Open AccessArticle

A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan

Ali Muhammad

^1,2,3

Donghui Shangguan

^1,2,3,*

Ghulam Rasool

⁴,

Amjad Ali Khan

^1,2,3

Asim Qayyum Butt

^1,2,3

Ayesha Hussain

⁵ and

Muhammad Ahsan Mukhtar

^1,2,3

Northwest Institute of Eco-Environment and Resources (NIEER), Chinese Academy of Sciences, Lanzhou 730000, China

University of Chinese Academy of Sciences, Beijing 100049, China

China-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad 45320, Pakistan

⁴

Department of Chemistry, Quaid-i-Azam University Islamabad, Islamabad 15320, Pakistan

⁵

Department of Economics, Government College Women University, Faisalabad 38000, Pakistan

Author to whom correspondence should be addressed.

ISPRS Int. J. Geo-Inf. 2024, 13(11), 393; https://doi.org/10.3390/ijgi13110393

Submission received: 25 August 2024 / Revised: 27 October 2024 / Accepted: 30 October 2024 / Published: 2 November 2024

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Abstract

Surface water quality in Skardu, Gilgit-Baltistan, Pakistan, is of immense importance because of the city’s dependence on these resources for domestic uses, agriculture, and drinking water. The water quality index (WQI) was integrated with the Geographic Information System (GIS) to spatially envision and examine water quality data to facilitate the identification of pollution hotspots, trend analysis, and knowledge-based decision-making for effective water resource management. This study aims to evaluate the physiochemical and bacteriological parameters of the Satpara watershed and to provide the spatial distribution of these parameters. This study endeavors to achieve Sustainable Development Goal 6 (SDG 6) by identifying localities with excellent and unfit water for drinking, sanitation, and hygiene. A total of fifty-one surface water samples were collected from various parts of the Satpara watershed during the fall season of 2023. Well-established laboratory techniques were used to investigate water for parameters like Electrical Conductivity (EC), pH, turbidity, total dissolved solids (TDSs), major cations (

K^{+}

{Na}^{+}

{Mg}^{2 +}

{Ca}^{2 +}

), major anions (

{Cl}^{-}

{SO}_{4}^{2 -}

{NO}_{3}^{-}

{HCO}_{3}^{-}

), and bacteriological contaminants (E. coli). Spatial distribution maps of all these parameters were created using the Inverse Distance Weighted (IDW) technique in a GIS environment. A significant variation in the quality of water was observed along the study area. The level of Escherichia coli (E. coli) contamination is above the permissible limit at various locations along the watershed, making water unsafe for direct human consumption in these areas. Some regions showed low TDS values, which could adversely affect human health and agricultural yield. From the WQI valuation, 58.82% of the collected samples were “Poor”, 31.8% were “Very poor” and 9.8% were found to be “Unfit for drinking”. The research findings emphasize the pressing need for consistent monitoring and adoption of water management strategies in Skardu City to warrant sustainable soil and water use. The spatial maps generated for various parameters and the water quality index WQI offer critical insights for targeted intercessions.

Keywords:

water quality index; ArcGIS; interpolation; physio-chemical; bacteriological

1. Introduction

Earth and environmental sciences have a strong connection between them, and it becomes significant when humans change the natural ecosystem during their development [1]. Clean drinking water is the smallest portion of the Earth’s surface total water that is being polluted due to the world’s rapidly growing population [2]. Water, however, also serves as a passive carrier for a variety of creatures, such as bacteria, viruses, and protozoa, which can infect humans and cause disease [3]. Water quality degradation, caused by exceptional population, industrialization, and urbanization, has been a major concern for several decades. Point and non-point sources of pollution, such as wastewater discharge, sewerage discharge, cattle waste, urban runoff, agricultural wastes, etc., have resulted in deteriorated water quality [4]. As per available literature, 12,000,000 m³ per day of fresh drinking water is required for the entire global population if every person consumes 2 L per day. In such a way, the annual demand for fresh water for the entire global population comes out to be 5000 to 6000 m³. However, according to WHO, the hydrosphere contains 1.4 billion cubic kilometers (km³) of water, of which 97% is seawater and 3% is freshwater (2.38% glaciers and icecaps, 0.397 groundwater, 0.222 surface water, and 0.001 atmospheres). Unfortunately, due to the unavailability of fresh drinking water, about 1.7 million annual deaths have been recorded due to waterborne diseases [5].

Future water demand is assumed to be strongly associated with the values and lifestyle of future generations [6]. Moreover, freshwater aquifers, lakes, and all other water sources are becoming polluted due to the abruptly rising population and anthropogenic activities causing severe problems. Rough estimates have shown that almost 1.7 billion people live in water-stressed countries [7]. Most of the health problems in developing countries are either due to the scarcity or quality degradation of potable water [8]. However, SDG 6 ensures the provision of fresh, clean drinking water for the public.

According to the World Health Organization (WHO) 2014 records, 844 million people are deprived of essential drinking water, including a surface water-dependent population of 159 million [9]. Globally, two billion people were estimated to drink polluted water with feces. Filthy water could contribute to the spread of epidemics like cholera, dysentery, schistosomiasis, polio, etc. Moreover, contaminated drinking water is reported to cause 502,000 deaths each year due to diarrhea [10]. Gastroenteritis is the main cause of illness in humans globally due to the consumption of contaminated water. Physiochemical parameters, i.e., calcium, potassium, magnesium, zinc, iron, etc., are important for the human body, but in a specific amount; if the amount is exceeded, it leaves toxic effects on human life [11].

Pakistan, the fifth largest population in the world, is one of the developing countries [12]. Contaminated water is reported to be responsible for 30% of all health problems and 40% of total mortality [13]. By adopting the Sustainable Development Goals (SDGs) as the country’s national development plan through a unanimous National Assembly Resolution in 2016, Pakistan affirmed its dedication to the 2030 plan for sustainable development. Through a National Assembly Resolution, Pakistan became the first nation in the world to include the SDGs in its national development strategy [14]. Due to the unsuitable and inadequate sanitation system, a more significant share of the budget must be invested for better management and life surveillance. The use of open and shared toilets due to lack of resources and awareness may cause severe health issues [15].

The main three sources of potable water in Gilgit-Baltistan are streams, springs, and rivers. However, in winter, the flow accumulation of surface water decreases due to the slow melting of glaciers or snow [16].

Satpara Lake is the most important water source available to the people and biodiversity of Skardu City. Poor sanitation systems, absence of wastewater treatment facilities, and lack of awareness result in pollution of the watershed, consequently harming public health in Skardu City [17]. In the study area, microbial contamination is a foremost risk for waterborne diseases. Furthermore, potable freshwater reservoirs over here are not properly protected [13].

The water quality of a specific area and source can be identified with the help of field surveys and laboratory analysis by analyzing physiochemical and bacteriological parameters. In the current study, pH and salinity were analyzed with a Hach Lange sensION 156 multiparameter device. TDS and chloride were analyzed through gravimetric and argentometric procedures [18]. The EC and pH values were measured onsite, while soluble cations and anions (bicarbonate, carbonate, calcium, magnesium, and chloride), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC) were analyzed following respective protocols as described by Richards 1954 [19].

The identified results can later be interpreted using the WQI to describe the suitability of clean water consumption. WQI is a very effective method to describe water quality in different ways for drinking and other purposes [20]. Geospatial mapping makes it easier to understand the quality of drinking water in various localities. GIS is the best-suited mapping, analyzing, retrieving, and data manipulation software for assessing and representing water quality vulnerability through maps [21].

Various previous researchers combined water quality with GIS techniques such as IDW and Kriging for the assessment of surface as well as groundwater quality mapping.

Azhari et al., 2023 assessed the surface water quality of Oued Laou Mediterranean Watershed, Morocco, using WQI integrated with Multivariate Statistical Analysis (MSA) and GIS [22]. Similarly, Azzirgue et al., 2022 evaluated groundwater quality in the Jouamaa Hakama Region (North of Morocco) using WQI and the Fuzzy Logic Method [23]. In Gilgit-Baltistan, Principal Component Analysis (PCA) and WQI have been used for the geospatial analysis of drinking water quality in 2022, and the water quality of Chu Tran Valley Shigar was instigated using geospatial analysis through the IDW technique in 2022, and the water quality index of Chapurson Valley Hunza was evaluated in 2023 by Fatima et al. [24,25,26]. The water quality of Skardu District has been investigated by Ahsan et al. using the WQI in 2021 [27]. The water quality of natural springs and surface water was investigated by Hussain et al. in Gilgit-Baltistan for health risk assessment in 2022 [16]. Lodi et al. evaluated drinking water quality in the Skardu-Northern Area concerning heavy metals in 2003 [28]. The water quality status of upper KPK and Skardu Northern Areas was investigated in Malik et al. in 2010 [29]. The water quality status of natural springs and surface water in Gilgit-Baltistan was investigated by the GB Government [30]. However, there was no such detailed study related to geospatial analysis of surface drinking water quality within Satpara Watershed due to kit topographical locality, hard accessibility to Deosai top, and harsh weather.

