Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

Table 2

Correlational analysis between DO and the WQ parameters.

	Discharge	Temp	pH	Turbidity	EC	TP	TN	TSS	DO
Discharge	1
Temp	0.271748	1
pH	−0.22542	0.069421	1
Turbidity	0.53972	0.287929	−0.28211	1
EC	0.190513	0.282863	0.352155	−0.14834	1
TP	0.133385	0.194775	0.114777	0.185624	0.237535	1
TN	0.034775	−0.00622	−0.03917	0.016368	0.283277	0.231251	1
TSS	0.689712	0.260862	−0.34453	0.818282	−0.02368	0.119882	−0.03906	1
DO	−0.13954	−0.20597	−0.24034	−0.09428	−0.27706	−0.4543	−0.34444	0.05042	1