Type:	Package
Title:	Calculate the Open Bodem Index (OBI) Score
Version:	3.0.3
Description:	The Open Bodem Index (OBI) is a method to evaluate the quality of soils of agricultural fields in The Netherlands and the sustainability of the current agricultural practices. The OBI score is based on four main criteria: chemical, physical, biological and management, which consist of more than 21 indicators. By providing results of a soil analysis and management info the 'OBIC' package can be use to calculate he scores, indicators and derivatives that are used by the OBI. More information about the Open Bodem Index can be found at https://openbodemindex.nl/.
Depends:	R (≥ 3.5.0)
Imports:	checkmate, data.table
License:	GPL-3
URL:	https://github.com/AgroCares/Open-Bodem-Index-Calculator
BugReports:	https://github.com/AgroCares/Open-Bodem-Index-Calculator/issues
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.3.2
Suggests:	testthat (≥ 2.1.0), knitr, rmarkdown, ggplot2, patchwork, covr
VignetteBuilder:	knitr
NeedsCompilation:	no
Packaged:	2024-09-09 07:53:10 UTC; sven.verweij
Author:	Sven Verweij [aut, cre], Gerard Ros [aut], Yuki Fujita [aut], Wilbrand Hendrik Riechelman [aut], Kees van den Dool [aut], Job de Pater [ctb], Nutriënten Managment Instituut [cph]
Maintainer:	Sven Verweij <sven.verweij@nmi-agro.nl>
Repository:	CRAN
Date/Publication:	2024-09-09 08:30:02 UTC

Estimate default values for management

Description

This function adds default management input variables given soil type and land use

Usage

add_management(
  ID,
  B_LU_BRP,
  B_SOILTYPE_AGR,
  M_GREEN = NA,
  M_NONBARE = NA,
  M_EARLYCROP = NA,
  M_COMPOST = NA_real_,
  M_SLEEPHOSE = NA,
  M_DRAIN = NA,
  M_DITCH = NA,
  M_UNDERSEED = NA,
  M_LIME = NA,
  M_NONINVTILL = NA,
  M_SSPM = NA,
  M_SOLIDMANURE = NA,
  M_STRAWRESIDUE = NA,
  M_MECHWEEDS = NA,
  M_PESTICIDES_DST = NA
)

Arguments

Value

A data.table with all default estimates for the management measures that are used for the Label Sustainable Soil Management. For each B_LU_BRP 15 management measures are given, all as boolean variables except for M_COMPOST being a numeric value.

Examples

add_management(ID = 1, B_LU_BRP = 256, B_SOILTYPE_AGR = 'dekzand')
add_management(ID = 1, B_LU_BRP = c(256,1019), B_SOILTYPE_AGR = rep('dekzand',2))

Example dataset for use in OBIC package

Description

This table contains a series of agricultural fields with soil properties needed for illustration OBIC.

Usage

binnenveld

Format

An object of class data.table (inherits from data.frame) with 3251 rows and 55 columns.

Details

ID

A field id (numeric)

YEAR

The year that the crop is grown (integer)

B_LU_BRP

A series with crop codes given the crop rotation plan (integer, source: the BRP)

B_SC_WENR

The risk for subsoil compaction as derived from risk assessment study of Van den Akker (2006) (character).

B_GWL_CLASS

The groundwater table class (character)

B_SOILTYPE_AGR

The agricultural type of soil (character)

B_HELP_WENR

The soil type abbreviation, derived from 1:50.000 soil map (character)

B_AER_CBS

The agricultural economic region in the Netherlands (CBS, 2016) (character)

A_SOM_LOI

The percentage organic matter in the soil (%) (numeric)

A_CLAY_MI

The clay content of the soil (%) (numeric)

A_SAND_MI

The sand content of the soil (%) (numeric)

A_SILT_MI

The silt content of the soil (%) (numeric)

A_PH_CC

The acidity of the soil, measured in 0.01M CaCl2 (-) (numeric)

A_CACO3_IF

The carbonate content of the soil (%) (numeric)

A_N_RT

The organic nitrogen content of the soil in mg N / kg (numeric)

A_CN_FR

The carbon to nitrogen ratio (-) (numeric)

A_COM_FR

The carbon fraction of soil organic matter (%) (numeric)

A_S_RT

The total Sulfur content of the soil (in mg S per kg) (numeric)

A_N_PMN

The potentially mineralizable N pool (mg N / kg soil) (numeric)

A_P_AL

The P-AL content of the soil (numeric)

A_P_CC

The plant available P content, extracted with 0.01M CaCl2 (mg / kg) (numeric)

A_P_WA

The P-content of the soil extracted with water (mg P2O5 / 100 ml soil) (numeric)

A_CEC_CO

The cation exchange capacity of the soil (mmol+ / kg), analysed via Cobalt-hexamine extraction (numeric)

A_CA_CO_PO

The The occupation of the CEC with Ca (%) (numeric)

A_MG_CO_PO

The The occupation of the CEC with Mg (%) (numeric)

A_K_CO_PO

The occupation of the CEC with K (%) (numeric)

A_K_CC

The plant available K content, extracted with 0.01M CaCl2 (mg / kg) (numeric)

A_MG_CC

The plant available Mg content, extracted with 0.01M CaCl2 (ug / kg) (numeric)

A_MN_CC

The plant available Mn content, extracted with 0.01M CaCl2 (ug / kg) (numeric)

A_ZN_CC

The plant available Zn content, extracted with 0.01M CaCl2 (ug / kg) (numeric)

A_CU_CC

The plant available Cu content, extracted with 0.01M CaCl2 (ug / kg) (numeric)

A_EW_BCS

The presence of earth worms (optional, score 0-1-2, numeric)

A_SC_BCS

The presence of compaction of subsoil (optional, score 0-1-2, numeric)

A_GS_BCS

The presence of waterlogged conditions, gley spots (optional, score 0-1-2, numeric)

A_P_BCS

The presence / occurrence of water puddles on the land, ponding (optional, score 0-1-2, numeric)

A_C_BCS

The presence of visible cracks in the top layer (optional, score 0-1-2, numeric)

A_RT_BCS

The presence of visible tracks / rutting or trampling on the land (optional, score 0-1-2, numeric)

A_RD_BCS

The rooting depth (optional, score 0-1-2, numeric)

A_SS_BCS

The soil structure (optional, score 0-1-2, numeric)

A_CC_BCS

he crop cover on the surface (optional, score 0-1-2, numeric)

M_COMPOST

The frequency that compost is applied (optional, every x years, numeric)

M_GREEN

A soil measure. Are catch crops sown after main crop (optional, option: yes or no, boolean)

M_NONBARE

A soil measure. Is parcel for 80 percent of the year cultivated and 'green' (optional, option: yes or no, boolean)

M_EARLYCROP

A soil measure. Use of early crop varieties to avoid late harvesting (optional, option: yes or no, boolean)

M_SLEEPHOSE

A soil measure. Is sleephose used for slurry application (optional, option: yes or no, boolean)

M_DRAIN

A soil measure. Are under water drains installed in peaty soils (optional, option: yes or no, boolean)

M_DITCH

A soil measure. Are ditched maintained carefully and slib applied on the land (optional, option: yes or no, boolean)

M_UNDERSEED

A soil measure. Is grass used as second crop in between maize rows (optional, option: yes or no, boolean)

M_LIME

A soil measure. Has field been limed in last three years (option: yes or no, boolean)

M_NONINVTILL

A soil measure. Non inversion tillage (option: yes or no, boolean)

M_SSPM

A soil measure. Soil Structure Protection Measures, such as fixed driving lines, low pressure tires, and light weighted machinery (option: yes or no, boolean)

M_SOLIDMANURE

A soil measure. Use of solid manure (option: yes or no, boolean)

M_STRAWRESIDUE

A soil measure. Application of straw residues (option: yes or no, boolean)

M_MECHWEEDS

A soil measure. Use of mechanical weed protection (option: yes or no, boolean)

M_PESTICIDES_DST

A soil measure. Use of DST for pesticides (option: yes or no, boolean)

Table with water retention properties of 'bouwstenen'

Description

This table contains water retention curve parameters and typical mineral composition of 18 'bouwstenen'

Usage

bouwsteen_tb

Format

An object of class data.table (inherits from data.frame) with 36 rows and 14 columns.

Details

bouwsteen

soil type bouwsteen

omschrijving

description of 'bouwsteen'

thres

residual water content (cm3/cm3). Table 3 of Wosten 2001

thsat

water content at saturation (cm3/cm3). Table 3 of Wosten 2001

Ks

saturated hydraulic conductivity (cm/d). Table 3 of Wosten 2001

alpha

parameter alpha of pF curve (1/cm) Table 3 of Wosten 2001

l

parameter l of pF curve (-). Table 3 of Wosten 2001

n

parameter n of pF curve (-). Table 3 of Wosten 2001

sand%

sand content (%) within soil mineral parts. Middle value of Table 1 of Wosten 2001

silt%

silt content (%) within soil mineral parts. Middle value of Table 1 of Wosten 2001

clay%

clay content (%) within soil mineral parts. Middle value of Table 1 of Wosten 2001

OM%

organic matter content (%). Middle value of Table 1 of Wosten 2001

bulkdensity

soil bulk density (g/cm3). Middle value of Table 2 of Wosten 2001

M50

size of sand particles (um). Middle value of Table 2 of Wosten 2001

Calculate aggregate stability index based on occupation CEC

Description

This function calculates an aggregate stability index given the CEC and its occupation with major cations.

Usage

calc_aggregatestability(
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  A_K_CO_PO,
  A_CA_CO_PO,
  A_MG_CO_PO
)

Arguments

Value

The aggregate stability index of a soil given the Cation Exchange Capacity and its composition with major cations. A numeric value.

Examples

calc_aggregatestability(B_SOILTYPE_AGR = 'dekzand', A_SOM_LOI = 3.5, 
A_K_CO_PO = 6,A_CA_CO_PO = 83 ,A_MG_CO_PO = 9)
calc_aggregatestability(B_SOILTYPE_AGR = c('dekzand','rivierklei'), A_SOM_LOI = c(3.5,6.5), 
A_K_CO_PO = c(6,9),A_CA_CO_PO = c(83,75) ,A_MG_CO_PO = c(9,4))

Calculate the BodemConditieScore

Description

This function calculates the BodemConditieScore given input from manual observations made in the field. The individual parameters are scored in three classes: poor (0), neutral (1) or good (2) More information on this test can be found here

Usage

calc_bcs(
  B_LU_BRP,
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  D_PH_DELTA,
  A_EW_BCS = NA,
  A_SC_BCS = NA,
  A_GS_BCS = NA,
  A_P_BCS = NA,
  A_C_BCS = NA,
  A_RT_BCS = NA,
  A_RD_BCS = NA,
  A_SS_BCS = NA,
  A_CC_BCS = NA,
  type = "score"
)

Arguments

Value

A visual soil assessment score derived from field observations driven by organic matter content and soil structure properties. Returns a numeric value.

