Open AccessArticle

An Assessment of Seasonal Water Quality in Phewa Lake, Nepal, by Integrating Geochemical Indices and Statistical Techniques: A Sustainable Approach

Rojesh Timalsina

¹,

Surendra Acharya

¹,

Bojan Đurin

^2,*

Mahesh Prasad Awasthi

Ramesh Raj Pant

^1,*

Ganesh Raj Joshi

⁴,

Rejina Maskey Byanju

Khim Prasad Panthi

⁵,

Susan Joshi

⁶,

Amit Kumar

⁷

Tarun Kumar Thakur

⁸

and

Ahmed M. Saqr

⁹

Central Department of Environmental Science, Institute of Science and Technology, Tribhuvan University, Kathmandu 44600, Nepal

Department of Civil Engineering, University North, 42000 Varaždin, Croatia

Faculty of Science and Technology, Far Western University, Mahendranagar 10400, Nepal

⁴

United Nations Centre for Regional Development, Nagoya 450-0001, Japan

⁵

Tri-Chandra Multiple Campus, Tribhuvan University, Kathmandu 44600, Nepal

⁶

Central Department of Chemistry, Institute of Science and Technology, Tribhuvan University, Kathmandu 44618, Nepal

⁷

School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China

⁸

Department of Environmental Science, Indira Gandhi National Tribal University, Amarkantak 484887, India

⁹

Irrigation and Hydraulics Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt

Authors to whom correspondence should be addressed.

Water 2025, 17(2), 238; https://doi.org/10.3390/w17020238

Submission received: 5 December 2024 / Revised: 13 January 2025 / Accepted: 14 January 2025 / Published: 16 January 2025

(This article belongs to the Special Issue Aquatic Ecosystem: Problems and Benefits—2nd Edition)

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Figure 1
Study area map showing sampling sites in Phewa Lake, Nepal. "> Figure 2
Methodological steps of this research. "> Figure 3
Physicochemical parameters for Phewa Lake, Nepal, during pre- and post-monsoon periods. "> Figure 4
Principal components of the loading plot for Phewa Lake, Nepal. The figure illustrates the relationships among various water quality parameters using different symbols and colors. The red circle represents the chloride ion (Cl−), while blue squares denote other ions such as sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), sodium (Na+), potassium (K+), and phosphate (PO43−). Green triangles represent physicochemical parameters, including electrical conductivity (EC), total dissolved solids (TDS), magnesium (Mg2+), calcium (Ca2+), and bicarbonate (HCO3−). The background planes correspond to the projections of the data points onto the component 1 (PC1), component 2 (PC2), and component 3 (PC3) planes, respectively, derived from a dimensionality reduction technique, i.e., principal component analysis (PCA). "> Figure 5
Piper diagram characterizing the hydrochemical facies for Phewa Lake, Nepal. Note: Region 1 corresponds to waters dominated by alkaline earths (Ca2+ + Mg2+) and weak acids (HCO3−), typically reflecting carbonate weathering. Region 2 denotes waters with alkaline earths and strong acids (Cl− + SO42−), often linked to gypsum dissolution or anthropogenic inputs. Region 3 represents mixed waters without a dominant ion type, suggesting blending of sources. Region 4 includes waters dominated by alkali metals (Na+ + K+) and weak acids, indicating silicate weathering or ion exchange. Region 5 features waters rich in alkali metals and strong acids, possibly due to evaporite dissolution or industrial contamination. Lastly, and Region 6 represents transitional waters with no clear dominance, indicating complex geochemical processes or mixing. "> Figure 6
Piper diagram showing dominant hydrochemical facies for Phewa Lake compared to Lesser Himalayan freshwater lakes in Nepal. Note: Region 1 corresponds to waters dominated by alkaline earths (Ca2+ + Mg2+) and weak acids (HCO3−), typically reflecting carbonate weathering. Region 2 denotes waters with alkaline earths and strong acids (Cl− + SO42−), often linked to gypsum dissolution or anthropogenic inputs. Region 3 represents mixed waters without a dominant ion type, suggesting blending of sources. Region 4 includes waters dominated by alkali metals (Na+ + K+) and weak acids, indicating silicate weathering or ion exchange. Region 5 features waters rich in alkali metals and strong acids, possibly due to evaporite dissolution or industrial contamination. Lastly, and Region 6 represents transitional waters with no clear dominance, indicating complex geochemical processes or mixing. "> Figure 7
Gibbs diagram showing (a) TDS vs. Na+/ (Na+ + Ca2+) and (b) TDS vs. Cl−/(Cl− + HCO3−) for Phewa Lake, Nepal. "> Figure 8
Variation in weight ratio of (a) Na+/(Na+ + Ca2+) and (b) Cl−/(Cl− + HCO3−), as a function of TDS, in Gibbs diagram for Phewa Lake compared to Lesser Himalayan freshwater lakes in Nepal. "> Figure 9
Mixing diagram for Phewa Lake, showing Na+-normalized molar ratios of (a) Ca2+ vs. HCO3−, and (b) Ca2+ vs. Mg2+. "> Figure 10
Mixing diagram showing Na+-normalized molar ratios of (a) Ca2+ vs. HCO3−, and (b) Ca2+ vs. Mg2+, for Phewa Lake, compared to lesser Himalayan freshwater lakes, in Nepal. "> Figure 11
Quantitative correlation of sustainable management strategy (SMS) with sustainable development goals (SDGs) for Phewa Lake, Nepal. ">

Versions Notes

Abstract

Lakes are vital freshwater ecosystems that sustain biodiversity, support livelihoods, and drive socio-economic growth globally. However, they face escalating threats from anthropogenic activities, including urbanization, agricultural runoff, and pollution, which are exacerbated by climate change. Phewa Lake in Nepal was selected for this study due to its increasing rates of nutrient enrichment, sedimentation, and pollution. This study evaluated seasonal and spatial water quality variations within the lake by analyzing water samples from 30 sites during the pre-monsoon and post-monsoon seasons. Twenty physicochemical parameters, including the potential of hydrogen (pH), dissolved oxygen (DO), electrical conductivity (EC), and major ions, e.g., calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), potassium (K⁺), bicarbonate (HCO₃⁻), chloride (Cl⁻), sulfate (SO₄²⁻), nitrate (NO₃⁻), phosphate (PO₄³⁻), and ammonium (NH₄⁺), were measured. The average pH ranged from 8.06 (pre-monsoon) to 8.24 (post-monsoon), reflecting dilution from monsoon rains and increased carbonate runoff. Furthermore, the DO levels in Phewa Lake averaged 7.46 mg/L (pre-monsoon) and 8.62 mg/L (post-monsoon), with higher values observed post-monsoon due to rainfall-driven oxygenation. Nutrient concentrations were shown to be elevated, with the nitrate concentration reaching 2.31 mg/L during the pre-monsoon period, and the phosphate concentration peaking at 0.15 mg/L in the post-monsoon period, particularly near agricultural runoff zones. The dominant cations in the lake’s hydrochemistry were Ca²⁺ and Mg²⁺, while HCO₃⁻ was the primary anion, reflecting the influence of carbonate weathering. Cluster analysis identified the lake outlet as a high-pollution zone, with the total dissolved solids (TDS) reaching 108–135 mg/L. Additionally, Principal component analysis revealed agricultural runoff and sewage effluents as the main pollution sources. Seasonal dynamics highlighted monsoon-induced dilution and pre-monsoon pollution peaks. These findings underscore the need for targeted pollution control and eutrophication management. By aligning with the sustainable development goals (SDGs) relevant to clean water and climate action, this research provides a replicable framework for sustainable lake management that is applicable to freshwater ecosystems worldwide.

Keywords:

Phewa Lake; water quality; principal component analysis; seasonal variation; Ramsar sites; sustainable development goals

1. Introduction

Freshwater habitats, especially lakes, are essential for preserving biodiversity, supporting human livelihoods, and facilitating global socio-economic growth [1]. These ecosystems offer critical services, including water retention, nutrient cycling, flood management, and climate regulation, making them indispensable for biological and human systems [2,3]. They function as vital freshwater reservoirs, providing drinking water, facilitating agriculture, and producing hydropower [4]. They serve practical purposes and play a crucial role in towns’ cultural and recreational identities, drawing tourism and cultivating a sense of place [5]. Despite their critical significance, lakes are increasingly jeopardized by human-induced pressures such as urbanization, agricultural intensification, deforestation, and industrial activities [6]. Climate change intensifies these stressors by increasing temperatures, altering precipitation patterns, and causing extreme weather events, which modify hydrological cycles, enhance evaporation, and disturb water temperature profiles, compromising water quality and ecosystem resilience [7,8]. Accordingly, there is an urgent need for effective measures to preserve water quality, as highlighted in the United Nations’ Sustainable Development Goals (SDGs) agenda, to protect and rehabilitate lakes for future generations [9,10].

