Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment

Table 1

The descriptive statistics for irrigation water quality and input parameters.

	EC	pH	TDS						SAR	SSP	KR	PI	MH	%Na
Max	6.11	8.00	4,350	17.30	2.71	6.20	21.67	10.84	8.54	71.75	2.54	82.27	71.62	72.41
Mean	2.38	6.00	1,531	3.91	0.93	4.07	4.61	4.61	1.92	29.67	0.48	46.18	47.59	34.69
Min	1.19	0.99	690	1.22	0.10	0.60	1.16	2.30	0.65	10.49	0.12	16.71	15.79	11.00
SD	0.94	0.59	674	2.51	0.62	1.21	3.08	1.49	1.36	11.54	0.38	12.44	12.55	11.06
Skewness	1.88	−0.09	2.33	3.53	0.89	−0.38	3.10	1.33	3.49	1.41	3.36	0.48	−0.04	1.12
Kurtosis	3.83	−1.09	5.99	14.42	0.67	−0.31	13.18	2.83	13.49	2.63	12.98	0.32	−0.69	1.74

EC (dS/m), TDS (ppm), K, HCO₃, Mg and Ca (meq/l), Max – maximum, Min – minimum, and SD – standard deviation.