In this study, five statistical parameters R² (coefficient of determination), NSE (Nash–Sutcliffe efficiency), PBIAS (percent bias), RMSE (root mean square error), and RSR (RMSE-observation's standard deviation ratio) methods were applied to assess the performance of different models to estimate river discharge and sediment load. R² describes data collinearity between observations and simulations. NSE indicates how well an observed plot fits a simulated plot. The PBIAS determines whether simulations are larger or smaller than observations based on their average magnitude. RMSE indicates the difference between the observed and simulated series. Similarly, the residual variance of a prediction is represented by the RSR. Generally, a better-performing model has higher R², NSE, and lower PBIAS, RMSE, and RSR. These statistical indicators are listed in Table 4, along with their mathematical expressions and ranges.

Table 4

Performance metrics

Mathematical equation .	Range .
	Range [0,1], and 1 is the optimal value (o.v.)
	Range [−∞,1], and 1 is the o.v.
	Range [−∞, + ∞], and 0 is the o.v.
	Range [0, + ∞], and 0 is the o.v.
	Range [0, + ∞], and 0 is the o.v.

Mathematical equation .	Range .
	Range [0,1], and 1 is the optimal value (o.v.)
	Range [−∞,1], and 1 is the o.v.
	Range [−∞, + ∞], and 0 is the o.v.
	Range [0, + ∞], and 0 is the o.v.
	Range [0, + ∞], and 0 is the o.v.

Note: O is the observed value and S is the simulated value, avg is the average of the total values, and n is the total number of observations.

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