fa {adc} | R Documentation |

## Calculate Flow Anomalies

### Description

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}`

.

### Usage

```
fa(discharge, dates, T_1, T_2, clean_up = FALSE, transform = "log10")
```

### Arguments

`discharge` |
numeric vector of daily discharges |

`dates` |
vector of dates coresponding to daily discharge measurements.
Must be class |

`T_1` |
size of period |

`T_2` |
size of period |

`clean_up` |
logical. runs .... prior to .... |

`transform` |
on of |

### 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.

### Value

vector of numeric values corresponding to `X_{T_1}(t) - X_{T_2}(t)`

.

### 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")
## 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")
```

*adc*version 1.0.0 Index]