Data on assessment of corrosion-scaling potential and chemical parameters of groundwater quality for industrial and agricultural sectors in the Piranshahr Watershed in the West Azerbaijan province, Iran.

The present work sets out to 1) evaluate the corrosion-scaling potential of groundwater resources for the industrial sector as well as to 2) examine groundwater chemical parameters for the agricultural sector in the Piranshahr Watershed in the West Azerbaijan province, Iran, using geostatistical analyses and the Wilcox diagram in a GIS environment. A total of 145 spring locations as representatives of groundwater potentiality were recorded by a handheld GPS device and the corrosion and scaling potential states were further scrutinized. The latter was carried out on the basis of examining the chemical parameters at each sample location including alkalinity, pH, temperature, Na+, Ca++, Mg++, TH, HCO 3 - , Co 3 - 2 , Cl - , SO 4 - 2 , Electrical conductivity, and Total dissolved solids. The corrosion and scaling potential of groundwater was then evaluated by using Langelier saturation index (LSI), Larson-Skold index (LS), Ryznar stability index (RSI), Aggressive index (AI), and Puckorius scaling index (PSI). Also, the groundwater quality state for agriculture was assessed by the Wilcox diagram on the basis of Electrical conductivity and Sodium adsorption ratio parameters. The provided data are beneficial for researchers, policymakers, and authorities for taking pragmatic actions. Also, the compiled data can be used in the context of corrosion/scaling and groundwater quality assessment can be generalized around the world.

Data

This dataset contains 5 Tables and 3 Figures which present in detail the corrosion-scaling potential and chemical parameters of groundwater quality for the industrial and agricultural sectors in the Piranshahr Watershed. Fig. 1 shows the geographical location of the springs (i.e., sampling points) across the Piranshahr Watershed in the West Azerbaijan Province, Iran. Table 1 presents the water quality chemical parameters including alkalinity, pH, temperature, Na+, Ca++, Mg++, TH, , , , , EC, and TDS which have been measured during the field surveys and analyzed in the laboratory. Table 2 shows the descriptive statistics such as maximum, minimum, mean, and standard deviation of hydro-geochemical parameters. Table 3 presents some indices, equations, definitions, and criteria which were further used for classifying water corrosion and scaling [2], [3], [4], [5], [6], [7]. Table 4 shows the results obtained from the RSI, LSI, AI, PSI and LS analyses as well as other detailed information on pHs and pHeq. Table 5 shows the descriptive statistics such as maximum, minimum, mean, and standard deviation of corrosion and scaling indices. Mapping the corrosion and scaling indices was carried out by geostatistical analyses in ArcGIS 10.3.1 [8] which are shown in Fig. 2. Fig. 3 depicts the groundwater quality classes for the agricultural sector based on the Wilcox diagram in ArcGIS.

Fig. 1

The geographical location of the Piranshahr Watershed and the recorded springs in the West Azerbaijan province in Iran.

Table 1

Hydro-geochemical characterization of 145 groundwater samples in the Piranshahr Watershed.

