Deciphering geospatial variations in water quality of a perennial river for human consumption and agricultural application

Water is a crucial natural resource for the survival of all organisms on earth (Shammi et al. 2023; Singh et al. 2024). More than a billion people around the world do not have access to safe water for their daily needs. Every year 6–8 million people die due to water related disease (diarrhea, typhoid, cholera, skin disease, kidney and gastrointestinal disorders) and disasters (Ashrafuzzaman et al. 2023; Guenouche et al. 2024). Surface water is a prime resource required in domestic, recreational, irrigation, fishery and industrial activities (Ravi et al. 2023; Shahmirnoori et al. 2023; Bisht et al. 2024). Fresh water demand is exponentially increasing due to industrialization, intense urbanization, population growth, and agricultural activities (Anwar & Mazhar 2024; Williams 2024). Human actions and natural processes have led to the excessive exploitation of these resources. Water quality easily deteriorates as it acts as a universal solvent. Water can dissolve significant contaminants from agricultural, industrial, and domestic sources (Lata 2021; Yadav et al. 2024a, 2024b). The deterioration of river water quality has become a serious global issue because of anthropogenic (agricultural runoff, municipal waste water, and industrial sewage discharge) and natural activities (flood, weathering of rocks, dust deposition, geochemical variations, lithological interaction) (Akhtar et al. 2021; Wu et al. 2021; Kumar et al. 2024). Water contamination not only affects the quality but also poses a threat to aquatic ecology, human health, and social prosperity economic developments (Dean & Mitchell 2022; Sahoo & Goswami 2024). Thus, continuous spatio-temporal monitoring of water quality can play a crucial role in water resource management and long-term protection of river health. Globally, approximately 70% of surface water resources are used for agricultural purposes, while 10% is used for domestic uses (Amiri et al. 2021). The of Food and Agricultural Organization (FAO 1994) reported that 20% of cultivated land produces 40% of food supply. Therefore, the suitability of river water for domestic and irrigation purposes is essential.

To ensure effective water resource management, it is vital to collect reliable data on river water quality, track spatio-temporal variation, identify contamination sources, assess the state of water quality, and regularly monitor pollution levels (Ustaoglu et al. 2021). Physicochemical indices serve as a supplementary approach to evaluate the water suitability. Various concepts and approaches such as multivariate statistical analysis, principal component analysis (PCA), Pearson correlation coefficient (PCC), WQI, permeability index (PI), Kelly ratio (KR), sodium absorption ratio (SAR), chloro-alkaline indices (CAI), soluble sodium percentage (SSP), and magnesium adsorption ratio (MAR) are broadly used to assess the drinking/irrigational water suitability. The WQI is broadly used for developing plans to manage both groundwater and surface water, particularly rivers (Uddin et al. 2021; Fentahun et al. 2023; Syeed et al. 2023). The computation of WQI considers various physicochemical parameters to effectively convert it into one numeric value to understand the usability for various purposes. Several WQI calculation models have been developed by researchers, however, no method is universally accepted worldwide (Abba et al. 2020; Masoud et al. 2022). The quality of irrigation water has a significant impact on crop growth and yield (Mupaso et al. 2024). As a result, there is an urgent need to increase our understanding about irrigation water quality. The water quality evaluation for irrigation is closely linked to the minerals found in soil, water, and plants (Kareem & Leventeli 2024). These minerals affect the nutrients availability for plants, structure and fertility of the soil, as well as overall health of the agricultural ecosystem (Kome et al. 2019). The minerals such as calcium, magnesium, and sodium also influence soil salinity and the absorption of nutrients by plants. Therefore, it is important to evaluate the mineral content for sustainable irrigation management.

In addition to water quality assessment, many studies focused on the health risks caused river contaminants. Study of river quality with reference to domestic and agricultural use was carried out in distinct regions of the world by researchers (Aminiyan et al. 2018; Uddin et al. 2024). Researchers also evaluated heavy metal pollution indices. Yadav et al. (2024a, 2024b) conducted a study on groundwater in the Basuhi River basin in Jaunpur, India. Abdullah (2013) focused on the Diyala River in Iraq, while Poshtegal & Mirbagheri (2019) examined the Zarrineh River in Iran. Additionally, Mokarram et al. (2020) studied the Kor River in Iran for the health assessment of rivers. Polluted water impacts on human health and aquatic life were also assessed by Okereafor et al. (2020) in mining tailing and Singh et al. (2022) in Kabul River Basin, Afghanistan. However, Basuhi River water suitability for domestic and irrigation needs is necessary considering hydro-chemicals facies.