A significant challenge in freshwater management is the gradual decline in lake water quality [11]. Lakes are natural reservoirs for organic and anthropogenic inputs, rendering them particularly vulnerable to contamination [12]. Non-point source pollution, exemplified by agricultural runoff, contributes excessive nutrients, such as nitrogen and phosphorus, to lake systems, frequently resulting in eutrophication [13,14]. This process fosters algal bloom proliferation, depleting oxygen dissolved in water, disrupting aquatic ecosystems, and reducing water’s usefulness for drinking, recreation, and fisheries [15]. Point source pollution, such as untreated sewage and industrial effluents, exacerbates these issues by introducing heavy metals, harmful substances, and infections [16,17]. These pollutants significantly impact biodiversity and human health, especially in highly inhabited and economically active areas with severe pollution [18]. These challenges are not confined to a particular place, but signify a global issue, jeopardizing lakes in urban, rural, and industrial areas globally [19]. Phewa Lake in Nepal exemplifies these difficulties. It is encumbered by silt, nitrogen loading, and pollution due to the encroachment of fast-developing metropolitan areas and intensive agricultural operations [2,16]. These pressures endanger its ecological integrity and harm the livelihoods and cultural legacy of populations reliant on its resources [20,21]. Such instances underscore the imperative of formulating focused, science-based policies for managing lake ecosystems amid the simultaneous challenges of anthropogenic activity and environmental change [22].

Addressing these intricate challenges necessitates thorough evaluations of lake water quality that account for spatial and temporal variability [23]. Natural processes, including rock weathering, precipitation, and evaporation, substantially affect the geochemical composition of lake waters [24]. Local climatic circumstances and geological factors frequently alter these processes, resulting in distinctive chemical signatures within lake systems [25]. Nonetheless, human activities, like agricultural runoff, urban effluents, and industrial discharges, can disrupt these natural processes, adding contaminants that significantly modify water quality [26]. Seasonal fluctuations, especially in areas characterized by pronounced monsoon and arid phases, introduce further intricacy to these processes. Monsoon rains can attenuate specific pollutants while exacerbating nutrient and sediment loading from surface runoff [27]. Advanced analytical instruments, such as geochemical indicators and multivariate statistical methods, are essential for elucidating these intricate relationships [28]. Principal component analysis (PCA) is highly efficient in discerning the predominant elements affecting water quality, as it condenses extensive datasets into essential variables that account for variance [29]. Cluster analysis (CA) facilitates the categorization of locations or timeframes based on analogous water quality measures, enabling researchers to pinpoint pollution hotspots and classify sites according to their ecological health [30]. These approaches provide essential information for formulating focused actions and strategies for lake management. Concerning Phewa Lake, these strategies are crucial for tackling its complex water quality issues and securing its enduring ecological and socio-economic sustainability [22].

This study addresses the global challenge of freshwater resource management through a comprehensive analysis of the hydrochemical properties of Phewa Lake, Nepal. The innovation of this study lies in its integration of advanced geochemical investigations with multivariate statistical techniques to offer a sustainable management strategy (SMS) aimed at mitigating water pollution, aligning with the SDGs through a sustainable approach. The study analyzes both natural processes, like carbonate weathering, and human-induced stressors, including agricultural runoff and urban encroachment, to elucidate the complex aspects influencing lake ecosystems. Hence, this research aims to (a) evaluate spatial and temporal fluctuations in essential physicochemical parameters to discern seasonal trends and pollution hotspots in Phewa Lake, Nepal; (b) delineate the predominant geochemical processes that influence water chemistry, offering insights into the natural forces affecting lake ecosystems; and (c) introduce an SMS to act as a countermeasure for water pollution in the study area. This alignment with the SDGs highlights the study’s greater significance and applicability, rendering it valuable to local and global freshwater resource management efforts.

2. Materials and Methods

2.1. Physical and Geographical Background of Phewa Lake

Phewa Lake is the second-largest lake in Nepal, situated in the Kaski District of Gandaki Province, Nepal (Figure 1). It is located from 28°13′38.74″ N, 83°56′2.31″ E to 28°11′44.93″ N, 83°58′4.43″ E, with an elevation of approximately 742 m above sea level (masl) [31]. The lake is located in the Pokhara Valley, with an area of 4.53 km², a maximum depth of 23.30 m, an average depth of 11.71 m, and a watershed area of roughly 119.89 km² [32]. This monsoon-rain-fed lake obtains over 80% of its precipitation from May to September. The projected water storage capacity of Phewa Lake is around 43,000,000 m³ [2].

The principal tributaries of Phewa Lake are Harpan Khola, Hani Khola, Khahare Khola, and Sedi Khola. The lake receives inflow from the west via the Harpan Khola and is included within a Ramsar site that encompasses the city of Pokhara. Harpan Khola contributes pristine and unpolluted water. In contrast, Sedi Khola is heavily influenced by human activities, mainly urban runoff, and supplies contaminants to the lake [33]. Furthermore, there are other seasonal inlets, with Pardi Khola as the primary outflow. The lake’s eastern shore is heavily populated, while the northern and western shores are characterized by woods and agricultural areas, with the north shore exhibiting minimal population density. The lake was constructed in 1933 for agriculture and hydroelectric power generation. In recent decades, the lake’s area has diminished due to sediment accumulation [20]. Phewa Lake’s water is used to generate electricity at the Phewa Power House, located approx. 1.5 km south of the lake, and is also utilized for irrigational purposes. Additionally, a section of the lake is employed for commercial cage fisheries.

The catchment structure of Phewa Lake, situated in a hilly region, is crucial for maintaining water quality. High discharge from feeding rivers promotes dilution, which helps to reduce pollutant concentrations [34]. Dense forests in the southwest act as buffers, filtering pollutants, while direct discharge into the lake is restricted. Notably, monsoon rainfall enhances dilution, and pristine tributaries like Harpan Khola flow further reduce pollution. The lake’s hydrochemical quality remains high despite tourism, business activities near the Lake Side Area, the Talbarahi Temple, and municipal waste from Sedi Khola. However, microorganism contamination warrants further study. Generally, the water quality parameters remain good in areas with specific land uses, highlighting the effectiveness of natural and managed buffers [35].

2.2. Research Methodology

This section delineates the methodological framework utilized in the study, specifying the sampling approach, analytical techniques, and statistical methodologies performed to assess the water quality of Phewa Lake, Nepal. Furthermore, it delineates the methods employed to evaluate the study’s impact on sustainable development by incorporating environmental, economic, and social dimensions, as described in the following subsections (Figure 2).

2.2.1. Sampling and Physicochemical Analysis

A comprehensive sampling technique was developed to guarantee the exhaustive assessment of Phewa Lake’s water quality. Thirty sampling sites were designated to represent varied conditions throughout the lake, encompassing regions affected by natural inflows, agricultural runoff, and urban effluents. The geographic spread of these sites enabled the study to consider variations in pollutant sources and hydrological inputs. Samples were taken at various depths, from 0.5 m below the lake’s surface to 0.5 m above the lake’s bottom, to assess vertical stratification in water quality indicators, which is frequently pronounced in lakes due to thermal and chemical gradients [36]. Seasonal sampling occurred during the pre-monsoon season (March) and post-monsoon period (November) in 2021, reflecting different hydrological conditions. This methodology guaranteed that the research encompassed the effects of monsoon-induced runoff and nutrient influx alongside dry-season phenomena, including evaporation and diminished hydrological contributions [25].

Water samples were obtained using high-density polyethylene (HDPE) bottles, pre-cleaned with deionized water to avert contamination. To preserve the chemical integrity of the samples, they were promptly stored in insulated coolers at 4 °C following collection [37]. The samples were sent to the laboratory and tested within 24 h to mitigate any modifications resulting from their storage [38]. Proper storage and handling practices ensured the reproducibility of the analytical data and adherence to standard sampling standards (ISO 5667-3:2018) [39].