Sample numbers	UTM Zone 38 N		(μs/cm)	PH	(mg/l)										(°C)
	UTMX	UTMY	EC		TDS	CO3-2	HCO3-	Cl−	TH	SO4-2	Alkalinity	Ca++	Mg++	T	Na+
S1	489895	4073692	292	8.26	146	52.03	34.78	14.18	110	316.08	86.81	60.08	2.43	11.5	153.85
S2	489463	4078050	238	7.19	119	35.62	126.31	17.73	120	137.70	161.93	32.06	9.73	10	124.32
S3	507028	4062034	375	7.57	187	36.02	176.96	14.18	200	304.56	212.98	48.10	19.46	9	184.67
S4	500854	4075624	349	7.36	275	38.02	67.12	21.28	160	238.76	105.14	60.12	2.43	10.5	138.58
S5	491043	4077392	266	7.42	133	52.03	103.73	14.18	130	41.40	155.76	36.07	9.73	10	91.08
S6	502107	4075725	212	7.29	106	18.01	91.53	14.18	110	103.94	109.54	28.06	9.73	11	66.98
S7	508513	4065028	347	7.72	174	46.02	36.61	10.64	190	150.62	82.64	20.04	34.05	9	55.75
S8	512472	4070778	540	7.2	270	80.04	79.33	17.73	170	16.09	159.37	60.12	4.86	8.4	110.61
S9	500905	4075583	294	7.43	147	38.42	51.87	17.73	150	119.59	90.29	36.07	14.59	5	78.75
S10	489336	4072764	131	7.08	64	34.21	170.86	14.18	140	111.43	205.07	12.02	26.75	14	55.75
S11	503018	4076689	303	7.52	151	37.22	75.66	17.73	140	95.87	112.88	48.10	4.86	11	78.75
S12	489492	4072776	266	7.91	133	28.81	149.50	17.73	120	23.92	178.31	44.09	2.43	7	66.98
S13	506224	4067765	296	7.63	148	42.42	53.70	10.64	120	48.37	96.12	36.07	7.30	13.3	61.30
S14	503318	4076826	378	7.39	189	22.01	151.94	24.82	170	133.24	173.95	64.13	2.43	9	91.08
S15	499015	4074453	431	7.4	216	38.42	198.93	17.73	170	51.92	237.34	68.14	0.00	10	84.85
S16	506527	4077079	251	7.53	125	52.03	147.06	14.18	150	0.48	199.08	56.11	2.43	11	78.75
S17	499789	4076186	259	7.88	128	16.01	164.75	10.64	130	53.79	180.76	40.08	7.30	9	55.75
S18	500450	4075866	337	7.94	168	32.02	118.99	14.18	220	162.15	151.01	28.06	36.48	7.5	78.75
S19	507982	4062881	289	7.78	144	52.03	42.71	10.64	160	85.35	94.74	60.12	2.43	5	72.80
S20	488803	4073280	137	7.69	68	12.01	148.28	14.18	140	52.98	160.28	16.03	24.32	6	39.95
S21	511006	4063326	339	7.69	169	52.43	78.11	10.64	180	52.78	130.53	40.08	19.46	10	61.30
S22	513290	4071876	371	7.89	185	44.02	122.04	14.18	200	58.64	166.06	48.10	19.46	6	72.80
S23	505696	4075016	472	7.52	235	68.03	36.61	14.18	240	190.34	104.65	76.15	12.16	12.2	97.45
S24	510999	4063342	345	7.57	172	62.03	10.98	10.64	210	111.72	73.01	36.07	29.18	12	66.98
S25	488956	4072973	106	7	53	8.00	103.73	10.64	140	97.60	111.74	12.02	26.75	11	34.96
S26	503395	4076532	373	7.52	186	13.61	190.38	14.18	170	99.61	203.99	60.12	4.86	10	66.98
S27	505571	4077779	289	7.67	145	41.62	211.13	14.18	210	32.71	252.75	48.10	21.89	12	72.80
S28	500830	4075753	403	7.73	202	56.03	59.19	14.18	230	119.64	115.22	40.08	31.62	9	72.80
S29	505270	4076461	448	7.44	224	46.02	117.16	17.73	240	140.01	163.18	60.12	21.89	7.6	84.85
S30	500527	4074864	418	7.4	210	50.03	79.33	14.18	250	170.07	129.35	56.11	26.75	9	84.85
S31	507190	4062507	282	7.6	141	58.43	47.60	10.64	140	17.96	106.02	40.08	9.73	11	45.08
S32	499798	4076382	385	8.12	187	36.82	87.26	14.18	200	107.78	124.08	52.10	17.02	14	66.98
S33	506864	4061918	265	7.68	132	48.02	3.05	10.64	150	63.02	51.08	36.07	14.59	7.5	45.08
S34	502271	4076724	310	7.53	150	31.62	81.16	10.64	130	20.27	112.77	28.06	14.59	11	34.96
S35	489824	4073902	162	7.41	81	52.03	17.70	14.18	130	2.07	69.72	40.08	7.30	10	39.95
S36	502815	4076271	304	7.76	152	32.42	59.80	14.18	150	69.45	92.22	40.08	12.16	11	45.08
S37	492271	4081165	240	7.53	120	44.02	26.85	14.18	150	42.89	70.87	28.06	19.46	13	39.95
S38	499719	4074885	316	7.75	158	42.02	103.73	14.18	180	52.16	145.76	48.10	14.59	6	55.75
S39	512230	4074644	359	7.5	180	42.02	140.35	14.18	200	53.36	182.37	52.10	17.02	12	61.30
S40	512406	4072929	375	7.44	188	54.43	99.46	14.18	160	20.41	153.89	52.10	7.30	13	50.35
S41	499983	4076733	384	8	142	32.02	85.43	14.18	150	50.72	117.44	48.10	7.30	10	45.08
S42	512366	4070895	412	7.36	206	76.04	64.07	14.18	210	17.72	140.11	52.10	19.46	9	61.30
S43	501924	4077966	382	7.22	191	48.02	97.63	14.18	220	85.35	145.66	48.10	24.32	12	61.30
S44	508606	4064686	307	7.59	153	32.42	84.21	10.64	170	75.70	116.62	40.08	17.02	6.7	45.08
S45	499236	4075648	316	7.97	158	38.02	85.43	14.18	160	38.71	123.45	44.09	12.16	6	45.08
S46	489693	4073875	176	7.45	88	16.01	118.38	14.18	100	16.28	134.39	20.04	12.16	13	20.82
S47	499246	4075713	315	7.78	157	26.41	151.33	14.18	140	1.30	177.74	44.09	7.30	10	39.95
