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NSE-and-Variance-Components

Author: Sacha Ruzzante Last Updated: 2026-02-19

This code was written to produce the analyses and plots in the manuscript:

Ruzzante, S. W., Knoben, W. J. M., Wagener, T., Gleeson, T., and Schnorbus, M. Technical Note: High Nash Sutcliffe Efficiencies conceal poor simulations of interannual variance in seasonal regimes. Submitted to Hydrology and Earth System Sciences, 2025

The repository is organized as follows:

/1.code/ contains all R codes

/1.code/1.climatologicalBenchmarkGOF/ contains the scripts to extract climatology data for each CAMELS datasets and calculte the Koppen-Geiger climate zone.

/1.code/2.KoppenGeiger/ contains the scripts to calcult

/1.code/3.modelComparison/ contains the scripts to calculate goodness-of-fit statistics for all 18 models analysed.

/1.code/4.Plotting/ contains the scripts to make all four figures in the manuscript

/1.code/5.utils/ contains utility functions used throughout other scripts

/2.data/ contains data produced by this project

/2.data/GOF/ contains goodness-of-fit stats for the climatological benchmark model, (Figure 2)

/2.data/highLowBenchmarkGOF/ contains goodness-of-fit statistics for each of the 18 models.

/2.data/NHM_Q/ contains simulation data from the National Hydrologic Model

/2.data/varComponents/ contains the variance components for 17,245 gauges (Figure 2)

/2.data/worldclim/ includes climate indices calculated from WorldClim for each gauges

/3.figures/ is where figures will be saved

/4.lstm-camelsbr/ is where the LSTM model for the camels-br data is saved. This was created using the NeuralHydrology package for Python.

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Code for Technical Note : The Nash Sutcliffe Efficiency conceals inferior representations of hydrologic variability in seasonal regimes

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