Keeping the above important facts in view and focusing on SDG 6, the objectives of the current research were to determine the physio-chemical and bacteriological contamination and assess the water quality of Satpara Watershed by using WQI and GIS techniques to ensure whether the water is suitable for drinking and agricultural purposes or unsuitable with health-related hazards. The current study is most significant to enable the public and private management authorities and the concerned public to improve decision-making and inflexible monitoring of the distribution of contamination into a healthy environment. The geospatial mapping will identify the point and non-point sources of pollution to be aware of the above-mentioned concerns. The surface water quality in Skardu, Gilgit-Baltistan, Pakistan, is of immense importance because of the city’s dependence on these resources for domestic uses, agriculture, eco-systems and biodiversity, drinking water, and climate vulnerability. Furthermore, GIS mapping and temporal water quality monitoring can be innovative for tracking the sources of pollutants and the contaminations in the watershed. This research can approach indigenous water management practices with the latest science. Moreover, it is also significant for the safety of public health and plan-makers.

2. Study Area

Satpara watershed is located south of Skardu City, Gilgit-Baltistan, Pakistan. It includes various small tributaries and a natural lake. The government of Pakistan upgraded the lake to a dam. It lies between longitude 75°45′24″ E and latitude 35°17′52″ N at an altitude of 8692.7 feet (2649.5 m) and pounds roughly 90,000 acre-feet (110,000,000 m³) of water [31]. Satpara watershed spreads across an estimated area of 2.5 km². It extends from the Deosai plateau (upstream) to Ranga (downstream), where the stream is drained into the Indus River. Figure 1 provides a map of the channels and tributaries of the watershed. It supplies 3.1 million gallons of potable freshwater and irrigates 15,000 acres (61 km²) of land daily. Satpara Village is located along the Satpara Dam, and most of the inhabitants practice farming and cattle rearing. In the figures given below; Figure 1A is showing Skardu district with provinces of Pakistan and Gilgit-Baltistan districts in the inset, Figure 1B is showing the Satpara Watershed with sampling localities labeled with sample identification numbers 1 to 51 explained in the Appendix A section Table A1, and Figure 1C is showing the town boundaries of the municipal areas and Satapara Watershed, respectively.

The main driving force of the watershed is temperature, wherein flow accumulation within the Satpara stream increases in the summer due to snow melting and decreases in the winter due to frost wedging. The mean daily temperature of the Deosai Plateau ranges from −20 °C in winter to 9 °C in summer, having an annual precipitation of 510 mm–750 mm. The Deosai Plateau is rich in hydrology, with four big water bodies draining three streams into the Sheosar Lake and an extensive marshy basin [32].

Contour lines are extracted from the 30 m Shuttle Radar Topography Mission (SRTM) and the Digital Elevation Model (DEM) acquired from the United States Geological Survey (USGS), and these are significant for measuring the height of any topography shown in Figure 2A. Contour values are changing consistently due to the uneven topography, having a minimum of 7162.07 feet and a maximum of 16,653.5 feet (Figure 2A) from the Chumik desert new city area to the top of the Deosai plateau, like the elevation map (Figure 2C). The slope of the study area varies from 0 to 8 degrees or 0–1.29% (Figure 2B) along Skardu new city Chumik area and Deosai Shatong Nullah adjacent areas; however, the steepest slopes consist of 46–73 degrees or 12–23.5% along Ulding Broq, Grayul Broq, Chundah Broq, and adjacent slopes near Ali Malik area shown in Figure 2B. Elevation varies from 7295 feet (Chumik village) to 13,750 feet (Shatong Nullah Origin). In the elevation difference map, the light to dark brown color shows the height difference from lowest to highest areas. However, the other two maps show the elevation changes through the viewshed, as shown in Figure 2C.

3. Hydrology

The chief water sources in Satpara Lake are natural springs, glaciers, and compacted snow; several small and ordinary-sized perpetual streams; and seasonal tributaries from the Deosai Plateau. The total command area of the watershed is 10,131 acres (41.00 km²), including 8 119 acres (32.86 km²) left and 2012 acres (8.14 km²) right bank canals of Satpara Reservoir. The gross capacity of the reservoir is 0.0932 MAF (93,385 AF). The reservoir’s length, width, and height are 560 ft., 80 ft., and 128 ft., including 59,000 ft. left and 30,000 ft. right bank canal lengths [33]. Peaks upstream remain permafrost for the whole year, excluding the months from July to September. Snowfall starts along most parts of the watershed and on the peaks upstream after September. The average annual precipitation in the study area is 7.40157 inches, or 188.02 mm [34]. Various permafrost sites accrue snow in the winter season, which then melts down in the summer and feeds these minor streams. Due to the uneven and wide-ranging topography and geology, various streams generate their ways to flow into the main watershed. The water level of the watershed rises to its peak in summer, and in winter, it reduces to the bottom. Hardly heavy precipitation causes seasonal flash floods in the area.

4. Geology of the Area

Altered geology (somewhere hard rocks or somewhere soft) of the entire watershed alters the mineral contents while flowing into the Satpara stream. Adjoining parts of the mainstream comprised silty and loamy soil due to the seasonal water channel and glacial activities over the whole watershed except hard rock geology at a few places. The main reservoir on this watershed is Satpara Dam (a natural glacial lake that was upgraded after 2008), a high-altitude dam in the Karakorum Range. However, several tiny and medium-sized lakes exist at the Deosai Plateau. Karakorum mountain ranges have been formed due to the collision of Indian and Asian continental plates along the western terminal of the Trans-Himalayan Mountain Ranges [34].

Satpara Watershed is strongly controlled by tectonic activity because it is concerned with Main Mantle Thrust (MMT), but still, no tectonically formed lake exists there. Skardu Valley and Deosai Plateau exist among Main Karakorum Thrust (MKT) and Main MMT. A parallel formation of the appropriate rock crosses through the Deosai Plateau, and Laddakh ranges from the east of the Nanga Parbat massif. The granitic geomorphology in the Deosai Plateau comprises quartz-dioritic, granitic gneisses, amphibole ± mica diorites, two-mica, aplite pegmatite, and white mica granites [35].

At the northern slope of the Deosai Plateau and south of Skardu, the Shagarthang Sedimentary group (sedimentary and volcanic separate belt) is exposed [36]. Still, another writer considered it the extension of the Burji Formation. He also described that this formation consists of chlorite-epidotic greenschist, phyllites, and slates resulting from volcanogenic deposits and limestone and is reported as an assemblage of upper cretaceous fossils from this formation [37].

However, adjacent valleys have formed with loamy and silty strata due to weathering, erosion, and deposition processes having a more excellent ratio of silt than clay. Satpara Watershed has the lithology of the main Karakorum complex. Adjacent to the dam extent, mostly granodiorite, diorite, hornfels, talc, etc. were found. Hornfels are talc rocks that transformed underwater action for several years. Glacial deposits like Moraines, erratic, and tillites were also found there. Satpara Dam can also be called a moronic earthen dam [38].

5. Materials and Methods

5.1. Sample Collection

Water samples were collected during October and November 2023 from 51 spatial locations with their spatial attributes along Satpara Watershed. All the samples were collected in acid-washed, cleaned, and sterilized polyethylene bottles. Special preventive measures were considered during the collection of samples for bacteriological analysis. Moreover, sample bottles were rinsed three to four times with the water to be sampled before taking every sample. Water taps were heated to a considerable temperature to prevent external contamination before taking samples from houses and ensuring water flow for half an hour. Water samples were taken from the tributaries’ deep areas, the mainstream and dam bodies, and the household water supply of the same watershed. These samples were taken after keeping the water pipes open for approximately half an hour. All the bottles were correctly sealed to prevent evaporation. Special preventive measures were taken to avoid agitation of the samples during their transfer to the laboratory. All the samples were stored at a temperature below 4 °C during laboratory analysis.

5.2. Laboratory Measurements

Physio-chemical and microbial parameters were performed in the Public Health and Engineering Department Lahore, Geochemistry Lab, and University of the Punjab Lahore.