References

mijnbodemconditie.nl

Examples

calc_bcs(B_LU_BRP = 265, B_SOILTYPE_AGR = 'dekzand', A_SOM_LOI = 3.5, D_PH_DELTA = 0.4,
A_EW_BCS = 1, A_SC_BCS = 1, A_GS_BCS = 1, A_P_BCS = 1, A_C_BCS = 1, A_RT_BCS =1, A_RD_BCS = 1, 
A_SS_BCS = 1, A_CC_BCS = 1)

Calculate the bulk density

Description

This function calculates the bulk density of the soil based on texture and organic matter

Usage

calc_bulk_density(B_SOILTYPE_AGR, A_SOM_LOI, A_CLAY_MI = NULL)

Arguments

Value

The bulk density of an arable soil (kg / m3). A numeric value.

Examples

calc_bulk_density(B_SOILTYPE_AGR = 'zeeklei', A_SOM_LOI = 6.5, A_CLAY_MI = 28)
calc_bulk_density(B_SOILTYPE_AGR = 'dekzand', A_SOM_LOI = 3.5)
calc_bulk_density(B_SOILTYPE_AGR = c('dekzand','rivierklei'), A_SOM_LOI = c(3.5,8.5))

Calculate a soil fertility index based on the CEC

Description

This function calculates the capacity of the soil to buffer cations

Usage

calc_cec(A_CEC_CO)

Arguments

Value

The capacity of the soil to buffer cations. A numeric value.

Examples

calc_cec(A_CEC_CO = 85)
calc_cec(A_CEC_CO = c(85,125,326))

Calculate the availability of the metal Cu

Description

This function calculates the availability of Cu for plant uptake

Usage

calc_copper_availability(
  B_LU_BRP,
  A_SOM_LOI,
  A_CLAY_MI,
  A_K_CC,
  A_MN_CC,
  A_CU_CC
)

Arguments

Value

The function of the soil to supply Copper. A numeric value.

Examples

calc_copper_availability(B_LU_BRP = 265, A_SOM_LOI = 3.5, A_CLAY_MI = 4,A_K_CC = 65, 
A_MN_CC = 110, A_CU_CC = 250)
calc_copper_availability(B_LU_BRP = 265, 3.5, 4,65, 110, 250)
calc_copper_availability(B_LU_BRP = c(1019,265), c(3.5,5), c(4,8),c(65,95), c(110,250), c(250,315))

Determine classification rules for crops used to prepare crops.obic

Description

This function determines crop classes given crop response to P, K and S fertilizers

Usage

calc_cropclass(B_LU_BRP, B_SOILTYPE_AGR, nutrient)

Arguments

Value

The crop class representing its sensitivity for P, K or S deficiency. A character value.

References

CBAV (2022) Handboek Bodem en Bemesting,https://www.handboekbodemenbemesting.nl/

Examples

calc_cropclass(B_LU_BRP = 256, B_SOILTYPE_AGR = 'dekzand', nutrient = 'P')
calc_cropclass(B_LU_BRP = c(256,1027), B_SOILTYPE_AGR = c('dekzand','rivierklei'),nutrient = 'P')

Calculate the crumbleability

Description

This function calculates the crumbleability. This value can be evaluated by ind_crumbleability

Usage

calc_crumbleability(A_SOM_LOI, A_CLAY_MI, A_PH_CC)

Arguments

Value

The crumbleability index of a soil, a measure for a physical soil property. A numeric value.

Examples

calc_crumbleability(A_SOM_LOI = 3.5, A_CLAY_MI = 12, A_PH_CC = 5.4)
calc_crumbleability(A_SOM_LOI = c(3.5,12), A_CLAY_MI = c(4,12), A_PH_CC = c(5.4, 7.1))

Calculate the average age of the grass

Description

This function calculates the average age of the grass

Usage

calc_grass_age(ID, B_LU_BRP)

Arguments

Details

The function assumes that the order of crop codes are descending, so the latest year is on top.

Value

The age of the grassland within a crop rotation plan. A numeric value.

Examples

calc_grass_age(ID = rep(1,5), B_LU_BRP = c(1091,265,256,256,1091))
calc_grass_age(ID = rep(1,5), B_LU_BRP = c(265,265,265,265,1091))

Calculate the capacity of soils to supply Magnesium

Description

This function calculates an index for the availability of Magnesium in soil

Usage

calc_magnesium_availability(
  B_LU_BRP,
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  A_CLAY_MI,
  A_PH_CC,
  A_CEC_CO,
  A_K_CO_PO,
  A_MG_CC,
  A_K_CC
)

Arguments

Value

An index representing the availability of Magnesium in a soil. A numeric value.

Examples

calc_magnesium_availability(B_LU_BRP = 265, B_SOILTYPE_AGR = 'dekzand',
A_SOM_LOI = 3.5,A_CLAY_MI = 8.5,A_PH_CC = 5.4, 
A_CEC_CO = 185,A_K_CO_PO = 4.5,A_MG_CC = 125,A_K_CC = 65)

Add Makkink correction factors and crop cover to crop rotation table

Description

This function adds Makkink correction factors for ET and crop cover to the crop rotation table

Usage

calc_makkink(B_LU_BRP)

Arguments

Value

A datatable with the crop dependent Makkink correction factor per month. Output is a single data.table with for each B_LU_BRP code the monthly correction factor. Columns of the data.table are: crop_makkink, month, year, mcf and crop_cover.

Examples

calc_makkink(B_LU_BRP = 265)
calc_makkink(B_LU_BRP = c(265,1019))

Calculate the 'performance' of sustainable soil management given a required ecosystem service

Description

This function evaluates the contribution of sustainable soil management for a given ecosystem service

Usage

calc_man_ess(
  A_SOM_LOI,
  B_LU_BRP,
  B_SOILTYPE_AGR,
  B_GWL_CLASS,
  D_SOM_BAL,
  D_CP_GRASS,
  D_CP_POTATO,
  D_CP_RUST,
  D_CP_RUSTDEEP,
  D_GA,
  M_COMPOST,
  M_GREEN,
  M_NONBARE,
  M_EARLYCROP,
  M_SLEEPHOSE,
  M_DRAIN,
  M_DITCH,
  M_UNDERSEED,
  M_LIME,
  M_NONINVTILL,
  M_SSPM,
  M_SOLIDMANURE,
  M_STRAWRESIDUE,
  M_MECHWEEDS,
  M_PESTICIDES_DST,
  type
)

Arguments

Value

The evaluated soil management score for multiple soil ecosystem services. This is done for the following ESS: I_M_SOILFERTILITY, I_M_CLIMATE, I_M_WATERQUALITY and I_M_BIODIVERSITY

Examples

calc_man_ess(A_SOM_LOI = 4.5,B_LU_BRP = 3732, B_SOILTYPE_AGR = 'dekzand',
B_GWL_CLASS = 'GtIV',D_SOM_BAL = 1115,D_CP_GRASS = 0.2,D_CP_POTATO = 0.5,
D_CP_RUST = 0.3,D_CP_RUSTDEEP = 0.2,D_GA = 0,M_COMPOST = rep(25,1),
M_GREEN = TRUE, M_NONBARE = TRUE, M_EARLYCROP = TRUE, M_SLEEPHOSE = TRUE, 
M_DRAIN = TRUE, M_DITCH = TRUE, M_UNDERSEED = TRUE,M_LIME = TRUE, 
M_NONINVTILL = TRUE, M_SSPM = TRUE, M_SOLIDMANURE = TRUE,M_STRAWRESIDUE = TRUE,
M_MECHWEEDS = TRUE,M_PESTICIDES_DST = TRUE,type="I_M_SOILFERTILITY")

Calculate the 'performance' of sustainable soil management

Description

This function evaluates the contribution of sustainable soil management following the Label Sustainable Soil Management.

Usage

calc_management(
  A_SOM_LOI,
  B_LU_BRP,
  B_SOILTYPE_AGR,
  B_GWL_CLASS,
  D_SOM_BAL,
  D_CP_GRASS,
  D_CP_POTATO,
  D_CP_RUST,
  D_CP_RUSTDEEP,
  D_GA,
  M_COMPOST,
  M_GREEN,
  M_NONBARE,
  M_EARLYCROP,
  M_SLEEPHOSE,
  M_DRAIN,
  M_DITCH,
  M_UNDERSEED,
  M_LIME,
  M_NONINVTILL,
  M_SSPM,
  M_SOLIDMANURE,
  M_STRAWRESIDUE,
  M_MECHWEEDS,
  M_PESTICIDES_DST
)

Arguments

Value

The evaluated soil management score according to the Label Sustainable Soil Management. A nmumeric value.

Examples

calc_management(A_SOM_LOI = 4.5,B_LU_BRP = 3732, B_SOILTYPE_AGR = 'dekzand',
B_GWL_CLASS = 'GtIV',D_SOM_BAL = 1115,D_CP_GRASS = 0.2,D_CP_POTATO = 0.5,
D_CP_RUST = 0.3,D_CP_RUSTDEEP = 0.2,D_GA = 0,M_COMPOST = rep(25,1),
M_GREEN = TRUE, M_NONBARE = TRUE, M_EARLYCROP = TRUE, M_SLEEPHOSE = TRUE, 
M_DRAIN = TRUE, M_DITCH = TRUE, M_UNDERSEED = TRUE,M_LIME = TRUE, 
M_NONINVTILL = TRUE, M_SSPM = TRUE, M_SOLIDMANURE = TRUE,M_STRAWRESIDUE = TRUE,
M_MECHWEEDS = TRUE,M_PESTICIDES_DST = TRUE)

Calculate nitrogen use efficiency and leaching based on N surplus

Description

This function gives an indication of the nitrogen use efficiency, the function calculates the N surplus and the resulting N leaching

Usage

calc_n_efficiency(
  B_LU_BRP,
  B_SOILTYPE_AGR,
  B_GWL_CLASS,
  B_AER_CBS,
  A_SOM_LOI,
  A_CLAY_MI,
  D_PBI,
  D_K,
  D_PH_DELTA,
  leaching_to,
  M_GREEN = FALSE,
  B_FERT_NORM_FR = 1
)

Arguments

Value

The estimated index for the nitrogen use efficiency, as being affected by soil properties. A numeric value.

Examples

calc_n_efficiency(1019,'dekzand','GtIV','Zuidwest-Brabant',4.5,3.5,0.8,0.6,0.2,78,FALSE,1)
calc_n_efficiency(256,'veen','GtII','Centraal Veehouderijgebied',4.5,3.5,0.8,0.6,0.2,250,FALSE,1)

Calculate the N leaching

Description

This function calculates the potential N leaching of a soil.