S48	506703	4063133	277	7.45	138	56.03	21.36	14.18	170	27.81	77.39	36.07	19.46	6	39.95
S49	502352	4075839	442	7.34	221	40.02	128.14	14.18	240	99.28	168.16	68.14	17.02	10	72.80
S50	488969	4072954	222	7.76	110	35.62	50.04	10.64	150	31.60	85.65	8.02	31.62	9	25.39
S51	514296	4073673	336	7.63	168	52.03	54.92	14.18	190	52.40	106.94	44.09	19.46	12	50.35
S52	510991	4063427	333	7.56	167	52.03	73.22	14.18	250	137.70	125.25	36.07	38.91	5	61.30
S53	500341	4075302	464	7.63	232	44.02	118.99	17.73	250	99.13	163.01	52.10	29.18	7	66.98
S54	503063	4080485	161	6.91	80	20.41	67.73	10.64	200	160.71	88.14	28.06	31.62	12	45.08
S55	503734	4076407	370	7.7	185	40.02	23.19	17.73	180	74.25	63.21	68.14	2.43	9	55.75
S56	502892	4080580	236	7.7	118	26.01	76.89	14.18	120	20.41	102.90	40.08	4.86	8	30.11
S57	488879	4073071	138	7.57	69	28.01	21.36	14.18	140	64.84	49.37	12.02	26.75	12	25.39
S58	502847	4076196	309	7.82	155	38.02	85.43	14.18	160	28.00	123.45	44.09	12.16	10	39.95
S59	489762	4073992	370	7.7	182	44.02	79.33	10.64	140	13.35	123.35	44.09	7.30	8	34.96
S60	501235	4076169	309	7.39	155	24.41	154.38	10.64	210	97.55	178.79	44.09	24.32	5	50.35
S61	509088	4076270	256	7.89	128	52.03	79.33	10.64	80	118.73	131.35	32.06	0.00	13	16.38
S62	510997	4063143	334	7.65	167	52.83	60.41	14.18	220	64.60	113.24	40.08	29.18	9	50.35
S63	499623	4079089	370	7.48	185	46.02	67.12	10.64	180	67.82	113.15	52.10	12.16	5	45.08
S64	506162	4067723	301	7.82	150	26.81	99.46	14.18	260	186.64	126.28	36.07	41.34	7	55.75
S65	502959	4073178	288	7.63	144	48.42	128.75	10.64	170	57.44	177.18	36.07	19.46	7	34.96
S66	506569	4062916	283	7.65	141	30.02	158.65	10.64	180	14.22	188.67	28.06	26.75	11	34.96
S67	506865	4061919	339	7.61	170	50.03	18.31	14.18	150	17.87	68.33	44.09	9.73	13	34.96
S68	514334	4073728	382	7.54	191	64.83	39.66	14.18	220	47.12	104.50	48.10	24.32	13	50.35
S69	506229	4067785	277	7.66	138	29.61	85.43	10.64	230	152.78	115.04	48.10	26.75	9	50.35
S70	500568	4077247	314	7.6	157	36.82	90.31	14.18	180	47.60	127.13	48.10	14.59	11	39.95
S71	501303	4077125	432	7.61	217	52.43	106.17	10.64	230	46.16	158.60	52.10	24.32	5	50.35
S72	514465	4073946	434	7.3	218	46.42	106.17	10.64	230	86.45	152.60	68.14	14.59	7	55.75
S73	511101	4074923	390	7.51	195	72.44	45.77	14.18	210	5.04	118.20	64.13	12.16	13	50.35
S74	506852	4063762	321	7.62	160	56.03	134.24	10.64	230	108.16	190.27	48.10	26.75	10	45.08
S75	506042	4067874	275	7.7	135	30.02	91.53	10.64	220	125.45	121.55	44.09	26.75	14	45.08
S76	502367	4076892	221	7.3	111	29.61	75.66	14.18	180	75.02	105.28	40.08	19.46	9	34.96
S77	506415	4062900	247	7.64	123	51.23	20.14	10.64	130	22.29	71.36	40.08	7.30	9	25.39
S78	500923	4072627	287	8.05	143	42.82	87.26	10.64	170	5.43	130.08	36.07	19.46	14	30.11
S79	501791	4080487	288	7.32	144	28.81	108.01	10.64	150	9.61	136.82	32.06	17.02	8	25.39
S80	503543	4077895	408	7.58	203	44.82	109.84	14.18	210	43.03	154.66	56.11	17.02	13	45.08
S81	500256	4077743	306	7.95	153	28.01	124.48	10.64	210	86.12	152.49	40.08	26.75	14	39.95
S82	504359	4075552	453	7.51	227	48.02	200.15	14.18	280	61.53	248.17	68.14	26.75	10	61.30
S83	504110	4077328	425	7.69	212	54.03	122.04	14.18	220	10.66	176.07	56.11	19.46	12	45.08
S84	511744	4074496	448	7.38	225	61.63	122.04	14.18	230	3.12	183.67	68.14	14.59	14	50.35
S85	508134	4062063	213	8.02	106	49.62	3.66	14.18	130	17.92	53.29	32.06	12.16	10	20.82
S86	499030	4072670	332	7.67	166	36.02	122.04	10.64	200	49.52	158.06	56.11	14.59	10	39.95
S87	507919	4058846	334	7.6	167	67.23	42.10	10.64	180	29.49	109.34	52.10	12.16	8	34.96
S88	490180	4074445	382	7.5	191	88.04	73.22	14.18	190	80.07	161.27	64.13	7.30	7	39.95
S89	501034	4078308	289	7.9	144	37.62	70.17	10.64	120	32.13	107.79	40.08	4.86	5	20.82
S90	508102	4068804	363	7.67	181	56.03	48.82	10.64	280	133.67	104.84	48.10	38.91	6	50.35
S91	500423	4078928	309	7.59	155	21.61	178.18	14.18	200	42.36	199.79	44.09	21.89	11	34.96
S92	505910	4067811	290	7.65	145	32.02	91.53	14.18	230	112.05	123.55	44.09	29.18	7	39.95
S93	507399	4059229	280	7.42	140	40.02	91.53	14.18	190	34.68	131.55	52.10	14.59	5	34.96
S94	502213	4076503	251	7.58	126	32.42	76.89	14.18	190	63.93	109.30	36.07	24.32	10	30.11
S95	502204	4077810	380	7.66	190	52.03	35.39	14.18	210	54.85	87.42	40.08	26.75	13	34.96
S96	507787	4067834	217	8.35	108	42.42	40.27	14.18	140	20.75	82.69	16.03	24.32	11	16.38
S97	501903	4078291	423	7.47	211	57.23	145.84	14.18	260	18.35	203.07	52.10	31.62	7	45.08