5.3. Physico-Chemical Analysis

All the samples were analyzed for the physio-chemical parameters like (EC), temperature, pH, TDS, total hardness (TH), significant anions like chloride (

{Cl}^{-}

), sulfate (

{SO}_{4}^{2 -})

, bicarbonate (

{HCO}_{3}^{-}

), carbonate (

{CO}_{3}^{2 -}

), and major cations like potassium (

K^{+}

), sodium (

{Na}^{+}

), calcium (

{Ca}^{2 +}

), and magnesium (

{Mg}^{2 +}

) in the laboratory using well-established methods specified by American Public Health Association (AHPA) [18]. Temperature, electric conductivity (EC), and pH were measured on the spot using a portable E.C. meter and pH meter. TDS values were analyzed in mg/L using a consort electrochemical analyzer. Chemical analysis for ions (i.e.,

{Cl}^{-}, {SO}_{4}^{2 -}, {HCO}_{3}^{-}, {CO}_{3}^{2 -}, {NO}_{3}^{-}, {Ca}^{2 +}, {Mg}^{2 +}, {Na}^{+}, {and K}^{+}

were made at water quality testing laboratories Public Health and Engineering Department (PHED), Soil and Water Testing Laboratory (SWTL), and Geochemistry Lab University of the Punjab Lahore. Chloride concentration was determined by titration with 0.02 M AgNO₃ solution using

K_{2} {Cr}_{2} O_{7}

as an indicator. The turbidimetric method was used to determine

{SO}_{4}^{2 -}

concentration.

{HCO}_{3}^{-}

and

{CO}_{3}^{2 -}

concentrations were determined by titrating against a 0.2 N solution of H₂SO₄ employing methyl orange as an indicator. Volumetric titration was used to determine TH using 0.01 M EDTA solution as standard and Eriochrome Black T as an indicator. An inductively coupled plasma (ICP) mass spectrophotometer was used to determine the concentration of the main cations (

{Na}^{+}, K^{+}, {Ca}^{2 +}, {and Mg}^{2 +}

). All other determined concentrations were shown in mg/L, excluding EC and pH. The results were then assessed by drinking water quality standards specified by the World Health Organization [9].

5.4. Bacteriological Analysis

Water quality analysis for bacteriological parameters is handled carefully due to its sensitive nature. Sterilized polyethylene bottles and collected and transported water samples from the field. Town-wise water sampling was performed, and then the samples were carried to the LG and RD water testing laboratories for further analysis. Standard procedures were already reported to be used for bacteriological tests [39].

The membrane filtration method was used to count total coliform. A membrane filter with 0.45 µm (micrometer) pore size was employed to filter 50 mL of sample water. These filter papers were then placed in a culture medium containing m-Endo ager, and then these were incubated at 35 °C for 24 h, followed by an examination of bacterial colonies under a light microscope. Total coliform/100 mL of water was calculated using these results.

5.5. GIS Analysis and GPS

ArcGIS 10.5, Visual Terrain Builder (VTB)_130614, Arc Hydro 10.5, and MATLAB 8.4 R2014b were used to view, interpret, retrieve, analyze, and store data from the topographic sheets into vector layers and the Digital Elevation Model (DEM). The topographic sheets of the study area have a 1:50,000 scale and were prepared by the Universal Transverse Mercator (UTM) coordinate system. The topographic sheets (source: Institute of Geology, University of the Punjab, Lahore, Pakistan) were geo-referenced according to the WGS1984 projected coordinate system. Shuttle Radar Topographic Mission (SRTM) 30 m DEM was downloaded from the USGS website to analyze the surface and 3D analysis of the study area. VTB was used to select and retrieve the required DEM based on our choice. The retrieved DEM was saved into TIFF file format and then added to Arc Map 10.5 and geo-referenced according to WGS1984 for further analysis.

A Global Positioning System (GPS) was used to collect spatial locations of the sampling points. GPS-saved points were uploaded into Arc Map to specify the attributes of the sample points. All the attributes related to the sample points were added to the attribute table in Arc Map.

IDW was used to interpolate the sample points. Interpolation techniques tell about the concentration levels of the pollutants in drinking water. It gives information about the concentration of unknown points with the help of known points [40]. This method generates thematic isohyets of the same quality regions of the watershed. The study area classification map with 13 parameters

({Na}^{+}, K^{+}, {Ca}^{2 +}, {Mg}^{2 +}, {Cl}^{-} {NO}_{3}^{-}, {CO}_{3}^{2 -}, {HCO}_{3}^{-}, {SO}_{4}^{2 -}, pH, and TDS

Hardness, and E. coli) was created based on the World Health Organization, European Union, and United States drinking water quality standards.

5.6. Water Quality Index (WQI)

Horton, 1965 in the United States, developed an index system known as the water quality index, firstly, by selecting the quality characteristics on which the index was based; secondly, by establishing a rating scale for each characteristic; and thirdly, by assigning the weights of the several characteristics [41]. Brown et al. developed the general in 1970, which was later refined by Deininger for the Scottish Development Department in 1975 [42]. Furthermore, this paper follows the previous studies conducted by some researchers at Saveh-Nobaran aquifer, Iran, on groundwater quality assessment in 2014 [43].

Water quality parameters and their corresponding WHO standards were used in this research to calculate the weighted arithmetic index (WAWQI). According to literature by Chaudhari et al., 2022 [44] and Şener et al., 2017 [45], each of the eleven parameters (

{Mg}^{2 +}

{Ca}^{2 +}

K^{+}

{Na}^{+}

{SO}_{4}^{2 -}

{Cl}^{-}

{HCO}_{3}^{-}

{NO}_{3}^{-}

, TDS, E. coli, and pH) were individually assigned weights (w_i) from 1 to 5 concerning their impacts on human health for the estimation of water quality. The highest weights were assigned to E. coli and TDS due to their higher impacts on human health, as mentioned in Table 1 [43,46].

W_{i} = \frac{w_{i}}{\sum_{i = 1}^{n} w_{i}}

(1)

Here, (W_i) is the relation of weight or mass, (w_i) shows the weight of each parameter, and (n) shows the total of parameters [43].

For the calculation and measurement of quality ranking/rating, the concentration of each parameter within each water sample was divided by the National Standards for Drinking Water Quality (NSDWG) [46] and WHO water quality standards for individual parameters in mg/L and multiplied by 100.

The equation for water quality rating is given as follows:

Q_{i} = \frac{C_{i}}{S_{i}} \times 100

(2)

where;

Q_i = Quality rating of ith parameter,

c_i = Concentrating of the sample

For the calculation of sub-index, the following formula was used:

{SI}_{i} = w_{i} \times q_{i}

(3)

where;

SI_i = Sub-index of ith parameter,

w_i = Quality rating of ith parameter

n Total sum of samples

Finally, WQI has been calculated through the following formula:

WQI = \sum_{i = 1}^{n} {SI}_{i}

(4)

The results have been categorized and classified into 5 different classes after calculation for the valuation of excellent water quality zones. These classes are argued in the result section.

Evaluated WQI values are typically categorized into five classes shown in (Table 2), ranging from excellent to unfit for drinking purposes [43]. The estimation method of WQI has been defined by (Pradhan et al., 2001 [47]; Asadi et al., 2007 [48]; Dwivedi and Patha, 2007 [49]; Yidana and Yidana 2010 [50]; Saeedi et al., 2010 [51]; and Sadat-Noori, S. M., et al., 2014 [43]).

Surface water plays a vital role all over the world and in mountainous areas where it is the primary source for drinking water and irrigation sources as well. Keeping this in view, its suitability for drinking purposes was examined properly according to globally recognized and recommended standards shown in Table 1 mentioned above. The following parameters (E. coli, TDS, EC, pH, Hardness,

{Mg}^{2 +}

{Ca}^{2 +}

K^{+}

{Na}^{+}

{Cl}^{-}

{SO}_{4}^{2 -}, {HCO}_{3}^{-}

, and

{NO}_{3}^{-}

) were selected for the preparation of the classification map using point data spatial analysis of GIS.

5.7. Correlation Matric

To develop effective management strategies and to identify key indicators of water quality changes, it is essential to understand the interrelationship between various water quality parameters. In the current research, a correlation matrix was developed to understand the relationships between these parameters, i.e., how a change in one parameter influences others.

6. Results

6.1. Geospatial Variations in Temperature (°C) of Satpara Watershed

The geospatial map Figure 3 shows temperature changes within the study area during the fall season of 2023, where the minimum temperature (−3 °C to 6 °C) and maximum temperature (11 °C to 13 °C) were recorded from along the municipal area, illustrated in gray and red colors, respectively.

6.2. Geospatial Variations in Bacterial (E. coli) Contamination of Satpara Watershed

Bacterial contamination is more common and threatening along surface water bodies. The highest of 8 microbial colonies were recorded nearby to reservoir areas shown in Figure 4. Bacteria are the threatening parameter in water quality among physiochemical qualities. The area becomes prone to pollutants in winter due to a water shortage, and in the summer, reservoirs are accumulated by snowmelt water. Fifty meters from the Gateway Hotel downstream, 5 colonies/100 mL were also found. Under the PTDC Motel, a low risk of 2 colonies/100 mL was recorded, which shows the sewerage infiltration into the reservoir body. A low risk of 1 colony/100 mL was also recorded at Satpara Village. However, the overall microbial contamination risk is low, and the quality of water meets category B shown in (Table 3) according to WHO water quality standards, including the other three categories.