The present work was conducted for the detailed study of water quality for drinking and irrigational purposes. The research was conducted with the following aims: (1) to evaluate the spatiotemporal variation in physicochemical parameters in the water of Basuhi River using statistical methods; (2) to evaluate the water quality index for water suitability for drinking uses; and (3) to evaluate the agricultural suitability of water by using PI, CAI, SAR, SSP, MAR, and KR. Research findings will provide important information for policymakers working towards the UN Agenda 2030 for restoring the riverine ecosystem.

The water samples were collected from 17 identified locations of Basuhi River pre- and post-monsoon. Sampling sites map along with coordinates is presented in Figure 1. Applying standard sampling procedures, water samples were collected in previously washed 1 L high density polyethylene plastic bottle. Analysis of pH, EC, and DO was carried out instantly at the sampling points using a portable ion meter (Thermo Scientific Orion Versa Star Pro Advance electrochemistry). Subsequently, samples were labeled and kept at 4 °C for laboratory analysis of TH, Na⁺, K⁺, Ca²⁺, Mg²⁺, ⁠, ⁠, Cl⁻, ⁠, F⁻, and ⁠. The analysis of all parameters was done in triplicate and results expressed as average ± SD. Electrical conductivity is the measure of a minerals ability to conduct an electric current, typically influenced by the presence of ions. The electrical conductivity values in water, <250, 250–750, 750–2250, >2250, are considered as excellent, good, permissible, and doubtful, respectively. Dissolved oxygen in surface water is a critical indicator of water quality, reflecting the water's ability to support aquatic life and overall ecosystem health. The dissolved oxygen in river water can be classified as healthy (>8–15 mg/L), contaminated (5–8 mg/L) and highly contaminated (<5). Total hardness is an important parameter for domestic, industrial and agricultural uses. Total hardness is a measure of the concentration of calcium and magnesium ions in water. Total hardness can be classified into four categories: soft (75 mg/L), moderately soft (75–150 mg/L), hard (150–300 mg/L), and very hard (>300 mg/L).

All experiments were conducted using analytical-grade reagents. Physico-chemical characteristics were analyzed by standard methods followed by American Public Health Association (APHA 2017).

The water quality of Basuhi River was also compared with the international standard given by the Food and Agricultural Organization (FAO 1994) for suitability of agricultural use. The Basuhi River water is generally used for irrigation of agricultural lands. Therefore, evaluation of the fitness of water for irrigational uses is very important by using the following indices: PI, SSP, KR, CAI, SAR, and MAR to evaluate the suitability of water for irrigational uses.

The PI is used to evaluate the suitability of water for irrigation, particularly its effect on soil permeability. A higher PI value indicates better water quality for maintaining soil structure and permeability. It is calculated based on the concentrations of sodium, calcium, magnesium, and bicarbonate ions in water (Equation (3)) (all ionic concentrations are expressed in meq/L).

The SSP is used to assess the sodium hazard in irrigational water. It is calculated as the ratio of sodium and bicarbonate to the total cations (sodium, calcium, and magnesium) in the water (Equation (4)) (all ionic concentrations expressed in meq/L).

The descriptive statistical analysis of observed physico-chemical parameters in river water was evaluated using software (PAST 4.3). PCA and PCC were also performed to the find the existing relationship between the parameters and their regulating effects on water quality.

During the experiment, analytical grade chemical/reagent were used for better accuracy and precision. Standard methods were used for water quality analysis given by APHA (2017). Before the physicochemical analysis of water samples, the equipment was standardized with deionized water to ensure accurate results. Blank and replicate readings were also analysed at all sampling locations to ensure quality control assurance (Shammi et al. 2023). These values also were carefully record for identified reference values and exact concentration of the analyzed samples.