S98	490129	4074513	375	7.83	187	51.63	67.73	14.18	180	1.73	119.36	64.13	4.86	13	34.96
S99	501712	4077530	331	7.52	165	37.62	129.36	10.64	170	11.29	166.98	52.10	9.73	9	30.11
S100	508922	4064022	427	7.3	213	60.03	70.17	14.18	250	58.21	130.20	60.12	24.32	5	45.08
S101	501705	4076849	380	7.63	190	50.03	45.77	14.18	200	34.63	95.79	36.07	26.75	7	30.11
S102	502142	4077381	372	7.63	185	44.02	86.65	14.18	200	5.00	130.67	52.10	17.02	8	34.96
S103	501562	4077774	339	7.72	169	52.03	59.80	10.64	220	45.68	111.83	40.08	29.18	11	30.11
S104	500240	4077700	370	7.43	183	33.22	81.16	14.18	210	86.55	114.37	48.10	21.89	9	34.96
S105	493412	4079059	312	7.45	156	12.81	235.54	17.73	180	5.52	248.34	48.10	14.59	14	30.11
S106	501803	4077951	352	7.66	176	48.42	133.02	14.18	200	54.99	181.45	36.07	26.75	10	30.11
S107	508150	4063779	455	7.41	228	52.03	30.51	10.64	290	149.61	82.54	64.13	31.62	11	50.35
S108	503573	4077824	377	7.65	188	52.03	79.33	14.18	200	13.64	131.35	56.11	14.59	10	34.96
S109	501735	4071713	229	7.63	114	23.61	94.58	14.18	140	13.50	118.19	40.08	9.73	13	20.82
S110	499209	4072297	324	7.34	162	19.61	208.69	14.18	180	4.08	228.30	52.10	12.16	13	30.11
S111	508748	4063981	282	7.44	141	34.02	54.31	10.64	260	132.51	88.32	44.09	36.48	7	39.95
S112	500943	4072450	233	7.46	169	44.42	80.55	14.18	190	9.17	124.97	48.10	17.02	10	20.82
S113	502200	4077812	374	8.04	187	38.02	109.84	14.18	220	10.13	147.86	32.06	34.05	6	30.11
S114	508676	4076141	259	7.88	129	40.82	89.09	10.64	130	58.21	129.91	32.06	12.16	12	16.38
S115	500759	4078091	300	7.85	150	40.02	57.97	10.64	220	94.72	97.99	56.11	19.46	13	34.96
S116	498985	4072329	288	7.57	144	28.81	131.80	10.64	150	20.22	160.62	40.08	12.16	14	20.82
S117	503166	4078473	407	7.58	204	48.02	207.47	14.18	230	47.36	255.49	52.10	24.32	10	34.96
S118	499096	4071930	284	7.4	142	42.02	72.61	10.64	150	21.18	114.63	44.09	9.73	7	20.82
S119	501069	4070642	279	7.57	140	41.22	60.41	14.18	240	94.76	101.63	36.07	36.48	6	30.11
S120	500920	4072713	295	7.59	148	30.02	112.28	14.18	200	43.71	142.29	36.07	26.75	6	25.39
S121	507437	4069650	514	7.28	257	45.62	88.48	17.73	300	138.61	134.10	60.12	36.48	12	45.08
S122	507064	4062505	384	7.17	192	69.63	100.07	7.09	240	19.88	169.71	60.12	21.89	8	34.96
S123	506138	4064156	273	7.82	137	52.03	36.61	10.64	170	15.23	88.64	40.08	17.02	5	20.82
S124	501394	4078648	379	8.51	189	35.62	120.21	14.18	220	2.69	155.83	28.06	36.48	12	25.39
S125	509406	4076588	423	7.48	211	36.02	103.73	14.18	200	40.11	139.75	68.14	7.30	5	30.11
S126	501789	4073710	315	7.62	158	36.42	145.23	14.18	180	24.50	181.65	56.11	9.73	14	25.39
S127	499715	4077021	300	7.8	150	32.02	82.38	14.18	200	70.65	114.39	68.14	7.30	11	30.11
S128	503638	4078371	383	7.54	191	43.22	198.93	14.18	300	54.42	242.15	48.10	43.78	9	39.95
S129	500018	4080350	346	7.72	173	46.02	134.24	10.64	190	36.02	180.27	56.11	12.16	11	25.39
S130	499995	4078255	256	7.66	128	18.01	116.55	10.64	130	2.31	134.56	52.10	0.00	14	16.38
S131	508088	4068205	393	7.19	196	42.42	114.72	14.18	270	84.34	157.14	56.11	31.62	12	34.96
S132	506369	4064339	354	7.37	177	40.02	79.33	10.64	220	30.26	119.35	48.10	24.32	6	25.39
S133	500214	4072445	328	7.47	164	37.22	147.67	10.64	170	43.66	184.89	52.10	9.73	12	20.82
S134	502162	4077854	365	7.81	183	54.03	88.48	21.28	260	36.17	142.51	52.10	31.62	6	30.11
S135	500838	4072298	306	7.52	153	51.23	57.36	14.18	150	56.00	108.58	48.10	7.30	12	16.38
S136	501393	4078648	378	8.44	189	34.82	181.84	10.64	300	82.66	216.66	24.05	58.37	9	30.11
S137	512772	4074497	417	7.6	208	64.03	109.84	17.73	300	34.68	173.87	52.10	41.34	8	34.96
S138	502736	4078062	355	7.67	177	49.22	197.70	17.73	270	20.41	246.93	48.10	36.48	6	30.11
S139	501868	4071744	216	7.73	108	29.21	52.48	10.64	260	156.87	81.69	36.07	41.34	9	25.39
S140	495825	4078269	362	7.53	181	17.21	209.91	10.64	200	8.21	227.12	56.11	14.59	8	20.82
S141	508347	4064749	460	7.57	230	48.02	27.46	10.64	260	93.95	75.48	48.10	34.05	13	25.39
S142	513091	4071434	393	7.57	196	64.03	20.14	10.64	220	25.41	84.17	48.10	24.32	8	20.82
S143	499205	4071866	309	7.46	154	43.22	105.56	14.18	170	46.30	148.79	56.11	7.30	13	16.38
S144	499917	4078691	327	8.05	164	30.02	131.19	10.64	170	14.12	161.21	60.12	4.86	14	16.38
S145	507988	4067798	233	8.03	117	22.01	113.50	10.64	230	77.28	135.51	20.04	43.78	9	12.08