Usage

calc_nleach(
  B_SOILTYPE_AGR,
  B_LU_BRP,
  B_GWL_CLASS,
  D_NLV,
  B_AER_CBS,
  leaching_to
)

Arguments

Value

The potential nitrogen leaching from the soil originating from soil nitrogen mineralization processes. A numeric value.

Examples

calc_nleach('dekzand',265,'GtIII',145,'Zuidwest-Brabant','gw')
calc_nleach('rivierklei',1019,'GtIV',145,'Rivierengebied','ow')

Calculate the NLV

Description

This function calculates the NLV (nitrogen producing capacity) for the soil

Usage

calc_nlv(B_LU_BRP, B_SOILTYPE_AGR, A_N_RT, A_CN_FR, D_OC, D_BDS, D_GA)

Arguments

Value

The capacity of the soil to supply nitrogen (kg N / ha / yr). A numeric value.

Examples

calc_nlv(B_LU_BRP = 256, B_SOILTYPE_AGR = 'dekzand',A_N_RT = 2500, 
A_CN_FR = 11, D_OC = 86000,D_BDS = 1300, D_GA = 4)
calc_nlv(1019,'dekzand',2315,13,86000,1345,0)

Calculate amount of organic carbon

Description

This function calculates the amount of organic carbon in the soil

Usage

calc_organic_carbon(A_SOM_LOI, D_BDS, D_RD)

Arguments

Value

The total amount of Carbon in the soil (kg C / ha). A numeric value.

Examples

calc_organic_carbon(A_SOM_LOI = 4.3, D_BDS = 1100, D_RD = 0.2)
calc_organic_carbon(A_SOM_LOI = c(1,4.3), D_BDS = c(1100,1300), D_RD = c(0.2,0.6))

Calculate the permeability of the top soil

Description

This function calculates the permeability of the top soil

Usage

calc_permeability(A_CLAY_MI, A_SAND_MI, A_SILT_MI, A_SOM_LOI)

Arguments

Calculate risk of pesticide leaching

Description

This function calculates the risk of pesticide leaching from a soil. The risk is calculated by comparing the current leached fraction with a worst case scenario

Usage

calc_pesticide_leaching(
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  A_CLAY_MI,
  A_SAND_MI,
  A_SILT_MI,
  D_PSP,
  M_PESTICIDES_DST,
  M_MECHWEEDS
)

Arguments

Value

The risk of pesticide leaching from soils. A numeric value.

Examples

calc_pesticide_leaching(B_SOILTYPE_AGR = 'rivierklei', A_SOM_LOI = 4, 
A_CLAY_MI = 20, A_SAND_MI = 45, A_SILT_MI = 35, 
D_PSP = 225, M_PESTICIDES_DST = TRUE,M_MECHWEEDS = TRUE)
calc_pesticide_leaching('rivierklei', 4, 20, 45, 35, 225, TRUE,TRUE)
calc_pesticide_leaching('dekzand', 4.8, 4.2, 85, 10.8, 225, TRUE,TRUE)

Calculate the difference between pH and optimum

Description

This functions calculates the difference between the measured pH and the optimal pH according to the Bemestingsadvies

Usage

calc_ph_delta(
  B_LU_BRP,
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  A_CLAY_MI,
  A_PH_CC,
  D_CP_STARCH,
  D_CP_POTATO,
  D_CP_SUGARBEET,
  D_CP_GRASS,
  D_CP_MAIS,
  D_CP_OTHER
)

Arguments

Value

The difference between the actual and desired optimum soil pH. A numeric value.

References

Handboek Bodem en Bemesting tabel 5.1, 5.2 en 5.3

Examples

calc_ph_delta(B_LU_BRP = 265, B_SOILTYPE_AGR = "rivierklei", A_SOM_LOI = 5,
A_CLAY_MI = 20,A_PH_CC = 6, D_CP_STARCH = 0,D_CP_POTATO = 0.3,D_CP_SUGARBEET = 0.2,
D_CP_GRASS = 0,D_CP_MAIS = 0.2,D_CP_OTHER = 0.3)
calc_ph_delta(265, "rivierklei", 5,20,6, 0,0.3,0.2,0,0.2,0.3) 

Calculate the phosphate availability (PBI)

Description

This function calculates the phosphate availability. This value can be evaluated by ind_phosphate_availability

Usage

calc_phosphate_availability(
  B_LU_BRP,
  A_P_AL = NULL,
  A_P_CC = NULL,
  A_P_WA = NULL
)

Arguments

Value

The phosphate availability index estimated from extractable soil P fractions. A numeric value.

Examples

calc_phosphate_availability(B_LU_BRP = 265, A_P_AL = 45, A_P_CC = 2.5)
calc_phosphate_availability(c(265,1019),A_P_AL = c(35,54),A_P_CC = c(2.5,4.5), A_P_WA = c(35,65))

Calculate the index for the microbial biological activity

Description

This function assesses the microbial biological activity (of microbes and fungi) via the Potentially Mineralizable N pool, also called PMN (or SoilLife by Eurofins in the past).

Usage

calc_pmn(B_LU_BRP, B_SOILTYPE_AGR, A_N_PMN)

Arguments

Value

the normalized potentially mineralizable Nitrogen pool (mg N / kg), a numeric value.

Examples

calc_pmn(B_LU_BRP = 256, B_SOILTYPE_AGR = 'dekzand', A_N_PMN = 125)
calc_pmn(B_LU_BRP = c(256,1027), B_SOILTYPE_AGR = c('dekzand','rivierklei'), A_N_PMN = c(125,45))

Calculate the K availability

Description

This function calculates the K availability of a soil.

Usage

calc_potassium_availability(
  B_LU_BRP,
  B_SOILTYPE_AGR,
  A_SOM_LOI,
  A_CLAY_MI,
  A_PH_CC,
  A_CEC_CO,
  A_K_CO_PO,
  A_K_CC
)

Arguments

Value

The capacity of the soil to supply and buffer potassium. A numeric value.

Examples

calc_potassium_availability(B_LU_BRP = 265, B_SOILTYPE_AGR = 'dekzand',
A_SOM_LOI = 4, A_CLAY_MI = 11,A_PH_CC = 5.4, A_CEC_CO = 125, 
A_K_CO_PO = 8.5, A_K_CC = 145)
calc_potassium_availability(265, 'dekzand',4, 11,5.4,  125,8.5, 145)
calc_potassium_availability(c(265,1019), rep('dekzand',2),c(4,6), c(11,14),
c(5.4,5.6),  c(125,145),c(8.5,3.5), c(145,180))

Calculate the precipitation surplus

Description

This function calculates the precipitation surplus (in mm / ha) given the crop rotation plan.

Usage

calc_psp(B_LU_BRP, M_GREEN)

Arguments

Value

The estimated precipitation surplus (in mm / ha) depending on averaged precipitation and evaporation. A numeric value.

Examples

calc_psp(B_LU_BRP = 265, M_GREEN = TRUE)
calc_psp(B_LU_BRP = c(265,1019,265,1019), M_GREEN = rep(TRUE,4))

Determine the root depth of the soil for this crop

Description

This function determines the depth of the soil

Usage

calc_root_depth(B_LU_BRP)

Arguments

Details

This is a helper function to estimate the rooting depth of crops, as being used for calculations for soil nutrient supplies. Be aware, this is not the real rooting depth; it rather represents the sampling depth of the soils collected for routine soil analsyis.

Value

The root depth of a crop corresponding to the sampling depth analyzed by agricultural labs. A numeric value.

Examples

calc_root_depth(B_LU_BRP = 256)
calc_root_depth(B_LU_BRP = c(256,265,1019,992))

Calculates the fraction in the crop rotation

Description

This function calculates the fraction present in the crop rotation

Usage

calc_rotation_fraction(ID, B_LU_BRP, crop)

Arguments

Details

This function calculates the fraction present in the crop rotation for specific crop categories. These categories include "starch", "potato", "sugarbeet", "grass", "mais", "alfalfa","catchcrop","cereal","clover",'nature', rapeseed',"other","rustgewas",and "rustgewasdiep".

Value

The fraction of specific crop types within the crop rotation sequence. A numeric value.

Examples

calc_rotation_fraction(ID = rep(1,4), B_LU_BRP = c(265,1910,1935,1033),crop = 'potato')
calc_rotation_fraction(ID = rep(1,4), B_LU_BRP = c(265,1910,1935,1033),crop = 'grass')

Calculate the indicator for delta S-balance arable

Description

This function calculates the change in S-balance compared to averaged S-supply as given in fertilizer recommendation systems.

Usage

calc_sbal_arable(D_SLV, B_LU_BRP, B_SOILTYPE_AGR, B_AER_CBS)

Arguments

Value

Estimated contribution of the soil to the S balance of arable fields. A numeric value.

Examples

 
calc_sbal_arable(D_SLV = 65, B_LU_BRP = 1019, B_SOILTYPE_AGR = 'dekzand', 
B_AER_CBS = 'Rivierengebied')

Calculate soil sealing risk

Description

This function calculates the risks of soil sealing. This value can be evaluated by ind_sealing

Usage

calc_sealing_risk(A_SOM_LOI, A_CLAY_MI)

Arguments

Value

The risk of soil sealing as affected by the soil organic matter and clay content. A numeric value.

Examples

calc_sealing_risk(A_SOM_LOI = 3.5, A_CLAY_MI = 7.5)
calc_sealing_risk(A_SOM_LOI = c(3.5,6.5), A_CLAY_MI = c(7.5,15))

Calculate the SLV

Description

This function calculates a S-balance given the SLV (Sulfur supplying capacity) of a soil

Usage

calc_slv(B_LU_BRP, B_SOILTYPE_AGR, B_AER_CBS, A_SOM_LOI, A_S_RT, D_BDS)

Arguments

Value

The capacity of the soil to supply Sulfur (kg S / ha / yr). A numeric value.

Examples

calc_slv(B_LU_BRP = 1019, B_SOILTYPE_AGR = 'dekzand', 
B_AER_CBS = 'Rivierengebied',A_SOM_LOI = 3.5,A_S_RT = 3500, D_BDS = 1400)
calc_slv(1019, 'dekzand', 'Rivierengebied',3.5,3500,1400)
calc_slv(c(256,1019), rep('dekzand',2), rep('Rivierengebied',2),c(6.5,3.5),
c(3500,7500),c(1400,1100))

Calculate simple organic matter balance

Description

This function calculates a simple organic matter balance, as currently used in agricultural practice in the Netherlands.For more details, see www.os-balans.nl

Usage

calc_sombalance(B_LU_BRP, A_SOM_LOI, A_P_AL, A_P_WA, M_COMPOST, M_GREEN)

Arguments

Value

The estimated soil organic matter balance in kg EOS per ha per year. A numeric value.