The summary of statistical analysis including average, minimum, maximum and standard deviation of analyzed physicochemical parameters in the water of Basuhi River is presented in Table 1. The pH plays a crucial role in measuring quality of water and its impact on human health and aquatic life (Dewangan et al. 2023). The mean pH value at various sampling sites was varied from 7.50 to 9.10 and 6.57 to 8.69 in the pre- and post-monsoon seasons, respectively. The pH value was found beyond the limit (8.5) prescribed by WHO (2017) and BIS (2012) in 58.82 and 5.88% of samples in pre- and post-monsoon season, respectively, probably due to dilution brought about by the surface run off. Noticeably, the pH of the study area in both seasons was found neutral to alkaline in nature. The higher pH at a few locations could be connected with the domestic and industrial inputs. The pH of Kali River varied between 6.93 to 7.43 in the summer and 7.04 and 7.47 in the winter season, similar results were also found by Shukur et al. (2024) in the Tigris River, Iraq. Electrical conductivity (EC) also plays a crucial role in water suitability for domestic and irrigation (Ahmed et al. 2020). EC values in both seasons was obtained in the range of 389–844 and 320.9–856 μs/cm, respectively with corresponding averages of 598 and 433 μs/cm. The measured value of EC at most of the locations fall within the permissible (1,500 μs/cm) and desirable limits (750 μs/cm) of WHO (2017) and BIS (2012), only two (11.76%) water samples exceeded the standard limit (750 μs/cm). Basuhi river falls under type 1 water class on the basis of observed EC values with low salt enrichment.

Table 1

Mean concentration of physicochemical parameters

Parameters .	Mean ± SD .		Max .		Min .		FAO .	WHO (2017)  .		BIS (2012)  .
	Pre .	Post .	Pre .	Post .	Pre .	Post .		Highest permissible .	Max. desirable .	Highest permissible .	Max. desirable .
pH	8.52 ± 0.42	8.01 ± 0.46	9.1	8.69	7.5	6.57	6.5–8.4	6.5–9.2	7.0–8.5	6.5–8.5	N.R.
EC	598 ± 118	433 ± 165.29	841	856	389	320.9	3,000	1,500	750	–	–
DO	5.29 ± 0.97	7.10 ± 1.19	8	9.33	4	4.48	NA
TH	172.4 ± 33.30	183.53 ± 68.95	245	412	95.5	76	200–500	500	100	600	200
Na+	11.36 ± 4.34	12.81 ± 5.83	23	28.1	4.1	6.3	0–920	200	50	–	–
K+	2.37 ± 1.85	3.08 ± 1.76	7.5	7.8	0.85	0.7	NA	200	100	–	–
Ca2+	51.04 ± 30.89	82.52 ± 34.19	112.26	168	12.26	46.2	0–400	200	75	200	75
Mg2+	37.97 ± 21.34	49.91 ± 15.76	87.5	82.56	13.7	8.8	0–60	150	30	100	30
	62.64 ± 22.66	74.47 ± 31.14	114.5	147	23.5	47	0–610	600	200	600	200
Cl–	24.73 ± 10.22	10.09 ± 5.24	51.98	24.026	12	4.004	0–1,065	600	250	1000	250
	84.17 ± 44.28	84.39 ± 43.58	169.15	178.82	11.60552	19.3	0–960	600	200	400	200
	0.52 ± 0.28	1.32 ± 1.23	1.159	3.613	0.198	0.0123	NA
F–	0.40 ± 0.14	0.532 ± 0.174	0.71	0.95	0.19	0.32	NA	1.5	0.6–0.9	1.5	1
	3.01 ± 1.64	1.763 ± 0.83	8.765	3.8	0.355723	0.48	0–10	50	–	N.R.	45

