knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )

In this package you will find a series of functions for soil physics data analysis. These functions includes five models of water retention curve, seven methods of soil precompression stress, least limiting water range (LLWR), Integral Water Capacity (IWC), soil penetration resistance curve by Busscher's model, calculation of Soil Aggregate-Size Distribution, S Index, critical soil moisture and maximum bulk density using data from Proctor test, calculation of equivalent pore radius as a function of soil water tension, simulation of sedimentation time of soil particles through Stokes' law, simulation of soil pore size distribution, calculation of the hydraulic cut-off introduced by Dexter et al. (2008) and simulation of soil compaction induced by agricultural field traffic. Other utilities like functions to calculate the void ratio and to determine the maximum curvature point are available.

From CRAN:

install.packages("soilphysics")

Or you can install the development version from GitHub:

install.packages("devtools") devtools::install_github("arsilva87/soilphysics")

Then, load it

```
library(soilphysics)
```

Using the function stressTraffic, it it possible calculate the contact area, stress distribuition and stress propagation based on the SoilFlex model.

stress <- stressTraffic(inflation.pressure=200, recommended.pressure=200, tyre.diameter=1.8, tyre.width=0.4, wheel.load=4000, conc.factor=c(4,5,5,5,5,5), layers=c(0.05,0.1,0.3,0.5,0.7,1), plot.contact.area = TRUE)

Unsing the funtion soilDeformation, it is possible calculates the bulk density variation as a function of the applied mean normal stress using critical state theory, by O'Sullivan and Robertson (1996).

soilDeformation(stress = 300, p.density = 2.67, iBD = 1.55, N = 1.9392, CI = 0.06037, k = 0.00608, k2 = 0.01916, m = 1.3,graph=TRUE,ylim=c(1.4,2.0))

mois <- c(0.083, 0.092, 0.108, 0.126, 0.135) bulk <- c(1.86, 1.92, 1.95, 1.90, 1.87) criticalmoisture(theta = mois, Bd = bulk)

Quantifying the soil water availability for plants through the IWC approach:

iwc(theta_R = 0.166, theta_S = 0.569, alpha = 0.029, n = 1.308, a = 0.203, b = 0.256, hos = 200, graph = TRUE)

Quantifying the soil water availability for plants through the LLWR approach:

# Usage data(skp1994) with(skp1994, llwr(theta = W, h = h, Bd = BD, Pr = PR, particle.density = 2.65, air = 0.1, critical.PR = 2, h.FC = 100, h.WP = 15000))

Quantifying the LLWR using van Genuchten's parameters:

par(mfrow=c(1,2)) llwr_llmpr(thetaR=0.1180, thetaS=0.36, alpha=0.133, n=1.30, d=0.005, e=-2.93, f=3.54, PD=2.65, critical.PR=4, h.FC=100, h.PWP=15000, air.porosity=0.1, labels=c("AFP", "FC","PWP", "PR"), graph1=TRUE,graph2=FALSE, ylab=expression(LLMPR~(hPa)), ylim=c(15000,1)) mtext(expression("Bulk density"~(Mg~m^-3)),1,line=2.2, cex=0.8) llwr_llmpr(thetaR=0.1180, thetaS=0.36, alpha=0.133, n=1.30, d=0.005, e=-2.93, f=3.54, PD=2.65, critical.PR=4, h.FC=100, h.PWP=15000, air.porosity=0.1, labels=c("AFP", "FC","PWP", "PR"), graph1=FALSE,graph2=TRUE, ylab=expression(LLMPR~(hPa)), ylim=c(0.1,0.5)) mtext(expression("Bulk density"~(Mg~m^-3)),1,line=2.2, cex=0.8)

Estimating the precompression stress by several methods:

pres <- c(1, 12.5, 25, 50, 100, 200, 400, 800, 1600) VR <- c(0.846, 0.829, 0.820, 0.802, 0.767, 0.717, 0.660, 0.595, 0.532) sigmaP(VR, pres, method = "casagrande", n4VCL = 2)

Fitting (interactive!) water retention curve using van Genuchten's model

h <- c(0.001, 50.65, 293.77, 790.14, 992.74, 5065, 10130, 15195) w <- c(0.5650, 0.4013, 0.2502, 0.2324, 0.2307, 0.1926, 0.1812, 0.1730) fitsoilwater(theta=w, x=h, ylim=c(0.1,0.6))

Sindex(theta_R=0, theta_S=0.395, alpha=0.0217, n=1.103, xlim = c(0, 1000))

data(SoilAggregate) head(SoilAggregate) classes <- c(3, 1.5, 0.75, 0.375, 0.178, 0.053) out <- aggreg.stability(sample.id = SoilAggregate[ ,1], dm.classes = classes, aggre.mass = SoilAggregate[ ,-1]) head(out)

De Lima, R.P.; Da Silva, A.R.; Da Silva, A.P. (2021) soilphysics: An R package for simulation of soil compaction induced by agricultural field traffic. *SOIL and TILLAGE RESEARCH*, 206: 104824. DOI: https://doi.org/10.1016/j.still.2020.104824

De Lima, R.P.; Tormena, C.A.; Figueiredo, G.C; Da Silva, A.R.; Rolim, M.M. (2020) Least limiting water and matric potential ranges of agricultural soils with calculated physical restriction thresholds. *Agricultural Water Management*, 240: 106299. DOI: https://doi.org/10.1016/j.agwat.2020.106299

Da Silva, A.R.; De Lima, R.P. (2017) Determination of maximum curvature point with the R package soilphysics. *International Journal of Current Research*, 9: 45241-45245.

De Lima, R.P.; Da Silva, A.R.; Da Silva, A.P.; Leao, T.P.; Mosaddeghi, M.R. (2016) soilphysics: an R package for calculating soil water availability to plants by different soil physical indices. *Computers and Eletronics in Agriculture*, 120: 63-71. DOI: https://doi.org/10.1016/j.compag.2015.11.003

Da Silva, A.R.; De Lima, R.P. (2015) soilphysics: an R package to determine soil preconsolidation pressure. *Computers and Geosciences*, 84: 54-60. DOI: https://doi.org/10.1016/j.cageo.2015.08.008

soilphysics is an ongoing project. Then, contributions are very welcome. If you have a question or have found a bug, please open an or reach out directly by e-mail: anderson.silva@ifgoiano.edu.br or renato_agro_@hotmail.com.

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