Examples

calc_sombalance(B_LU_BRP = 1019,A_SOM_LOI = 4, A_P_AL = 35, A_P_WA = 40, 
M_COMPOST = 4, M_GREEN = TRUE)
calc_sombalance(1019,4, 35, 40, 4, TRUE)
calc_sombalance(c(256,1024,1019),c(4,5,6), c(35,35,35), c(40,42,45), c(4,4,3), c(TRUE,FALSE,TRUE))

Calculate indicators for water retention in topsoil

Description

This function calculates different kind of Water Retention Indices given the continuous pedotransferfunctions of Wosten et al. (2001) These include : 'wilting point','field capacity','water holding capacity','plant available water' and 'Ksat'

Usage

calc_waterretention(
  A_CLAY_MI,
  A_SAND_MI,
  A_SILT_MI,
  A_SOM_LOI,
  type = "plant available water",
  ptf = "Wosten1999"
)

Arguments

Value

The function returns by default the amount of plant available water in the ploughing layer of the soil (in mm). A numeric value. If another type of output is selected, the function gives also the amount of water at 'wilting point' or 'field capacity' or 'water holding capacity'. Also the saturated permeability 'Ksat' can be selected. Units are always in mm, except for Water Holding Capacity (

References

Wosten et al. (2001) Pedotransfer functions: bridging the gap between available basic soil data and missing hydraulic characteristics. Journal of Hydrology 251, p123.

Examples

calc_waterretention(A_CLAY_MI = 20.5,A_SAND_MI = 65,A_SILT_MI = 14.5,A_SOM_LOI = 3.5)
calc_waterretention(A_CLAY_MI = 5,A_SAND_MI = 15,A_SILT_MI = 80,A_SOM_LOI = 6.5)
calc_waterretention(A_CLAY_MI = 5,A_SAND_MI = 15,A_SILT_MI = 80,A_SOM_LOI = 6.5, 
type = 'water holding capacity')

Calculate the Water Stress Index

Description

This function calculates the Water Stress Index (estimating the yield depression as a function of water deficiency or surplus)

Usage

calc_waterstressindex(B_HELP_WENR, B_LU_BRP, B_GWL_CLASS, WSI = "waterstress")

Arguments

Value

The yield depression (in %) through wetness or drought stress (depending on the WSI selected). Numeric value.

References

STOWA (2005) Uitbreiding en Actualisering van de HELP-tabellen ten behoeve van het Waternood instrumentarium

Examples

 
calc_waterstressindex(B_HELP_WENR = 'ABkt',B_LU_BRP = 1019,B_GWL_CLASS = 'GtIV'
, WSI = 'droughtstress')

Calculate indicator for wind erodibility

Description

This function calculates the risk for wind erodibility of soils, derived from Van Kerckhoven et al. (2009) and Ros & Bussink (2013)

Usage

calc_winderodibility(B_LU_BRP, A_CLAY_MI, A_SILT_MI)

Arguments

Value

The vulnerability of the soil for wind erosion. A numeric value.

Examples

calc_winderodibility(B_LU_BRP = 265, A_CLAY_MI = 4, A_SILT_MI = 15)
calc_winderodibility(B_LU_BRP = c(265,1019), A_CLAY_MI = c(4,18), A_SILT_MI = c(15,65))

Calculate indicator for workability

Description

This function calculates the workability of soils, given as a value of relative season length between 0 and 1. A relative season length of 1 indicates that the water table is sufficiently low for the soil to be workable for the entire growing season required by the crop. The required ground water table for workability is determined by soil type and soil properties. Hydrological variables determine the groundwater table for each day of the year. The option calcyieldloss allows for calculation of yield loss based on the relative season length, differentiating in yield loss between six groups of crops Based on Huinink (2018)

Usage

calc_workability(
  A_CLAY_MI,
  A_SILT_MI,
  B_LU_BRP,
  B_SOILTYPE_AGR,
  B_GWL_GLG,
  B_GWL_GHG,
  B_GWL_ZCRIT,
  calcyieldloss = FALSE
)

Arguments

Value

The workability of a soil, expressed as a numeric value representing the relative season length that the soil can be managed by agricultural activities.

References

Huinink (2018) Bodem/perceel geschiktheidsbeoordeling voor Landbouw, Bosbouw en Recreatie. BodemConsult-Arnhem

Examples

calc_workability(A_CLAY_MI = 18,A_SILT_MI = 25,B_LU_BRP = 265,
B_SOILTYPE_AGR = 'dekzand',B_GWL_GLG = 145,B_GWL_GHG = 85,B_GWL_ZCRIT = 400,
calcyieldloss = FALSE)
calc_workability(18,25,265,'dekzand',145,85,400,FALSE)

Calculate the availability of the metal Zinc

Description

This function calculates the availability of Zn for plant uptake

Usage

calc_zinc_availability(B_LU_BRP, B_SOILTYPE_AGR, A_PH_CC, A_ZN_CC)

Arguments

Value

The function of the soil to supply zinc A numeric value.

Examples

calc_zinc_availability(B_LU_BRP = 265, B_SOILTYPE_AGR = 'dekzand',A_PH_CC = 4.5, A_ZN_CC = 3000)
calc_zinc_availability(B_LU_BRP = 265, 'dekzand',4,3500)
calc_zinc_availability(B_LU_BRP = c(1019,265), c('dekzand','rivierklei'),c(4.5,4.8),c(2500,4500))

Helper function to weight and correct the risk and scores

Description

Helper function to weight and correct the risk and scores

Usage

cf_ind_importance(x)

Arguments

Value

A transformed variable after applying a inverse weighing function so that lower values will gain more impact when applied in a weighed.mean function. A numeric value.

Examples

cf_ind_importance(x = 0.5)
cf_ind_importance(x = c(0.1,0.5,1.5))

Column description for the OBIC

Description

This table defines the columns used in the OBIC and which unit is used

Usage

column_description.obic

Format

An object of class data.table (inherits from data.frame) with 216 rows and 6 columns.

Details

column

The column name used in OBIC

type

The type of column

description_nl

A description of the column in Dutch

description_en

A description of the column in English

unit

The unit used for this column

method

The method to measure/obtain the values for this column

Makkink correction factor table

Description

This table contains the makkink correction factors for evapo-transpiration per month

Usage

crops.makkink

Format

An object of class data.table (inherits from data.frame) with 24 rows and 13 columns.

Details

crop_makkink

Makkink crop category

1

Evapotranspiration correction factors for January

2

Evapotranspiration correction factors for February

3

Evapotranspiration correction factors for March

4

Evapotranspiration correction factors for April

5

Evapotranspiration correction factors for May

6

Evapotranspiration correction factors for June

7

Evapotranspiration correction factors for July

8

Evapotranspiration correction factors for August

9

Evapotranspiration correction factors for September

10

Evapotranspiration correction factors for October

11

Evapotranspiration correction factors for November

12

Evapotranspiration correction factors for December

Linking table between crops and different functions in OBIC

Description

This table helps to link the different crops in the OBIC functions with the crops selected by the user

Usage

crops.obic

Format

An object of class data.table (inherits from data.frame) with 521 rows and 22 columns.

Details

crop_code

The BRP gewascode of the crop

crop_name

The name of the crop, in lower case

crop_waterstress

Classification linking for linking crops to waterstress.obic

crop_intensity

Whether crop is root/tuber crop, rest crop, or other.

crop_eos

Effective soil organic matter produced by the crop in kg/ha

crop_eos_residue

Effective soil organic matter from plant residues in kg/ha

crop_category

Classification of crop per land use type (arable, maize, grass, nature)

crop_rotation

Classification of crop to determine function within crop rotations

crop_crumbleability

The category for this crop at crumbleability

crop_phosphate

The category for this crop for evaluation phosphate availability

crop_sealing

The category for this crop at soil sealing

crop_n

The category for this crop for evaluation nitrogen

crop_k

The category for this crop for evaluation potassium

crop_measure

The category for this crop for evaluating measures

nf_clay

Allowed effective N dose on clay soils

nf_sand.other

Allowed effective N dose on sandy soils

nf_sand.south

Allowed effective N dose on sandy soils sensitive to leaching

nf_loess

Allowed effective N dose on loess soils

nf_peat

Allowed effective N dose on peat soils

crop_name_scientific

All-lower-case scientific name of the crop species. When crop is not species specific the genus of the crop is given

crop_season

Crop category for length growing season

crop_makkink

Crop category for makkink correction factors

Coefficient table for evaluating crumbleability

Description

This table contains the coefficients for evaluating the crumbleability. This table is used internally in ind_crumbleability

Usage

eval.crumbleability

Format

An object of class data.table (inherits from data.frame) with 16 rows and 4 columns.

Evaluate using the general logistic function

Description

This function evaluates the calculated values from an indicator using a general logistic function

Usage

evaluate_logistic(x, b, x0, v, increasing = TRUE)

Arguments

Value

A transformed variable after applying a logistic evaluation function. A numeric value.

References

https://en.wikipedia.org/wiki/Generalised_logistic_function

Examples

evaluate_logistic(x = 5, b = 2, x0 = 3, v = 2.6)
evaluate_logistic(x = c(0.1,0.5,1.5,3.5), b = 2, x0 = 3, v = 2.6)

Evaluate using parabolic function with

Description

This function evaluates the calculated values from an indicator using a parabolic function. After the optimum is reached the it stays at its plateau.

Usage

evaluate_parabolic(x, x.top)

Arguments

Value

A transformed variable after applying a parabolic evaluation function. A numeric value.

Examples

evaluate_parabolic(x = 5, x.top = 8)
evaluate_parabolic(x = c(0.1,0.5,1.5,3.5), x.top = 6.5)

Convert possible B_AER_CBS values to standardized values

Description

This function formats information of Agricultural Economic Region so it can be understood by other OBIC functions

Usage

format_aer(B_AER_CBS)

Arguments

Value

A standardized B_AER_CBS value as required for the OBIC functions. A character string.

Examples

format_aer(c("LG13","LG12"))
format_aer(c("LG13","LG12",'Rivierengebied'))

Convert possible B_GWL_CLASS values to standardized values

Description

This function formats ground water table information so it can be understood by other OBIC functions

Usage

format_gwt(B_GWL_CLASS)

Arguments

Value

A standardized B_GWL_CLASS value as required for the OBIC functions. A character string.

Examples

format_gwt(c('sVII', 'sVI'))
format_gwt(c('sVII', 'sVI','GtII', 'GtI'))

Convert possible B_SC_WENR values to standardized values

Description

This function converts numeric values for B_SC_WENR to values used by other OBIC functions if numeric values are entered.