Parameters .	Mean ± SD .		Max .		Min .		FAO .	WHO (2017)  .		BIS (2012)  .
	Pre .	Post .	Pre .	Post .	Pre .	Post .		Highest permissible .	Max. desirable .	Highest permissible .	Max. desirable .
pH	8.52 ± 0.42	8.01 ± 0.46	9.1	8.69	7.5	6.57	6.5–8.4	6.5–9.2	7.0–8.5	6.5–8.5	N.R.
EC	598 ± 118	433 ± 165.29	841	856	389	320.9	3,000	1,500	750	–	–
DO	5.29 ± 0.97	7.10 ± 1.19	8	9.33	4	4.48	NA
TH	172.4 ± 33.30	183.53 ± 68.95	245	412	95.5	76	200–500	500	100	600	200
Na+	11.36 ± 4.34	12.81 ± 5.83	23	28.1	4.1	6.3	0–920	200	50	–	–
K+	2.37 ± 1.85	3.08 ± 1.76	7.5	7.8	0.85	0.7	NA	200	100	–	–
Ca2+	51.04 ± 30.89	82.52 ± 34.19	112.26	168	12.26	46.2	0–400	200	75	200	75
Mg2+	37.97 ± 21.34	49.91 ± 15.76	87.5	82.56	13.7	8.8	0–60	150	30	100	30
	62.64 ± 22.66	74.47 ± 31.14	114.5	147	23.5	47	0–610	600	200	600	200
Cl–	24.73 ± 10.22	10.09 ± 5.24	51.98	24.026	12	4.004	0–1,065	600	250	1000	250
	84.17 ± 44.28	84.39 ± 43.58	169.15	178.82	11.60552	19.3	0–960	600	200	400	200
	0.52 ± 0.28	1.32 ± 1.23	1.159	3.613	0.198	0.0123	NA
F–	0.40 ± 0.14	0.532 ± 0.174	0.71	0.95	0.19	0.32	NA	1.5	0.6–0.9	1.5	1
	3.01 ± 1.64	1.763 ± 0.83	8.765	3.8	0.355723	0.48	0–10	50	–	N.R.	45

Note: Results are expressed in mg/L except pH and EC (μs/cm).

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The DO is the most important parameter in the surface water bodies for the survival of aquatic life (Guemmaz et al. 2020). The concentration of DO in Basuhi River was found between 4.12 and 8.30 and 4.48 and 9.33 mg/L during pre- and post-monsoon, respectively, whereas the corresponding average was 5.29 and 7.10 mg/L. The DO value in six (35.29%) samples in pre-monsoon and two (11.75%) samples in post-monsoon season were found lower than 5 mg/L. Highest DO was observed at S3 (8.30) during pre-monsoon and S14 (9.33) during post-monsoon while it was lowest at S13 (4.12 mg/L) during pre-monsoon and S8 (4.48 mg/L) in post-monsoon season. High temperatures, rapid organic matter decomposition, and sluggish water flow contributed to reduced DO levels in the water during pre-monsoon, while higher DO levels were observed during the post-monsoon season, attributed to the cooler temperatures (Patel & Parikh 2013). The DO levels lower than 8 mg/L can affect the physical and biological processes in aquatic ecosystems and <5 mg/L represents the highly contaminated category of water. The DO level in the present study indicated that the river water is ‘healthy’ to ‘highly contaminated’.

Total hardness of the water is an indicator of usability of water, whether for domestic, industrial or agricultural purposes. Total hardness in water is generally found due to dissolved minerals, magnesium and calcium ions (Ustaoğlu et al. 2020). The investigated mean value of TH varied between 95.5 to 245 and 76 to 412 mg/L in both seasons and the corresponding averages were 172.4 and 183.53 mg/L. Total hardness in all locations in both seasons was found to be above the recommended limits given by WHO (2017) and BIS (2012). Based on the TH classification as given by Tiwari et al. (2017), 82.35% of samples in pre-monsoon and 87.23% of samples post- monsoon were found to be ‘hard’ water type. Prolonged exposure to hard water may elevate the risk of certain cancers, anencephaly, urolithiasis, prenatal mortality, and cardiovascular disease (Li et al. 2022). Analyzed physicochemical data with standard deviation (n = 3) in both seasons are provided in Supplementary material, Tables S2 and S3.

Physicochemical parameters such as pH, electrical conductivity, dissolved oxygen, and total hardness in the Basuhi River reveal significant seasonal variations. The pH and electrical conductivity limits were exceeded in most samples during the pre-monsoon season, likely due to the prevalence of hard water.