6.3. Geo-Spatial Variations in pH Concentration of Satpara Watershed

pH of water is among the indicators describing its acidic or basic nature. Geospatial variation in pH concentration within the Satpara Watershed ranges from 7.2 to 8.1 with a mean value of 7.6 shown in Figure 5A. Standard values for pH were set by 33 representatives, i.e., the United Nations Development Programme (UNDP), the Pakistan Council of Scientific and Industrial Research (PCSIR), the Pakistan Council of Research in Water Resources (PCRWR), the United Nations Children’s Fund (UNICEF), the Pakistan Standards and Quality Control Authority (PSQCA), the Pakistan Atomic Energy Commission (PAEC), the Pakistan Institute of Science and Technology (PIST), etc., through a workshop by Pakistan Ministry of Health (PMH) and World Health Organization (WHO) staff.

The minimum 7.2 to 7.3 and maximum 8.0 to 8.1 concentration levels of pH were recorded at Tufail Colony, Chumik, and Sundus areas, respectively illustrated in different color ramps. Thus, the pH concentration level meets WHO-prescribed limits for drinking purposes.

6.4. Geospatial Variation in Electrical Conductivity (EC) of Satpara Watershed

The overall concentration level of (EC) in Satpata Watershed is ranging from 67 μScm⁻¹ to 430 μScm⁻¹, with a mean value of 152.1 μS/cm. However, minimum and maximum levels of EC were recorded at Deosai top (67 μScm⁻¹) and spring near Jamia Mosque Skardu (420 μs/cm), illustrated in light gray and red colors in Figure 5B. The overall concentration level of EC is falling within the European Union’s (UN’s) drinking water permissible limits, which show a (2500 μs/cm) concentration level at 20 °C for drinking water.

6.5. Geospatial Variation in Total Alkalinity of Satpara Watershed

The geospatial distribution of total alkalinity falls between 0.5 and 5.00 ppm. The lowest 0.5–0.89 ppm and highest 2.8–5.4 ppm concentration levels were recorded at Deosai top and Chumik areas showing (acidified) and (endangered) natures, respectively. The overall alkalinity concentration level is falling below the WHO and EU’s prescribed permissible limits. For drinking water quality standards, the US EPA has set 6 categories for alkalinity, where the relationship between alkalinity and pH. If the concentration of CaCO₃ is <1 mg/L, then pH will be <5 and acidic, and for <2, 2–5, 5–10, 10–20, and >20 mg/L, alkalinity will be critical, endangered, highly sensitive, sensitive, and not sensitive, respectively. Geospatial variation in the distribution of total alkalinity in Satpara Watershed was recorded at 0.5 to 5.4 ppm, where the lowest concentration was recorded at Deosai Plateau, i.e., 0.5–0.99 (acidified nature), and the highest concentration value was recorded at Chumik, ranging from 5 to 5.4 ppm (overly sensitive), as shown in Figure 6A. However, the saythung to Rangah area’s total alkalinity concentration was falling in the critical condition category [52].

6.6. Geospatial Variation in Bicarbonate Concentration of Satpara Watershed

Geospatial variation in the distribution of bicarbonate ranged between 0 and 6.5 ppm, varying from the Deosai Plateau to the Rangah area, wherein Satapara village and adjoining areas are contributing a greater amount of bicarbonate. However, the lowest concentration (0.6–1.2 ppm) was found in the Deosai Plateau, Saythung, and Hussainabad areas. The maximum concentration (6–6.5 ppm) was recorded in the Chumik area shown in Figure 6B. The overall bicarbonate concentration falls within the WHO and ESDWQ water quality standard limits, having no health-related hazards [53].

6.7. Geospatial Variation in Total Hardness Concentration of Satapara Watershed

Geospatial variation in the TH concentration was found between 30 and 200 mg/L as Calcium Carbonate (CaCO₃). The highest and lowest concentrations were recorded at Deosai Plateau and Chumik areas, i.e., 30 mg/L and 200 mg/L (as CaCO₃), respectively shown in Figure 7A and (Table 4). Overall, Satapara Watershed holds a normal concentration of TH according to WHO and EU’s water quality standards. The US Department of Interior and Water Quality Association has categorized the hardness of drinking water in the following way: if hardness ranges from 0 to 17.1, 17.1 to 60, 61 to 120, 121 to 180, and 180 to over, the hardness is classified as soft, slightly hard, moderately hard, hard, and very, respectively [54].

6.8. Geospatial Variation in TDS Concentration Satpara Watershed

Geospatial variation in TDS concentration ranged from 44 to 280 ppm. The lowest (44–63 ppm) and highest (200–280) concentrations were recorded at Deosai Plateau and Chumik area, respectively shown in Figure 7B. W.H.O. has categorized water quality for drinking purposes according to concentration levels as Excellent, Good, Fair, Poor, and Unfit for TDS less than 300 ppm, 301–600 ppm, 601–900 ppm, 901–1200 ppm, and above 1200 ppm, respectively [55].

6.9. Geospatial Variations in Cations

Cations spatial variability distribution of (

{Mg}^{2 +}

{Ca}^{2 +}

K^{+}

{Na}^{+}

) is shown in Figure 8, where variations in concentrations of

{Mg}^{2 +}

are illustrated in ppm (parts per million). The entire Deosai Plateau to Satpara Gol indicates the lowest concentration of

{Mg}^{2 +}

ranging from 0 to 1.3 ppm, illustrated in gray color in the map. Satpara village and Satpara reservoir show a 1.4 to 2.7 ppm concentration level of

{Mg}^{2 +}

illustrated in green color. Satpara Nullah gorge to Satpara Bridge, and the entire municipal area has a concentration level of

{Mg}^{2 +}

ranging from 2.8 to 4.0 ppm.

Division area and Bazar areas indicate 4.1 to 5.4 ppm

{Mg}^{2 +}

concentration levels illustrated in cyan color. Concentration levels of

{Mg}^{2 +}

along Chumik village range from 5.5 to 6.7; however, the highest concentration of 14 ppm was found in the spring near Jamia Mosque, shown in Figure 8A. The whole Satpara Watershed holds suitable water quality according to

{Mg}^{2 +}

concentration according to the WHO water quality permissible limit, which is 50 mg/L.

Geospatial variations in the distribution of

{Ca}^{2 +}

are illustrated in Figure 8B along the Satpara Watershed. The highest and lowest concentrations of

{Ca}^{2 +}

are 12 ppm and 60 ppm, respectively. Concentration levels along Shatong Nullah, southern side of Deosai Plateau, northern side of Deosai Plateau, Satpara village, reservoir body, Skardu municipal area, Chumik, and spring near Jamia mosque have been recorded as 12 to 16 ppm, 18 to 22 ppm, 23 to 26 ppm, 27 to 31 ppm, 32 to 36 ppm, 37 to 41 ppm, 42 to 46 ppm, 47 to 50 ppm, 51 to 55 ppm, 56 to 60 ppm, respectively, and illustrated in various color ramps. The concentration level of

{Ca}^{2 +}

was recorded within the permissible limits of WHO, which are 75 or 75.086 ppm mg/L recommended as hygienic for drinking purposes.

Potassium (

K^{+}

) concentration varies from 0.4 to 3.9 ppm in Satpara Watershed, illustrated in the geospatial Figure 8C. The lowest concentration of 0.4 to 0.76 ppm was recorded at the south corner of Deosai Plataea, shown gray.

Light brown, blue, and yellow colors represent concentration levels from 0.77 to 1.1 ppm, 1.2 to 1.5 ppm, and 1.6 to 1.8 ppm fluctuating from the entire south-east to south-west hooked on a slender belt beyond Satpara Gol and about 50% south-west area from the reservoir. Satpara village and Pakistan Tourism Development Corporation (PTDC) Motel area is showing 1.2–1.5 ppm concentration. Upper Satpara village near spring has 1.6–1.8 ppm, however. Concentration levels recorded along Sundus, Eid-Gah colony, and Saythung were 1.9 to 2.5 ppm. Whereas the Skardu municipal area has 2.3 to 2.5 ppm and Chumik Village and Khargrong areas have 2.6 to 2.9 ppm concentration levels, respectively. The overall results of

K^{+}

concentration are meeting the quality standards of WHO water quality standard limits, i.e., 12.014 ppm or 12 mg/L.

