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 also available.
You can install and load the released version of soilphysics from GitHub with:
install.packages("devtools")
devtools::install_github("arsilva87/soilphysics")
library(soilphysics) Using the function stressTraffic, it it possible calculate the contact area, stress distribuition and stress propagation based on the SoilFlex model.
# Usage
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)
# Results
---------- Boundaries of Contact Area
Parameters Value Units
1 Max Stress 289.00 kPa
2 Contact Area 0.29 m^2
3 Area Length 0.83 m
4 Area Width 0.40 m
---------- Wheel Loads
Parameters Loads (kg)
1 Applied Wheel Load 4000
2 Modeled Wheel Load 4030
3 Diference -30
---------- Stress Propagation
Layers (m) Zstress p
1 0.05 275 169
2 0.10 262 132
3 0.30 154 62
4 0.50 85 31
5 0.70 51 18
6 1.00 28 10
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).
# Usage
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))
# Results
iBD fBD vi vf I%
1 1.55 1.6385 1.7226 1.6295 5.71
mois <- c(0.083, 0.092, 0.108, 0.126, 0.135)
bulk <- c(1.86, 1.92, 1.95, 1.90, 1.87)
# Usage
criticalmoisture(theta = mois, Bd = bulk)
# Results
Critical Moisture and Maximum Bulk Density
Sample 1
Intercept 0.4825950
mois 26.9265767
mois^2 -123.7120431
R.squared 0.9515476
n 5.0000000
critical.mois 0.1088276
max.bulk 1.9477727
Quantifying the soil water availability for plants through the IWC approach:
# Usage
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)
# Results
IWC EI h.Range
EKa(h, hos) 0.0144000 0.9600 66.43 - 139.49
EK(h, hos) 0.0405000 5.3700 139.49 - 330
C(h, hos) 0.0846000 49.4800 330 - 2471.44
ER(h, hos) 0.0288000 87.1200 2471.44 - 15000
ERKdry(h, hos) 0.0006000 4.9100 12000 - 15000
Sum 0.1689139 147.8336 0 - 15000
Quantifying the soil water availability for plants through the LLWR approach:
# Usage
data(skp1994)
ex1 <- 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:
# Usage
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)
# Results
$CRITICAL_LIMITS
theta potential
AIR 0.2600 41.02
FC 0.2285 100.00
PWP 0.1428 15000.00
PR 0.1939 356.65
$LLRW_LLMPR
Upper Lower Range
LLWR 0.2285 0.1939 0.0346
LLMPR 100.0000 356.6500 256.6500
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)
# Usage
sigmaP(VR, pres, method = "casagrande", n4VCL = 2)
# Results
Preconsolidation stress: 104.2536
Method: casagrande, with mcp equal to 1.7885
Compression index: 0.2093
Swelling index: 0.0179 Fitting 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)
# Usage
fitsoilwater(theta=w, x=h, ylim=c(0.1,0.6))
# Results
Parameters:
Estimate Std. Error t value Pr(>|t|)
theta_R 0.16761 0.01272 13.179 0.000192 ***
theta_S 0.56531 0.01092 51.786 8.32e-07 ***
alpha 0.04748 0.01177 4.035 0.015671 *
n 1.52926 0.09579 15.965 9.00e-05 ***
---
# Usage
Sindex(theta_R=0, theta_S=0.395, alpha=0.0217,
n=1.103)
# Results
The S Index
h_i : 395.4757
theta_i : 0.3139
|S| : 0.0296
Soil physical quality : Poor data(SoilAggregate)
head(SoilAggregate)
ID D3 D1.5 D0.75 D0.375 D0.178 D0.053
1 A1 25.80 7.55 5.50 5.10 3.00 3.05
2 A2 19.85 5.30 7.45 7.30 4.40 5.70
3 A3 7.10 9.80 11.60 8.10 2.35 11.05
4 B1 6.10 4.85 11.20 13.10 7.15 7.60
5 B2 12.00 6.30 16.10 7.35 3.70 4.55
6 B3 14.10 6.15 8.80 11.05 4.60 5.30
classes <- c(3, 1.5, 0.75, 0.375, 0.178, 0.053)
# Usage
out <- aggreg.stability(sample.id = SoilAggregate[ ,1],
dm.classes = classes,
aggre.mass = SoilAggregate[ ,-1])
# Results
head(out)
sample.id MWD GMD total.mass X3 X1.5 X0.75 X0.375 X0.178 X0.053
1 A1 1.909163 1.2382214 50 52 15 11 10 6 6
2 A2 1.538206 0.8239103 50 40 11 15 15 9 11
3 A3 0.974829 0.4865272 50 14 20 23 16 5 22
4 B1 0.811260 0.4311214 50 12 10 22 26 14 15
5 B2 1.223620 0.7282644 50 24 13 32 15 7 9
6 B3 1.267369 0.6853162 50 28 12 18 22 9 11Sedimentation time of soil particle (Stokes' law): https://renatoagro.shinyapps.io/stokesapp/
Exploring water retention curve using van Genuchten's model: https://soilphysics.shinyapps.io/wrcAPP/
Soil Aggregate-Size Distribution: https://renatoagro.shinyapps.io/Agre/
Usual Least Limiting Water Range (LLWR): https://soilphysics.shinyapps.io/LLWRAPP/
Water suction at the point of hydraulic cut-off (Dexter et al. 2012): https://soilphysics.shinyapps.io/h_cutoff/
LLWR and LLMPR: https://soilphysics.shinyapps.io/LLWR_LLMPR/
PredComp 1.0: https://appsoilphysics.shinyapps.io/PredComp/
fisoilwater: https://appsoilphysics.shinyapps.io/fitsoilwaterAPP/
Automatically fit the Water Retention Curve online:
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 Issue or reach out directly by e-mail: [email protected] or [email protected].
Anderson R. da Silva & Renato P. de Lima