Ground-water conditions in southern Florida
Data presented: Gage heights at selected site, reported in feet above the National Geodetic Vertical Datum of 1929. Also displayed are the frequency characteristic values for the period of record, recalculated to a zero-order linear regression. The operational assumption is that there are generally no statistically significant long-term trends in surface-water data. The zero-order linear regression is a best-fit analysis of the data to a level (zero-slope), flat line through time. The value for this line is generally very close to the long-term mean of the data used. The output parameters of the regression are then stored in the project database.
Timeframe of the graph: The 365 days preceding graph generation.
Data time lag: All data is presented without systematic forward or backward lag.
Narrative text: Long-term gage height trends are estimated by statistical analysis, then gage heights for the past year are compared to the duration information, compensated for long-term trends, for the corresponding weeks of the year.
Barring computational errors, the following information is expected to be conveyed in the figure:
"Daily mean gage height" - The daily mean gage heights (mean gage height recorded in the 24-hour period from midnight to midnight, local time) are retrieved for the the period of time for the 365 days prior to the time graphed for continuous water elevation.
"1st percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression. The residual values of the regression, which are the actual water levels minus the regression output value (discussed Data presented above), are then analyzed to obtain various population statistics.
To account for normal seasonal variation in gage heights, the residual values were grouped by calendar week before running the population statistics. The resulting line plotted represents the weekly value below which only one percent of the gage heights occurred. This represents historically low gage heights, with rising or declining average gage heights factored in. Because of the relatively small amount of data that constitutes the bottom one percent of values, the resulting graph line can show considerable variance.
"10th percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value below which only ten percent of the gage heights occurred. This still represents unusually low gage heights, with rising or declining average gage heights factored in.
"30th percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value below which 30 percent of the gage heights occurred. This represents a fair estimate of the low end of historically normal gage heights for the time of year, with rising or declining average gage heights factored in.
"Median (50th percentile) of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value below which 50 percent of the gage heights occurred. This represents a fair estimate of historically normal gage heights for the time of year, with rising or declining average water levels factored in.
"70th percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value above which 30 percent of the gage heights occurred. This represents a fair estimate of the upper end of historically normal gage heights for the time of year, with rising or declining average gage heights factored in.
"90th percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value above which only 10 percent of the gage heights occurred. This represents unusually high gage heights, with rising or declining average gage heights factored in.
"99th percentile of data" - The available daily mean gage heights are retrieved and analyzed via zero-order linear regression to determine if there are any long-term trends in the historical data. Population statistics were calculated as described above for the 1st percentile of data.
The resulting line plotted represents the weekly value above which only 10 percent of the gage heights occurred. This represents historically high gage heights, with rising or declining average gage heights factored in. Because of the relatively small amount of data that constitutes the top one percent of values, the resulting graph line can show considerable variance.
Missing data in a plot (a blank part of a graph, or gaps in a plotted line) can be caused by any of the following:
The station may not have been on the USGS cooperative data collection program for that period of record.
The recorder at the site may have been malfunctioning and the data either lost or not collected.
The data may have failed quality assurance standards and been either deleted or set for non-release.
For these reasons, all data presented on these pages must be considered provisional, even if released for official use elsewhere.
Funding for the USGS to design and maintain this site has been provided through a cooperative agreement with the South Florida Water Management District (SFWMD). Water-level conditions are monitored by the USGS with support from Federal, State, and local cooperators.
U.S. Department of the Interior |
U.S. Geological Survey
URL: http://www.sflorida.er.usgs.gov/ddn_data/text/template_14.html
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