The geospatial distribution of sodium (

{Na}^{+}

) is illustrated in Figure 8D, with concentration levels varying from 1.0 ppm to 10 ppm. Minimum 1.0 to 1.9 ppm and maximum 8.8 to 10 ppm concentrations were recorded at Deosai Plateau and spring near Jamia mosque Skardu, respectively. Skaru municipal area has 2.6 to 3.6 ppm; Satpara village and Chimk village have 3.7 to 4.4 ppm and 4.5 ppm to 5.3 ppm, respectively. However, the maximum concentration level of 8.8 ppm to 10 ppm was recorded at a spring near Jamia mosque Skardu.

The entire watershed holds good water quality in the case of

{Na}^{+}

concentration according to WHO water quality limits, which range from 250.26 ppm to 250 mg/L [56].

6.10. Geospatial Variations in Anions

Geospatial variation in the concentration of carbonate (

{CO}_{3}^{2 -}

) has been illustrated in Figure 9A within Satpara Watershed, ranging from 0 to 0.005 ppm comprising Shatong Nullah to Satpara Gol and 0.0051 to 0.01 along Satpara village, Satpara reservoir, Bazar, and Aliabad areas. Concentration levels along Khargrong and Chumik, Hammed Garh and Chumik, Jamia Mosque area, Hargisa area, Muhib Line, and Spring near Chumik village are 0.016–0.02 ppm, 0.021–0.025 ppm, 0.026–0.03 ppm, 0.031–0.035 ppm, 0.036–0.04 ppm, and 0.046–0.5 ppm, respectively [57]:

{NO}_{3}^{-}

concentration level of the Satpara watershed has been shown in Figure 9B. Check post area, and Shatong Nullah has the lowest range of

{NO}_{3}^{-}

concentration, ranging from 0.37 to 0.86 ppm. Adjacent areas of Deosai Plateau, Satpara Reservoir, and Hajigam have 0.87 to 0.13 ppm concentration levels of

{NO}_{3}^{-}

. Areas from north to south up to the Division have 1.1–1.2 ppm concentration levels. Skardu City and Satpara Gol have 1.4 to 1.8 ppm concentration levels. While the highest concentration level of

{NO}_{3}^{-}

was found within the spring on the way to Chumik hamlet, ranging from 4.6 to 5.0 ppm. Overall, Satpata Watershed holds suitable water quality according to

{NO}_{3}^{-}

concentration according to WHO water quality standards, which is 50mg/L and has no health-related hazards.

Chloride (

{Cl}^{-}

) concentration is geospatially indicated in Figure 9C. Upstream areas, i.e., Shatong Nullah, Deosai check post place, Manthal to Division, Gulshan e Ali, and Eid Gah Colony (Brolmo Colony), have the lowest level of chloride concentration, fluctuating from 10 to 11 ppm correspondingly. A maximum level of 22 ppm chloride concentration was found along Gateway Hotel’s adjoining areas, although the whole Satpara settlement and Skardu municipal area have 13 to 17 ppm; concentration levels of chloride. Deosai gorge and half of the reservoir have concentration levels of

{NO}_{3}^{-}

from 16 to 17 ppm, however, a large area of Deosai plateau, Manthal village, Ulding, and Eid Gah colony have concentration levels ranging from 12 to 14 ppm, respectively. Spring near Jamia Mosque has a 22 ppm concentration level of chloride. Satpara watershed holds excellent water quality results having chloride (

{Cl}^{-}

) concentration within the standard limits of WHO, which is 250 mg/L.

Sulfate

{SO}_{4}^{2 -}

concentration is shown in Figure 9D with geospatial distribution, ranging from 13–29 ppm, 30–44 ppm, 45–60 ppm, 61–76 ppm, 77–91 ppm, 92–110 ppm, 130–140 ppm, 150–100 ppm, and 160–170 ppm for Shatong Nullah, upper Deosai plain, lower Deosai, gorge, Satpara Gol and Dam center, Satpara spring region, entire Skardu city excluding Aliabad to Chumik and Bazar area, Aliabad and Bazar area, Chumik village, and spring near Chumik village, respectively. The concentration of

{SO}_{4}^{2 -}

was within WHO 1993 and EPA 1998 water quality limits for drinking as well as irrigation purposes ranging from 250 mg/L to 500 mg/L. Satpara watershed holds perfect water quality results for drinking and irrigation purposes, having no health-related hazards.

6.11. Spatial Variation of Sodium Adsorption Ratio

SAR concentration plays a vital role in agricultural practices; however, its excessive concentration affects the prevention of soil by declining the absorptivity or permeability of the soil. The overall concentration of SAR along Satpara Watershed is illustrated in Figure 10, falling within the permissible WHO suggested limit s mentioned in the (Table 5) [58].

The following formula is used for the calculation of Sodium Adsorption Ratio (SAR):

SAR = \frac{{Na}^{+}}{\frac{\sqrt{{Ca}^{2 +} + {Mg}^{2 +}}}{2}}

where;

{Na}^{+}

{Mg}^{2 +}

{Ca}^{2 +}

are the concentrations of sodium, magnesium, and calcium, milliequivalents of charge per liter [19].

6.12. Residual of Sodium Carbonate (RSC)

The quantity of

{HCO}_{3}^{-}

and

{CO}_{3}^{2 -}

^- ions minus

{Ca}^{2 +}

and

{Mg}^{2 +}

ions concentrations provide the concentration level of RSC in me/L, where “me” means milliequivalents. Surplus calcium and magnesium can be expected as carbonate, while in the surplus negative RSC, the growth of sodium is ostensible. However, in the case of positive RSC, sodium growth is possible. The overall RSC results show that the water quality is best suited for agricultural practices according to WHO water quality standards mentioned below in Table 6. Geospatial maps have not been included as the overall value was 0 me/L. The RSC value can be used to determine the quantity of sulfuric acid and gypsum applied per acre-foot of irrigation water for overcoming or neutralizing the residuals of carbonates. The calculation formulas are given below [19].

RSC, {meL}^{- 1} = \frac{({CO}_{3}^{2 -} + {HCO}_{3}^{-}) - ({Ca}^{2 +} + {Mg}^{2 +})}{acre - foot}

6.13. Water Quality Classification of Satpara Watershed

The water quality classification map is prepared with the help of the WQI in Arc Map 10.5. The following Figure 11 shows the classification of drinking water along the Satpara watershed. The quality of the water is poor due to concentrations of sulfate and E. coli with mean values 53.52 ppm and 0.52 Colonies/100 mL, respectively shown in the (Table 7). The upper region contains better quality than the regions near settlements. The spring near the army camp has maximum concentration and contamination, which might be due to the infiltration of effluents from agriculture or households into the subsurface.

6.14. Correlation Analysis of Water Quality

To find out the correlation among physiochemical parameters of drinking water in Satpara Watershed, a statistical method, “Pearson Correlation,” was applied to the representative water samples of the area [59].

For these parameters, physio-chemical parameters such as

{Na}^{+}

K^{+}

{Ca}^{2 +}

{Cl}^{-}

{HCO}_{3}^{-}

{NO}_{3}^{-}

{SO}_{4}^{2 -}

, EC, E. coli,

{Mg}^{2 +}

, pH, Hardness, TDS, and

{CO}_{3}^{2 -}

Table 8 shows the interrelationship of the mentioned parameters in Satpara Watershed. The correlation matrix showed the except two parameters all the other parameters have strong positive correlation such as

