Standard Precipitation Index Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Support Vector Regression

Table 3

(a) Performance results for the Ejersalele station, Upper Awash Basin, (b) Performance results of Nazereth Station, Middle Awash Basin, (c) Performance results of Dubti Station, Lower Awash Basin.

(a)

Model-Lead time	SPI 3			SPI 12
	𝑅^2	RMSE	MAE	𝑅^2	RMSE	MAE
ANN-L1	0.7694	0.1574	0.1433	0.9451	0.0610	0.0603
ANN-L6	0.6232	0.1744	0.1567	0.8614	0.1011	0.0885
WN-L1	0.8829	0.0700	0.0352	0.9534	0.0600	0.0536
WN-L6	0.6433	0.1070	0.0356	0.8731	0.0790	0.0662
SVR-L1	0.7219	0.1046	0.0915	0.7611	0.1312	0.1129
SVR-L6	0.6647	0.1118	0.1042	0.6941	0.1341	0.1247

(b)

Model-Lead time	SPI 3			SPI 12
	𝑅^2	RMSE	MAE	𝑅^2	RMSE	MAE
ANN-L1	0.7319	0.1170	0.1016	0.9158	0.1003	0.0911
ANN-L6	0.6546	0.1240	0.1142	0.7542	0.1104	0.0919
WN-L1	0.9483	0.0510	0.0441	0.9167	0.0753	0.0629
WN-L6	0.8641	0.0727	0.0512	0.8012	0.1072	0.0802
SVR-L1	0.7114	0.1216	0.1114	0.7713	0.1147	0.1130
SVR-L6	0.6540	0.1320	0.1217	0.7326	0.1244	0.1215

(c)

Model-Lead time	SPI 3			SPI 12
	𝑅^2	RMSE	MAE	𝑅^2	RMSE	MAE
ANN-L1	0.7368	0.1175	0.1095	0.9188	0.0710	0.0648
ANN-L6	0.6806	0.1302	0.1147	0.7135	0.0938	0.0836
WN-L1	0.9018	0.0652	0.0581	0.9473	0.0648	0.0560
WN-L6	0.8119	0.0706	0.0642	0.8641	0.0846	0.0747
SVR-L1	0.6990	0.1146	0.1022	0.7041	0.1102	0.1009
SVR-L6	0.6331	0.1309	0.1242	0.6705	0.1107	0.1025