A broad range of physicochemical parameters were examined to deliver a thorough evaluation of the lake’s water quality:

In Situ Measurements

Parameters including the water temperature (Temp), turbidity (Turb), the potential of hydrogen (pH), dissolved oxygen (DO), electrical conductivity (EC), and total dissolved solids (TDS) were directly measured at the sampling locations using portable, calibrated equipment [18]. For instance, Turb was assessed with the Oakton TN-100 Turbidity Meter (Oakton Instruments, Vernon Hills, IL, USA). Due to its superior accuracy and precision, the Oakton TN-100 Turbidity Meter is generally more useful than the Secchi disk for evaluating water clarity, particularly in scientific and professional contexts. Unlike the Secchi disk, which relies on subjective visual evaluation, the TN-100 provides objective numerical readings in Nephelometric Turbidity Units (NTU), reducing human error. These metrics offered prompt insights into the lake’s fundamental water chemistry and were crucial for detecting localized discrepancies in water quality.

Laboratory Evaluations

The concentrations of the principal ions, such as calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), potassium (K⁺), bicarbonate (HCO₃⁻), chloride (Cl⁻), sulfate (SO₄²⁻), and nitrate (NO₃⁻), were ascertained by a combination of volumetric titration, flame photometry, and UV-VIS spectrophotometry; phosphate (PO₄³⁻) concentration was calculated using the ammonium molybdate method, the ammonium (NH₄⁺) concentration using sodium nitroprusside, and the free carbon dioxide (F-CO₂) concentration using the titrimetic method. These methodologies facilitated the accurate measurement of both natural geochemical components and anthropogenic contaminants [2]. Nutrient characteristics, including phosphate (PO₄³⁻) and ammonium (NH₄⁺), were evaluated to assess nutrient loading, which is essential for comprehending eutrophication processes [40]. Additionally, other parameters, such as total hardness (TH), calcium hardness (CaH), magnesium hardness (MgH), and free carbon dioxide (F-CO₂), were evaluated for further analysis.

The field instruments were calibrated before each sample session according to manufacturer-recommended standards, to guarantee precise and dependable data. Blank and standard solutions were examined concurrently with the samples throughout the laboratory procedures, to ensure quality assurance and control (QA/QC). Repeated measurements and inter-laboratory comparisons were conducted to verify the consistency of the data [38].

2.2.2. Statistical Tools and Techniques

The gathered data underwent thorough statistical analysis to discern trends, correlations, and critical elements affecting water quality. A correlation matrix was constructed to evaluate the relationships among several physicochemical characteristics, revealing significant interdependencies, such as the effect of conductivity on ion concentrations, which reflect geochemical processes. These correlations provided valuable insights into the interaction between natural factors and human-induced variables influencing water quality [25]. To further analyze the dataset, PCA was employed to reduce dimensionality and identify the primary components driving variability in water quality. Parameters with substantial factor loadings (exceeding 0.75) were recognized as critical determinants, highlighting the impact of processes like carbonate weathering, seasonal fluctuations, and anthropogenic pollution [29]. Complementing this, CA categorized the 30 sampling sites based on similarities in water quality characteristics, enabling the identification of pollution hotspots and relatively pristine regions. This classification is crucial for prioritizing management interventions and targeting areas requiring immediate attention [1]. Data analysis and visualization were performed using SPSS (Version 20) for statistical evaluations, and OriginPro (Version 9.8) for creating loading plots, dendrograms, and spatial maps [22]. These tools effectively illustrated the inter-relationships among variables and the spatial distribution of water quality across the lake.

2.2.3. Linkages Between Study Findings and Sustainable Development Goals (SDGs)

This study assessed the pollution hazards associated with Phewa Lake, Nepal, to introduce an SMS to meet the SDGs (SDG 6: Water and Sanitation). Conservation measures should be introduced to mitigate the severe consequences of water pollution based on the three pillars of sustainability [41].

3. Results

3.1. Spatio-Temporal Variations in Physicochemical Parameters

The average pH measured was 8.24 ± 0.35 (post-monsoon) and 8.06 ± 0.3 (pre-monsoon). Throughout all seasons, the water of Phewa Lake had average DO levels, low conductivity, low TDS, and negligible Turb. The average concentration of Ca²⁺ was 14.77 ± 7.61 mg L⁻¹ in the pre-monsoon period and 13.39 ± 6.06 mg L⁻¹ in the post-monsoon period. The mean concentration of SO₄²⁻ was 7.64 ± 2.67 mg L⁻¹ during the pre-monsoon period and 1.79 ± 1.7 mg L⁻¹ during the post-monsoon period. K⁺ concentrations averaged 0.31 ± 0.15 mg L⁻¹ during the pre-monsoon period and rose to 2.68 ± 0.85 mg L⁻¹ post-monsoon period (Figure 3).

3.2. Correlations Between Physicochemical Parameters

The correlation matrix (Table 1) illustrates the links between the physicochemical parameters across both seasons. The emphasized contexts are taken into account for the links among the parameters. The correlation matrix indicates a robust positive association between magnesium hazard (MgH) and Mg²⁺ (r = 0.80), Na⁺ and K⁺ (r = 0.86), and a moderate correlation among EC and TDS, Na⁺ and K⁺, Mg and MgH, and Cl⁻ and SO₄²⁻, as well as TH and HCO₃⁻. A moderate negative association exists between K⁺ and NO₃⁻ (r = −0.76), PO₄³⁻ and NO₃⁻ (r = −0.75), NO₃⁻ and Na⁺ (r = −0.72), and SO₄²⁻ and K⁺ (r = −0.74).

3.3. Principal Component Analysis (PCA)

Table 2 demonstrates the relationships among PC1, PC2, and PC3. PCA was conducted for Ca²⁺, Mg²⁺, K⁺, Na⁺, NO₃⁻, Cl⁻, SO₄²⁻, HCO₃⁻, PO₄³⁻, NH₄⁺, EC, and TDS. Values with factor loadings, specifically eigenvalues exceeding 1, were employed to interpret the results. Additionally, the categorization of the hydrochemical characteristics into three components, PC1, PC2, and PC3, is illustrated in Figure 4. The PCA results are deemed robust if the factor loadings exceed 0.75, moderate in the range from 0.75 to 0.50, and weak if they fall between 0.50 and 0.30 [29].

3.4. Characterization of Geochemical Facies

The Piper diagram, or trilinear diagram, illustrating the hydrochemical facies of Phewa Lake (Figure 5), presents the plotting of the milliequivalent percentage (M_eq%) of the major ions. A central diamond field was also projected to assess the geochemical facies influencing the lake water’s chemistry. Piper plots illustrate the comparative abundance of prevalent ions in water samples [42]. The central diamond field is partitioned into six subfields: Ca²⁺-HCO₃⁻, Na⁺-Cl⁻, Mixed Ca²⁺-Na⁺-HCO₃⁻, mixed Ca²⁺-Mg²⁺-Cl⁻, Ca²⁺-Cl⁻, and Na⁺-HCO₃⁻. Most of the samples in the lower left quadrant of the cations plot exhibited a predominance of Ca²⁺. In contrast, the samples in the lower left quadrant of the anion plot demonstrated a predominance of HCO₃⁻. In the cation plot of the post-monsoon period, most of the samples were predominantly distributed along the Ca²⁺ and Mg²⁺ axes, signifying the pre-eminence of both Ca²⁺ and Mg²⁺. Compared to Phewa Lake and other Lesser Himalayan freshwater lakes (Figure 6), most of the samples were situated in the lower left quadrant of the anion plot, signifying the predominance of HCO₃⁻. In the cation plot, most of the samples were also located in the lower left quadrant, indicating the dominance of Ca²⁺. The Jagadishpur Reservoir and Rajarani Lake samples exhibited higher levels of Na⁺ and K⁺, perhaps reflecting the impact of evaporites or anthropogenic activity.