Dissolved Ca²⁺ and Mg²⁺ were found below the highest permissible limit prescribed by WHO (2017). Ca²⁺ exceeded the maximum desirable limit in four (23.52%) samples in pre-monsoon and 7 (41.17%) samples in post-monsoon season, whereas, Mg²⁺ concentration in nine (52.94%) and 16 (94.11%) samples exceeded the maximum desirable limit (30 mg/L) pre- and post-monsoon, respectively. Highest concentrations of Ca²⁺ and Mg²⁺ were found at S16 and S4 in pre-monsoon, whereas in post-monsoon season, the highest concentration was recorded at S4 and S2. Consumption of demineralized (lack of calcium, magnesium, sodium, etc.) water was found to be associated with brittleness of nails, headache, nausea, leg and abdominal cramps, whereas higher concentrations of calcium and magnesium can cause urolithiasis, anencephaly, prenatal mortality, and certain types of cancer (Li et al. 2022). The weathering of carbonate rocks accounts for two-thirds of the Ca²⁺ in river water (Wang et al. 2021a, 2021b). The Basuhi River has an oversupply of calcium over magnesium due to the weathering of sedimentary rocks that contain a high proportion Mg²⁺ and Ca²⁺. Similar trends were also observed by Wang et al. (2021a, 2021b). Weathering of carbonate rocks contributed to high calcium levels. Elevated Ca²⁺ and Mg²⁺ at certain sites were attributed to agricultural runoff and industrial effluents, with potential health risks including urolithiasis and prenatal mortality (Li et al. 2022).

The higher levels of Na⁺ and K⁺ in river water are primarily due to the weathering of silicate minerals and rainfall. Sodium and potassium concentration at all the locations and in both the seasons was found higher than the recommended limit given by WHO (2017) and BIS (2012). Higher sodium intake in the human body adversely affects the heart, blood pressure and kidney failure, whereas higher K⁺ consumption can reduce blood pressure (Kogure et al. 2021). Sodium enters water as a result of the weathering of rocks and soil. Sodium compounds are highly soluble and do not form precipitates like Ca²⁺ and Mg²⁺ (Ravi et al. 2023). Sodium rich water can engage in acid base-exchange reactions and replace other ions in minerals present in clay soil. Potassium and sodium behave differently during base-exchange processes; sodium stays in water for a long period, whereas K⁺ participate in the weathering of soil and clay minerals (Zhao et al. 2023). Elevated sodium levels pose risks to human health, including heart and kidney issues, while higher potassium intake may lower blood pressure (Kogure et al. 2021).

The anionic abundance was found in the order of (45%) > (39%) > Cl⁻ (14) > (<1%) > F⁻ (<1%) and (49%) > (43%) > Cl⁻ (6%) > (1%) F⁻ (<1%) during pre-monsoon and post-monsoon, respectively (Figure 2). The anions ⁠, ⁠, Cl⁻, ⁠, F⁻, and during pre-monsoon season was found in the range of 23.5–114.5, 1–51.98, 11.60–169.15, 0.198–1.598, 0.19–0.71 and 0.35–8.76 mg/L and during post monsoon period it ranged between 47–147, 4–24.02, 19.3–178.82, 0.012–3.61, 0.32–0.95, and 0.048–3.8 mg/L. Noticeably, ⁠, Cl⁻, ⁠, and were found the within the permissible limits recommended by WHO (2017) and BIS (2012).

Bicarbonates are indirectly generated in the form of CO₂ by the respiration process in rivers. The obtained bicarbonate levels may be attributed to the respiration of aquatic life and irrigation with calcium rich water (Naorem et al. 2022). find its entry into the river mostly through the weathering of rocks (gypsum and anhydrite) in the river basin, besides biodegradation of organic matter and precipitation. The higher sulphate concentration may cause diarrhea and dehydration in human (Sharma & Kumar 2020). The anion composition of the Basuhi River was dominated by and in both pre- and post-monsoon seasons, because of weathering of rocks and biodegradation processes (Sharma & Kumar 2020). Bicarbonate levels in water are linked to aquatic respiration and calcium-rich irrigation (Naorem et al. 2022).

The Cl⁻ content in river water is mainly assigned to precipitation, halite deposit dissolution, and runoff from cities and farms. The elevated content of chloride in water can be toxic to aquatic life and inhibits vegetation growth (Parveen et al. 2022).

