Scientific Reports

Table 3 The results of all models for the regions.

From: Hybrid Wavelet–ML models for regional drought forecasting in Norway

Drammen
Before wavelet transformation
	SVM						LSTM						MLP
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.7656	0.5414	0.3034	1.0997	0.6750	M01	0.7104	0.4893	0.4933	1.1978	0.7123	M01	0.1497	−0.8887	−0.3027	3.4269	1.4162
M02	0.7641	0.5424	0.3228	1.0994	0.6743	M02	0.7691	0.5812	0.5546	1.0488	0.6451	M02	0.5706	0.1786	0.0741	1.6544	0.9339
M03	0.7562	0.5352	0.3507	1.1129	0.6795	M03	0.7708	0.5876	0.5956	1.0397	0.6402	M03	0.3350	−0.7619	0.0745	2.8505	1.3679
M04	0.7575	0.5362	0.3458	1.1109	0.6789	M04	0.7535	0.5562	0.5443	1.0892	0.6641	M04	0.3406	−0.7129	−0.0546	2.7990	1.3487

	XGBoost						Catboost
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.6200	0.3309	0.1879	1.4476	0.8430	M01	0.6973	0.4541	0.3227	1.2481	0.7614
M02	0.6178	0.3006	0.0455	1.4820	0.8618	M02	0.6786	0.4144	0.2269	1.3070	0.7886
M03	0.6411	0.3390	0.0794	1.4203	0.8378	M03	0.6937	0.4325	0.2249	1.2752	0.7763
M04	0.6409	0.3315	0.0408	1.4286	0.8426	M04	0.6839	0.4092	0.1668	1.3087	0.7921

After wavelet transformation
	SVMW						LSTMW						MLPW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.9095	0.8257	0.8282	0.6267	0.4161	M01	0.9687	0.9378	0.9115	0.3633	0.2487	M01	0.6793	0.4464	−0.1457	3.8154	1.1215
M02	0.9043	0.8138	0.7801	0.6497	0.4301	M02	0.9471	0.8950	0.8750	0.4772	0.3231	M02	0.3973	0.0145	−0.1473	5.2557	1.3574
M03	0.9709	0.9416	0.9132	0.3516	0.2409	M03	0.9735	0.9460	0.8776	0.3377	0.2317	M03	0.8676	0.7488	0.7937	0.7358	0.5678
M04	0.9690	0.9377	0.9248	0.3634	0.2488	M04	0.9765	0.9510	0.8641	0.3211	0.2207	M04	0.8438	0.7040	0.6811	0.7683	0.6626

	XGBoostW						CatboostW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.8461	0.7029	0.6083	0.8465	0.5617	M01	0.8746	0.7524	0.6481	0.7610	0.5128
M02	0.8510	0.6986	0.5212	0.8503	0.5657	M02	0.8831	0.7715	0.7185	0.7278	0.4926
M03	0.8968	0.7902	0.6963	0.6924	0.4721	M03	0.9236	0.8358	0.7119	0.6039	0.4176
M04	0.8967	0.7906	0.7075	0.6916	0.4715	M04	0.9182	0.8305	0.7396	0.6154	0.4243

Hamar
Before wavelet transformation
	SVM						LSTM						MLP
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.7206	0.4734	0.3020	1.1352	0.7233	M01	0.7188	0.5035	0.4905	1.1035	0.7024	M01	0.5452	0.1201	0.2316	1.6340	0.9345
M02	0.7177	0.4752	0.3267	1.1352	0.7221	M02	0.7222	0.5047	0.4672	1.0999	0.7015	M02	0.2918	−1.1474	−0.6264	3.0533	1.4599
M03	0.7153	0.4624	0.2734	1.1506	0.7309	M03	0.7216	0.4971	0.4221	1.1087	0.7069	M03	0.5999	0.1922	0.3122	1.5120	0.8953
M04	0.7186	0.4587	0.2421	1.1523	0.7334	M04	0.7201	0.4968	0.4386	1.1100	0.7071	M04	0.4939	−0.4772	0.3763	2.1898	1.2108

	XGBoost						Catboost
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.6850	0.4224	0.2937	1.2140	0.7571	M01	0.7072	0.4724	0.3911	1.1452	0.7236
M02	0.6750	0.4109	0.3353	1.2334	0.7646	M02	0.6995	0.4617	0.3900	1.1620	0.7309
M03	0.6802	0.4259	0.3788	1.2138	0.7548	M03	0.6901	0.4465	0.3686	1.1849	0.7412
M04	0.6519	0.3855	0.3346	1.2773	0.7809	M04	0.6815	0.4311	0.3426	1.2073	0.7514