3.5. Hydrochemistry of Phewa Lake

A Gibbs diagram can delineate the correlation between surface water chemistry and aquifer lithological characteristics [43]. According to this technique, the principal controlling mechanisms include evaporation, precipitation, and rock–water interactions. The Na⁺/(Ca²⁺ + Na⁺) ratio was plotted on the X-axis against TDS on the Y-axis, and similarly, the Cl⁻/(Cl⁻ + HCO₃⁻) ratio was plotted on the X-axis against TDS on the Y-axis, as illustrated in Figure 7. The boomerang-shaped cloud depicted in the illustration was interpreted through the scattering of data associated with the boomerang. The samples in the upper right quadrant, characterized by elevated TDS, Na⁺/(Na⁺ + Ca²⁺), and Cl⁻/(Cl⁻ + HCO₃⁻), suggest that evaporation and sedimentation are predominant influences. Conversely, the samples in the left quadrant, exhibiting moderate TDS and low Na⁺/(Na⁺ + Ca²⁺) and Cl⁻/(Cl⁻ + HCO₃⁻) ratios, indicate a pre-eminence of rock–water interactions. Similarly, the samples in the lower right quadrant, displaying low TDS alongside high Na⁺/(Na⁺ + Ca²⁺) and Cl⁻/(Cl⁻ + HCO₃⁻) ratios, point to precipitation as the primary factor governing lake water chemistry. Figure 8 offers a comparative examination of the governing mechanisms and sources of main ions, in addition to the ionic ratios of the water samples from the study area, compared to Lesser Himalayan freshwater lakes. The findings suggest that the regulatory mechanisms of these lakes are analogous, affected mainly by rock weathering.

3.6. Mixing Diagram

Figure 9 depicts the hydrochemical attributes of Phewa Lake, outlining its chemical makeup. The pre-monsoon samples are predominantly clustered between the carbonate end-members in the diagrams, underscoring the significance of carbonate weathering. Conversely, the post-monsoon samples have a broader distribution between carbonates and silicates, suggesting that rock weathering and underlying lithological features affect the lake’s physicochemical qualities. The comparative investigation of the chemical characteristics of Phewa Lake with other Lesser Himalayan freshwater lakes (Figure 10) reveals that carbonate weathering is prominent, as the samples are situated between the carbonate and silicate end-members.

3.7. Sustainable Management Strategy (SMS) Linked to Study Findings

The rising pollution levels in some regions of Phewa Lake emphasize the urgent need for an SMS that aligns with the United Nations’ SDGs (Figure 11). This strategy can address the multifaceted environmental, economic, and social challenges impacting lake ecosystems. The high pollution levels, driven by agricultural runoff, urban effluents, and sedimentation, require innovative approaches to mitigate environmental degradation while maintaining ecological balance. This study demonstrates how integrating geochemical indices and statistical techniques can help to overcome these challenges by providing actionable insights into pollution control and water quality restoration, as detailed in the following subsections.

3.7.1. Environmental-Based SDGs

The SMS can play a pivotal role in addressing key aspects of SDG 6 (Clean Water and Sanitation) by focusing on pollution reduction and ecosystem restoration. Specifically, it can directly contribute to Target 6.3 by identifying pollution hotspots driven by agricultural runoff and untreated urban effluents, which are primarily linked to elevated levels of NH₄⁺ and PO₄³⁻. To mitigate these issues, the proposed strategies may include regulating fertilizer usage and enhancing waste management systems to minimize nutrient enrichment. Seasonal insights, such as the dual role of monsoons in diluting pollutants while increasing nutrient inflows, can provide a foundation for designing tailored interventions to restore ecological balance. Furthermore, to achieve Target 6.6, this study shows how advanced geochemical tools and seasonal analyses can be integrated to monitor critical parameters such as DO and SO₄²⁻, offering vital data for effective ecosystem management. The SMS can collectively support sustainable water quality improvements that enhance biodiversity, fisheries, and recreational opportunities, aligning 25% of the SDG 6 targets with actionable and measurable outcomes.

In addition, the SMS can align with SDG 13 (Climate Action) by addressing Target 13.1, which emphasizes building resilience to climate-related hazards. Through seasonal analysis, this study has identified the impacts of monsoons on water chemistry, revealing their dual role in diluting pollutants while contributing to nutrient loading. These findings may provide a foundation for developing adaptive management strategies, such as implementing runoff control systems and establishing seasonal monitoring frameworks, to enhance the lake’s resilience to climate variability. By prioritizing climate-resilient water resource management, the SMS can ensure robust interventions that can adapt to shifting hydrological cycles and withstand extreme weather events. Addressing 20% of the SDG 13 targets, the SMS can effectively bridge the gap between climate science and sustainable water management, offering a scalable model for managing freshwater ecosystems amid global climate challenges.

In addition, the SMS can contribute to SDG 15 (Life on Land) by addressing Target 15.1, which focuses on the sustainable management of freshwater ecosystems. This study highlights the dominance of carbonate weathering processes in Phewa Lake’s hydrochemistry, emphasizing the need to preserve natural geochemical cycles while mitigating anthropogenic stressors such as NO₃⁻ and PO₄³⁻ loading. Using geochemical indices like the Piper and Gibbs diagrams, the SMS can identify natural and human-induced factors affecting water quality, providing actionable insights to safeguard the lake’s ecological integrity. Aligned with 8.33% of the SDG 15 targets, this approach may ensure the preservation of the lake’s natural processes while addressing pollution through strategic interventions. This can set a valuable precedent for balancing environmental conservation and sustainable human activities.

3.7.2. Economic-Based SDGs

The SMS can support SDG 8 (Decent Work and Economic Growth) by contributing to Target 8.4, which focuses on the sustainable use of resources for economic activities such as fisheries and tourism. With its natural beauty, cultural significance, and recreational opportunities, Phewa Lake can serve as a prime destination for tourism development. Enhancing infrastructure and promoting sustainable practices can further amplify its economic potential. Improved water quality, achieved through targeted pollution control measures, can foster aquatic biodiversity, sustain fish production, and attract eco-tourism, directly supporting local livelihoods and minimizing economic losses from environmental degradation. Furthermore, the SMS can highlight the financial viability of proactive management interventions, such as nutrient regulation and waste treatment, which can prevent costly future restoration efforts. Addressing 8.33% of the SDG 8 targets, the SMS can effectively integrate economic development with sustainable resource management, ensuring the long-term viability of economic activities tied to the lake.

Additionally, the SMS can contribute to SDG 12 (Responsible Consumption and Production) by addressing Targets 12.2 and 12.5 through the promotion of sustainable agricultural and urban planning practices. By identifying key pollution sources and analyzing seasonal trends, the SMS may advocate for efficient land use management, including reducing excessive fertilizer application and minimizing urban runoff, ensuring the sustainable use of natural resources in the catchment area under Target 12.2. Additionally, the SMS can address Target 12.5 by proposing measures to limit environmental pollution, such as enhancing urban waste treatment systems and regulating industrial discharges. By aligning with 18.18% of the SDG 12 targets, the SMS can play a pivotal role in fostering responsible consumption and production patterns, mitigating environmental harm, and promoting long-term sustainability.

3.7.3. Social-Based SDGs

The SMS can address Target 3.9 under SDG 3 (Good Health and Well-being) by prioritizing the reduction of health risks associated with waterborne diseases. By identifying and mitigating key pollutants such as NH₄⁺ and PO₄³⁻, which primarily originate from agricultural and urban sources, the proposed SMS aims to safeguard local communities from significant health hazards. The proposed measures, including controlling nutrient inflows and enhancing water treatment systems, may ensure safer water supplies and improve public health outcomes. Furthermore, maintaining stable DO levels and reducing Turb can enhance overall water quality, minimizing exposure to harmful contaminants. By addressing 7.69% of the SDG 3 targets, the SMS may underscore the critical intersection of water quality management and public health, ensuring that community well-being can be achieved, alongside environmental conservation.

Moreover, the SMS can address Target 11.6 under SDG 11 (Sustainable Cities and Communities) by identifying urban inflows as major contributors to pollution and proposing targeted interventions to mitigate their impact. Key strategies may include improving urban waste management infrastructure and regulating effluent discharge from residential and commercial areas. These measures aim to minimize the environmental footprint of urban activities and support the sustainable growth of cities surrounding Phewa Lake. By enhancing water quality, the SMS can promote healthier urban environments and bolster the region’s resilience to environmental challenges. Addressing 10% of the SDG 11 targets, the SMS can highlight the critical role of sustainable urban planning in protecting freshwater ecosystems while ensuring that urban development can harmonize with environmental and social priorities.

