hydrobm.benchmarks.bm_scaled_precipitation_benchmark

hydrobm.benchmarks.bm_scaled_precipitation_benchmark(data, cal_mask, precipitation='precipitation', streamflow='streamflow')[source]

Calculate the scaled precipitation benchmark model as a predictor of runoff-from-precipitation for each timestep in the whole dataframe.

Parameters:

datapandas DataFrame: Input data containing precipitation and streamflow columns.
cal_maskpandas Series: Boolean mask for the calculation period.
precipitationstr, optional: Name of the precipitation column in the input data. Default is [‘precipitation’].
streamflowstr, optional: Name of the streamflow column in the input data. Default is [‘streamflow’].

Returns:

bm_vals: float: Rainfall-runoff ratio value for the calculation period.
qbmpandas DataFrame: Benchmark flow time series for the scaled precipitation benchmark model. Computed as long-term RRR multiplied by precipitation at each timestep.

Notes

This benchmark is effectively the same as the rainfall-runoff ratio to timestep benchmark, though Schaefli & Gupta (2007) apply this with daily data only.

References

Schaefli, B. and Gupta, H.V. (2007), Do Nash values have value?. Hydrol. Process., 21: 2075-2080. https://doi.org/10.1002/hyp.6825