Table 2

Descriptive statistics of hydro-geochemical parameters.

Parameters	EC	PH	TDS	CO3-2	HCO3-	Cl−	TH	SO4-2	Alkalinity	Ca++	Mg++	Na+	T
Max	540	8.51	275	88.04	235.54	24.82	300	316.08	255.49	76.15	58.37	184.67	14
Min	106	6.91	53	8.00	3.05	7.09	80	0.48	49.37	8.02	0	12.08	5
Mean	326.67	7.61	163.83	41.92	95.66	13.35	190.97	64.46	137.58	45.41	18.97	46.29	9.68
St.dev.	77.21	0.25	39.53	14.04	49.50	2.60	46.63	55.94	45.42	13.21	11.24	26.25	2.68

Table 3

Corrosion and scaling indices, equations, and their associated status [2,3,4,5,6, and 7].

Index	Equation	Index value	Status
Aggressive index (AI)	AI = pH + log10(Alkalinity)*(H)	AI<10	Very aggressive
		10 < AI<12	Moderately aggressive
		AI>12	Nonaggressive
Langelier Saturation Index (LSI)	LSI = pH- pHs	LSI>0	Scale can form, CaCO3 precipitation may occur
		LSI = 0	Borderline scale potential
		LSI<0	No potential to scale, water will dissolve CaCO3
Puckorius Scaling Index (PSI)	PSI = 2pHs- pHeq	PSI>7	Likely to dissolve scale
		PSI<6	Scaling is unlikely to occur
Ryznar Stability Index (RSI)	RSI = 2pHs- pH	RSI<6	Scale tendency increases as the index decreases
		6 < RSI<7	Calcium carbonate formation probably does not lead to a protective corrosion inhibitor film
		RSI>7	Mild steel corrosion becomes an increasing problem.
Larson-skold index (LS)	LS=Cl^−+SO4−2HCO3−+CO3−2	LS < 0.8	Chlorides and sulfate unlikely to interfere with natural film formation
		0.8 < LS < 1.2	Chlorides and sulfates may interfere with natural film formation.
		LS > 1.2	High local corrosion tendency expected as the index increases

Where: pHs= (9.3 + A + B)-(C + D); A= (Log10 (TDS)-1)/10; B = −13.12 * Log10 (oC+273) + 34.55; C = Log10 (Ca2+ as CaCO3) - 0.4; D = Log10 (alkalinity as CaCO3); pHeq = 1.465 + Log10 (alkalinity) + 4.54; H in AI index has Calcium hardness (mg/l).

Table 4

Summary of water stability indices (corrosion and scaling) in the area.