Usage

format_soilcompaction(B_SC_WENR)

Arguments

Value

A standardized B_GWL_CLASS value as required for the OBIC functions. A character string.

Examples

format_soilcompaction(c('10', '11'))
format_soilcompaction(c('2', '3',"Matig", "Groot"))

Calculate the indicator aggregate stability

Description

This function calculates the indicator for the the aggregate stability of the soil by using the index calculated by calc_aggregatestability

Usage

ind_aggregatestability(D_AS)

Arguments

Value

The evaluated score for the soil function aggregate stability. A numeric value between 0 and 1.

Examples

ind_aggregatestability(D_AS = 0.3)
ind_aggregatestability(D_AS = c(0.3,0.6,0.9))

Calculate the indicator for BodemConditieScore

Description

This function calculates the final score for the BodemConditieScore by using the scores calculated by calc_bcs

Usage

ind_bcs(D_BCS)

Arguments

Value

The evaluated score for the Visual Soil Assessment. A numeric value between 0 and 50.

Examples

ind_bcs(D_BCS = 12)
ind_bcs(D_BCS = c(12,18,26,30))

Calculate the indicator for soil fertility given the CEC

Description

This function estimate how much cations can be buffer by soil, being calculated by calc_cec

Usage

ind_cec(D_CEC)

Arguments

Value

The evaluated score for the soil function to buffer cations. A numeric value between 0 and 1.

Examples

ind_cec(D_CEC = 85)
ind_cec(D_CEC = c(85,135,385))

Calculate indicator for subsoil compaction

Description

This function calculates the indicator for the risk for soil compaction of the subsoil. derived from van den Akker et al. (2013) Risico op ondergrondverdichting in het landelijk gebied in kaart, Alterra-rapport 2409, Alterra, Wageningen University and Research Centre,

Usage

ind_compaction(B_SC_WENR)

Arguments

Value

The evaluated score for the soil function for subsoil compaction. A numeric value between 0 and 1.

References

Akker et al. (2013) Risico op ondergrondverdichting in het landelijk gebied in kaart, Alterra-rapport 2409, Alterra, Wageningen University and Research Centre.

Examples

ind_compaction(B_SC_WENR = 'Zeer groot')
ind_compaction(B_SC_WENR = c('Zeer groot','Van nature dicht'))

Calculate the indicator for Cu-availability

Description

This function calculates the indicator for the the Cu availability in soil by using the Cu-index as calculated by calc_copper_availability

Usage

ind_copper(D_CU, B_LU_BRP)

Arguments

Value

The evaluated score for the soil function to supply copper for crop uptake. A numeric value between 0 and 1.

Examples

ind_copper(D_CU = 125, B_LU_BRP = 265)
ind_copper(D_CU = c(125,335), B_LU_BRP = c(1019,256))
 

Calculate the indicator for crumbleability

Description

This function calculates the indicator for crumbleability. The crumbleability is calculated by calc_crumbleability

Usage

ind_crumbleability(D_CR, B_LU_BRP)

Arguments

Value

The evaluated score for the soil function crumbleability. A numeric value between 0 and 1.

Examples

ind_crumbleability(D_CR = 3, B_LU_BRP = 1910)
ind_crumbleability(D_CR = c(2,6), B_LU_BRP = c(1910,1910))

Calculate groundwater recharge of a soil

Description

This function calculates an index score for groundwater storage based on precipitation surplus, infiltration at saturation, sealing risk, drainage and subsoil compaction

Usage

ind_gw_recharge(B_LU_BRP, D_PSP, D_WRI_K, I_P_SE, I_P_CO, B_DRAIN, B_GWL_CLASS)

Arguments

Value

The evaluated score for the soil function to improve groundwater recharge. A numeric value between 0 and 1.

Examples

ind_gw_recharge(B_LU_BRP = 265,D_PSP = 200, D_WRI_K = 10, I_P_SE = 0.6, I_P_CO = 0.9, 
B_DRAIN = FALSE, B_GWL_CLASS = 'GtV')
ind_gw_recharge(B_LU_BRP = 233, D_PSP = 400, D_WRI_K = 10, I_P_SE = 0.4, I_P_CO = 0.2, 
B_DRAIN = TRUE, B_GWL_CLASS = 'GtII')

Calculate the indicator for Magnesium

Description

This function calculates the indicator for the the Magnesium content of the soil by using the Mg-availability calculated by calc_magnesium_availability

Usage

ind_magnesium(D_MG, B_LU_BRP, B_SOILTYPE_AGR)

Arguments

Value

The evaluated score for the soil function to supply magnesium for crop uptake. A numeric value.

Examples

ind_magnesium(D_MG = 125, B_LU_BRP = 265, B_SOILTYPE_AGR = 'dekzand')
ind_magnesium(D_MG = c(125,35), B_LU_BRP = c(265,256), B_SOILTYPE_AGR = rep('dekzand',2))
 

Calculate the indicator for sustainable management given a required ecoystem service

Description

This function calculates the the sustainability of strategic management options for a given ecoystem service as calculated by calc_man_ess The main source of this indicator is developed for Label Duurzaam Bodembeheer (Van der Wal, 2016)

Usage

ind_man_ess(D_MAN, B_LU_BRP, B_SOILTYPE_AGR, type)

Arguments

Value

The evaluated score for the evaluated soil management for a specific ecosystem service. A numeric value between 0 and 1. This is done for the following ESS: I_M_SOILFERTILITY, I_M_CLIMATE, I_M_WATERQUALITY and I_M_BIODIVERSITY.

Examples

ind_man_ess(D_MAN = 3.5,B_LU_BRP = 1019, B_SOILTYPE_AGR = 'dekzand',type = 'I_M_SOILFERTILITY')
ind_man_ess(D_MAN = c(2,6,15), B_LU_BRP = c(1019,256,1019),B_SOILTYPE_AGR = rep('dekzand',3),
type = 'I_M_SOILFERTILITY')

Calculate the indicator for sustainable management

Description

This function calculates the the sustainability of strategic management options as calculated by calc_management The main source of this indicator is developed for Label Duurzaam Bodembeheer (Van der Wal, 2016)

Usage

ind_management(D_MAN, B_LU_BRP, B_SOILTYPE_AGR)

Arguments

Details

The current function allows a maximum score of 18 points for arable systems, 12 for maize and 10 for grass (non-peat), 17 for grass on peat, and 4 for nature.

Value

The evaluated score for the evaluated soil management given the Label Sustainable Soil Management. A numeric value between 0 and 1.

Examples

ind_management(D_MAN = 15,B_LU_BRP = 1019, B_SOILTYPE_AGR = 'dekzand')
ind_management(D_MAN = c(2,6,15), B_LU_BRP = c(1019,256,1019),B_SOILTYPE_AGR = rep('dekzand',3))

Calculate an indicator value for nitrogen use efficiency and leaching based on N surplus

Description

This function gives an indicator value for nitrogen use efficiency calculated by calc_n_efficiency, this function makes use of ind_nretention

Usage

ind_n_efficiency(D_NLEACH, leaching_to = "gw")

Arguments

Value

The evaluated score for the soil function to enhance the nitrogen use efficiency. A numeric value between 0 and 1.

Examples

ind_n_efficiency(D_NLEACH = 50, leaching_to = 'gw')
ind_n_efficiency(D_NLEACH = c(5,15,25,75), leaching_to = 'sw')
 

Calculate indicator for plant parasitic nematodes

Description

This function calculates the indicator for the presence of plant parasitic nematodes. If input values are not given, the number is assumed to be zero.

Usage

ind_nematodes(
  B_LU_BRP = B_LU_BRP,
  A_RLN_PR_TOT = 0,
  A_RLN_PR_CREN = 0,
  A_RLN_PR_NEG = 0,
  A_RLN_PR_PEN = 0,
  A_RLN_PR_PRA = 0,
  A_RLN_PR_THO = 0,
  A_RLN_PR_FLA = 0,
  A_RLN_PR_FAL = 0,
  A_RLN_PR_PIN = 0,
  A_RLN_PR_PSE = 0,
  A_RLN_PR_VUL = 0,
  A_RLN_PR_DUN = 0,
  A_RLN_PR_ZEA = 0,
  A_RKN_ME_TOT = 0,
  A_RKN_ME_HAP = 0,
  A_RKN_ME_CHIFAL = 0,
  A_RKN_ME_CHI = 0,
  A_RKN_ME_NAA = 0,
  A_RKN_ME_FAL = 0,
  A_RKN_ME_MIN = 0,
  A_RKN_ME_INC = 0,
  A_RKN_ME_JAV = 0,
  A_RKN_ME_ART = 0,
  A_RKN_ME_ARE = 0,
  A_RKN_ME_ARD = 0,
  A_DSN_TR_TOT = 0,
  A_DSN_TR_SIM = 0,
  A_DSN_TR_PRI = 0,
  A_DSN_TR_VIR = 0,
  A_DSN_TR_SPA = 0,
  A_DSN_TR_CYL = 0,
  A_DSN_TR_HOO = 0,
  A_DSN_PA_TER = 0,
  A_DSN_PA_PAC = 0,
  A_DSN_PA_ANE = 0,
  A_DSN_PA_NAN = 0,
  A_DSN_TY_TOT = 0,
  A_DSN_RO_TOT = 0,
  A_DSN_XI_TOT = 0,
  A_DSN_LO_TOT = 0,
  A_DSN_HEM_TOT = 0,
  A_DSN_HEL_TOT = 0,
  A_SN_DI_TOT = 0,
  A_SN_DI_DIP = 0,
  A_SN_DI_DES = 0,
  A_OPN_PA_TOT = 0,
  A_OPN_PA_BUK = 0,
  A_OPN_CY_TOT = 0,
  A_OPN_AP_TOT = 0,
  A_OPN_AP_FRA = 0,
  A_OPN_AP_RIT = 0,
  A_OPN_AP_SUB = 0,
  A_OPN_CR_TOT = 0,
  A_OPN_SU_TOT = 0,
  A_NPN_SA_TOT = 0
)

Arguments

Value

The evaluated score for the soil function for nematode community. A numeric value between 0 and 1.

Examples

ind_nematodes(B_LU_BRP = 1019)
ind_nematodes(B_LU_BRP = 1019,A_RLN_PR_TOT = 250,A_RLN_PR_ZEA = 400,A_SN_DI_DIP = 5)

Calculate indicator for plant parasitic nematodes

Description

This function calculates the indicator for the presence of plant parasitic nematodes. All nematodes present in a sample are used. A subset of nematodes is weighted in the set regardless of their presence.

