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Crop water balance accounting in the root zone for irrigation purposes.
{CropWaterBalance} is an R package designed to assist users in irrigation scheduling based on the Water Balance Approach. The package is capable of calculating reference evapotranspiration (ET0) through various methods and conducting crop water balance accounting. Additionally, {CropWaterBalance} includes auxiliary functions for comparing different ET0 estimation methods, calculating descriptive statistics for ET0 and rainfall series, and estimating soil heat flux and water stress coefficient. The functions ET0_HS(), ET0_PT(), and ET0_PM() are used to estimate daily ET0 amounts using the methods of Hargreaves-Samani, Priestley-Taylor, and FAO-56 Penman-Monteith, respectively. The Descriptive() function is specifically designed to calculate descriptive statistics for ET0 and rainfall series, including sample mean, median, standard deviation, standard error, maximum value, minimum value, and frequency of zeros. Additionally, the Compare() function may be used to calculate measures of accuracy and agreement between two ET0 or rainfall series. The Soil_Heat_Flux() function uses average air temperature data to estimate the soil heat flux, and the Water_Stress_Coef() function calculates the water stress coefficient for a crop. The package depends on R (>= 2.10) and imports functions from the R packages {PowerSDI} and {lubridate}.
Calculates daily reference evapotranspiration amounts using the Penman and Monteith method.
NULL and if NULL it is assumed to be zero. May be provided by Soil_Heat_Flux.Daily reference evapotranspiration amounts in millimetres.
Tavg <- DataForCWB[, 2]
Tmax <- DataForCWB[, 3]
Tmin <- DataForCWB[, 4]
Rn <- DataForCWB[, 6]
WS <- DataForCWB[, 7]
RH <- DataForCWB[, 8]
G <- DataForCWB[, 9]
head(ET0_PM(Tavg, Tmax, Tmin, Rn, RH, WS, G, Alt = 700))## ET0_PM
## [1,] 2.440372
## [2,] 4.171917
## [3,] 4.290477
## [4,] 3.665459
## [5,] 4.848520
## [6,] 5.669878Calculates daily reference evapotranspiration amounts using the Priestley-Taylor method.
NULL and if NULL it is assumed to be zero. May be provided by Soil_Heat_FluxDaily reference evapotranspiration amounts in millimetres.
## ET0_PT
## [1,] 3.432709
## [2,] 5.849554
## [3,] 6.432616
## [4,] 5.695334
## [5,] 7.023900
## [6,] 7.817355Calculates daily reference evapotranspiration amounts using the Hargreaves-Samani method.
Daily reference evapotranspiration amounts in millimetres.
Tavg <- DataForCWB[, 2]
Tmax <- DataForCWB[, 3]
Tmin <- DataForCWB[, 4]
Ra <- DataForCWB[, 5]
head(ET0_HS(
Ra = Ra,
Tavg = Tavg,
Tmax = Tmax,
Tmin = Tmin
))## ET0
## [1,] 4.703700
## [2,] 5.331592
## [3,] 5.664174
## [4,] 6.163377
## [5,] 5.291303
## [6,] 6.251883Calculates the daily amounts of Soil Heat Flux.
Daily amounts of soil Heat flux in MJ m-2 day-1.
## Warning in Soil_Heat_Flux(Tavg): The first 3 G values were set to zero
## [,1]
## [1,] 0.0000000
## [2,] 0.0000000
## [3,] 0.0000000
## [4,] 0.3806333
## [5,] -0.7796333
## [6,] -0.2007667Calculates descriptive statistics for rainfall, evapotranspiration, or other variable.
Sample: A vector, 1-column matrix or data frame with rainfall, evapotranspiration, or other variable. ## Value
sample mean (Avg), sample median (Med), sample standard variation (SD), sample standard Error (SE), maximum value (MaxValue), minimum value (MinValue), and frequency of zeros (FreqZero%) ## Examples