Sample numbers	pHs	pHeq	RSI	LSI	AI	PSI	LS
S1	8.19	7.94	8.12	0.07	12.24	8.43	3.8
S2	7.90	8.21	8.61	−0.71	11.48	7.59	0.96
S3	7.60	8.33	7.63	−0.03	12.20	6.87	1.5
S4	7.99	8.03	8.62	−0.63	11.59	7.95	2.47
S5	7.89	8.20	8.36	−0.47	11.73	7.58	0.36
S6	8.08	8.04	8.88	−0.79	11.37	8.12	1.08
S7	8.03	7.92	8.34	−0.31	11.92	8.14	1.95
S8	7.83	8.21	8.45	−0.63	11.63	7.44	0.21
S9	8.17	7.96	8.91	−0.74	11.56	8.38	1.52
S10	7.70	8.24	8.33	−0.62	11.46	7.17	0.74
S11	7.98	8.06	8.44	−0.46	11.72	7.91	1.01
S12	7.93	8.26	7.94	−0.02	12.24	7.59	0.23
S13	8.07	7.99	8.51	−0.44	11.69	8.16	0.61
S14	7.76	8.25	8.13	−0.37	11.86	7.27	0.91
S15	7.61	8.38	7.82	−0.21	12.01	6.84	0.29
S16	7.70	8.30	7.86	−0.17	12.01	7.09	0.07
S17	7.84	8.26	7.80	0.04	12.25	7.42	0.36
S18	7.73	8.18	7.53	0.21	12.46	7.28	1.17
S19	8.12	7.98	8.46	−0.34	11.96	8.26	1.01
S20	7.90	8.21	8.10	−0.21	12.04	7.58	0.42
S21	7.83	8.12	7.98	−0.14	12.06	7.55	0.49
S22	7.77	8.23	7.65	0.12	12.41	7.31	0.44
S23	7.78	8.02	8.03	−0.26	11.92	7.53	1.95
S24	7.98	7.87	8.39	−0.41	11.76	8.09	1.68
S25	7.94	8.05	8.88	−0.94	11.19	7.83	0.97
S26	7.67	8.31	7.82	−0.15	12.06	7.02	0.56
S27	7.43	8.41	7.20	0.24	12.39	6.46	0.19
S28	7.81	8.07	7.89	−0.08	12.15	7.55	1.16
S29	7.67	8.22	7.91	−0.23	12.03	7.13	0.97
S30	7.73	8.12	8.05	−0.33	11.91	7.33	1.42
S31	8.01	8.03	8.41	−0.41	11.77	7.98	0.27
S32	7.74	8.10	7.35	0.38	12.51	7.37	0.98
S33	8.36	7.71	9.04	−0.68	11.56	9.01	1.44
S34	8.01	8.06	8.50	−0.48	11.70	7.97	0.27
S35	8.22	7.85	9.02	−0.81	11.37	8.58	0.23
S36	8.04	7.97	8.32	−0.28	11.90	8.11	0.91
S37	8.10	7.86	8.68	−0.57	11.56	8.35	0.81
S38	7.86	8.17	7.98	−0.11	12.17	7.56	0.46
S39	7.61	8.27	7.71	−0.11	12.06	6.95	0.37
S40	7.76	8.19	8.08	−0.32	11.83	7.32	0.22
S41	7.95	8.07	7.90	0.05	12.25	7.83	0.55
S42	7.77	8.15	8.17	−0.41	11.83	7.38	0.23
S43	7.66	8.17	8.11	−0.44	11.73	7.16	0.68
S44	7.97	8.07	8.35	−0.38	11.89	7.87	0.74
S45	7.99	8.10	8.01	−0.02	12.27	7.88	0.43
S46	7.99	8.13	8.53	−0.54	11.58	7.84	0.23
S47	7.81	8.25	7.83	−0.03	12.18	7.36	0.09
S48	8.16	7.89	8.87	−0.71	11.57	8.42	0.54
S49	7.61	8.23	7.88	−0.27	11.95	6.99	0.67
S50	8.10	7.94	8.44	−0.34	11.87	8.26	0.49
S51	7.86	8.03	8.08	−0.23	11.94	7.68	0.62
S52	7.81	8.10	8.06	−0.25	12.06	7.52	1.21
S53	7.67	8.22	7.71	−0.04	12.24	7.12	0.72
S54	7.89	7.95	8.86	−0.98	11.16	7.82	1.94
S55	8.17	7.81	8.65	−0.47	11.76	8.54	1.46
S56	8.14	8.02	8.58	−0.44	11.79	8.26	0.34
S57	8.29	7.70	9.00	−0.72	11.41	8.87	1.6
S58	7.91	8.10	7.99	−0.09	12.12	7.72	0.34
S59	8.01	8.10	8.32	−0.31	11.94	7.93	0.19
S60	7.73	8.26	8.07	−0.34	11.96	7.20	0.61
S61	8.11	8.12	8.33	−0.22	11.91	8.10	0.98
S62	7.83	8.06	8.01	−0.18	12.05	7.60	0.7
S63	8.00	8.06	8.52	−0.52	11.79	7.95	0.69
S64	7.74	8.11	7.67	0.08	12.34	7.38	1.59
S65	7.78	8.25	7.93	−0.15	12.11	7.31	0.38
S66	7.65	8.28	7.64	0.00	12.18	7.01	0.13
S67	8.13	7.84	8.66	−0.52	11.62	8.43	0.47
S68	7.79	8.02	8.04	−0.25	11.90	7.55	0.59
S69	7.79	8.07	7.93	−0.13	12.08	7.52	1.42
S70	7.82	8.11	8.05	−0.22	11.96	7.54	0.49
S71	7.76	8.21	7.90	−0.15	12.17	7.31	0.36
S72	7.73	8.19	8.16	−0.43	11.85	7.28	0.64
