time_series_flood: Return a time series of flood metrics by county codes or...

Description Usage Arguments Value Examples

View source: R/user_fun.R

Description

Access USGS databases to retrieve gages and flow data for the specified counties/states or county FIPS codes and the specified date ranges. Flooding at these gage locations are assessed by one of two metrics. Data on timing and magnitude of flooding will be returned at the gage level or the county level.

Usage

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time_series_flood(county_cd = NULL, state = NULL, start_date, end_date,
  threshold = "Q2", flood_type = "flood", weight = "Q2",
  Q2_magnitude = "Moderate", filter_data = TRUE)

Arguments

county_cd

Character vector with the county FIPS code(s)

state

Character vector of state names. Used to obtain county FIPS codes if county_cd is NULL

start_date

Character string with the starting date, using "YYYY-MM-DD" notation.

end_date

Character string with the end date, using "YYYY-MM-DD" notation.

threshold

Character string of the flood threshold to be used in the analysis (either "Q2" or "NWS"). Defaults to "Q2".

flood_type

Character string of the defined flood type based on NWS classifications (one of "action", "flood", "moderate", or "major")

weight

Character string of variable to be used to scale by river size for weighted averages and scaling point sizes on maps. Options are median annual flood ("Q2") or drainage area ("DA"). Defaults to "Q2".

Q2_magnitude

Character string of ratio of daily streamflow to Q2 used as a binary flood threshold. One of "Minor" (1 < Flow / Q2 < 1.5), "Moderate" (< 2), "Major" (< 5), and "Extreme" (> 5). Defaults to "Moderate".

filter_data

Logical. If TRUE only dates with a flood occurring are returned for both gage and county-level data. If FALSE, all dates are returned.

Value

A list with two data frames, summarizing the results by gage and by county:

Gage:

Name Type Description
site_no character USGS gage ID
date date Date of observation
lat numeric Gage latitude
long numeric Gage longitude
county_cd character FIPS code of gage county location
Q2 numeric Median annual discharge (cubic feet per second)
DA numeric Drainage area of the gage (square miles)
size numeric Relative river size, logarithm of either Q2 or DA depending on user specified weight
discharge numeric Observed mean daily discharge (cubic feet per second)
flood_val numeric Selected threshold flood value. Either Q2 or an NWS flood threshold.
flood_ratio numeric Ratio of the observed discharge divided by the defined flood threshold
state character State name
county character County name
flood character Flood magnitude category based on peak

County:

Name Type Description
date date Date of observation
county character County name
state character State name
num_gage numeric Number of analyzed gages in county
max_peak numeric Maximum observed flood ratio
avg_peak numeric Average flood ratio among county gages
minor numeric Percentage of gages at or above "minor" flood class (flood ratio > 1)
moderate numeric Percentage of gages at or above "moderate" flood class (flood ratio > 1.5)
major numeric Percentage of gages at or above "major" flood class (flood ratio > 2)
extreme numeric Percentage of gages at or above "extreme" flood class (flood ratio > 5)
flood_metric numeric Fraction of gages in county experiencing a flood, weighted by river size (size from gage-level output)

If threshold = "NWS", the columns "minor", "moderate", "major", and "extreme" are replaced with two columns: "no_flood" and "yes_flood" which show the percentage of gages in the county with or without flooding.

Examples

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## Not run: 
#Use Q2 as flood threshold
va_time_series <- time_series_flood(state = "Virginia", start_date = "2015-01-01",
                      end_date = "2015-12-31", threshold = "Q2")

#Use NWS flood thresholds
va_time_series <- time_series_flood(state = "Virginia", start_date = "2015-01-01",
                      end_date = "2015-12-31", threshold = "NWS",
                      flood_type = "action")

## End(Not run)

countyfloods documentation built on May 2, 2019, 2:38 a.m.