4. Discussion

4.1. Spatio-Temporal Variations in Water Quality of Phewa Lake

The pH values during the pre-monsoon and post-monsoon periods ranged from 8.06 ± 0.31 to 8.24 ± 0.35, confirming the alkaline nature of Phewa Lake’s surface water. Compared to other mountainous lakes in Nepal, the lake’s conductivity was moderate, higher than Mai Pokhari’s 18 μS cm⁻¹ [44], but lower than Begnas Lake’s 123.6 μS cm⁻¹ [45]. Over the past decade, conductivity has increased from 40.60 μS cm⁻¹ [46] to 94.835 μS cm⁻¹ (current study), likely due to agricultural runoff and sewage discharge. The average Turb of Phewa Lake was measured at 4.125 NTU, with pre-monsoon turbidity approximately double that of post-monsoon levels. This reduction in Turb during the post-monsoon period reflects the monsoon’s dilution effect, which improves water clarity. The primary sources of Turb included stormwater, agricultural runoff, and discharges from the hospitality and household sectors. Elevated Cl⁻ levels at specific locations can be attributed to direct sewage discharge. At the same time, increased nitrate NO₃⁻ concentrations across most sites indicate degradation caused by excessive use of agricultural fertilizers, manure, industrial effluents, and trash disposal. The higher mean concentration of NO₃⁻ compared to PO₄³⁻ suggest that Phewa Lake is phosphorus-limited.

The Ca²⁺, Mg²⁺, and Na⁺ concentrations showed significant temporal fluctuations compared to K⁺ in Phewa Lake. During the pre-monsoon period, the Ca²⁺ levels ranged between 5.6 and 51.2 mg/L, decreasing to 4.4–28 mg/L in the post-monsoon period, while the Mg²⁺ concentrations spanned from 3 to 6.2 mg/L pre-monsoon and from 0.1 to 13.18 mg/L post-monsoon. These fluctuations were primarily influenced by interactions with silicate minerals and processes within the carbonate system [47]. Variations in K⁺ concentrations were less pronounced, and likely stemmed from anthropogenic activities, such as agricultural runoff and domestic sewage discharge from residential areas. Similarly, the average surface concentration of SO₄²⁻ declined significantly from 7.64 mg/L (pre-monsoon) to 1.79 mg/L (post-monsoon). This reduction can be attributed to the dilution effects of monsoon rains. Notably, the SO₄²⁻ levels observed in this study are considerably lower than those reported by Kafle et al. [48], suggesting a significant decline over time. HCO₃⁻ concentrations, primarily driven by rock weathering and the decomposition of organic matter [49], ranged from 59.83 to 61.4 mg/L. These estimates, with higher levels recorded in post-monsoon samples, indicate intensified chemical weathering in the watershed. The TH concentration was measured at an average of 41.43 mg/L (pre-monsoon) and 46.93 mg/L (post-monsoon), classifying the lake’s water as relatively soft. Additionally, the F-CO₂ concentration increased from 7.2 mg/L (pre-monsoon) to 8.82 mg/L (post-monsoon), highlighting the role of F-CO₂ in influencing the lake’s pH and hydrochemical dynamics.

Additionally, the internal lake supply plays a pivotal role in shaping the water quality of Phewa Lake, Nepal, as it involves recycling nutrients and pollutants through sediment resuspension. This process can occur when sediments at the bottom of the lake are disturbed by natural forces, such as wind and water currents, or by human activities like boating and fishing [2]. Shallower zones of the lake are especially vulnerable to these disturbances, as their sediments are more easily resuspended. This recycling can release significant amounts of nutrients, such as phosphorus and nitrogen, back into the water column, which in turn fuels processes like eutrophication [1]. Eutrophication, characterized by excessive algal growth, reduces water clarity and can deplete DO levels, creating conditions that are detrimental to aquatic life. Studies have shown that in some cases, internal nutrient loading from sediments can exceed pollution derived from external sources, such as agricultural runoff or urban effluents [16]. This pattern underscores the importance of understanding internal nutrient dynamics and implementing targeted management strategies to mitigate their impact.

4.2. Hydrochemical Comparison of Present Study with Previous Studies on Phewa Lake

A comparative analysis between the current study and previous research highlights the critical need for regular cleaning initiatives to preserve Phewa Lake’s ecological balance (Table 3). A study by Khadka and Ramanathan [45] observed increased average TDS levels, likely linked to extensive chemical weathering in the catchment area and anthropogenic activities. Similarly, Kafle et al. [48] reported higher Turb levels than the present findings, potentially due to the lake’s eutrophic condition. In this study, pre-monsoon water sampling was conducted shortly after lake cleaning procedures. At the same time, the reduction in Turb during the post-monsoon period could be attributed to the diluting effect of monsoon rainfall. DO levels across various studies show comparable values, indicating relatively low levels of organic water pollution [28]. However, this study recorded elevated concentrations of Ca²⁺, Mg²⁺, and HCO₃⁻, reflecting intensified chemical weathering. According to Li et al. [50], carbonate ions dominated when the pH exceeded 8, and this study corroborated that finding, as the pH values surpassed 8, confirming the influence of chemical weathering processes. Additionally, higher Cl⁻ concentrations, consistent with findings from Malla Pradhan et al. [16], suggest contributions from Cl⁻-rich rocks or agricultural runoff. Khadka and Ramanathan [45] also reported greater NO₃⁻ levels than those observed in the present study, likely indicative of heightened microbial activity and nitrogen runoff from human activities. In this study, the elevated NO₃⁻ concentrations during the pre-monsoon period compared to post-monsoon levels were attributed to the leaching of chemical fertilizers from the catchment area. The findings underscore the dynamic interplay between natural processes and anthropogenic influences on Phewa Lake’s water quality. While most physicochemical parameters remained within acceptable limits for fisheries and recreational use, persistent human-induced stressors, such as organic pollution and eutrophication, pose significant long-term risks to the lake’s ecological health and sustainability.

4.3. Comparative Analysis of Major Ion Concentrations in Phewa Lake with Those in Other Lesser Himalayan Lakes

The concentrations of major ions observed in this study were compared with those of other lakes, as detailed in Table 4. Research has shown that most lakes in the Lesser Himalayas exhibit alkaline characteristics [47]. Compared to Renuka Lake, Pandoh Lake, and Begnas Lake, Phewa Lake has lower levels of PO₄³⁻. However, the concentration of HCO₃⁻ in Phewa Lake is higher than that in Begnas Lake and Pandoh Lake, while its K⁺ levels are lower than those in Renuka Lake, Pandoh Lake, and Begnas Lake. Atmospheric deposition and agricultural runoff in the catchment area likely influenced the NO₃⁻ concentrations in Pandoh Lake, as highlighted by Anshumali and Ramanathan [13], and these factors may also impact the NO₃⁻ levels in Phewa Lake. The increasing use of chemical fertilizers in the Phewa Lake basin may be expected to contribute to higher NO₃⁻ concentrations. Compared to lakes in the Terai region, lakes in the Himalayas experience less weathering due to temperature differences [11]. The chemical composition of Lesser Himalayan lakes is influenced by their lithological characteristics, alongside natural and anthropogenic contributions from the surrounding catchment areas. Most of Nepal’s water bodies are predominantly influenced by Ca²⁺ and HCO₃⁻ [1], reflecting the region’s underlying geology and environmental factors.

4.4. Statistical Analysis

The correlation coefficients among the physicochemical parameters, including Temp, pH, EC, TDS, Ca²⁺, Mg²⁺, Na⁺, K⁺, NO₃⁻, Cl⁻, SO₄²⁻, HCO₃⁻, PO₄³⁻, NH₄⁺, DO, Turb, CaH, MgH, TH, and F-CO₂, are summarized in Table 1. The study revealed a weak correlation between pH, EC, and TDS. However, HCO₃⁻ displayed a moderate positive correlation with EC, TDS, and Ca²⁺ (p < 0.05), indicating a shared natural weathering process influencing the ion composition of the lake. Similarly, Mg²⁺ showed a strong positive correlation with MgH (p < 0.05) and a moderate correlation with CaH (p < 0.05), suggesting that lithological factors contributed to the lake’s TH level. A positive correlation between Na⁺ and K⁺ (p < 0.05) further highlights the impact of the lake’s lithology on water quality. The correlations observed in this study align with the findings from PCA and CA analyses, reinforcing the interpretation of the underlying processes [1].

PCA of pre-monsoon and post-monsoon water quality data revealed three significant components with eigenvalues greater than 1, collectively accounting for 69.55% of the total variance, as shown in Table 2. The first component, explaining 39.81% of the variance, showed strong positive loadings for K⁺, Na⁺, PO₄³⁻, and NH₄⁺, as well as significant negative loadings for NO₃⁻ and SO₄²⁻. The second component, contributing 20.69% of the variance, exhibited strong positive loadings for EC, TDS, and HCO₃⁻, with moderate contributions from Ca²⁺ and Mg²⁺. The third component, accounting for 9.048% of the variance, displayed strong positive loadings for Cl⁻. These factors provide insights into the primary drivers of variability in water quality across the pre- and post-monsoon periods [58].