## SampleSize Avg Med SD SE MaxValue MinValue FreqZero%
## 1 129 6.53 0.25 13.06 1.15 71.37 0 48.06Calculates measures of accuracy and agreement.
Tavg <- DataForCWB[, 2]
Tmax <- DataForCWB[, 3]
Tmin <- DataForCWB[, 4]
Rn <- DataForCWB[, 6]
WS <- DataForCWB[, 7]
RH <- DataForCWB[, 8]
G <- DataForCWB[, 9]
Sample1 <-
ET0_PM(
Tavg = Tavg,
Tmax = Tmax,
Tmin = Tmin,
Rn = Rn,
RH = RH,
WS = WS,
G = G,
Alt = 700
)
Sample2 <- ET0_PT(Tavg = Tavg, Rn = Rn, G = G)
Compare(Sample1 = Sample1, Sample2 = Sample2)## AME RMSE dorig dmod dref RQuad
## 1 1.69222 1.813449 0.6403158 0.376103 -0.05737454 0.8675223Calculates several parameters of the crop water balance. It also suggests when and how much to irrigate.
Rain: Vector, 1-column matrix or data frame with daily rainfall totals in millimetres.
ET0: Vector, 1-column matrix or data frame with daily reference evapotranspiration in millimetres.
AWC: Vector, 1-column matrix or data frame with the available water capacity of the soil, that is: the amount of water between field capacity and permanent wilting point in millimetres of water per centimetre of soil.
Drz: Vector, 1-column matrix or data frame defining the root zone depth in centimetres.
Kc: Vector, 1-column matrix or data frame defining the crop coefficient. If NULL its values are assumed to be 1.
Irrig: Vector, 1-column matrix or data frame with net irrigation amount infiltrated into the soil for the current day in millimetres.
MAD: Vector, 1-column matrix or data frame defining the management allowed depletion. Varies between 0 and 1.
InitialD Single number defining in millimetre, the initial soil water deficit. It is used to start the water balance accounting. Default value is 0, which assumes the root zone is at the field capacity.
start.date: Date at which the accounting should start. Formats: “YYYY-MM-DD”, “YYYY/MM/DD”.
Tavg <- DataForCWB[, 2]
Tmax <- DataForCWB[, 3]
Tmin <- DataForCWB[, 4]
Rn <- DataForCWB[, 6]
WS <- DataForCWB[, 7]
RH <- DataForCWB[, 8]
G <- DataForCWB[, 9]
ET0 <- ET0_PM(Tavg, Tmax, Tmin, Rn, RH, WS, G, Alt = 700)
Rain <- DataForCWB[, 10]
Drz <- DataForCWB[, 11]
AWC <- DataForCWB[, 12]
MAD <- DataForCWB[, 13]
Kc <- DataForCWB[, 14]
Irrig <- DataForCWB[, 15]
head(CWB(
Rain = Rain,
ET0 = ET0,
AWC = AWC,
Drz = Drz,
Kc = Kc,
Irrig = Irrig,
MAD = MAD,
start.date = "2023-11-23"
))## DaysSeason Rain Irrig ET0 Kc WaterStressCoef_Ks ETc (P+Irrig)-ETc
## 2023-11-23 1 45.5 0 2.4 1 1 2.4 43.0
## 2023-11-24 2 0.3 0 4.2 1 1 4.2 -3.9
## 2023-11-25 3 0.0 0 4.3 1 1 4.3 -4.3
## 2023-11-26 4 11.4 0 3.7 1 1 3.7 7.8
## 2023-11-27 5 0.3 0 4.8 1 1 4.8 -4.6
## 2023-11-28 6 0.0 0 5.7 1 1 5.7 -5.7
## NonStandardCropEvap ET_Defict TAW SoilWaterDeficit d_MAD D>=dmad
## 2023-11-23 2.4 0 45.7 0.0 13.7 No
## 2023-11-24 4.2 0 45.7 3.9 13.7 No
## 2023-11-25 4.3 0 45.7 8.2 13.7 No
## 2023-11-26 3.7 0 45.7 0.4 13.7 No
## 2023-11-27 4.8 0 45.7 5.0 13.7 No
## 2023-11-28 5.7 0 45.7 10.7 13.7 NoCalculates several parameters of the crop water balance. It also suggests how much irrigate.