Usage

ind_nematodes_list(A_NEMA)

Arguments

Value

The evaluated score for the soil function for nematode community. A numeric value between 0 and 1.

Examples

## Not run: 
ind_nematodes_list(data.table(species = 'Cysteaaltjes',count = 200))
ind_nematodes_list(data.table(species = c('Cysteaaltjes','Ditylenchus dipsaci'),
count = c(200,7)))

## End(Not run)

Calculate the indicator for NLV

Description

This function calculates the indicator for the the nitrogen content of the soil by using the NLV calculated by calc_nlv

Usage

ind_nitrogen(D_NLV, B_LU_BRP)

Arguments

Value

The evaluated score for the soil function to supply nitrogen for crop uptake. A numeric value between 0 and 1.

Examples

ind_nitrogen(D_NLV = 85,B_LU_BRP = 256)
ind_nitrogen(D_NLV = c(150,65,35),B_LU_BRP = c(256,1019,1019))
 

Calculate the indicator for N retention for groundwater or surface water

Description

This function calculates the indicator for the N retention of the soil by using the N leaching to groundwater or surface water calculated by calc_nleach

Usage

ind_nretention(D_NW, leaching_to)

Arguments

Value

The evaluated score for the soil function to supply nitrogen for crop uptake. A numeric value between 0 and 1.

Examples

ind_nretention(D_NW = 15,leaching_to = 'gw')
ind_nretention(D_NW = c(.2,5.6,15.6),leaching_to = 'ow')
 

Calculate the indicator score for the permeability of the top soil

Description

This function calculates the indicator score for the permeability of the top soil

Usage

ind_permeability(D_WRI_K)

Arguments

Calculate an indicator score for pesticide leaching

Description

This function calculates the indicator value for pesticide leaching from a soil

Usage

ind_pesticide_leaching(D_PESTICIDE)

Arguments

Value

The evaluated score for the soil function to minimize pesticide leaching. A numeric value between 0 and 1.

Examples

ind_pesticide_leaching(D_PESTICIDE = 0.7)
ind_pesticide_leaching(D_PESTICIDE  = c(0.4,0.6,0.8,1))
 

Calculate the indicator for pH

Description

This function calculates the indicator for the pH of the soil by the difference with the optimum pH. This is calculated in calc_ph_delta.

Usage

ind_ph(D_PH_DELTA)

Arguments

Value

The evaluated score for the soil function to buffer pH within optimum range for crop growth. A numeric value between 0 and 1.

Examples

ind_ph(D_PH_DELTA = 0.8)
ind_ph(D_PH_DELTA = c(0.2,0.6,0.8,1.5))
 

Calculate the indicator for the the phosphate availability

Description

This function calculates the indicator for the phosphate availability calculated by calc_phosphate_availability

Usage

ind_phosphate_availability(D_PBI)

Arguments

Value

The evaluated score for the soil function to supply and buffer phosphorus for crop uptake. A numeric value between 0 and 1.

Examples

ind_phosphate_availability(D_PBI = 3.5)
ind_phosphate_availability(D_PBI = c(0.5,0.8,2.5,5,15,35,75))
 

Calculate the indicator for microbial biological activity

Description

This function calculates the indicator that assess the microbial biological activity of the soil by using the PMN calculated by calc_pmn

Usage

ind_pmn(D_PMN)

Arguments

Value

The evaluated score for the soil function reflecting the microbial activity of a soil (specifically the potentially mineralizable N rate). A numeric value between 0 and 1.

Examples

ind_pmn(D_PMN = 24)
ind_pmn(D_PMN = c(54,265))

Calculate the indicator for Potassium Availability

Description

This function calculates the indicator for the the Potassium Availability of the soil by using the K-availability calculated by calc_potassium_availability

Usage

ind_potassium(D_K, B_LU_BRP, B_SOILTYPE_AGR, A_SOM_LOI)

Arguments

Value

The evaluated score for the soil function to supply potassium for crop uptake. A numeric value between 0 and 1.

Examples

ind_potassium(D_K = 4.5,B_LU_BRP = 256,B_SOILTYPE_AGR='dekzand',A_SOM_LOI=4)
ind_potassium(c(2.5,3.5,6.5),c(256,1019,1019),rep('dekzand',3),c(3.5,4.5,7.5))
 

Calculate indicator for precipitation surplus

Description

This function calculates the indicator value for precipitation surplus

Usage

ind_psp(D_PSP, B_LU_BRP)

Arguments

Calculate indicator for soil resistance

Description

This function calculates the indicator for the resistance of the soil against diseases and is indicated by the amount of soil life.

Usage

ind_resistance(A_SOM_LOI)

Arguments

Value

The evaluated score for the soil function to resist diseases. A numeric value between 0 and 1.

Examples

ind_resistance(A_SOM_LOI = 3.5)
ind_resistance(A_SOM_LOI = c(3.5,5.5,15,25))

Calculate the soil sealing indicator

Description

This function calculates the indicator for the soil sealing calculated by calc_sealing_risk

Usage

ind_sealing(D_SE, B_LU_BRP)

Arguments

Value

The evaluated score for the soil function to avoid crop damage due to sealing of surface. A numeric value between 0 and 1.

Examples

ind_sealing(D_SE = 15,B_LU_BRP = 256)
ind_sealing(D_SE = c(5,15,35),B_LU_BRP = c(1019,1019,1019))
 

Calculate the indicator for SLV

Description

This function calculates the indicator for the the S-index by using the SLV calculated by calc_slv

Usage

ind_sulfur(D_SLV, B_LU_BRP, B_SOILTYPE_AGR, B_AER_CBS)

Arguments

Value

The evaluated score for the soil function to supply sulfur for crop uptake. A numeric value between 0 and 1.

Examples

ind_sulfur(D_SLV = 15,B_LU_BRP = 256,B_SOILTYPE_AGR = 'dekzand',B_AER_CBS = 'Rivierengebied')
ind_sulfur(c(10,15,35),c(256,1019,1019),rep('rivierklei',3),rep('Rivierengebied',3))
 

Calculate the indicator for SLV (deprecated)

Description

This function calculates the indicator for the the S-index by using the SLV calculated by calc_slv

Usage

ind_sulpher(D_SLV, B_LU_BRP, B_SOILTYPE_AGR, B_AER_CBS)

Arguments

Details

Pl

Value

The evaluated score for the soil function to supply sulfur for crop uptake. A numeric value between 0 and 1.

Examples

ind_sulpher(D_SLV = 15,B_LU_BRP = 256,B_SOILTYPE_AGR = 'dekzand',
B_AER_CBS = 'Rivierengebied')
ind_sulpher(c(10,15,35),c(256,1019,1019),rep('rivierklei',3),rep('Rivierengebied',3))
 

Calculate indicator for Water Retention index

Description

This function evaluates different Water Retention Indices. These include : 'wilting point','field capacity','water holding capacity','plant available water' and 'Ksat'

Usage

ind_waterretention(D_P_WRI, type = "plant available water")

Arguments

Value

The evaluated score for the soil function to retain and buffer water. Depending on the "type" chosen, the soil is evaluated for 'wilting point','field capacity','water holding capacity','plant available water' or 'Ksat'. Output is a numeric value varying between 0 and 1.

Examples

ind_waterretention(D_P_WRI = 75)
ind_waterretention(D_P_WRI = c(15,50,75,150))
ind_waterretention(D_P_WRI = c(0.1,0.2,0.5,0.8), type = 'water holding capacity')

Calculate the Water Stress Index

Description

This function calculates the risk for yield depression due to drought, an excess of water or a combination of both. The WSI is calculated by calc_waterstressindex

Usage

ind_waterstressindex(D_WSI)

Arguments

Value

The evaluated score for the soil function to resist drought or wetness stress by crops. A numeric value between 0 and 1.

Examples

ind_waterstressindex(D_WSI = 45)
ind_waterstressindex(D_WSI = c(5,15,25,35))
 

Calculate indicator for wind erodibility

Description

This function calculates the indicator for the resistance of the soil against wind erosion.

Usage

ind_winderodibility(D_P_DU)

Arguments

Value

The evaluated score for the soil function to avoid soil damage due to wind erosion. A numeric value between 0 and 1.

Examples

ind_winderodibility(D_P_DU = 0.85)
ind_winderodibility(D_P_DU = c(0.15,0.6,0.9))
 

Calculate indicator for workability

Description

This function calculates the indicator for the workability of the soil expressed as the period in which the soil can be worked without inflicting structural damage that cannot be restored by the regular management on the farm.

Usage

ind_workability(D_WO, B_LU_BRP)

Arguments

Value

The evaluated score for the soil function to allow the soil to be managed by agricultural activities. A numeric value between 0 and 1.

Examples

ind_workability(D_WO = 0.85,B_LU_BRP = 256)
ind_workability(D_WO = c(0.15,0.6,0.9),B_LU_BRP = c(256,1019,1019))
 

Calculate the indicator for Zn-availability

Description

This function calculates the indicator for the the Zn availability in soil by using the Zn-index as calculated by calc_zinc_availability

Usage

ind_zinc(D_ZN)

Arguments

Value

The evaluated score for the soil function to supply zinc for crop uptake. A numeric value between 0 and 1.

Examples

ind_zinc(D_ZN = 45)
ind_zinc(D_ZN = c(12.5,35,65))
 

Relational table linking soil management measures to ecosystem services

Description

This table assigns which measures positively contribute to the ecosystem services included

Usage

management.obic

Format

An object of class data.table (inherits from data.frame) with 15 rows and 6 columns.

Details

measure

The name of measure

I_M_SOILFERTILITY

integrated soil management indicator for soil fertility

I_M_CLIMATE

integrated soil management indicator for soil carbon sequestration

I_M_WATERQUALITY

integrated soil management indicator for water quality

I_M_BIODIVERSITY

Integrated soil management indicator for soil biodiversity

Damage and reproduction of soil-borne pathogens and pests on crops

Description

This table includes information from aaltjesschema (April 2021), a website where information is collected on the vulnerability of crops to plant parasitic nematodes and diseases that use nematodes as vector.

Usage

nema.crop.rot.obic

Format

An object of class data.table (inherits from data.frame) with 7059 rows and 21 columns.

