stfl_trend_regional: Regional analysis on trends Computes a regional analysis...

In bcgov/StreamFlowTrend: Trend analysis on annual streamflow metrics from HYDAT database

Description

Regional analysis on trends Computes a regional analysis using least squares (LM), Mann-Kendall (MK), or robust least squares (LMrob) with HAC corrections for autocorrelation. This computes the individual slopes for each station within each region, and then weights the individual slopes using the weights.

Usage

stfl_trend_regional(
  data,
  station.weights,
  log.Y = FALSE,
  REGION.var = "REGION",
  STATION_NUMBER.var = "STATION_NUMBER",
  WEIGHT.var = "WEIGHT",
  Year.var = "Year",
  Statistic.var = "Statistic",
  Value.var = "Value",
  Parameter.var = "Parameter",
  offset = NULL,
  nsim.bbmks = 2000,
  trend.min.n = stfl_options()$trend.min.n
)

Arguments

data	data frame with REGION STATION NUMBER, Parameter, Statistic, Year (X) and Value (Y) variables
station.weights	data frame with STATION_NUMBER, and WEIGHT
log.Y	Should the analysis be done on the log(Y+offset) scale where log() referes to natural logarithms. If log(y) makes no sense (e.g., if statistic is DoY), the log() is ignored and set to FALSE automatically. Refer to the offset argument for more details. In most cases, the analysis on the log(Y) scale is preferred because of the simple interpretation of the trend. For example, an slope of .02 on the log(Y) corresponds to a 2% increase/year regardless of the underlying units. In some cases, a log(Y) transform makes no sense. For example, the Day_of_Year (DoY) when a minimum occurs is arbitrary and depends on when the start of the year begins (e.g. a water year starts on 1 October). The stfl_get_avail_stat() function has a list of available statistics and if a log(Y) transform is allowable.
REGION.var	Character string with the name of the variable containing the REGION in the data and in the output results..
STATION_NUMBER.var	Character string with the name of the variable containing the station number in the daily data and in the output results..
WEIGHT.var	Character string with the name of the variable containing the relative weight to be used when finding thre regional estimates. These are normalized to sum to 1 internally.
Year.var	Name of the Year variable (usually the year the data was collected)
Statistic.var	Character string with the name of the variable containing the statistic that was computed
Value.var	Character string with the name of the variable containing the value to be analyzed.
Parameter.var	Character string with the name of the variable containing the name of the Parameter in the daily data and in the output results.
offset	What is the value of the offset used when taking log(Y+offset). If unspecified, then the offset is 1/2 of the smallest positive values. The offset is needed to avoid taking log(0).
nsim.bbmks	Number of bootstrapped simulations for Mann-Kendall block boot strap
trend.min.n	Minimum number of data points for trend computation

Value

List with a list for every station containing the station trends and additional entries for region with the following elements

• data.augData frame augmented with the LM, MK, LMrob station trend predictions

• estimatesData frame with estimates and standard errors and the following columns for each station x, y, log.Y, estimate (intercept or Y variable), std error (ignoring autocorrelation), p.value (ignoring autocorrelation), std.error adjusted for HAC

• regional.estimateData frame with similar variables but with a weighted average of trends trends from the stations

• regional.predData frame augmented with the LM, MK, LMrob regional trend predictions

Examples

## Not run: 
# needs the HYDAT package installed
station.id <- c("08NM053","08NM116")
mydata <- stfl_get_annual_stat(station.id, Statistic=c("MEAN"))
mydata$REGION <- "AnyOldRegion"
mystation.weights <- data.frame(STATION_NUMBER=station.id, WEIGHT=c(2,1))
stfl_trend_regional(mydata, mystation.weights, log.Y=TRUE)

## End(Not run)

bcgov/StreamFlowTrend documentation built on Dec. 19, 2021, 7:38 a.m.