Cluster analysis further delineated spatial and temporal variations in water quality. Clusters I to V exhibited low pollution levels, with average TDS values ranging from 40.2 to 42 mg/L during the pre-monsoon period, indicating minimal anthropogenic stress. In contrast, Cluster VI, represented by sample site PS21, near Tal Barahi Temple in the core Lakeside area, recorded a TDS of 108 mg/L, reflecting significant anthropogenic impact. During the post-monsoon period, Cluster III showed an average TDS of 135 mg/L, with sites PS3, PS4, PS22, and PS28 identified as turbid water zones. Cluster I had the cleanest water, with an average TDS of 36.07 mg/L, while Cluster II recorded 60.73 mg/L. The TDS levels in Cluster III were more than double those of Cluster II and nearly quadruple those of Cluster I. Sites PS3 and PS4, located near agricultural zones, and PS22 and PS28, situated close to the lake’s outlet, are identified as critical areas requiring management to prevent long-term ecological and esthetic degradation [59].

Most of the water samples from Phewa Lake showed a predominance of Ca²⁺ ions, as depicted in the lower left corner of the Piper diagram (cation plot). However, specific sampling locations exhibited elevated Mg²⁺ levels, consistent with a carbonate-dominated lithology. The anion plot of the Piper diagram showed that most of the samples were clustered near the HCO₃⁻ apex, reaffirming the dominance of carbonate lithology. Some samples also displayed Cl⁻ enrichment, suggesting limited evaporation effects. Overall, the findings highlight the intricate interplay between lithological characteristics and external influences on Phewa Lake’s water quality [18].

In the central diamond plot of the Piper diagram, 98.34% of the samples from both the pre-monsoon and post-monsoon periods were categorized in subfield 1, indicating a dominance of Ca²⁺ and Mg²⁺ over Na⁺ and K⁺, as well as a higher prevalence of HCO₃⁻ and Cl⁻ compared to SO₄²⁻. The Piper diagram (Figure 5), which illustrated the hydrochemical facies of Phewa Lake, confirms the dominance of carbonate lithology. The observed prevalence of Ca²⁺/Mg²⁺ and HCO₃⁻ suggest that rock weathering is the primary factor influencing the lake’s water chemistry [60]. Similar patterns have been reported in the geochemical facies of Rara Lake [46], the West Seti River basin in far western Nepal [61], and the Dudhkoshi River basin in eastern Nepal [62]. Table 5 summarizes the six subfields of the diamond Piper diagram and the percentage of samples classified into each segment.

The Gibbs diagram (Figure 7) further highlighted the chemical composition during both the pre-monsoon and post-monsoon periods, with most of the samples in the middle left area, demonstrating that rock–water interactions are the predominant drivers of Phewa Lake’s water chemistry. These findings are consistent with previous studies on numerous freshwater bodies across Nepal [51]. Additionally, the mixing diagram (Figure 10), which plotted Ca²⁺ against HCO₃⁻ and Ca²⁺ against Mg²⁺ (using normalized molar ratios), reveals heterogeneity in the lake’s hydrochemistry. The results show that carbonates, being more soluble and reactive to natural weathering than silicates [63], play a significant role. Most of the samples from both the pre-and post-monsoon periods were clustered near carbonate end-members, reaffirming the dominance of carbonate weathering [25]. Correlation analyses of Ca²⁺/Na⁺ with Mg²⁺/Na⁺ and HCO₃⁻/Na⁺ suggest that atmospheric deposition and anthropogenic contributions have a negligible influence on the lake’s hydrochemical profile.

4.5. Implications of Sustainable Management Strategy (SMS)

The SMS outlined in this study (Figure 11) can present a cohesive and replicable method for addressing the intricate water quality challenges faced by Phewa Lake. The SMS can offer comprehensive insights into pollution sources and their impacts by applying geochemical indices, advanced statistical analyses, and seasonal monitoring. This alignment with the SDGs may ensure that the proposed actions can be environmentally sustainable, economically viable, and socially advantageous. Below, the implications of the SMS are examined within the environmental, economic, and social dimensions of sustainability, supplemented by references to similar studies.

4.5.1. Environmental Pillar

The SMS can offer valuable insights for mitigating nutrient loading and identifying pollution hotspots, particularly from agricultural runoff and untreated urban effluents, which are major contributors to eutrophication. The SMS can focus on preserving natural geochemical processes while effectively addressing human-induced stressors by utilizing tools such as the Piper and Gibbs diagrams. Unlike studies that primarily concentrate on seasonal variations [15], the SMS can incorporate long-term restoration initiatives to strengthen ecosystem resilience. Furthermore, it can highlight the importance of adaptive management strategies to tackle climate variability, a critical challenge emphasized by Gurung et al. [46]. In addition to protecting natural processes, the SMS can enhance the ecological integrity of freshwater ecosystems, providing a scalable framework for managing lakes subjected to similar anthropogenic pressures.

4.5.2. Economic Pillar

The economic implications of the SMS can be closely linked to its emphasis on sustainable resource utilization and cost-effective interventions. By enhancing water quality, the SMS can support essential economic activities, such as fisheries and eco-tourism, while simultaneously reducing the financial impact of water resource degradation. Similar economic advantages have observed in studies like that by Watson et al. [20], which highlighted the cost-saving potential of proactive management in minimizing restoration expenses. The incorporation of spatial and temporal analyses within the SMS can enable precise intervention targeting, optimizing economic outcomes while safeguarding vital natural resources. Furthermore, the alignment of the SMS with SDG 12 is evident in its promotion of practices such as reducing pesticide and fertilizer misuse and improving waste management systems, ensuring sustainable economic benefits over the long term.

4.5.3. Social Pillar

The SMS can strongly emphasize public health and social equity by addressing contaminants that can pose risks to local communities. Through seasonal monitoring, the SMS can ensure that pollutant levels, such as NH₄⁺ and PO₄³⁻, can be effectively managed, reducing the risk of waterborne diseases. Research by Pant et al. [18] has highlighted the importance of Himalayan freshwater systems and community-based interventions. The SMS can expand on these efforts by integrating urban waste management strategies. These initiatives can align with SDG 11, improving urban environments and fostering local stewardship. Moreover, by preserving the lake’s recreational and cultural significance, the SMS can promote community engagement in its management, an approach also advocated by Pradhan et al. [16].

By addressing these interconnected dimensions, the SMS can establish itself as a holistic and scalable framework for sustainable lake management, offering significant contributions to local and global sustainability efforts.

5. Limitations and Future Research

This study on Phewa Lake’s water quality provides a detailed insight into seasonal and spatial variations, yet it exhibits notable limitations. One significant limitation is the reliance on a limited temporal dataset, with sampling confined to two periods (pre-monsoon and post-monsoon), which might not fully capture year-round variability or extreme events. This temporal restriction limits the ability to generalize findings across other seasonal conditions or climatic extremes [64]. Furthermore, the study primarily examined physicochemical parameters, potentially neglecting biological and ecological aspects, such as the diversity and abundance of aquatic biota, which may be essential for a comprehensive understanding of ecosystem health [65]. While detailed within the lake, the spatial resolution of sampling did not account for upstream and diffuse pollution sources adequately, potentially missing critical contributions from anthropogenic activities in the catchment area. Additionally, the absence of longitudinal data and predictive modeling constrained the ability to forecast future water quality trends under scenarios of increased climatic variability and human activities [66].

Future studies should adopt a more holistic and integrative approach to address these gaps, focusing on urban-centered lakes to understand the role of internal lake supply better. In addition, long-term monitoring covering year-round variations, is necessary to understand the impacts of extreme climatic events and anthropogenic influences on water quality [67]. Incorporating trace elements, biological indicators such as phytoplankton diversity, macroinvertebrate populations, and fish assemblages would provide an ecological dimension to complement physicochemical analyses [68]. Expanding spatial coverage to include upstream tributaries and adjacent land uses would help to identify specific pollution sources and their contributions to lake water quality. Advanced modeling techniques that integrate geochemical, hydrological, and ecological parameters could enhance predictive capabilities under different climate and land use scenarios [69]. Finally, incorporating community engagement and traditional ecological knowledge can provide valuable insights and promote sustainable water resource management strategies [70].