Mineral weathering (fluorspar, apatite, and fluorite), as well as sewage and biomedical waste discharge, mostly contribute to F⁻ levels in water. Fluoride is an essential micronutrient at 0.5–1.5 mg/L, but higher levels can cause dental and skeletal fluorosis in humans (Makete et al. 2022). Fluoride concentration in water samples was found below 1.5 mg/L at all locations.

Phosphates play a crucial role in aquatic ecosystems by serving nutrients for the growth of plant and algae. The concentration was found to be greater than 0.3 mg/L at all the sampling sites in both the seasons except at two sampling stations during pre-monsoon. Higher phosphate concentration is mainly due to agricultural runoff and wastewater discharge in river water (Neal et al. 2010). Phosphate-rich agricultural fertilizers and household detergents can contribute PO₄⁻ in water, which causes eutrophication in surface water bodies (Fadiran et al. 2008). Higher Cl⁻ concentrations in river water, primarily due to urban runoff and halite dissolution, pose risks to aquatic life (Parveen et al. 2022). More than 0.3 mg/L phosphate concentration at most of the sites is probably due to agricultural runoff, contributing to eutrophication (Fadiran et al. 2008; Neal et al. 2010).

Calcium, magnesium, bicarbonate, and sulphate ions dominated pre- and post-monsoon seasons. This significant seasonal variation in ions concentration is linked to weathering, agricultural runoff, and industrial effluents, with a notable oversupply of calcium and magnesium posing potential health risks. The findings provide critical insights into the anthropogenic impacts on ion dynamics and their implications for water quality and human health in the river basin.

The ions concentration was found within the limit of FAO (1994) except pH & Mg²⁺ in both seasons, indicating that at present the quality of water is fit for irrigational use.

Several indices (NPI, PI, KR, SSP, SAR, CAI, and MAR) were used to evaluate the applicability of river water for irrigational use using concentrations of ⁠, Cl⁻, Na⁺, K⁺, Ca²⁺ and Mg²⁺ ions (Table 2).

Prolonged use of ion rich water in agriculture adversely affects the soil permeability. The PI was calculated taking consideration of the Ca²⁺, Mg²⁺, Na⁺, and concentration in river water (Shammi et al. 2023). Water having PI ≥ 75% is considered suitable and lower than 25% is regarded as unfit for irrigation. Doneen (1964) classified the PI in three classes; class I, II and III (Supplementary material, Table S1). The PI during pre-monsoon falls in classes I and II, while the post-monsoon season falls in only class I, i.e. suitable for irrigational use. High bicarbonate and sodium ion in water is directly related to the PI due to exchange of carbonate dissolution (Xu et al. 2019). Shammi et al. (2023) also highlight the impact of ions on soil permeability, underscoring the importance of managing bicarbonate and sodium concentration in agricultural water.

The KR represents the abundance of Na⁺ against Ca²⁺ and Mg²⁺. The KR is another criterion for evaluating water suitability for irrigation applications, KR >1 characterizes unsuitability of water due to excess sodium, whereas water having KR <1 is considered suitable for irrigation (Hoque et al. 2022). The KR value varied between 0.03–0.73 and 0.04–0.21 during pre- and post-monsoon seasons, respectively. KR of all the water samples indicates their suitability for irrigational application. Ravi et al. (2023) found similar results of KR (0.03 to 0.18) while working on Ghaghra River, India. The lower KR values reflect an appropriate balance of sodium relative to calcium and magnesium, reducing the risk of soil degradation due to excess sodium (Hoque et al. 2022).

The MAR has been conventionally used to quantify the negative impacts of magnesium on agricultural water. MAR is calculated by considering the Ca²⁺ and Mg²⁺ concentration in water. In pre-monsoon season the MAR value of Basuhi River was found to be 22.61–86.23, whereas in post-monsoon it was recorded as 11.57–51.71 with corresponding mean values of 44.05 and 38.26. MAR of 23.52% water samples during pre-monsoon was found to be >50 and was found to be unsuitable for irrigation, whereas during post-monsoon only one (5.88%) sample was found unsuitable. Raghunath (1987) emphasized that high MAR negatively affects crop yields and increases soil alkalinity, consistent with findings in other agricultural regions.

