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Rating curve

About Rating curve

Translating data by applying it to a continuous curve is a common practise in hydrological fields. This simple model allows you to define a curve and apply it to your system to produce a resulting translated data file.

Model purpose

The purpose of the model is to translate timeseries data by applying a continuous curve to each value.

Development context

This is a simple, general purpose model.

Spatial application

This is a general purpose model and is applicable to any location.

Model description

Ecohydrological rules

The model applies the specified curve to each value in the provided timeseries data, resulting in a new value for each day in the result file. The curve is defined by a series of points, where x is the value in the input file and y is the resulting translation that will be in the output file. Additionally, the curve can be imported from a csv file.

Assessment method

This model produces continuous daily results (value translated by the provided curve). These results are then aggregated to a binary daily result,  then to a binary yearly result, and then further to a binary temporal result based on the defined assessment parameters.

The temporal results are then analysed across locations to report an overall landscape risk by considering the simultaneous occurrence of failures across the system.

Inputs

Data
  • Daily time series data. This can be any type (flow, depth, rainfall, evaporation, etc.) provided it is at the daily or sub-daily time step.
Parameter Sections
  • Data – define the data type to run analysis on. All time series data types are valid options.
  • Curve – define the curve to apply to the data. Points can be added or removed. The curve can be imported from a CSV file, where column 1 will be treated as the x value, and column 2 as the y value.

Outputs

  • Daily time series of translated values
  • Daily time series of assessment results
  • Yearly time series of assessment results
  • Temporal time series of assessment results
  • Spatial time series of assessment results

User interface

Underlying code

This plugin is written in Python and its underlying code is publicly available from the Eco Risk Projector computation repository.