{Na}^{+} - K^{+}

(r = 0.79),

{Na}^{+} - {Ca}^{2 +}

(r = 0.71),

{Na}^{+} - {HCO}_{3}^{-}

(r = 0.54),

{Na}^{+} - {NO}_{3}^{-}

(r = 0.58),

{Na}^{+} -

EC (r = 0.80),

{Na}^{+}

− Hardness (r = 0.71),

{Na}^{+}

− TDS (r = 0.80),

{Na}^{+} - {CO}_{3}^{2 -}

(r = 0.69),

K^{+} - {Ca}^{2 +}

(r = 0.56),

K^{+} - {SO}_{4}^{2 -}

(r = 0.64),

K^{+}

− EC (r = 0.59),

K^{+}

− Hardness (r = 0.62),

K^{+}

− TDS (r = 0.58),

{Ca}^{2 +} - {HCO}_{3}^{-}

(r = 0.73),

{Ca}^{2 +} - {NO}_{3}^{-}

(r = 0.80),

{Ca}^{2 +} - {SO}_{4}^{2 -}

(r = 084),

{Ca}^{2 +}

− EC (r = 0.88),

{Ca}^{2 +}

− Hardness (r = 0.89),

{Ca}^{2 +}

− TDS (r = 0.88),

{Ca}^{2 +} - {CO}_{3}^{2 -}

(r = 0.71),

{HCO}_{3}^{-} - {NO}_{3}^{-}

(r = 0.87),

{HCO}_{3}^{-} - {SO}_{4}^{2 -}

(r = 0.77),

{HCO}_{3}^{-}

− EC (r = 0.73),

{HCO}_{3}^{-} - {Mg}^{2 +}

(r = 0.67),

{HCO}_{3}^{-}

−Hardness (r = 0.83),

{HCO}_{3}^{-}

− TDS (r = 0.74),

{HCO}_{3}^{-} - {CO}_{3}^{2 -}

(r = 0.57),

{NO}_{3}^{-} - {SO}_{4}^{2 -}

(r = 0.77),

{NO}_{3}^{-}

− EC (r = 0.76),

{NO}_{3}^{-} - {Mg}^{2 +}

(r = 0.62),

{NO}_{3}^{-}

− Hardness (r = 0.85),

{NO}_{3}^{-}

− TDS (r = 0.77),

{NO}_{3}^{-} - {CO}_{3}^{2 -}

(r = 0.67),

{SO}_{4}^{2 -}

− E (r = 0.83),

{SO}_{4}^{2 -} - {Mg}^{2 +}

(r = 0.68),

{SO}_{4}^{2 -}

− Hardness (r = 0.94),

{SO}_{4}^{2 -}

− TDS (r = 0.83),

{SO}_{4}^{2 -} - {CO}_{3}^{2 -}

(r = 0.71), EC − Hardness (r = 0.68), EC −

{CO}_{3}^{2 -}

(r = 0.82),

{Mg}^{2 +}

− Hardness (r = 0.69), Hardness − TDS (r = 0.86), Hardness −

{CO}_{3}^{2 -}

(r = 0.74), TDS −

{CO}_{3}^{2 -}

(r = 0.82) and weak negative correlation between

K^{+} - {Cl}^{-}

(r = −0.03),

K^{+}

− E. coli (r = −0.05), and

{Cl}^{-} - {SO}_{4}^{2 -}

(r = −0.04), respectively.

7. Discussion

Water is the most essential resource on Earth, giving life to plants, animals, and humans. As freshwater makes up 2.5% of the world’s total water, it is the most widely used water source for agriculture, industry, and domestic consumption. The overall water quality classification ranges of Satpara Watershed Skardu are presented in Table 8, where there is a spatial variability in the microbial and physiochemical parameters. Regarding microbial analysis results, 8 colonies of E. coli/100 mL were found, which shows that the area is prone to anthropogenic activities near the watershed, causing fecal coliform generation into the watershed [60]. The sulfate concentration level was uneven along the whole watershed but within the permissible limit, with a maximum value of 170 mg/L. However, the hardness of water is due to the presence of cations like sulfate, carbonate, bicarbonate, and chloride [43]. The overall correlation among the elements is significantly correlated, and if no correlation existed among the elements, then the metals/elements were controlled by no one factor [61]. There are strong positive correlations between

{Na}^{+}

K^{+}

{HCO}_{3}^{-}

, Hardness, and EC have strong correlation with all the parameters except pH. The correlation between physicochemical and microbiological parameters might reveal important details about the sources and routes of emissions [62].

All the parameters except E. coli had values within the permissible limits with undulant changes according to their sources [27]. According to the WHO, the maximum permissible limit for sodium (

{Na}^{+}

) is 75 mg/L. In the study area, maximum and minimum concentrations of sodium were observed to be 7.7 mg/L and 1.0 mg/L, with an average of 2.814 mg/L, indicating that sodium is within permissible limits. The maximum permissible limit for potassium (

K^{+}

) is 12 mhg/L, according to WHO. In the study area, the maximum potassium concentration was found to be 3.95 mg/L, and the minimum concentration was 0.4 mg/L, with an average of 1.573 mg/L. The presence of sodium and potassium minerals in the Satpara Watershed is due to the carbonate and silicate mineral weathering and dissolution into the stream water [50]. In the study area, the maximum

{Ca}^{2 +}

concentration was found to be 60 mg/L, and the minimum concentration was 40 mg/L with an average of 22.92 mg/L. This shows that all the samples have

{Ca}^{2 +}

concentration within WHO’s desired limit (i.e., 75 mg/L). The highest concentration of

{Mg}^{2 +}

in the study area was 13.8 mg/L, which is well below WHO’s desirable limit (i.e., 30 mg/L).

{Mg}^{2 +}

concentration was as low as 0 mg/L at certain sites. The average concentration of

{Mg}^{2 +}

was observed to be 2.808 mg/L. The presence of

{Ca}^{2 +}

and

{Mg}^{2 +}

minerals in Satpara Watershed was due to the carbonate and silicate minerals weathering, erosion, and dissolution into the stream water. Furthermore, less than 500 mg of CaCO₃/L is needed for the water to be portable according to WHO standard limits. Maximum and minimum concentrations of CaCO₃ were to be 200 mg/L and 30 mg/L, with an average of 71.62 mg/L in the study area, which shows that there are source calcite minerals near Satpara reservoir that are adding CaCO₃ minerals into Satpara Watershed, which is causing hardness in water quality [63]. Chloride concentration should be less than 250 mg/L according to WHO drinking water quality limits. In the study area, the maximum chloride concentration was 22 mg/L, and the minimum concentration was 10 mg/L, with an average of 13.96 mg/L. In Figure 9C, chloride concentration is increasing gradually from the Deosai Plateau to the Rangah area, which means anthropogenic sources (synthetic inorganic fertilizers, landfill leaches, effluents from nearby settlements into the stream) are becoming the source of concentration increment [64].

{HCO}_{3}^{-}

concentration ranged from 0.8 mg/L to 6.5 mg/L with an average of 1.74 mg/L. WHO’s maximum desirable limit for

{HCO}_{3}^{-}

is 120 mg/L. The low concentration of

{HCO}_{3}^{-}

is due to the geology of the study area, which is comprised of granodiorites. It is very clear from the obtained results that the mineral composition of the Deosai Plateau is mostly granodiorite of the Eocene age, known as Satpura granodiorite, and also metamorphosed igneous geology. The results show the very rare presence of carbonate minerals within the Satpara Watershed [65]. Sulfate concentration should be less than 250 mg/L, according to WHO. In the study area, the maximum sulfate concentration was observed to be 170 mg/L, and the minimum concentration was 13 mg/L, with an average of 53.52 mg/L. The chemical properties of soil present the sulfate

{SO}_{4}^{2 -}

mineral content along Satpara Watershed which can be dissolved into the stream water [50]. Maximum and minimum concentrations of

{NO}_{3}^{-}

were recorded at 5 mg/L and 0.37 mg/L, with an average of 1.2438 mg/L falling within the WHO permissible limit, which is 50 mg/L. The obtained results show that nitrate concentration in Satpara Watershed is very low as compared to other minerals because natural processes cause very low concentrations of nitrogen in drinking water. It shows that the watershed is safe from sewerage and effluents from households [66]. As per WHO, (EC < 2500 μS/cm) at 20 °C. Maximum EC was found to be 427 μS/cm and the minimum EC was 67.3 μS/cm with an average of 152.1 μS/cm in the area. The obtained results show that concentration is within the limit, and the presence of suspended and soluble cations and anions is due to the weathered rocks in the vicinity being incised and eroded by the flow of the stream [67].

WHO describes that E. coli should be 0 number/L, but the study area was highly contaminated with as many as 8 colonies of E. coli/100 mL. Most areas were found with 0 number/100 mL E. coli concentration with an average of 0.52 colonies/100 mL. The main cause of E. coli contamination was the wildlife movement and malfunctioning septic system along the main reservoir of Satpara Watershed, leaving inimical health effects on the inhabitants utilizing the same water source for drinking purposes. The maximum permissible concentration of TDS is 500 mg/L, according to WHO. Within the study area, the maximum and minimum concentrations of TDS were 282 mg/L and 44.42 mg/L, with an average of 100.25 mg/L. It is obvious from the results that the weathering of rock minerals and anthropogenic activities add dissolved minerals to the Satpara Watershed [27]. For water to be portable, its pH should be less than 8.5 and greater than 6.5, as per WHO. pH results show that it is falling within the permissible limits. The pH of the study area varied between 7.2 and 8.5, with a mean concentration value of 7.662, which is likely to be low, which is obviously due to the acidic ions and the dissolved salt minerals in the watershed causing weathering and transportation of carbonate and silicate rock minerals right into the watershed [27,68]. In the mountainous regions, another source of carbon dioxide is weathering, which modifies the pH of the areas [69]. Satpara Watershed is the only source of drinking water for the Skardu municipal area, and due to the increasing population adjacent to the main Satapara reservoir, the quality of the watershed is being altered and contaminated by E. coli and agricultural effluents. This research outcome will help the community as well as the law enforcement agencies to minimize the deterioration of water quality through various anthropogenic activities.

