View source: R/Calculation_LHB.R
Cal_LHB | R Documentation |
A function to calculate sap flow density using the LHB approach (Trcala and Cermak 2016). The temperatures that are directly measured by sensors (upper, lower and side) must be provided.
Cal_LHB(data, T_up, T_low, T_side, K, ratio = 2, Heat, Zax = 1.5, Ztg = 0.5)
data |
a data frame that includes the measured sap flow data |
T_up |
a string indicates the column name for the temperature measured by the upper sensor |
T_low |
a string indicates the column name for the temperature measured by the lower sensor |
T_side |
a string indicates the column name for the temperature measured by the side sensor |
K |
a numeric value (constant K) or a string that indicates the column name (dynamic K). K value indicates the dTasym value when zero sap flow occurs, see Nadezhdina et al. 2012 |
ratio |
a numeric value; the ratio between the thermal conductivities of wood in the axial and tangential directions; default: 2 (Trcala and Cermak 2016) |
Heat |
a numeric value; the heating power used for the probe (W m-1) |
Zax |
a numeric value; axial distance of the sensors, cm. Default: 1.5 |
Ztg |
a numeric value; tangential distance of the sensors, cm. Default: 0.5 |
a data frame with an additional column of the calculated sap flow density (SFD_lhb, g cm-2 h-1).
# load example data df <- read.csv(file = system.file("extdata", "Soil_resp_example.csv", package = "FluxGapsR"), header=T) # convert the data into long format df <- df %>% pivot_longer(cols = Temp1U:Temp8S, names_to = c(".value","Position"), names_sep = c(5)) %>% pivot_longer(cols = starts_with(c("K","Temp")), names_to = c(".value","Depth"), names_sep = -1) %>% pivot_wider(names_from = Position, values_from = Temp) # calculate sap flow density using dynamic K values that are provided as a variable df_lhb1 <- Cal_LHB(df,T_up = "U",T_low = "L",T_side = "S",K="K",Heat=2.6) tapply(df_lhb1$SFD_lhb, df_lhb1$Depth, summary) # calculate sap flow density using constant K value df_lhb2 <- Cal_LHB(df,T_up = "U",T_low = "L",T_side = "S",K=.8,Heat=2.6) tapply(df_lhb2$SFD_lhb, df_lhb2$Depth, summary)
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