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The stand-alone RAP tools and accompanying user guides are available from www.toolkit.net.au/RAP.
Hydraulic Analysis module
The Hydraulic Analysis (HA) module of the River Analysis Package (RAP) is based on the Flow Events Method (Stewardson and Gippel, 2003) of allocating environmental flows. The HA module allows you to construct a one dimensional hydraulic model of a river reach and to determine ecologically-relevant flow thresholds based on hydraulic parameters such as water depth and velocity. Plugin file: Ensure that the following plugin file is present in Source prior to opening a project:
| Code Block |
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C:\Program Files\eWater\Source version\Plugins\Ecology.RAP.HA.dll |
Location in Source: > Plugins > Ecology > name of RAP tool
HA allows you to create a time series of potentially ecologically relevant hydraulic data for subsequent analysis in TSA (Time series Analysis module) and comparison with biological data or alternative flow regimes.
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HA uses channel cross-sectional data to create a one-dimensional hydraulic model. To run the 1-D hydraulic model, you must assign channel roughness factors for each cross-section. The channel roughness (Manning’s n) can be varied according to discharge, or set as a constant value for all discharges.
The main output from the hydraulic analysis module is a time series of hydraulic parameters.
Time Series Analysis module
The Time Series Analysis (TSA) module of the River Analysis Package (RAP) allows you to investigate time series.Plugin file: Ensure that the following plugin file is present in Source prior to opening a project:
| Code Block |
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C:\Program Files\eWater\ |
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Source version\Plugins\Ecology.RAP.TSA.dll |
Location in Source:
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- Comma delimited (.CSV) with the first column a daily time-step date and subsequent column(s) as data; and
- IQQM-standard output format from the Integrated Quality, Quantity Model produced by the New South Wales Department of Land and water Conservation.
See File formats for more information.
The basic time unit of TSA is daily, however sub-daily, monthly, seasonal and annual time series can also be handled by TSA. Time series must be gap-free (ie. no empty cells if viewed in a spreadsheet). As well as a visual output, TSA provides tabulated numeric output that can be saved as a comma-delimited file for input into other post processing statistical packages.