 publications

(16 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dourado-Neto et al, 2000). The isolated treatment-specific model fitting has three main disadvantages: (i) comparison of SWRC between treatments via formal statistical tests is not possible due to the absence of an error structure that accounts for overall variance within treatments; (ii) autocorrelations among random errors of moisture measurements taken in the same sample unit (the cylinder) under different matric potentials are ignored, leading to incorrect quantification of model uncertainty; and (iii) the spatial variability, likely to be high under field conditions, cannot be fully accounted for (Omuto et al, 2006). In this study we propose the use of a nonlinear mixed (NLM) model to overcome these disadvantages.…”

Section: T De Melo Carvalho Et Al: Biochar Increases Plant-availmentioning

confidence: 99%

“…By adopting such an approach, the quantification of uncertainty of shape parameters α and n and the test of the null hypothesis of interest were performed considering the overall variance of soil moisture arising from within treatments variance. Further, the NLM model permits accounting for potential random effects associated with plot location, as proposed by Omuto et al (2006). In our study, correlations among measurements taken within the same sample unit (one cylinder per plot for each soil depth) were accounted for by including plot as a random effect u in the model.…”

Section: Measurements On Soil Wrc and The Modelling Of Swrcsmentioning

confidence: 99%

See 1 more Smart Citation

Biochar increases plant-available water in a sandy loam soil under an aerobic rice crop system

et al. 2014

View full text Add to dashboard Cite

Abstract. The main objective of this study was to assess the impact of biochar rate (0, 8, 16 and 32 Mg ha −1 ) on the water retention capacity (WRC) of a sandy loam Dystric Plinthosol. The applied biochar was a by-product of slow pyrolysis (∼ 450 • C) of eucalyptus wood, milled to pass through a 2000 µm sieve that resulted in a material with an intrinsic porosity ≤ 10 µm and a specific surface area of ∼ 3.2 m 2 g −1 . The biochar was incorporated into the top 15 cm of the soil under an aerobic rice system. Our study focused on both the effects on WRC and rice yields 2 and 3 years after its application. Undisturbed soil samples were collected from 16 plots in two soil layers (5-10 and 15-20 cm). Soil water retention curves were modelled using a nonlinear mixed model which appropriately accounts for uncertainties inherent of spatial variability and repeated measurements taken within a specific soil sample. We found an increase in plant-available water in the upper soil layer proportional to the rate of biochar, with about 0.8 % for each Mg ha −1 biochar amendment 2 and 3 years after its application. The impact of biochar on soil WRC was most likely related to an effect in overall porosity of the sandy loam soil, which was evident from an increase in saturated soil moisture and macro porosity with 0.5 and 1.6 % for each Mg ha −1 of biochar applied, respectively. The increment in soil WRC did not translate into an increase in rice yield, essentially because in both seasons the amount of rainfall during the critical period for rice production exceeded 650 mm. The use of biochar as a soil amendment can be a worthy strategy to guarantee yield stability under short-term water-limited conditions. Our findings raise the importance of assessing the feasibility of very high application rates of biochar and the inclusion of a detailed analysis of its physical and chemical properties as part of future investigations.

show abstract

Section: T De Melo Carvalho Et Al: Biochar Increases Plant-availmentioning

confidence: 99%

Section: Measurements On Soil Wrc and The Modelling Of Swrcsmentioning

confidence: 99%

Biochar increases plant-available water in a sandy loam soil under an aerobic rice crop system

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Performance of the biexponential model in relating to soil physical conditions was also tested using data from Omuto et al (2006). This dataset contains WRC for topsoil samples from physically degraded and non-degraded sites in the Upper Athi river basin in eastern Kenya.…”

Section: Datamentioning

confidence: 99%

“…WRC model testing on measured data was achieved through the use of nonlinear mixed effects (NLME) approach (Omuto et al, 2006). According to this approach, estimation of WRC model parameters is split into two stages: stage one that involves estimation of average model parameters from the entire datasets and stage two that involves estimation of individual sample parameters as random deviations around average estimates.…”

Section: Nonlinear Mixed-effects Approach For Model Testingmentioning

confidence: 99%

“…According to this approach, estimation of WRC model parameters is split into two stages: stage one that involves estimation of average model parameters from the entire datasets and stage two that involves estimation of individual sample parameters as random deviations around average estimates. The average estimates in this approach are known as fixed-effects and the random deviations around average estimates are known as random-effects (Omuto et al, 2006). NLME approach considers global and individual samples variability and possible WRC model parameter interdependency during parameter estimation process.…”

Section: Nonlinear Mixed-effects Approach For Model Testingmentioning

confidence: 99%

See 1 more Smart Citation

Biexponential model for water retention characteristics

Omuto¹

2009

Geoderma

View full text Add to dashboard Cite

Digital soil assessment in support of a soil information system for monitoring salinization and sodification in agricultural areas

et al. 2022

View full text Add to dashboard Cite

Salinization and sodification are types of degradation associated with the accumulation of salts and alkaline materials in the soil. They gradually advance unnoticed till severe degradation appears if not properly controlled. Relevant soil information is not routinely kept by many countries thus contributing to their advancement particularly in agricultural areas where their impacts have huge consequences on food security. We developed a 3‐step protocol to detect salinization and sodification advancement at different spatial scales and support soil information system development. The first step establishes an indicator database focusing on measured soil Electrical Conductivity (EC), pH, Exchangeable Sodium Percent (ESP), and a suit of environmental covariates. The second step outlines data harmonization strategies and classification of salinization and sodification problems. It also incorporates digital soil mapping for spatial information on salinization or sodification. The third step has time‐series modelling of salinization and sodification using mixed‐effects approach to improve hotspot detection in agricultural areas. The protocol was tested in Afghanistan, Sudan, and Lesotho using time‐series data between 2001 and 2018. It successfully identified salt and soda accumulation at different soil depths with more than 80% accuracy on holdout samples. In Sudan and Afghanistan, it identified topsoils as more prone to salinization than the subsoils and consequently depicted more salt accumulation in topsoils than subsoils in agricultural areas. In Lesotho, it identified emerging subsoil sodification. The protocol has potential for supporting the development of soil information on salinization and sodification which is currently lacking at many national and regional levels.

show abstract

Nonlinear mixed effect modelling for improved estimation of water retention and infiltration parameters

Cited by 16 publications

References 29 publications

Biochar increases plant-available water in a sandy loam soil under an aerobic rice crop system

Biochar increases plant-available water in a sandy loam soil under an aerobic rice crop system

Biexponential model for water retention characteristics

Digital soil assessment in support of a soil information system for monitoring salinization and sodification in agricultural areas

Contact Info

Product

Resources

About