8. Limitations of the Study

In the recent study, a few limitations should be acknowledged. First of all, the samples were taken in the fall season only, which may not fully capture short-term changes in the quality of water due to seasonal flash floods, unexpected contamination discharges, etc. This limitation might alter the effectiveness of the findings for seasonal trends. Secondly, heavy metal contaminants were not investigated, which may also affect the overall quality of the watershed. Moreover, the study’s site selection is limited to one watershed, which may restrict the generalizability of the findings to other watersheds and potentially overlook disease dynamics unique to those areas. Future studies may be carried out for more accuracy and reliability of the findings; sampling frequency might be increased for exploring the hidden point and non-point contamination sources all over the Skardu District.

9. Conclusions

Contamination of surface water for drinking has serious threats for humans and biodiversity in the region. The research has tried to assess the surface water quality using laboratory measurements, physiochemical analysis, and bacteriological analysis. Spatialization of the Water Quality Index (WQI) using Geographic Information Systems (GISs) has provided meaningful insights for visualizing and analyzing the spatial distribution of water quality across different regions. The quality of drinking water was poor due to the presence of contamination. The whole water quality has been estimated and ranked according to their concentration levels as Excellent, Good, Poor, Very Poor, and Unfit for drinking purposes. The risk of whole bacteriological contamination is low and is according to the World Health Organization drinking water quality standard, but it can be reduced further with proper management of livestock movements near the freshwater streams. The correlation analysis of physiochemical parameters of drinking water in the Satpara watershed reveals the presence of nitrate, chloride, and electrical conductivity resulted in the deterioration of water quality. The research has highlighted the areas where water quality is poor and where management efforts need to be prioritized.

Author Contributions

Conceptualization, Ali Muhammad and Donghui Shangguan; Methodology, Ayesha Hussain; Software, Ali Muhammad; Validation, Ali Muhammad; Formal analysis, Ghulam Rasool and Ayesha Hussain; Investigation, Ghulam Rasool and Asim Qayyum Butt; Resources, Amjad Ali Khan; Data curation, Amjad Ali Khan and Muhammad Ahsan Mukhtar; Writing—original draft, Ali Muhammad and Ghulam Rasool; Writing—review & editing, Donghui Shangguan, Amjad Ali Khan, Asim Qayyum Butt, Ayesha Hussain and Muhammad Ahsan Mukhtar; Supervision, Donghui Shangguan; Project administration, Donghui Shangguan; Funding acquisition, Donghui Shangguan. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Gansu Provincial Science and Technology Program (Grant No. 22ZD6FA005), an international partnership of the Chinese Academy of Sciences (Grant No. 131C11KYSB20200022, Grant No. 046GJHZ2023069MI), and the National Natural Science Foundation of China (Grant No. 42171148).

Data Availability Statement

The data used to substantiate the findings of this research are accessible upon request from the corresponding author.

Acknowledgments

The authors would like to thank every person who collaborated throughout this research work, Local Government and Rural Development Program, (LG and RD) Skardu, Public Health and Engineering Department (PHED), Lahore, Geo-Chemistry lab, Punjab University, Lahore. The completion of this research work could not have been possible without their help and support. The constructive contribution of Sharaft Ali Baqri (Microbiologist), as well as the careful review and sincere suggestions by the anonymous referees, are gratefully acknowledged.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Water Quality Range Classification Table.

Sr. No	Sample No.	Sampling Localities	Source of Water	WQI	Classification
1	S_1	Way to Deosai Plateau	Stream	188.262	Poor
2	S_2	Way to Deosai Plateau	Stream	171.558	Poor
3	S_3	Way to Deosai Plateau	Stream	163.8	Poor
4	S_4	Asmani Mour site	Stream	163.73	Poor
5	S_5	Tributary Checkpost area	Stream	190.641	Poor
6	S_6	Spring near Hassan Satpara Cafe	Stream	146.356	Poor
7	S_7	Spring Satpara Gol	Stream	223.5	Very Poor
8	S_8	Spring Satpara Gol	Stream	166.555	Poor
9	S_9	Satpara inlet left tributary	Stream	298.347	Unfit for Drinking
10	S_10	Satpara inlet left tributary	Stream	317.813	Unfit for Drinking
11	S_11	Satpara Grong bridge site	Stream	175.915	Poor
12	S_12	Irrigation channel Eastward	Stream	180.548	Poor
13	S_13	Spring near irrigation channel	Stream	181.249	Poor
14	S_14	Satpara main stream	Stream	167.065	Poor
15	S_15	Satpara main stream	Stream	157.595	Poor
16	S_16	Satpara main stream	Stream	170.261	Poor
17	S_17	RCC Bridge site	Stream	165.212	Poor
18	S_18	Satpara Grong spring	Stream	194.68	Very Poor
19	S_19	Sat. Grong Western tributary	Stream	144.684	Poor
20	S_20	Satpara Grong main stream	Stream	175.384	Poor
21	S_21	Satpara upper Grong	Spring	307.011	Unfit for Drinking
22	S_22	Satpara Grong bridge site	Stream	176.253	Poor
23	S_23	Spring near dam inlet	Spring	194.954	Very Poor
24	S_24	Dam inlet	Stream	218.994	Very Poor
25	S_25	Spring near irrigation channel	Spring	210.717	Very Poor
26	S_26	Irrigation channel discharge site	Stream	191.794	Very Poor
27	S_27	Spring Hargisa	Spring	185.262	Poor
28	S_28	Tufail Colony	Tap	192.383	Poor
29	S_29	Eid Gah	Tap	188.234	Very Poor
30	S_30	Hospital Colony	Tap	190.711	Poor
31	S_31	Main Reservoir	Reservoir	191.323	Very Poor
32	S_32	Main Reservoir	Reservoir	186.679	Very Poor
33	S_33	Main Reservoir	Reservoir	210.643	Very Poor
34	S_34	Main Reservoir	Reservoir	204.974	Very Poor
35	S_35	Main Reservoir	Reservoir	186.309	Very Poor
36	S_36	Main Reservoir	Reservoir	177.008	Poor
37	S_37	Main Reservoir	Reservoir	181.681	Very Poor
38	S_38	Main Reservoir	Reservoir	254.791	Very Poor
39	S_39	Main Reservoir	Reservoir	184.066	Poor
40	S_40	Main Reservoir	Reservoir	175.303	Poor
41	S_41	Main Reservoir	Reservoir	177.36	Poor
42	S_42	Main Reservoir	Reservoir	181.26	Poor
43	S_43	Main Reservoir	Reservoir	181.84	Poor
44	S_44	Main Reservoir	Reservoir	232.058	Very Poor
45	S_45	Main Reservoir	Reservoir	206.568	Very Poor
46	S_46	Water Safety Tank	Tap	195.315	Poor
47	S_47	WAPDA Water Complex	Tap	2411.909	Poor
48	S_48	Deosai Plateau	Spring	183.017	Poor
49	S_49	Spring near Jamia Mosque	Spring	382.869	Unfit for Drinking
50	S_50	LG and RD	Stream	248.472	Unfit for Drinking
51	S_51	Shatong Deosai	Tap	188.262	Poor

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Figure 1. (A) Skardu District with Pakistan and Gilgit-Baltistan map inset, (B) Satpara Watershed, (C) Skardu Municipal Areas.

Figure 2. Showing (A) Contour Map of Satpara Watershed (B) Slope Map in degrees of Satpara Watershed (C) Altitude Map of Satpara Watershed.

Figure 3. Temperature °C variation map of Satpara Watershed.

Figure 4. Geo-spatial variation map of Escherichia Coli within Satpara Watershed.

Figure 5. (A) Spatial variation map of pH of Satpara Watershed (B) Spatial variation in EC of Satpara Watershed.

Figure 6. (A) Alkalinity variation map of Satpara Watershed (B) Bicarbonates (

{HCO}_{3}^{-}

) concentration map of Satpara Watershed.

Figure 6. (A) Alkalinity variation map of Satpara Watershed (B) Bicarbonates (

{HCO}_{3}^{-}

) concentration map of Satpara Watershed.

Figure 7. (A). Map of spatial variation in TH in Satpara Watershed (B). Map of spatial variation in total TDS of Satpara Watershed.

