Flow anomalies are a dimensionless term that reflects the difference in in current discharges compared to past discharges. A positive flow anomaly indicates the current time period, \(T_{1}\), is wetter than the precedent time period, \(T_{2}\).
Arguments
- discharge
numeric vector of daily discharges
- dates
vector of dates coresponding to daily discharge measurements. Must be class
"Date"
.- T_1
size of period \(T_{1}\) preceding a given day t. Specified in the same way as the
by
argument inseq.POSIXt
.- T_2
size of period \(T_{2}\) preceding a given day t. Specified in the same way as the
by
argument inseq.POSIXt
. Period T_2 is expected to be longer than T_1.- clean_up
logical. runs .... prior to ....
- transform
on of
NA, log, log10
,
Details
The FA term describes how different the antecedent discharge conditions are for a selected temporal period compared to a selected period or day of analysis. Ryberg and Vecchia (2014) and Vechia et al. (2009) describe the flow anomaly (FA) term as:
$$FA(t)=X_{T_1}(t) - X_{T_2}(t)$$
The T_1
and T_2
arguments can be specified as character strings
containing one of "sec"
, "min"
, "hour"
, "day"
,
"DSTday"
, "week"
, "month"
, "quarter"
, or
"year"
. This is generally preceded by an integer and a space. Can also
be followed by an "s"
. Additionally, T_2
accepts
"period"
which coresponds with the mean of the entire flow record.
References
Ryberg, Karen R., and Aldo V. Vecchia. 2012. “WaterData—An R Package for Retrieval, Analysis, and Anomaly Calculation of Daily Hydrologic Time Series Data.” Open Filer Report 2012-1168. National Water-Quality Assessment Program. Reston, VA: USGS. https://pubs.usgs.gov/of/2012/1168/.
Vecchia, Aldo V., Robert J. Gilliom, Daniel J. Sullivan, David L. Lorenz, and Jeffrey D. Martin. 2009. “Trends in Concentrations and Use of Agricultural Herbicides for Corn Belt Rivers, 1996-2006.” Environmental Science & Technology 43 (24): 9096–9102. doi:10.1021/es902122j .
Examples
## examples from Ryberg & Vechia 2012
## Long-term Flow Anomaly LTFA
LTFA <- fa(lavaca$Flow,
dates = lavaca$Date,
T_1 = "1 year",
T_2 = "period",
clean_up = TRUE,
transform = "log10")
# \donttest{
## Mid-term Flow Anomaly MTFA
MTFA <- fa(lavaca$Flow,
dates = lavaca$Date,
T_1 = "1 month",
T_2 = "1 year",
clean_up = TRUE,
transform = "log10")
## Short-term Flow Anomaly STFA
STFA <- fa(lavaca$Flow,
dates = lavaca$Date,
T_1 = "1 day",
T_2 = "1 month",
clean_up = TRUE,
transform = "log10")
# }