S73	7.76	8.08	8.00	−0.25	11.90	7.44	0.16
S74	7.56	8.28	7.50	0.06	12.26	6.84	0.62
S75	7.69	8.09	7.68	0.01	12.13	7.29	1.12
S76	7.93	8.03	8.56	−0.63	11.58	7.83	0.85
S77	8.24	7.86	8.85	−0.60	11.61	8.63	0.46
S78	7.77	8.12	7.50	0.28	12.39	7.43	0.12
S79	7.93	8.14	8.53	−0.61	11.63	7.71	0.15
S80	7.64	8.19	7.70	−0.06	12.09	7.09	0.37
S81	7.62	8.19	7.28	0.33	12.46	7.04	0.63
S82	7.38	8.40	7.24	0.13	12.35	6.35	0.31
S83	7.59	8.25	7.48	0.10	12.28	6.92	0.14
S84	7.51	8.27	7.64	−0.13	12.01	6.76	0.09
S85	8.34	7.73	8.67	−0.32	11.86	8.96	0.6
S86	7.70	8.20	7.74	−0.03	12.17	7.21	0.38
S87	7.95	8.04	8.30	−0.35	11.89	7.86	0.37
S88	7.79	8.21	8.07	−0.29	11.99	7.36	0.58
S89	8.19	8.04	8.48	−0.29	12.01	8.34	0.4
S90	7.82	8.03	7.97	−0.15	12.14	7.62	1.38
S91	7.58	8.31	7.57	0.01	12.19	6.85	0.28
S92	7.81	8.10	7.96	−0.16	12.10	7.51	1.02
S93	7.90	8.12	8.38	−0.48	11.82	7.68	0.37
S94	7.88	8.04	8.17	−0.30	11.90	7.71	0.71
S95	7.89	7.95	8.11	−0.23	11.92	7.83	0.79
S96	8.10	7.92	7.85	0.25	12.41	8.28	0.42
S97	7.55	8.31	7.64	−0.08	12.19	6.79	0.16
S98	7.82	8.08	7.81	0.01	12.16	7.55	0.13
S99	7.77	8.23	8.02	−0.25	11.97	7.32	0.13
S100	7.80	8.12	8.31	−0.50	11.81	7.49	0.56
S101	7.99	7.99	8.35	−0.36	11.91	7.99	0.51
S102	7.83	8.12	8.03	−0.20	12.05	7.54	0.15
S103	7.79	8.05	7.87	−0.07	12.11	7.54	0.5
S104	7.85	8.06	8.27	−0.42	11.81	7.63	0.88
S105	7.47	8.40	7.49	−0.02	12.10	6.54	0.09
S106	7.65	8.26	7.63	0.01	12.22	7.03	0.38
S107	7.82	7.92	8.23	−0.41	11.79	7.72	1.94
S108	7.79	8.12	7.93	−0.14	12.07	7.46	0.21
S109	7.91	8.08	8.19	−0.28	11.85	7.74	0.23
S110	7.53	8.36	7.72	−0.19	11.95	6.70	0.08
S111	7.90	7.95	8.35	−0.46	11.80	7.84	1.62
S112	7.83	8.10	8.20	−0.37	11.84	7.56	0.19
S113	7.78	8.17	7.52	0.26	12.55	7.38	0.16
S114	7.93	8.12	7.97	−0.05	12.11	7.73	0.53
S115	7.81	8.00	7.76	0.04	12.18	7.62	1.08
S116	7.74	8.21	7.90	−0.17	11.95	7.26	0.19
S117	7.44	8.41	7.31	0.14	12.35	6.48	0.24
S118	8.02	8.06	8.65	−0.62	11.64	7.98	0.28
S119	7.89	8.01	8.21	−0.32	11.96	7.77	1.07
S120	7.83	8.16	8.06	−0.24	12.04	7.49	0.41
S121	7.58	8.13	7.88	−0.30	11.88	7.03	1.17
S122	7.64	8.23	8.11	−0.47	11.78	7.05	0.16
S123	8.12	7.95	8.42	−0.30	12.00	8.29	0.29
S124	7.64	8.20	6.76	0.87	13.05	7.07	0.11
S125	7.87	8.15	8.26	−0.39	11.93	7.59	0.39
S126	7.61	8.26	7.60	0.01	12.13	6.95	0.21
S127	7.82	8.06	7.84	−0.02	12.16	7.58	0.74
S128	7.37	8.39	7.20	0.17	12.40	6.35	0.28
S129	7.65	8.26	7.58	0.07	12.25	7.04	0.26
S130	7.87	8.13	8.08	−0.21	11.90	7.61	0.1
S131	7.54	8.20	7.90	−0.35	11.82	6.89	0.63
S132	7.87	8.08	8.37	−0.50	11.79	7.66	0.34
S133	7.67	8.27	7.86	−0.20	11.97	7.06	0.29
S134	7.72	8.16	7.63	0.09	12.38	7.28	0.4
S135	7.95	8.04	8.38	−0.43	11.73	7.86	0.65
S136	7.42	8.34	6.39	1.02	13.25	6.49	0.43
S137	7.54	8.25	7.47	0.06	12.32	6.83	0.3
S138	7.46	8.40	7.26	0.21	12.49	6.53	0.15
S139	7.88	7.92	8.03	−0.15	12.06	7.84	2.05
S140	7.59	8.36	7.65	−0.06	12.19	6.82	0.08
S141	7.87	7.88	8.16	−0.30	11.86	7.85	1.39
S142	7.98	7.93	8.40	−0.41	11.84	8.04	0.43
S143	7.74	8.18	8.02	−0.28	11.86	7.30	0.41
S144	7.69	8.21	7.32	0.36	12.49	7.16	0.15
S145	7.72	8.14	7.40	0.31	12.52	7.29	0.65