Figure 8. Cations Spatial distributions of Satpara Watershed: (A). (

{Mg}^{2 +}

), (B). (

{Ca}^{2 +}

), (C). (

K^{+}

), and (D). (

{Na}^{+}

Figure 8. Cations Spatial distributions of Satpara Watershed: (A). (

{Mg}^{2 +}

), (B). (

{Ca}^{2 +}

), (C). (

K^{+}

), and (D). (

{Na}^{+}

Figure 9. Anions spatial distributions of Satpara Watershed: (A). (

{HCO}_{3}^{2 -}

), (B). (

{NO}_{3}^{-}

), (C). (

{Cl}^{-}

), (D). (

{SO}_{4}^{2 -}

Figure 9. Anions spatial distributions of Satpara Watershed: (A). (

{HCO}_{3}^{2 -}

), (B). (

{NO}_{3}^{-}

), (C). (

{Cl}^{-}

), (D). (

{SO}_{4}^{2 -}

Figure 10. Sodium Absorption Ratio (SAR) Map of Satpara Watershed.

Figure 11. Final Water Quality Index Map of Satpara Watershed.

Table 1. The weight (wi) and relative weight (Wi) of individual chemical parameter [46].

Parameters	NSDWG	WHO Standards	Weight (wi)	Relative Weight (Wi)
pH	8.5	8.5	3	0.09375
TDS	500	500	5	0.15625
${Na}^{+}$	75	75	2	0.0625
$K^{+}$	12	12	1	0.03125
${Ca}^{2 +}$	75	75	1	0.03125
${Mg}^{2 +}$	50	50	1	0.03125
${SO}_{4}^{2 -}$	250	250	4	0.125
${NO}_{3}^{-}$	50	50	3	0.09375
${HCO}_{3}^{-}$	120	120	2	0.0625
${Cl}^{-}$	250	250	4	0.125
E. coli	0	0	5	0.15625
			∑ wi = 32	∑ Wi = 0.97

Table 2. Water Quality Range Classification Table.

Sr. No	Water Quality Range	Type of Water
1	<50	Excellent
2	50–150.1	Good
3	150–250.1	Poor
4	250–350.1	Very Poor Water
5	>350	Unfit for Drinking

Table 3. Water Quality Range Classification Table.

Categories	Colonies/100 mL	Risks
Class A	No or 0 colony	Nil
Class B	Colonies (0 to10)	Low
Class C	Colonies (11–100)	High
Class D	Colonies (101–1000)	Very High

Table 4. Water Quality Range Classification Table.

$Classification of Water Hardness (Hardness in the Form of C a^{2 +}$ Carbonates)
Classification	mg/L or ppm
Soft	0–17.1
Slightly Hard	17.1–60
Moderately Hard	60–120
Hard	120–180
Very Hard	180 and greater

Table 5. Classification of Water Quality Range for SAR.

SAR Hazards of Irrigation Water
S. No.	SAR	Notes
1	<3.0	No, restriction or hazard
2	3–6	Should be taken in sensitive and tested
3	6–8	Gypsum should be used except for sensitive crops
4	>9.0	Unsuitable and causes severe damages

Table 6. Classification of Water Quality Range for RSC.

S. No.	RSC	Hazards
1	<0	None
2	1–1.25	Now, with the elimination of magnesium and calcium from irrigation water
3	1.25–2.50	Medium, with appreciable removal of calcium and magnesium
4	>2.50	High, with most calcium and magnesium removed, leaving sodium

Table 7. Statistical Analysis of Physiochemical Parameters of Surface Water Quality.

Parameters	Unit	Mean	Max.	Min.	Standard Deviation
${Na}^{+}$	Ppm	2.814	7.7	1	1.678
$K^{+}$	Ppm	1.573	3.95	0.4	1.254
${Ca}^{2 +}$	ppm	22.92	60	14	7.746
${Mg}^{2 +}$	ppm	2.808	13.8	0	3.126
${Cl}^{-}$	ppm	13.96	22	10	96.737
${HCO}_{3}^{-}$	ppm	1.738	6.5	0.8	0.938
${NO}_{3}^{-}$	ppm	1.2438	5	0.37	0.742
${SO}_{4}^{2 -}$	ppm	53.52	170	13	26.843
EC	(µS/cm)	152.1	427	67.3	58.000
E. coli	Colonies/100 mL	0.52	8	0	1.723
Hardness	ppm	71.62	200	30	26.792
TDS	ppm	100.25	282	44.42	38.57
pH		7.662	8.1	7.2	0.188

Table 8. Correlation Matrix Between Ground Water Quality Parameters.

Parameters	Na⁺	$N a^{+}$	$C a^{2 +}$	$C l^{-}$	$H C O_{3}^{-}$	$N O_{3}^{-}$	$S O_{4}^{2 -}$	EC	E. coli	$M g^{2 +}$	pH	Hardness	TDS	$C O_{3}^{2 -}$
${Na}^{+}$	1
$K^{+}$	0.79	1
${Ca}^{2 +}$	0.71	0.56	1
${Cl}^{-}$	0.08	−0.03	0.27	1
${HCO}_{3}^{-}$	0.54	0.49	0.73	0.22	1
${NO}_{3}^{-}$	0.58	0.44	0.80	0.29	0.87	1
${SO}_{4}^{2 -}$	0.73	0.64	0.84	−0.04	0.77	0.77	1
EC	0.80	0.59	0.88	0.14	0.73	0.76	0.83	1
E. coli	0.04	−0.05	0.24	0.25	0.04	0.19	0.07	0.11	1
${Mg}^{2 +}$	0.34	0.42	0.40	0.05	0.67	0.62	0.68	0.47	0.04	1
pH	0.09	0.07	0.21	0.23	0.16	0.30	0.12	0.18	0.31	0.25	1
Hardness	0.71	0.62	0.89	0.12	0.83	0.85	0.94	0.86	0.16	0.69	0.17	1
TDS	0.80	0.58	0.88	0.15	0.74	0.77	0.83	0.10	0.11	0.47	0.19	0.86	1
${CO}_{3}^{2 -}$	0.69	0.45	0.71	0.16	0.57	0.67	0.71	0.82	0.01	0.45	0.23	0.74	0.82	1

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Muhammad, A.; Shangguan, D.; Rasool, G.; Khan, A.A.; Butt, A.Q.; Hussain, A.; Mukhtar, M.A. A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan. ISPRS Int. J. Geo-Inf. 2024, 13, 393. https://doi.org/10.3390/ijgi13110393

AMA Style

Muhammad A, Shangguan D, Rasool G, Khan AA, Butt AQ, Hussain A, Mukhtar MA. A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan. ISPRS International Journal of Geo-Information. 2024; 13(11):393. https://doi.org/10.3390/ijgi13110393

Chicago/Turabian Style

Muhammad, Ali, Donghui Shangguan, Ghulam Rasool, Amjad Ali Khan, Asim Qayyum Butt, Ayesha Hussain, and Muhammad Ahsan Mukhtar. 2024. "A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan" ISPRS International Journal of Geo-Information 13, no. 11: 393. https://doi.org/10.3390/ijgi13110393

APA Style

Muhammad, A., Shangguan, D., Rasool, G., Khan, A. A., Butt, A. Q., Hussain, A., & Mukhtar, M. A. (2024). A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan. ISPRS International Journal of Geo-Information, 13(11), 393. https://doi.org/10.3390/ijgi13110393

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A Localized Evaluation of Surface Water Quality Using GIS-Based Water Quality Index along Satpara Watershed Skardu Baltistan, Pakistan

Abstract

1. Introduction

2. Study Area

3. Hydrology

4. Geology of the Area

5. Materials and Methods

5.1. Sample Collection

5.2. Laboratory Measurements

5.3. Physico-Chemical Analysis

5.4. Bacteriological Analysis

5.5. GIS Analysis and GPS

5.6. Water Quality Index (WQI)

5.7. Correlation Matric

6. Results

6.1. Geospatial Variations in Temperature (°C) of Satpara Watershed

6.2. Geospatial Variations in Bacterial (E. coli) Contamination of Satpara Watershed

6.3. Geo-Spatial Variations in pH Concentration of Satpara Watershed

6.4. Geospatial Variation in Electrical Conductivity (EC) of Satpara Watershed

6.5. Geospatial Variation in Total Alkalinity of Satpara Watershed

6.6. Geospatial Variation in Bicarbonate Concentration of Satpara Watershed

6.7. Geospatial Variation in Total Hardness Concentration of Satapara Watershed

6.8. Geospatial Variation in TDS Concentration Satpara Watershed

6.9. Geospatial Variations in Cations

6.10. Geospatial Variations in Anions

6.11. Spatial Variation of Sodium Adsorption Ratio

6.12. Residual of Sodium Carbonate (RSC)

6.13. Water Quality Classification of Satpara Watershed

6.14. Correlation Analysis of Water Quality

7. Discussion

8. Limitations of the Study

9. Conclusions

Author Contributions

Funding

Data Availability Statement

Acknowledgments

Conflicts of Interest

Appendix A

References

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