After wavelet transformation
	SVMW						LSTMW						MLPW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.8819	0.7769	0.8099	0.6756	0.4709	M01	0.9529	0.9021	0.7912	0.4313	0.3119	M01	0.6400	0.3931	−0.0439	3.6191	1.1404
M02	0.8834	0.7795	0.8120	0.6711	0.4680	M02	0.9560	0.9121	0.8920	0.4079	0.2955	M02	0.6045	0.3159	−0.7075	4.9156	1.1051
M03	0.9617	0.9241	0.9102	0.3781	0.2747	M03	0.9689	0.9369	0.8747	0.3433	0.2503	M03	0.6670	0.3150	0.5545	0.9484	0.8309
M04	0.9569	0.9134	0.9148	0.4047	0.2933	M04	0.9451	0.8876	0.7840	0.4639	0.3342	M04	0.6554	0.3475	0.5501	1.8062	0.8639

	XGBoostW						CatboostW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.8553	0.7265	0.7134	0.7588	0.5210	M01	0.8740	0.7629	0.7971	0.6993	0.4851
M02	0.8602	0.7295	0.6748	0.7526	0.5182	M02	0.8668	0.7497	0.7758	0.7213	0.4984
M03	0.8977	0.7972	0.7538	0.6387	0.4486	M03	0.9187	0.8375	0.7954	0.5656	0.4016
M04	0.8950	0.7898	0.7072	0.6513	0.4568	M04	0.9109	0.8143	0.7064	0.6069	0.4292

Lillehammer
Before wavelet transformation
	SVM						LSTM						MLP
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.7165	0.4593	0.2599	1.1318	0.7330	M01	0.7184	0.50048	0.47055	1.0866	0.7045	M01	0.5107	−0.1792	0.4323	1.8990	1.0553
M02	0.7195	0.4525	0.2116	1.1368	0.7375	M02	0.7232	0.51505	0.53577	1.0677	0.6941	M02	0.5162	−0.0980	0.0246	1.8259	1.0183
M03	0.7171	0.4610	0.2673	1.1296	0.7318	M03	0.7119	0.49617	0.51004	1.0954	0.7075	M03	0.5827	0.1841	0.4407	1.5078	0.8778
M04	0.7154	0.4441	0.1978	1.1483	0.7432	M04	0.6932	0.46974	0.49723	1.1362	0.7259	M04	0.4417	−0.3649	0.0427	2.1408	1.1354

	XGBoost						Catboost
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.6498	0.3954	0.5215	1.2451	0.7556	M01	0.7000	0.4649	0.4143	1.1368	0.7109
M02	0.6344	0.3765	0.5043	1.2764	0.7674	M02	0.6830	0.4427	0.4019	1.1719	0.7255
M03	0.6579	0.4136	0.4885	1.2203	0.7442	M03	0.7096	0.4796	0.4125	1.1147	0.7010
M04	0.6633	0.4150	0.3934	1.2148	0.7433	M04	0.6968	0.4608	0.3948	1.1432	0.7136

After wavelet transformation
	SVMW						LSTMW						MLPW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.8626	0.7407	0.7517	0.7223	0.5076	M01	0.9206	0.8364	0.7242	0.5564	0.4032	M01	0.5473	−0.2396	0.3032	1.9011	1.0820
M02	0.8721	0.7588	0.7808	0.6931	0.4896	M02	0.9604	0.9209	0.8935	0.3790	0.2804	M02	0.4754	−0.6028	0.3480	2.2670	1.2303
M03	0.9635	0.9258	0.8868	0.3666	0.2716	M03	0.9505	0.8996	0.8201	0.4291	0.3158	M03	0.8005	0.5018	0.6418	1.0357	0.6860
M04	0.9616	0.9232	0.8967	0.3733	0.2763	M04	0.9550	0.9086	0.8384	0.4086	0.3014	M04	0.8560	0.6784	0.8293	0.8073	0.5512

	XGBoostW						CatboostW
	r	NSE	KGE	PI	RMSE		r	NSE	KGE	PI	RMSE
M01	0.8406	0.6944	0.6258	0.7934	0.5372	M01	0.8396	0.7003	0.7149	0.7862	0.5320
M02	0.8333	0.6653	0.4932	0.8337	0.5622	M02	0.8486	0.7174	0.7415	0.7598	0.5166
M03	0.8650	0.7302	0.6021	0.7359	0.5048	M03	0.8807	0.7668	0.7036	0.6784	0.4693
M04	0.8506	0.7076	0.6000	0.7720	0.5255	M04	0.8907	0.7751	0.6354	0.6626	0.4609

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