6. Conclusions

This study analyzed seasonal and spatial fluctuations in Phewa Lake’s water quality by examining 20 physicochemical parameters across 30 sampling stations during the pre-monsoon and post-monsoon periods. The lake’s hydrochemistry was primarily influenced by carbonate weathering, with Ca²⁺ concentrations of 14.77 mg/L (pre-monsoon) and 13.39 mg/L (post-monsoon), and HCO₃⁻ levels ranging from 59.83 to 61.4 mg/L. Seasonal variations were evident in pH (8.06–8.24) and DO (7.46–8.62 mg/L), driven by monsoon dilution and carbonate runoff, which improved oxygenation. Nutrient enrichment remained prominent, particularly in regions affected by agricultural runoff and urban effluents, with NO₃⁻ and PO₄³⁻ concentrations reaching 2.31 mg/L and 0.15 mg/L, respectively. CA identified the lake’s outlet as a high-pollution zone, with TDS levels ranging from 108 to 135 mg/L, reflecting significant anthropogenic impacts. PCA further revealed that agricultural runoff and untreated sewage were the primary sources of pollution. Also, the study findings highlighted the severe impact of human-induced stress, particularly during pre-monsoon periods, when pollution levels peaked. While post-monsoon rains offered limited dilution, they failed to counterbalance cumulative anthropogenic effects. These conditions underscore the risks of prolonged eutrophication and ecological degradation if mitigation strategies are not implemented. The SMS can be aligned with SDG 6 (Clean Water and Sanitation), addressing Targets 6.3 (pollution reduction) and 6.6 (ecosystem restoration), while also supporting SDGs 13 (Climate Action) and 15 (Life on Land) by promoting sustainable freshwater management. This study emphasizes the need for continuous monitoring, incorporation of biological markers, and predictive modeling to address long-term climate and human-induced impacts. These insights can be crucial for guiding evidence-based policies and sustainable practices to preserve Phewa Lake’s vital ecological and touristic assets.

Author Contributions

R.T. and S.A. conducted the field and laboratory work. R.M.B. supervised the research. K.P.P., S.J. and M.P.A. supported the multivariate and GIS analysis. B.Đ., G.R.J., A.K., R.R.P., T.K.T. and A.M.S. developed the research concepts and reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by University North, Croatia, under the project “Hydrological and Geodetic Analysis of the Watercourse” in 2024, and the Department of Forests and Soil Conservation (DoFSC), Ministry Forests and Environment, Government of Nepal.

Data Availability Statement

Relevant data are included in the manuscript. Additional data will be available from the corresponding author upon reasonable request.

Acknowledgments

We thank the Central Department of Environmental Science at the Institute of Science and Technology, Tribhuvan University, Kathmandu, Nepal, for providing the laboratory facilities. Special thanks to the Ministry of Forests and Environment, Government of Nepal, for their partial support in this research’s fieldwork. The authors also thank University North, Koprivnica, Croatia, for supporting the research. The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the United Nations.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study area map showing sampling sites in Phewa Lake, Nepal.

Figure 2. Methodological steps of this research.

Figure 3. Physicochemical parameters for Phewa Lake, Nepal, during pre- and post-monsoon periods.

Figure 4. Principal components of the loading plot for Phewa Lake, Nepal. The figure illustrates the relationships among various water quality parameters using different symbols and colors. The red circle represents the chloride ion (Cl⁻), while blue squares denote other ions such as sulfate (SO₄²⁻), nitrate (NO₃⁻), ammonium (NH₄⁺), sodium (Na⁺), potassium (K⁺), and phosphate (PO₄³⁻). Green triangles represent physicochemical parameters, including electrical conductivity (EC), total dissolved solids (TDS), magnesium (Mg²⁺), calcium (Ca²⁺), and bicarbonate (HCO₃⁻). The background planes correspond to the projections of the data points onto the component 1 (PC1), component 2 (PC2), and component 3 (PC3) planes, respectively, derived from a dimensionality reduction technique, i.e., principal component analysis (PCA).

Figure 5. Piper diagram characterizing the hydrochemical facies for Phewa Lake, Nepal. Note: Region 1 corresponds to waters dominated by alkaline earths (Ca²⁺ + Mg²⁺) and weak acids (HCO₃⁻), typically reflecting carbonate weathering. Region 2 denotes waters with alkaline earths and strong acids (Cl⁻ + SO₄²⁻), often linked to gypsum dissolution or anthropogenic inputs. Region 3 represents mixed waters without a dominant ion type, suggesting blending of sources. Region 4 includes waters dominated by alkali metals (Na⁺ + K⁺) and weak acids, indicating silicate weathering or ion exchange. Region 5 features waters rich in alkali metals and strong acids, possibly due to evaporite dissolution or industrial contamination. Lastly, and Region 6 represents transitional waters with no clear dominance, indicating complex geochemical processes or mixing.

Figure 6. Piper diagram showing dominant hydrochemical facies for Phewa Lake compared to Lesser Himalayan freshwater lakes in Nepal. Note: Region 1 corresponds to waters dominated by alkaline earths (Ca²⁺ + Mg²⁺) and weak acids (HCO₃⁻), typically reflecting carbonate weathering. Region 2 denotes waters with alkaline earths and strong acids (Cl⁻ + SO₄²⁻), often linked to gypsum dissolution or anthropogenic inputs. Region 3 represents mixed waters without a dominant ion type, suggesting blending of sources. Region 4 includes waters dominated by alkali metals (Na⁺ + K⁺) and weak acids, indicating silicate weathering or ion exchange. Region 5 features waters rich in alkali metals and strong acids, possibly due to evaporite dissolution or industrial contamination. Lastly, and Region 6 represents transitional waters with no clear dominance, indicating complex geochemical processes or mixing.

Figure 7. Gibbs diagram showing (a) TDS vs. Na⁺/ (Na⁺ + Ca²⁺) and (b) TDS vs. Cl⁻/(Cl⁻ + HCO₃⁻) for Phewa Lake, Nepal.

Figure 8. Variation in weight ratio of (a) Na⁺/(Na⁺ + Ca²⁺) and (b) Cl⁻/(Cl⁻ + HCO₃⁻), as a function of TDS, in Gibbs diagram for Phewa Lake compared to Lesser Himalayan freshwater lakes in Nepal.

Figure 9. Mixing diagram for Phewa Lake, showing Na⁺-normalized molar ratios of (a) Ca²⁺ vs. HCO₃⁻, and (b) Ca²⁺ vs. Mg²⁺.

Figure 10. Mixing diagram showing Na⁺-normalized molar ratios of (a) Ca²⁺ vs. HCO₃⁻, and (b) Ca²⁺ vs. Mg²⁺, for Phewa Lake, compared to lesser Himalayan freshwater lakes, in Nepal.

Figure 11. Quantitative correlation of sustainable management strategy (SMS) with sustainable development goals (SDGs) for Phewa Lake, Nepal.

Table 1. Spearman correlation matrix of physicochemical parameters for Phewa Lake, Nepal.

	Temp	pH	EC	TDS	Ca²⁺	Mg²⁺	K⁺	Na⁺	NO₃⁻	Cl⁻	SO₄²⁻	HCO₃⁻	PO₄³⁻	NH₄⁺	DO	Turb	TH	CaH	MgH	F-CO₂
Temp	1
pH	−0.12	1
EC	0.30 *	−0.23	1
TDS	0.21	−0.15	0.75 **	1
Ca²⁺	0.12	−0.25	0.45 **	0.45 **	1
Mg²⁺	−0.16	0.04	0.27 *	0.41 **	0.39 **	1
K⁺	0.10	0.05	−0.02	0.02	−0.04	−0.38 **	1
Na⁺	0.08	0.18	−0.04	0.07	−0.10	−0.29 *	0.86 **	1
NO₃⁻	−0.10	−0.11	−0.04	−0.02	0.21	0.32 *	−0.76 **	−0.72 **	1
Cl⁻	0.005	0.22	−0.03	0.06	−0.22	−0.17	0.17	0.24	−0.19	1
SO₄²⁻	−0.04	−0.11	0.07	−0.01	0.06	0.29 *	−0.74 **	−0.70 **	0.75 **	−0.21	1
HCO₃⁻	0.16	0.04	0.53 **	0.69 **	0.61 **	0.37 **	0.05	0.06	0.03	0.03	0.02	1
PO₄³⁻	0.05	0.25	−0.11	−0.05	−0.16	−0.31 *	0.72 **	0.70 **	−0.75 **	0.15	−0.67 **	−0.010	1
NH₄⁺	0.07	0.25	−0.05	0.07	−0.15	−0.27 *	0.75 **	0.75 **	−0.70 **	0.13	−0.66 **	−0.009	0.64 **	1
DO	−0.19	0.02	−0.23	−0.05	−0.11	−0.33 **	0.62 **	0.55 **	−0.47 **	0.18	−0.56 **	−0.09	0.39 **	0.49 **	1
Turb	0.13	0.06	−0.09	−0.20	−0.08	0.006	−0.22	−0.20	0.23	−0.03	0.27 *	−0.15	−0.10	−0.19	−0.23	1
TH	0.08	0.04	0.54 **	0.63 **	0.72 **	0.65 **	0.02	0.07	0.008	−0.16	−0.03	0.75 **	−0.003	0.07	−0.15	−0.22	1
CaH	−0.05	0.07	0.31 *	0.23	0.57 **	0.25	0.09	0.11	0.009	−0.14	−0.08	0.39 **	0.007	0.005	−0.03	−0.29 *	0.62 **	1
MgH	−0.06	−0.06	0.26 *	0.41 **	0.29 *	0.80 **	−0.23	−0.19	0.18	−0.15	0.20	0.36 **	−0.14	−0.14	−0.21	0.06	0.57 **	−0.14	1
F-CO₂	0.02	−0.14	0.20	0.06	0.12	0.26 *	−0.57 **	−0.54 **	0.667 **	−0.20	0.69 **	0.15	−0.60 **	−0.55 **	−0.53 **	0.21	0.04	0.05	0.13	1