The CAI in irrigation studies assesses the proportion of chloro alkanes present in environmental samples to determine the level of contamination. High CAI values may indicate pollution from industrial and agricultural activities, potentially threatening soil health, crop quality, and groundwater resources. This contamination can have significant implications for agricultural sustainability and food safety.

The CAI gives the information about ion exchange between water and rocks. It considers the ion exchange between K⁺, Na⁺ with Mg²⁺ and Ca²⁺. The positive value of CAI implies that the Na⁺/K⁺ exchanged with Ca²⁺/Mg²⁺, while negative values exhibit Ca²⁺/Mg²⁺ exchanged with Na⁺/K⁺ (Shamsuddin et al. 2019). The range of CAI was found to be −1.11 to 0.80 and −2.44 to 0.18 during pre- and post-monsoon season, respectively. In pre-monsoon season the CAI value at all the studied locations was found to be positive except at S6 (–1.11). These negative results may be due to the presence of calcite and dolomite minerals on the riverbed or the surrounding geology which enhances calcium/magnesium concentration, whereas in the post-monsoon the CAI value at all locations was found to be negative except at S16 (CAI = 0.18). This can occur due to sodium/potassium rich minerals (feldspars) and other anthropogenic sources of Na⁺ and K⁺. During pre-monsoon season the majority of samples have CAI values representing cations exchange (Na⁺/K⁺ exchange with Ca²⁺/Mg²⁺), whereas in post-monsoon 95% of the samples showed negative CAI values, which indicates the rigorous involvement of cations (Ca²⁺/Mg²⁺ replaced with Na⁺/K⁺) in the ion exchange process. It has been reported that the concentration of alkaline earth metals (Ca²⁺ + Mg²⁺) is inversely related to the levels of alkali metals (Na⁺ + K⁺) (Abugu et al. 2021).

The SAR is a key factor used for the evaluation of appropriateness of water for irrigation (Kadri et al. 2022). It is calculated by considering the concentration of Na⁺, Ca²⁺ and Mg²⁺ in water. The SAR predicts the hazard in soil and plants due to higher sodium contents in the water. Higher sodium concentrations in water can inhibit the absorption of water by plants and soil permeability (Gautam et al. 2023). Based on the SAR score, water can be classified as ‘good’ (0–6), ‘doubtful’ (6–9) and ‘unsuitable’ (>9) for irrigation. The SAR values in the present study were found in the range of 0.8–8.24 and 1.06–3.88 during pre- and post-monsoon seasons, respectively. SAR score at all the sampling sites fell under the ‘good’ category except at one location during pre-monsoon (SAR = 8.24) representing its suitability for a wide range of crops (Tsado et al. 2014). The findings aligned with the study conducted by Kadri et al. (2022) and Gautam et al. (2023), which emphasize the negative impact of high sodium levels on soil and plant health.

The sodium concentration is essential for determining the water suitability for irrigational use due to its reactivity and influence on soil permeability and structure. Na⁺ levels in water are usually expressed in soluble sodium percentage (SSP) and percentage sodium (%Na). SSP was calculated using the formula given by Wilcox (1955) and Richards (1954). On the basis of percentage, sodium in irrigation water can be classified as ‘unsuitable’ (>80), ‘doubtful’ (60–80), ‘permissible’ (40–60), ‘good’ (20–40), and ‘excellent’ (<20). In the present study, SAR values during the pre-monsoon season were categorized as good (82.35%), permissible (11.76%), and excellent (5.8%), while during the post-monsoon season, all sampling locations were classified as excellent category, probably due to the addition of fresh water due to rainfall. The influx of fresh water reduces sodium concentrations and improves soil permeability (Kumar et al. 2021).

The NPI is used to measure possible combined effects of phosphate and nitrate on the ecological health of the river. This makes it easier to quickly evaluate the overall surface water quality. The calculated value of NPI is displayed in Table 3. NPI of river water during pre-monsoon season ranged between 0.10–0.28 (mean = 0.16), whereas in post-monsoon it was found to be 0.02–0.74 (mean = 0.29). The NPI value in both the seasons was found to be less than 1, representing the low nutrient load in the Basuhi River (Table 3). The highest value, i.e. 0.74, was found at S4 during post monsoon. The mean NPI in various water bodies was reported as five with seasonal variations of 1.58 and 8.2 during the dry and wet seasons, respectively (Isiuku & Enyoh 2020), whereas El Mountassir et al. (2022) observed NPI in the range of −0.9 to 7.8 while analyzing ground water.