CWB_FixedSchedule(
Rain,
ET0,
AWC,
Drz,
Kc = NULL,
Irrig = NULL,
MAD = NULL,
InitialD = 0,
Scheduling,
start.date
)Rain: Vector, 1-column matrix or data frame with daily rainfall totals in millimetres.
ET0: Vector, 1-column matrix or data frame with daily reference evapotranspiration in millimetres.
AWC: Vector, 1-column matrix or data frame with the available water capacity of the soil, that is: the amount of water between field capacity and permanent wilting point in millimetre of water per centimetre of soil.
Drz: Vector, 1-column matrix or data frame defining the root zone depth in centimetres.
Kc: Vector, 1-column matrix or data frame defining the crop coefficient. If NULL its values are assumed to be 1.
Irrig: Vector, 1-column matrix or data frame with net irrigation amount infiltrated into the soil for the current day in millimetres.
MAD: Vector, 1-column matrix or data frame defining the management allowed depletion. Varies between 0 and 1.
InitialD Single number defining in millimetre, the initial soil water deficit. It is used to start the water balance accounting. Default value is 0, which assumes the root zone is at the field capacity.
Scheduling Single integer number defining the number of days between two consecutive irrigations.
start.date: Date at which the accounting should start. Formats: “YYYY-MM-DD”, “YYYY/MM/DD”.
Tavg <- DataForCWB[, 2]
Tmax <- DataForCWB[, 3]
Tmin <- DataForCWB[, 4]
Rn <- DataForCWB[, 6]
WS <- DataForCWB[, 7]
RH <- DataForCWB[, 8]
G <- DataForCWB[, 9]
ET0 <- ET0_PM(Tavg, Tmax, Tmin, Rn, RH, WS, G, Alt = 700)
Rain <- DataForCWB[, 10]
Drz <- DataForCWB[, 11]
AWC <- DataForCWB[, 12]
MAD <- DataForCWB[, 13]
Kc <- DataForCWB[, 14]
Irrig <- DataForCWB[, 15]
Scheduling <- 5
head(CWB_FixedSchedule(
Rain = Rain,
ET0 = ET0,
AWC = AWC,
Drz = Drz,
Kc = Kc,
Irrig = Irrig,
MAD = MAD,
Scheduling = Scheduling,
start.date = "2023-11-23"
))## DaysSeason Rain Irrig ET0 Kc WaterStressCoef_Ks ETc
## 2023-11-23 1 45.470 0 2.440 1 1 2.440
## 2023-11-24 2 0.254 0 4.172 1 1 4.172
## 2023-11-25 3 0.000 0 4.290 1 1 4.290
## 2023-11-26 4 11.430 0 3.665 1 1 3.665
## 2023-11-27 5 0.254 0 4.849 1 1 4.849
## 2023-11-28 6 0.000 0 5.670 1 1 5.670
## (P+Irrig)-ETc NonStandardCropEvap ET_Defict TAW SoilWaterDeficit
## 2023-11-23 43.030 2.440 0 45.72 0.000
## 2023-11-24 -3.918 4.172 0 45.72 3.918
## 2023-11-25 -4.290 4.290 0 45.72 8.208
## 2023-11-26 7.765 3.665 0 45.72 0.444
## 2023-11-27 -4.595 4.849 0 45.72 5.038
## 2023-11-28 -5.670 5.670 0 45.72 10.708
## d_MAD Scheduling
## 2023-11-23 13.716 No
## 2023-11-24 13.716 No
## 2023-11-25 13.716 No
## 2023-11-26 13.716 No
## 2023-11-27 13.716 Time to Irrigate 5 mm
## 2023-11-28 13.716 NoAWC is the amount of water between field capacity and permanent wilting point. Given in millimetre of water per centimetre of soil. Extracted from: Irrigation Scheduling: The Water Balance Approach Fact Sheet No. 4.707 by A. A. Andales, J. L. Chávez, T. A. Bauder..
https://extension.colostate.edu/topic-areas/agriculture/.