Note: All parameters are expressed in mg/L, except for pH (dimensionless), Temp (°C), EC (μS/cm), and Tur (NTU). * Correlation is significant at the 0.05 level (one-tailed), and ** Correlation is significant at the 0.01 level (one-tailed).

Table 2. Rotated component matrix for Phewa Lake, Nepal.

Parameters	Components
Parameters	PC1	PC2	PC3
EC	0.195	0.827	0.098
TDS	0.228	0.867	0.058
Ca²⁺	−0.080	0.520	−0.405
Mg²⁺	−0.272	0.445	−0.220
K⁺	0.919	0.045	0.053
Na⁺	0.901	0.121	0.101
NO₃⁻	−0.925	−0.053	−0.081
Cl⁻	−0.005	0.049	0.934
SO₄²⁻	−0.833	−0.077	−0.036
HCO₃⁻	−0.003	0.783	0.038
PO₄³⁻	0.879	0.027	−0.019
NH₄⁺	0.724	−0.080	−0.047
Eigen Value	4.778	2.483	1.086
% of Variance	39.813	20.693	9.048
Cumulative %	39.813	60.506	69.553

Note: All parameters are expressed in mg/L, except for EC (μS/cm).

Table 3. Hydrochemical comparison of the present study and previous studies in Phewa Lake, Nepal.

pH	EC	TDS	DO	Turb	Ca²⁺	Mg²⁺	K⁺	Na⁺	NO₃⁻	Cl⁻	SO₄²⁻	HCO₃⁻	PO₄³⁻	NH₄⁺	Reference
8.06	80.5	43.13	7.46	5.68	14.77	4.13	0.31	2.62	2.31	10.81	7.64	59.83	0.12	0.08	Present study (pre-monsoon)
8.24	109.17	58.3	8.62	2.57	13.39	3.02	2.68	6.04	0.74	11.62	1.79	61.4	0.15	0.15	Present study (post-monsoon)
6.83	50.04	24.78	9.87	20.78	5.52	2.41	1.61	5.41	0.043	-	7.48	22.2	0.025	0.629	Kafle et al. [48]
7.93	86.45	74.89	10.39	-	8.68	1.84	1.4	3.32	5.2	1.57	9.16	28.24	0.08	-	Khadka and Ramanathan [2]
7.98	77	42	6.08	-	8.74	1.25	1.33	1.54	0.91	1.48	1.79	22.65	-	-	Pant et al. [18]
7.93	67.1	33.54	7.2	10.71	-	-	-	-	0.48	13.52	-	-	-	-	Pradhan et al. [16]

Note: All parameters are expressed in mg/L, except for pH (dimensionless), EC (μS/cm), and Turb (NTU).

Table 4. The major ion concentration of Phewa Lake is higher than that of some Lesser Himalayan freshwater lakes in Nepal.

Lakes	Ca²⁺	Mg²⁺	K⁺	Na⁺	NO₃⁻	Cl⁻	SO₄²⁻	HCO₃⁻	PO₄³⁻	NH₄⁺	Reference
Phewa	14.77	4.13	0.31	2.62	2.31	10.81	7.64	59.83	0.12	0.08	Present study (pre-monsoon)
Phewa	13.39	3.02	2.68	6.04	0.74	11.62	1.79	61.4	0.15	0.15	Present study (post-monsoon)
Begnas	17.5	2.17	1.2	3.08	3.36	2.77	9.77	40.4	0.16	-	Khadka and Ramanathan [45]
Ghodaghodi	21.48	2.78	2.76	3.52	0.15	0.38	0.045	81.48		0.255	Bhatta et al. [51]
Jagadishpur	10.73	5.2	2.92	8.53	0.99	10.89		100	0.2	2.44	Sapkota et al. [52]
Koshi Tappu	15.46	5.95	3.15	8.55	0.33	9.33	9.79	49.98	0.11	0.33	Neupane et al. [53]
Mai Pokhari	-	-	-	-	1.39	-	-	-	1.88	0.99	Josi and Sharma [44]
Rajarani	5.56	1.96	2.67	8.09	0.06	11.64	-	32.75	0.25	0.37	Pant et al. [54]
Ramaroshan	12.02	3.51	1.67	5.89	0.44	4.41	0.48	61.58	0.16	0.13	Thapa et al. [55]
Tilicho	20.7	5.75	0.31	0.86	-	1.8	8.6	-	-	-	Aizaki et al. [56]
Renuka	57.74	38.3	2.02	8.33	-	11.92	6.41	146.42	6.4	-	Das and Kaur [57]
Pandoh	17.96	3.31	2.06	3.82	10.33	2.37	2.74	49.17	1.28	-	Anshumali and Ramanathan [13]

Note: All parameters are expressed in mg/L.

Table 5. Subfields of diamond Piper diagram for Phewa Lake, Nepal.

Subfields	Water Type	Percentage of Sample
1	Ca²⁺-HCO₃⁻	98.34%
2	Na⁺-Cl⁻	-
3	Mixed Ca²⁺-Na⁺-HCO₃⁻	1.66%
4	Mixed Ca²⁺-Mg²⁺-Cl⁻	-
5	Ca²⁺-Cl⁻	-
6	Na⁺-HCO₃⁻	-

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Timalsina, R.; Acharya, S.; Đurin, B.; Awasthi, M.P.; Pant, R.R.; Joshi, G.R.; Byanju, R.M.; Panthi, K.P.; Joshi, S.; Kumar, A.; et al. An Assessment of Seasonal Water Quality in Phewa Lake, Nepal, by Integrating Geochemical Indices and Statistical Techniques: A Sustainable Approach. Water 2025, 17, 238. https://doi.org/10.3390/w17020238

AMA Style

Timalsina R, Acharya S, Đurin B, Awasthi MP, Pant RR, Joshi GR, Byanju RM, Panthi KP, Joshi S, Kumar A, et al. An Assessment of Seasonal Water Quality in Phewa Lake, Nepal, by Integrating Geochemical Indices and Statistical Techniques: A Sustainable Approach. Water. 2025; 17(2):238. https://doi.org/10.3390/w17020238

Chicago/Turabian Style

Timalsina, Rojesh, Surendra Acharya, Bojan Đurin, Mahesh Prasad Awasthi, Ramesh Raj Pant, Ganesh Raj Joshi, Rejina Maskey Byanju, Khim Prasad Panthi, Susan Joshi, Amit Kumar, and et al. 2025. "An Assessment of Seasonal Water Quality in Phewa Lake, Nepal, by Integrating Geochemical Indices and Statistical Techniques: A Sustainable Approach" Water 17, no. 2: 238. https://doi.org/10.3390/w17020238

APA Style

Timalsina, R., Acharya, S., Đurin, B., Awasthi, M. P., Pant, R. R., Joshi, G. R., Byanju, R. M., Panthi, K. P., Joshi, S., Kumar, A., Thakur, T. K., & Saqr, A. M. (2025). An Assessment of Seasonal Water Quality in Phewa Lake, Nepal, by Integrating Geochemical Indices and Statistical Techniques: A Sustainable Approach. Water, 17(2), 238. https://doi.org/10.3390/w17020238

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