AWCPTF: Available soil water capacity

In GSIF: Global Soil Information Facilities

Description

Derive available soil water capacity (in cubic-meter per cubic-meter) based on a Pedo-Transfer Function developed using the Africa Soil Profile Database (Hodnett and Tomasella, 2002; Wösten et al. 2013).

Usage

AWCPTF(SNDPPT, SLTPPT, CLYPPT, ORCDRC, 
    BLD=1400, CEC, PHIHOX, h1=-10, h2=-20, h3=-31.6, 
    pwp=-1585, PTF.coef, fix.values=TRUE, print.coef=TRUE)

Arguments

SNDPPT	numeric; sand content in percent
SLTPPT	numeric; silt content in percent
CLYPPT	numeric; clay content in percent
ORCDRC	numeric; soil organic carbon concentration in permille or g / kg
BLD	numeric; bulk density in kg / cubic-meter for the horizon/solum
CEC	numeric; Cation Exchange Capacity in cmol per kilogram
PHIHOX	numeric; soil pH in water suspension
h1	numeric; moisture potential in kPa e.g. -10 (pF 2.0)
h2	numeric; moisture potential in kPa e.g. -20 (pF 2.3)
h3	numeric; moisture potential in kPa e.g. -31.6 (pF 2.5)
pwp	numeric; moisture potential at wilting point in kPa e.g. -1585 (pF 4.2)
PTF.coef	data.frame; optional conversion coefficients (Pedo-Transfer Function) with rows "ai1", "sand", "silt", "clay", "oc", "bd", "cec", "ph", "silt^2", "clay^2", "sand*silt", "sand*clay" and colums "lnAlfa", "lnN", "tetaS" and "tetaR" (see Wösten et al. 2013 for more details)
fix.values	logical; specifies whether to correct values of textures and bulk density to avoid creating nonsensical values
print.coef	logical; specifies whether to attach the PTF coefficients to the output object

Value

Returns a data frame with the following columns:

• AWCh1: available soil water capacity (volumetric fraction) for h1;

• AWCh2: available soil water capacity (volumetric fraction) for h2;

• AWCh3: available soil water capacity (volumetric fraction) for h3;

• WWP: available soil water capacity (volumetric fraction) until wilting point;

• tetaS: saturated water content;

Note

Pedotransfer coefficients (PTF.coef) developed by Hodnett and Tomasella (2002). fix.values will correct sand, silt and clay fractions so they sum up to 100, and will replace bulk density values using global minimum maximum values.

Author(s)

Johan Leenaars, Maria Ruiperez Gonzalez and Tomislav Hengl

References

• Hodnett, M. G., & Tomasella, J. (2002). Marked differences between van Genuchten soil water-retention parameters for temperate and tropical soils: a new water-retention pedo-transfer functions developed for tropical soils. Geoderma, 108(3), 155-180.

• Wösten, J. H. M., Verzandvoort, S. J. E., Leenaars, J. G. B., Hoogland, T., & Wesseling, J. G. (2013). Soil hydraulic information for river basin studies in semi-arid regions. Geoderma, 195, 79-86.

Examples

SNDPPT = 30 
SLTPPT = 25 
CLYPPT = 48 
ORCDRC = 23 
BLD = 1200 
CEC = 12 
PHIHOX = 6.4
x <- AWCPTF(SNDPPT, SLTPPT, CLYPPT, ORCDRC, BLD, CEC, PHIHOX)
str(x)
attr(x, "coef")

## predict AWC for AfSP DB profile:
data(afsp)
names(afsp$horizons)
## profile of interest:
sel <- afsp$horizons$SOURCEID=="NG 28440_Z5"
hor <- afsp$horizons[sel,]
## replace missing values:
BLDf <- ifelse(is.na(hor$BLD), 
   mean(hor$BLD, na.rm=TRUE), hor$BLD)
hor <- cbind(hor, AWCPTF(hor$SNDPPT, hor$SLTPPT, 
  hor$CLYPPT, hor$ORCDRC, BLD=BLDf*1000, hor$CEC, 
  hor$PHIHOX))
str(hor)

Example output

GSIF version 0.5-4 (2017-04-25)
URL: http://gsif.r-forge.r-project.org/
'data.frame':	1 obs. of  5 variables:
 $ AWCh1: num 0.16
 $ AWCh2: num 0.122
 $ AWCh3: num 0.0999
 $ WWP  : num 0.259
 $ tetaS: num 0.511
 - attr(*, "coef")=List of 4
  ..$ lnAlfa: num  -2.29 0 -3.53 0 2.44 ...
  ..$ lnN   : num  62.986 0 0 -0.833 -0.529 ...
  ..$ tetaS : num  81.799 0 0 0.099 0 ...
  ..$ tetaR : num  22.733 -0.164 0 0 0 ...
 - attr(*, "PTF.names")=List of 1
  ..$ variable: chr  "ai1" "sand" "silt" "clay" ...
$lnAlfa
 [1]  -2.294   0.000  -3.526   0.000   2.440   0.000  -0.076 -11.331   0.019
[10]   0.000   0.000   0.000

$lnN
 [1] 62.986  0.000  0.000 -0.833 -0.529  0.000  0.000  0.593  0.000  0.007
[11] -0.014  0.000

$tetaS
 [1]  81.7990   0.0000   0.0000   0.0990   0.0000 -31.4200   0.0180   0.4510
 [9]   0.0000   0.0000   0.0000  -0.0005

$tetaR
 [1] 22.7330 -0.1640  0.0000  0.0000  0.0000  0.0000  0.2350 -0.8310  0.0000
[10]  0.0018  0.0000  0.0026

 [1] "SOURCEID" "UHDICM"   "LHDICM"   "MCOMNS"   "ORCDRC"   "PHIHOX"  
 [7] "SNDPPT"   "SLTPPT"   "CLYPPT"   "CRFVOL"   "BLD"      "CEC"     
[13] "NTO"      "EMGX"    
'data.frame':	5 obs. of  19 variables:
 $ SOURCEID: Factor w/ 26270 levels "100902","100903",..: 20369 20369 20369 20369 20369
 $ UHDICM  : num  0 8 39 61 117
 $ LHDICM  : num  8 39 61 117 200
 $ MCOMNS  : Factor w/ 289 levels "10BG4/1","10R2.5/1",..: NA NA NA NA NA
 $ ORCDRC  : num  4 2 2 1 1
 $ PHIHOX  : num  5.5 6.6 8.4 8.7 7.9
 $ SNDPPT  : num  74 74 66 70 98
 $ SLTPPT  : num  24 26 24 16 2
 $ CLYPPT  : num  2 0 10 14 0
 $ CRFVOL  : num  NA NA NA NA NA
 $ BLD     : num  1.5 1.5 1.6 1.5 NA
 $ CEC     : num  3 2 7 9 1.6
 $ NTO     : num  0.31 0.12 0.08 0.16 0.08
 $ EMGX    : num  0.53 0.2 0.98 1.3 0.04
 $ AWCh1   : num  0.163 0.184 0.168 0.172 0.106
 $ AWCh2   : num  0.117 0.134 0.126 0.123 0.0574
 $ AWCh3   : num  0.0922 0.106 0.1 0.0954 0.0377
 $ WWP     : num  0.0878 0.0745 0.105 0.105 0.00581
 $ tetaS   : num  0.373 0.377 0.361 0.397 0.375

GSIF documentation built on May 2, 2019, 5:44 p.m.