Pearson correlations between analyzed parameters were determined using SPSS software at 0.01 and 0.05 significant levels, while PCA was applied for source identification.

PCA is used to transform raw variables into new, uncorrelated variables called principal components, which are linear combinations of the original variables. It simplifies the original data into integrated variables known as principal components (PCs) (Ustaoğlu & Islam 2020). The PCA is a data reduction approach that employs correlation analysis to reduce numerous potentially linked small numbers of uncorrelated variables known as principal components or factors. In the present study, PCA was performed using 14 physicochemical parameters at 17 locations to find out probable sources that influence the quality of water. Based on an eigenvalue of >1, four PCs were extracted in both the seasons. The variance of PC1, PC2, PC3, and PC4 was found to be 96.75 and 98.68% during pre- and post-monsoon, respectively. Liu et al. (2003) classified three factors based on loading values such as ‘weak’ (0.50–0.30), ‘moderate’ (0.75–0.50), and ‘strong’ (>0.75). The eigenvalue and percent variance of the four extracted PC of both seasons are summarized in Supplementary material, Table S4. During pre-monsoon season PC1 exhibited strong positive correlation with EC (0.97), PC2 with SO⁴⁻ (0.97), PC3 moderate positive correlation with TH (0.74) and negative correlation was found with Ca²⁺ (−0.58), PC4 was found moderately correlated with TH (0.63) and Ca²⁺ (0.65). In the post-monsoon season, PC1 and PC2 showed similar positive correlation with EC (0.92) and (0.93), respectively. PC3 was found to be strongly correlated with TH (0.82) and PC4 with (0.88). The prime sources of and are livestock dung and fertilizer containing agricultural runoff from surrounding areas (Kim et al. 2023). It has been demonstrated that sodium-potassium and calcium-magnesium have similar origins and good homology. Cl⁻ displayed weak negative loading, which suggests that anthropogenic activities have produced a significant amount of non-biodegradable trash. presence may be caused by detergent discharges in industrial effluents and municipal sewage (Igbinosa & Okoh 2009).

The seasonal variations in ion concentrations, particularly higher calcium, magnesium, and chloride levels, highlight the need for regulations on agricultural runoff and industrial effluents, especially pre-monsoon. Promoting sustainable farming practices, such as reducing phosphate-rich fertilizers, could help prevent nutrient loading and eutrophication. Public awareness campaigns on the risks of hard water and promoting water softening in affected areas are essential health interventions. Enhancing water treatment infrastructure in industrial and agricultural zones, along with continuous water quality monitoring and stricter enforcement of WHO (2017) and BIS (2012) standards, is crucial for long-term water quality management.

Surface water serves as a major source to fulfill irrigational needs and is a key component in groundwater recharge. Water quality of Basuhi River was analyzed to determine its fitness for domestic and agricultural usages. Findings demonstrated the abundance of cations in the order of Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ during pre-monsoon and post-monsoon, whereas anionic abundance was found in the order of in both seasons. Anthropogenic inputs and chemical weathering may be held responsible for the observed ionic activities. Obtained WQI inferred the water quality variation from ‘moderate’ to ‘very poor’ category. Various irrigation suitability indices (PI, KR, SSP, SAR, CAI, and MAR) revealed that the majority of the samples are fit for irrigational uses. Multivariate approaches like PCA and CA were found to be effective and realistic in evaluating spatiotemporal changes in water quality and in detecting contamination sources. It is possible to reduce pollution from non-point sources by building wetlands, buffer strips, retention ponds, and sediment fences. Regular monitoring is recommended to avoid future toxicity chances. Findings shall be useful in determining the future costs of current/proposed development programs around the river basins.

The authors express gratitude to the Head of the Department of Environment Science at Babasaheb Bhimrao Ambedkar University (BBAU), Lucknow, for generously providing laboratory facilities.

Aneet Kumar Yadav: conceptualization, formal analysis; Monu Kumar: interpretation; Anita and Kamla Pat Raw: statistical analysis; Narendra Kumar: conceptualized, overall guidance and manuscript corrections.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.