Details

crop

crop as called in aaltjesschema

name_scientific

scientific name of nematode

propagation

how easily a nematode can propagate on a crop given as strings with 5 classes

damage

strings indicating how much damage a nematode can inflict on a crop, with 5 classes

cultivar_dependent

boolean whether there are differences in propgation between cultivars of the crop

serotype_dependant

boolean whether there are differences in propagation between serotypes of the pathogen

dalgrond

boolean whether information is valid for soiltype 'dalgrond'

klei

boolean whether information is valid for soiltype 'klei'

loess

boolean whether information is valid for soiltype 'loess'

zand

boolean whether information is valid for soiltype 'zand'

zavel

boolean whether information is valid for soiltype 'zavel'

info

string whether there is information on propgation, differentiating between none, yes, and some

name_common

string, common name of pathogen in Dutch, if no common name is available, scientific name is given

nema_name

string, full name of pathogen in aaltjesschema, includes common and scientific name

grondsoort

string with letters indicating for which soil the information is valid

groen_br

boolean indicating that the crop is a green manure on fallow

groen_vs

boolean indicating that the crop is a green manure in early stubble

groen_od

boolean indicating that the crop is a green manure beneath cover crop

groen_ls

boolean indicating that the crop is a green manure in late stubble

groen_st

boolean indicating that the crop is a green manure as drifting deck

crop_name_scientific

string, scientific name of crop species or genus

Nematode table

Description

This table contains information uses for calculations on nematode species counts

Usage

nema.obic

Format

An object of class data.table (inherits from data.frame) with 78 rows and 7 columns.

Details

geel

The intermediate infestation severity count

rood

The count at which a severe infestation is present

species

The species or sometimes genera of the plant parasitic nematode

standard

A boolean indicating whether the species should always be used in calculating the indicator score, regardless of the number of nematodes

b

Growth rate (b) for the evaluate_logistics function

v

v for the evaluate_logistics function, affects the growth rate near the maximum

Table with fractions of excess N which runs off to groundwater and surface water

Description

This table contains the fractions of N overshot which runs off to groundwater / surface water, per soil type, crop type, and groundwater table

Usage

nleach_table

Format

An object of class data.table (inherits from data.frame) with 198 rows and 7 columns.

Details

gewas

crop type

bodem

soil type

ghg

Lower value for groundwater table (cm-mv)

glg

Upper value for groundwater table (cm-mv)

B_GT

grondwatertrap

nf

Original values of N run-off fraction to surface water (kg N drain/ha/year per kg N overschot/ha/year) or groundwater (mg NO3/L per kg N overschot/ha/year)

leaching_to-set

Tells if leaching to ground water or surface water)

Evaluate effects of measures

Description

This function quantifies the effects of 11 soil measures on the OBI score

Usage

obic_evalmeasure(dt.score, extensive = FALSE)

Arguments

Calculate the Open Bodem Index score for a series of fields belonging to a farm

Description

This functions wraps the functions of the OBIC into one main function to calculate the score for Open Bodem Index (OBI). In contrast to obic_field, this wrapper uses a data.table as input.

Usage

obic_farm(dt)

Arguments

Details

The data.table should contain all required inputs for soil properties needed to calculate OBI score. Management information is optional as well as the observations from the visual soil assessment. The threshold values per category of soil functions need to have an equal length, with fractions defining the class boundaries in increasing order. The lowest boundary value (zero) is not needed.

Value

The output of the Open Bodem Index Calculator for a series of agricultural fields belonging to a single farm. Depending on the output type, different output objects can be returned. These include the estimated OBI scores (both total and aggregated subscores), the value of the underling indicators as well the possible recommendations to improve the soil quality. The output is a list with field properties as well as aggregated farm properties

Examples

 
## Not run: 
obic_farm(dt = data.table(B_SOILTYPE_AGR = 'rivierklei',B_GWL_CLASS = "II",
B_GWL_GLG = 75,B_GWL_GHG = 10,
B_GWL_ZCRIT = 50,B_SC_WENR = '2',B_HELP_WENR = "MOb72",B_AER_CBS = 'LG01',
B_LU_BRP = c( 1010, 1010,263,263, 263,265,265,265),A_SOM_LOI = 3.91,A_SAND_MI = 66.3,
A_SILT_MI = 22.8,A_CLAY_MI = 7.8,A_PH_CC = 5.4,A_N_RT = 1528.33,A_CN_FR = 13.02,
A_S_RT = 321.26,A_N_PMN = 63.3,A_P_AL = 50.2,A_P_CC = 2.9,A_P_WA = 50.5,
A_CEC_CO = 56.9,A_CA_CO_PO = 66.87,A_MG_CO_PO = 13.97,A_K_CO_PO = 3.06,
A_K_CC = 58.6,A_MG_CC = 77.53,A_MN_CC = 7586.61,A_ZN_CC = 726.2,A_CU_CC = 68.8,
A_C_BCS = 1,A_CC_BCS = 1,A_GS_BCS = 1,A_P_BCS = 1,A_RD_BCS = 1,A_EW_BCS = 1,
A_SS_BCS = 1,A_RT_BCS = 1,A_SC_BCS = 1,M_COMPOST = 0,M_GREEN = FALSE,M_NONBARE =FALSE,
M_EARLYCROP = FALSE,M_SLEEPHOSE = FALSE,M_DRAIN = FALSE,M_DITCH = FALSE,
M_UNDERSEED = FALSE,M_LIME = FALSE,M_MECHWEEDS = FALSE,M_NONINVTILL = FALSE,
M_PESTICIDES_DST = FALSE,M_SOLIDMANURE = FALSE,M_SSPM = FALSE,M_STRAWRESIDUE = FALSE))

## End(Not run)

Calculate the Open Bodem Index score for one field

Description

This functions wraps the functions of the OBIC into one main function to calculate the score for Open Bodem Index (OBI) for a single field.

Usage

obic_field(
  B_SOILTYPE_AGR,
  B_GWL_CLASS,
  B_SC_WENR,
  B_HELP_WENR,
  B_AER_CBS,
  B_GWL_GLG,
  B_GWL_GHG,
  B_GWL_ZCRIT,
  B_LU_BRP,
  A_SOM_LOI,
  A_SAND_MI,
  A_SILT_MI,
  A_CLAY_MI,
  A_PH_CC,
  A_N_RT,
  A_CN_FR,
  A_S_RT,
  A_N_PMN,
  A_P_AL,
  A_P_CC,
  A_P_WA,
  A_CEC_CO,
  A_CA_CO_PO,
  A_MG_CO_PO,
  A_K_CO_PO,
  A_K_CC,
  A_MG_CC,
  A_MN_CC,
  A_ZN_CC,
  A_CU_CC,
  A_C_BCS = NA,
  A_CC_BCS = NA,
  A_GS_BCS = NA,
  A_P_BCS = NA,
  A_RD_BCS = NA,
  A_EW_BCS = NA,
  A_SS_BCS = NA,
  A_RT_BCS = NA,
  A_SC_BCS = NA,
  B_DRAIN = FALSE,
  B_FERT_NORM_FR = 1,
  M_COMPOST = NA_real_,
  M_GREEN = NA,
  M_NONBARE = NA,
  M_EARLYCROP = NA,
  M_SLEEPHOSE = NA,
  M_DRAIN = NA,
  M_DITCH = NA,
  M_UNDERSEED = NA,
  M_LIME = NA,
  M_NONINVTILL = NA,
  M_SSPM = NA,
  M_SOLIDMANURE = NA,
  M_STRAWRESIDUE = NA,
  M_MECHWEEDS = NA,
  M_PESTICIDES_DST = NA,
  ID = 1,
  output = "all"
)

Arguments

Details

It is assumed that the crop series is a continuous series in decreasing order of years. So most recent year first, oldest year last.

Value

The output of the Open Bodem Index Calculator for a specific agricultural field. Depending on the output type, different output objects can be returned. These include the estimated OBI scores (both total and aggregated subscores), the value of the underling indicators as well the possible recommendations to improve the soil quality. The output is always a data.table.

Examples

## Not run: 
obic_field( B_SOILTYPE_AGR = 'rivierklei',B_GWL_CLASS = "II",B_GWL_GLG = 75,B_GWL_GHG = 10,
B_GWL_ZCRIT = 50,B_SC_WENR = '2',B_HELP_WENR = "MOb72",B_AER_CBS = 'LG01',
B_LU_BRP = c( 1010, 1010,263,263, 263,265,265,265),A_SOM_LOI = 3.91,A_SAND_MI = 66.3,
A_SILT_MI = 22.8,A_CLAY_MI = 7.8,A_PH_CC = 5.4,A_N_RT = 1528.33,A_CN_FR = 13.02,
A_S_RT = 321.26,A_N_PMN = 63.3,A_P_AL = 50.2,A_P_CC = 2.9,A_P_WA = 50.5,
A_CEC_CO = 56.9,A_CA_CO_PO = 66.87,A_MG_CO_PO = 13.97,A_K_CO_PO = 3.06,
A_K_CC = 58.6,A_MG_CC = 77.53,A_MN_CC = 7586.61,A_ZN_CC = 726.2,A_CU_CC = 68.8,
A_C_BCS = 1,A_CC_BCS = 1,A_GS_BCS = 1,A_P_BCS = 1,A_RD_BCS = 1,A_EW_BCS = 1,
A_SS_BCS = 1,A_RT_BCS = 1,A_SC_BCS = 1,M_COMPOST = 0,M_GREEN = FALSE,M_NONBARE =FALSE,
M_EARLYCROP = FALSE,M_SLEEPHOSE = FALSE,M_DRAIN = FALSE,M_DITCH = FALSE,
M_UNDERSEED = FALSE,M_LIME = FALSE,M_MECHWEEDS = FALSE,M_NONINVTILL = FALSE,
M_PESTICIDES_DST = FALSE,M_SOLIDMANURE = FALSE,M_SSPM = FALSE,M_STRAWRESIDUE = FALSE)

## End(Not run)
 

Calculate the Open Bodem Index score for a data table

Description

This functions wraps the functions of the OBIC into one main function to calculate the score for Open Bodem Index (OBI). In contrast to obic_field, this wrapper can handle a data.table as input. Multiple sites (distinguished in the column 'ID') can be simulated simultaneously.

Usage

obic_field_dt(dt, output = "all")

Arguments

Value

The output of the Open Bodem Index Calculator for a specific agricultural field. Depending on the output type, different output objects can be returned. These include the estimated OBI scores (both total and aggregated subscores), the value of the underling indicators as well the possible recommendations to improve the soil quality. The output is always a data.table.