## Soil.Texture AWC.Low AWC.High AWC.Average
## 1 Coarse sands 50 70 60
## 2 Fine sands 70 80 80
## 3 Loamy sands 70 100 80
## 4 Sandy loams 100 130 120
## 5 Fine sandy loams 130 170 150
## 6 Sandy clay loams 130 180 160
## 7 Loams 180 210 200
## 8 Silt loams 170 210 190
## 9 Silty clay loams 130 170 150
## 10 Clay loam 130 170 150
## 11 Silty clay 130 140 130
## 12 Clay 110 130 120Daily meteorological data from a weather station in Campinas, Brazil and other parameters required for calculating the crop water balance. The meteorological data belongs to the Agronomic Institute of the state of Sao Paulo.
## Date tmed tmax tmin Ra Rn W RH G Rain
## 1 11/23/2010 23.000 27.26 18.74 42.07246 6.04422 2.16 76.58 -0.64 45.470
## 2 11/24/2010 23.730 29.00 18.46 42.12238 11.08968 2.57 64.50 -0.30 0.254
## 3 11/25/2010 24.650 30.33 18.97 42.17043 12.71410 2.80 70.37 0.19 0.000
## 4 11/26/2010 24.795 31.46 18.13 42.21660 11.46852 1.86 73.03 0.38 11.430
## 5 11/27/2010 22.340 27.86 16.82 42.26093 12.89778 2.61 57.80 -0.78 0.254
## 6 11/28/2010 23.400 30.70 16.10 42.30341 15.02158 2.42 48.06 -0.20 0.000
## Drz AWC MAD Kc Irrig
## 1 0.3048 150 0.3 1 0
## 2 0.3048 150 0.3 1 0
## 3 0.3048 150 0.3 1 0
## 4 0.3048 150 0.3 1 0
## 5 0.3048 150 0.3 1 0
## 6 0.3048 150 0.3 1 0<https://github.com/gabrielblain/CropWaterBalance/issues >
MIT
Gabriel Constantino Blain, Graciela da Rocha Sobierajski, Regina Célia Matos Pires, Adam H. Sparks, Letícia L. Martins. Maintainer: Gabriel Constantino Blain, gabriel.blain@sp.gov.br
The package uses data from the Fact Sheet number 4707 Irrigation Scheduling: The Water Balance Approach, by A. A. Andales, J. L. Chávez, and T. A. Bauder. The authors greatly appreciate this initiative.
Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop evapotranspiration. In Guidelines for Computing Crop Water Requirements. Irrigation and Drainage Paper 56; FAO: Rome, Italy, 1998; p. 300.
Andales, A.A.; Chávez, J.L.;Bauder, T.A. 2012. Irrigation Scheduling: The Water Balance Approach. Fact Sheet number 4707, crop series | irrigation. https://extension.colostate.edu/docs/pubs/crops/04707.pdf
Hargreaves, G.H.; Samani, Z.A. 1985.Reference crop evapotranspiration from temperature. Appl. Eng. Agric,1, 96–99.
Package ‘lubridate’, Version 1.9.3, Author Vitalie Spinu et al., https://CRAN.R-project.org/package=lubridate
Package ‘PowerSDI’, Version 1.0. 0, Author Gabriel C. Blain et al., https://CRAN.R-project.org/package=PowerSDI
Priestley, C.H.B., Taylor, R.J., 1972. On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Monthly Weather Review, 100 (2), 81–92.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.