Table 5 Performance of the hybrid MVMD based L-SKRidge, dRVFL, LASSO, KRidge, and CFNN models based on assessment metrics in Brooke River.

	Methods	Mode	R	RMSE	MAPE	NSE	I_A	MaxAE	U_95%
WL (t + 1)	L-SKRidge	Train	0.971	0.054	7.371	0.940	0.984	0.484	0.148
	L-SKRidge	Test	0.970	0.051	6.309	0.937	0.982	0.411	0.142
	dRVFL	Train	0.951	0.068	8.532	0.905	0.975	0.938	0.188
	dRVFL	Test	0.963	0.066	7.860	0.896	0.968	0.469	0.176
	LASSO	Train	0.948	0.070	8.553	0.899	0.973	0.961	0.194
	LASSO	Test	0.960	0.066	8.022	0.895	0.968	0.465	0.178
	KRidge	Train	0.951	0.072	10.631	0.893	0.971	0.925	0.194
	KRidge	Test	0.963	0.061	8.362	0.909	0.972	0.435	0.170
	CFNN	Train	0.964	0.059	8.123	0.928	0.981	0.856	0.163
	CFNN	Test	0.955	0.062	8.527	0.907	0.973	0.380	0.172
WL (t + 3)	L-SKRidge	Train	0.967	0.056	7.019	0.935	0.983	0.355	0.156
	L-SKRidge	Test	0.928	0.079	8.664	0.849	0.957	0.535	0.215
	dRVFL	Train	0.916	0.089	11.357	0.838	0.954	1.109	0.245
	dRVFL	Test	0.912	0.088	10.735	0.813	0.942	0.692	0.240
	LASSO	Train	0.912	0.090	11.648	0.831	0.952	1.128	0.251
	LASSO	Test	0.915	0.086	10.445	0.820	0.944	0.706	0.236
	KRidge	Train	0.914	0.093	13.404	0.823	0.950	1.094	0.253
	KRidge	Test	0.916	0.084	10.943	0.831	0.948	0.675	0.232
	CFNN	Train	0.932	0.081	10.000	0.864	0.964	1.068	0.224
	CFNN	Test	0.882	0.096	11.026	0.776	0.935	0.636	0.266

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