Examples

 
## Not run: 
obic_field_dt(data.table(B_SOILTYPE_AGR = 'rivierklei',B_GWL_CLASS = "II",
B_GWL_GLG = 75,B_GWL_GHG = 10,
B_GWL_ZCRIT = 50,B_SC_WENR = '2',B_HELP_WENR = "MOb72",B_AER_CBS = 'LG01',
B_LU_BRP = c( 1010, 1010,263,263, 263,265,265,265),A_SOM_LOI = 3.91,A_SAND_MI = 66.3,
A_SILT_MI = 22.8,A_CLAY_MI = 7.8,A_PH_CC = 5.4,A_N_RT = 1528.33,A_CN_FR = 13.02,
A_S_RT = 321.26,A_N_PMN = 63.3,A_P_AL = 50.2,A_P_CC = 2.9,A_P_WA = 50.5,
A_CEC_CO = 56.9,A_CA_CO_PO = 66.87,A_MG_CO_PO = 13.97,A_K_CO_PO = 3.06,
A_K_CC = 58.6,A_MG_CC = 77.53,A_MN_CC = 7586.61,A_ZN_CC = 726.2,A_CU_CC = 68.8,
A_C_BCS = 1,A_CC_BCS = 1,A_GS_BCS = 1,A_P_BCS = 1,A_RD_BCS = 1,A_EW_BCS = 1,
A_SS_BCS = 1,A_RT_BCS = 1,A_SC_BCS = 1,M_COMPOST = 0,M_GREEN = FALSE,M_NONBARE =FALSE,
M_EARLYCROP = FALSE,M_SLEEPHOSE = FALSE,M_DRAIN = FALSE,M_DITCH = FALSE,
M_UNDERSEED = FALSE,M_LIME = FALSE,M_MECHWEEDS = FALSE,M_NONINVTILL = FALSE,
M_PESTICIDES_DST = FALSE,M_SOLIDMANURE = FALSE,M_SSPM = FALSE,M_STRAWRESIDUE = FALSE))

## End(Not run)

Recommend measurements for better soil management

Description

This function gives recommendations better soil management based on the OBI score

Usage

obic_recommendations(dt.recom)

Arguments

Recommend measurements for better soil management

Description

This function returns a list of management recommendations based on OBI scores as part of BodemKwaliteitsPlan.

Usage

obic_recommendations_bkp(dt.score, B_LU_BRP, B_SOILTYPE_AGR)

Arguments

Water retention curve

Description

This function compute water content at given pressure head, using Van Genuchten water retention curve

Usage

pF_curve(head, thetaR, thetaS, alfa, n)

Arguments

Value

theta (numeric) water content (cm3/cm3)

The moisture content of a soil given a certain pressure head. A numeric value.

Examples

pF_curve(head = 2.2, thetaR = 0.01, thetaS = 0.35, alfa = 0.3,n = 1.6)
pF_curve(head = 4.2, thetaR = 0.01, thetaS = 0.35, alfa = 0.3,n = 1.6)

Parameter estimation based on class of Staringreeks (Tabel 3, Wosten 2001)

Description

Parameter estimation based on class of Staringreeks (Tabel 3, Wosten 2001)

Usage

pFpara_class(Pklei, Pleem, Psom, M50)

Arguments

Value

a table with the following columns: ThetaR (numeric) residual water content (cm3/cm3) ThetaS (numeric) saturated water content (cm3/cm3) alfa (numeric) related to the inverse of the air entry suction, alfa > 0 (1/cm) n (numeric) a measure of the pore-size distribution, n>1, dimensionless ksat (numeric) saturated hydraulic conductivity (cm/d)

Examples

pFpara_class(Pklei = 25, Pleem = 15, Psom = 4.5,M50 = 150)
pFpara_class(Pklei = 45, Pleem = 3, Psom = 4.5,M50 = 150)

Estimate water retention curve parameters based on Wosten 1999

Description

This function estimates water retention curve parameters using Pedo transfer function of Wosten (1999) based on HYPRES

Usage

pFpara_ptf_Wosten1999(Pklei, Psilt, Psom, Bovengrond)

Arguments

Value

a table with the following columns:

Dichtheid (numeric) soil bulk density (g/cm3) ThetaR (numeric) residual water content (cm3/cm3) ThetaS (numeric) saturated water content (cm3/cm3) alfa (numeric) related to the inverse of the air entry suction, alfa > 0 (1/cm) n (numeric) a measure of the pore-size distribution, n>1, dimensionless ksat (numeric) saturated hydraulic conductivity (cm/d)

References

Wösten, J.H.M , Lilly, A., Nemes, A., Le Bas, C. (1999) Development and use of a database of hydraulic properties of European soils. Geoderma 90 (3-4): 169-185.

Examples

pFpara_ptf_Wosten1999(Pklei = 25, Psilt = 15, Psom = 4.5, Bovengrond = 1)
pFpara_ptf_Wosten1999(Pklei = 45, Psilt = 3, Psom = 4.5, Bovengrond = 1)

Estimate water retention curve parameters based on Wosten 2001

Description

This function estimates water retention curve parameters using Pedo transfer function of Wosten (2001)

Usage

pFpara_ptf_Wosten2001(Pklei, Pleem, Psom, M50, Bovengrond)

Arguments

Value

a table with the following columns: Dichtheid (numeric) soil bulk density (g/cm3) ThetaR (numeric) residual water content (cm3/cm3) ThetaS (numeric) saturated water content (cm3/cm3) alfa (numeric) related to the inverse of the air entry suction, alfa > 0 (1/cm) n (numeric) a measure of the pore-size distribution, n>1, dimensionless ksat (numeric) saturated hydraulic conductivity (cm/d) l (numeric) dimension parameter

References

Wösten, J. H. M., Veerman, G. ., de Groot, W. J., & Stolte, J. (2001). Waterretentie en doorlatendheidskarakteristieken van boven- en ondergronden in Nederland: de Staringreeks. Alterra Rapport, 153, 86. https://doi.org/153

Examples

pFpara_ptf_Wosten2001(Pklei = 25, Pleem = 15, Psom = 4.5,M50 = 150, Bovengrond = 1)
pFpara_ptf_Wosten2001(Pklei = 45, Pleem = 3, Psom = 4.5,M50 = 150,Bovengrond = 1)

Applicability range of measures, including literature based estimates, of effects on soil indicators

Description

This table defines the effects of 11 measures on soil indicators. This table is used internally in obic_evalmeasure

This table defines the effects of 11 measures on soil indicators

Usage

recom.obic

recom.obic

Format

An object of class data.table (inherits from data.frame) with 4048 rows and 11 columns.

An object of class data.table (inherits from data.frame) with 4048 rows and 11 columns.

Details

m_nr

The ID number of measure

m_description

The description of measure

m_prio

weighing factor for measure. This is not used in the script.

m_treshold

Threshold value of the indicator value. This is not used in the script.

m_order

Order of measures. When scores are tie, the measure with a smaller number is chosen.

m_soilfunction

description of the OBIC indicator variable

indicator

Name of OBIC soil indicator variable

m_effect

Effect of measure on soil indicator. 3/2/1/0/-1

m_sector

type of agricultural sector: dairy/arable/vegetable/tree cultivation (in dutch)

m_soiltype

type of soil: sand/clay/peat/loess (in dutch)

m_applicability

is the measure applicable for combination of sector and soil (1/0)

Effects of measures on soil indicators

Description

This table defines the effects of 22 measures on soil indicators

Usage

recom.obic_bkp

Format

A data.frame with 9152 rows and 11 columns:

m_nr

The ID number of measure

m_description

The description of measure

m_prio

weighing factor for measure. This is not used in the script.

m_treshold

Threshold value of the indicator value. This is not used in the script.

m_order

Order of measures. When scores are tie, the measure with a smaller number is chosen.

m_soilfunction

description of the OBIC indicator variable

indicator

Name of OBIC soil indicator variable

m_effect

Effect of measure on soil indicator. 3/2/1/0/-1

m_sector

type of agricultural sector: dairy/arable/vegetable/tree cultivation (in dutch)

m_soiltype

type of soil: sand/clay/peat/loess (in dutch)

m_applicability

is the measure applicable for combination of sector and soil (1/0)

Desired growing season period for maximum yield

Description

This table gives the required number of days before and after August 15 required for optimal yield or usability and has categories to determine yield loss having a shorter workable growing season based on Tabel 2 and several formulas from Huinink (2018)

Usage

season.obic

Format

An object of class data.table (inherits from data.frame) with 116 rows and 6 columns.

Details

landuse

The name of the crop or landuse category, used to link to crops.obic$crop_season

req_days_pre_glg

Required number of workable days before August 15 assuming this coincides with GLG, lowest groundwater

req_days_post_glg

Required number of workable days after August 15 assuming this coincides with GLG, lowest groundwater

total_days

Total number of days required for optimal growth or use

derving

Category to determine yield loss due to having a sub-optimal relative growing season length or RLG

Linking table between soils and different functions in OBIC

Description

This table helps to link the different crops in the OBIC functions with the crops selected by the user

Usage

soils.obic

Format

An object of class data.table (inherits from data.frame) with 9 rows and 4 columns.

Details

soiltype

The name of the soil type

soiltype.ph

The category for this soil at pH

soiltype.n

The category for this soil at nitrogen

Table with optimal pH for different crop plans

Description

This table contains the optimal pH for different crop plans and soil types

Usage

tbl.ph.delta

Format

An object of class data.table (inherits from data.frame) with 136 rows and 10 columns.

Details

table

The original table from Handboek Bodem en Bemesting

lutum.low

Lower value for A_CLAY_MI

lutum.high

Upper value for A_CLAY_MI

om.low

Lower value for organic matter

om.high

Upper value for organic matter

potato.low

Lower value for fraction potatoes in crop plan

potato.high

Upper value for fraction potatoes in crop plan

sugarbeet.low

Lower value for fraction potatoes in crop plan

sugarbeet.high

Upper value for fraction potatoes in crop plan

ph.optimum

The optimal pH (pH_CaCl2) for this range

#' @references Handboek Bodem en Bemesting tabel 5.1, 5.2 en 5.3

Linking table between crops, soils, groundwater tables and water induced stresses in OBIC

Description

This table helps to link the different crops in the OBIC functions with the crops selected by the user

Usage

waterstress.obic

Format

An object of class data.table (inherits from data.frame) with 393680 rows and 6 columns.

Details

cropname

The name of the crop

soilunit

The category for this soil, derived from 1:50.000 soil map

gt

The class describing mean highest and lowest groundwater table, derived from 1:50.000 soil map

droughtstress

The mean yield reduction due to drought (in percentage)

wetnessstress

The mean yield reduction due to water surplus (in percentage)

waterstress

The mean combined effect water stress (due to deficiency or excess of water)

Weather table

Description

This table contains the climatic weather data of the Netherlands for the period 1990-2020

Usage

weather.obic

Format

An object of class data.table (inherits from data.frame) with 12 rows and 4 columns.

Details

month

Month of the year

A_TEMP_MEAN

Mean monthly temperature

A_PREC_MEAN

Mean monthly precipitation

A_ET_MEAN

Mean monthly evapo-transpiration

Weight of indicators to calculate integrated scores

Description

This table defines the weighting factors (ranging between 0 and 1) of indicator values to calculate integrated scores.

Usage

weight.obic

Format

An object of class data.table (inherits from data.frame) with 196 rows and 5 columns.

Details

var

The name of the weight

weight

weighing factor