Table 5

Descriptive statistic of corrosion and scaling indices as well as pHs and pHeq.

Indices	pHs	pHeq	RSI	LSI	AI	PSI	LS
Max	8.36	8.41	9.04	1.02	13.25	9.01	3.80
Min	7.37	7.70	6.39	−0.98	11.16	6.35	0.07
Mean	7.83	8.12	8.05	−0.22	11.99	7.54	0.65
St.dev.	0.20	0.15	0.45	0.30	0.31	0.53	0.56

Fig. 2

Spatial distribution of LS, AI, LSI, RSI, and PSI respectively from top to down in the area interpolated by geostatistical analyses.

Fig. 3

Groundwater quality classes for the agricultural sector based on the Wilcox diagram (C1S1: excellent; C1S2–C2S1–C2S2: very good).

Experimental design, materials, and methods

Study area description

The Piranshahr Watershed extends for 426.15 km2 and is located within the geographical coordinates of 44° 49׳ 40״ and 45° 11׳ 40״ longitude and 36° 39׳ 00״ and 36° 56׳ 00״ latitude, in the West Azerbaijan province, northwest of Iran (Fig. 1). The area receives annual mean precipitation of 650 mm, most falls in the form of snow in winter. The area is characterized by cold semi-arid climate according to Emberger classification. Elevation ranges from 1400 to 3254 m [9].

Sample collection and analytical procedures

In the present work, 145 spring water samples were collected in the Piranshahr Watershed in West Azerbaijan province and further analyzed to measure water quality chemical parameters. For that purpose, 2 L sampling bottles were used for groundwater collection and temperature of the samples was in-situ measured. The EC was measured using an EC meter (CTS-406 Portable Conductivity Meter, EZDO, Taiwan) and then used for measuring the TDS. The acquired samples were transported into the Natural Resources College Laboratory at the University of Tehran for further analysis based on standard methods. The value of (pH) was measured with digital pH meter and chloride was determined by potentiometric titration with a standard silver nitrate solution [1]. Sodium was measured using Flame photometer (XP BWBTech, England). The concentration sulfate was determined using Spectrophotometer (UV-1800, Shimadzu, Japan). The calcium, magnesium and total hardness were measured by the EDTA titration method [1]. The alkalinity is expressed in (mg/L) of calcium carbonate and the basis of the endpoint of titration with sulfuric acid. Based on the Aggressive index, Langelier saturation index, Larson–Skold index, Ryznar saturation index and Puckorius scaling index were calculated as detailed in Table 3. Lastly, the intensity of scaling and corrosion were determined per spring and the derived values were interpolated over the entire area using geostatistical analysis (Inverse Distance Weighting) in ArcGIS. In addition, the prepared maps were reclassified based on the classification method proposed by Abbasnia et al. [3]. To assess the groundwater quality for the agricultural sector, the EC and SAR parameters were examined for each sample and interpolated over the area. The quality status was then determined based on the Wilcox diagram. Examination of SAR follows the equation:

Specifications Table

Subject area	Environmental Science
Specific subject area	Water quality, water science, groundwater management
Type of data	Table and figure
How data were acquired	Groundwater samples were collected in two-liter plastic bottles during extensive field surveys. Further analyses (i.e., measuring parameters by standard methods [1]) were carried out in the laboratory of Natural Resources College in the University of Tehran. Laboratory facilities were used to measure the parameters and the commercial software packages i.e. ArcGIS and Microsoft Excel were used for analyzing the derived data.
Data format	Raw, analyzed
Parameters for data collection	Sampling was conducted after the harvesting season. Groundwater samples were collected in 2 L bottles and transported to the laboratory of Natural Resources College in the University of Tehran on the next day and kept at a suitable temperature (4 °C). All samples were analyzed according to the standard methods.
Description of data collection	Firstly, the scope was identified and then, with the help of the local guide and field surveys, water springs were identified and their geographic coordinates were recorded using a handheld global positioning system (GPS) device. Groundwater samples were collected from a total of 145 springs across the Piranshahr Watershed. It was ensured that the collected samples were well distributed across the area.
Data source location	Piranshahr Watershed, West Azerbaijan Province, northwest of Iran. The latitude and longitude coordinates of the springs are presented in Table 1.
Data accessibility	Repository name: Mendeley DataData identification number: DOI:10.17632/zg27cgxk4p.2Direct URL to data: https://data.mendeley.com/datasets/zg27cgxk4p/2

Value of the data• The chemistry of groundwater is a determining factor for its uses in different water sectors: water supply, agriculture, and industry. Due to the scarce information available regarding groundwater data in the area, the provided data can enable the authorities to pinpoint the main water quality issues as well as to undertake precautionary measures. • The target communities of this data are the organizations that are continually making decisions on water quality issues, including the Water Resources Management Company, Water and Wastewater Organization, Ministry of Agriculture Jihad and the Ministry of Energy. Also, the compiled data can be used in the context of corrosion/scaling and groundwater quality assessment can be generalized around the world. • The dataset can be used for monitoring groundwater quality in Piranshahr Watershed. • Calculated scaling and corrosion indices are pivotal for monitoring water supply distribution networks and industrial utilities. From both economic and health security standpoints, assessing groundwater quality metrics, especially scaling and corrosion, are of great importance, which, in turn, will address the degree to which the suitable management plans are required for preventing economic and health consequences in the future. • Corrosion imposes many financial and health problems respectively on systems and consumers. Scaling, on the other hand, can cause blocking and head loss in the network. Altogether, corrosion/scaling controls are substantial aspects of safe drinking water supplies and other uses in miscellaneous sectors. • The dataset provided in the present work can be rendered into spatial distribution maps of the measured parameters' concentration across the area and also be used for the spatial distribution of groundwater quality across the world.