Abstract
Wetlands deliver many ecosystem services but are under continuous threat due to various anthropogenic activities. The present study has been carried out to examine the suitability of Kusheshwar-Asthan wetland's water for agriculture. A total of 57 water samples were analyzed for various water quality parameters like electrical conductivity, pH, temperature, dissolved oxygen (DO), major cations (Ca2+, Mg2+, Na+, K+), and major anions (PO43–, SO42−, N-NO3−, Cl−, HCO3−). Overall, the water of the wetland was found to be alkaline. The pre-monsoon samples had a relatively higher concentration in most of analyzed parameters except for pH, DO, NO3−, PO43− and Cl−. The concentration of cations follows the order of Na+ > Ca2+ > Mg2+ > K+ in both seasons and for anions it is HCO3− > SO42− > Cl− > NO3− > PO43− for pre-monsoon and HCO3− > Cl− > SO42− > NO3− > PO43− for post-monsoon. According to Piper diagram and Durov plot, Na-K-HCO3 was the major hydro chemical facies of the surface water. The various irrigation quality parameters showed that wetland water can be categorized as good to excellent quality. As a result, this finding can aid in the long-term sustainable use of the wetland water with regulated anthropogenic interventions. The study will be beneficial in designing long-term extensive management plans for the conservation of the wetland.
HIGHLIGHTS
Major cation was Na+ and major anion was HCO3− in Kusheshwar Asthan Wetland water.
The surface water was alkaline in nature.
Hydrochemistry of water is influenced by silicate weathering.
Salinity hazard, SAR, RSC, Mg/Ca and chloride hazard indicates the agriculture suitability of the water.
Novel work for wetlands protection and conservation.
Graphical Abstract
INTRODUCTION
Freshwater resources are essential for the survival of various life forms. The freshwater resources contribute only 3% of the total water resources, out of which only 1% is available for human usage (Deep et al. 2020). Due to the population explosion and higher human dependency on freshwater sources, these resources are under tremendous stress and are deteriorating at a faster rate (Bassi et al. 2014). The area of fresh water sources is shrinking and is also being polluted by anthropogenic influences, thus both quantity and quality are under threat. Today, the world is struggling with basic consumptive water usages like drinking, manufacturing, livestock rearing, and agriculture due to the dilapidated condition of freshwater resources and their distribution (Singh et al. 2017). Wetlands as an important freshwater resource are transition areas between land and water ecosystems and have unique features in terms of soil, vegetation, flora and fauna. Wetlands deliver many ecosystem services including flood control, food and water supply, water for irrigation, groundwater recharge, biodiversity support, nutrient cycling, pollution abatement, and livelihood support (Verma & Negandhi 2011). Ramsar Convention on wetlands (2021) points out that more than 35% of natural wetlands have been lost globally between 1970 and 2015 and the loss of inland wetlands is higher than the coastal ones. The wetlands are under continuous threat from various anthropogenic activities including encroachment for urbanization, industrialization, agricultural land expansion and alteration of hydrological regimes (Gopal 2013). The discharge of untreated or partially treated wastewaters emanating from sewage treatment plants (STPs), industries, municipalities, agricultural and urban runoff into wetlands are also reasons for the poor condition of the wetlands (Bassi et al. 2014; Shan et al. 2021). The inflow and outflow of the water from wetlands is an important factor that governs various wetland processes and their hydrological regimes (Mitsch & Gossilink 2000). The hydrological condition of the wetlands causes variations in the hydro-geochemistry of the water of the wetlands; at times these variations are influenced by human–wetlands relations. Hydro-geochemical assessment of wetlands water is thus conducive to the understanding of its nature, source of ions, pollution status and its suitability for water usage, mostly for irrigation.
North Bihar (northern side of the River Ganges) is blessed with plenty of wetlands locally known as chaurs (natural depressions), moins (oxbow lakes), and pokhars (natural or artificial ponds) that are lifelines by serving the community for irrigation, fishing, foxnut (makhana) and water chestnut (singhara) cultivation. Kusheshwar Asthan (KA) wetland is one of the important wetlands of North Bihar and is situated in the Darbhanga district of Bihar (India). The wetland has been considered a wetland of international importance (MoEF&CC 2020). It is a bird sanctuary and habitat for a variety of endemic birds and migratory birds of other countries. Besides that, the KA wetlands are a religious place. Still, KA wetlands are struggling with agriculture encroachment, railway-track construction and lesser inflow of water due to the construction of flood control embankments (bunds) on the Koshi and Kamla rivers (WII 2017). The KA wetlands have an unconsolidated boundary without clear-cut demarcations, which results in conflict in land usage. Approximately 78% of the land is government-owned and the rest is private land. The land settlement rights are still pending since it was designated as a bird sanctuary in 1994. Such conflicts have resulted in encroachment of land for agriculture and are responsible for the shrinkage of wetlands and change in land use. Studies on fish diversity (Das et al. 2015), prospects for fisheries development (CIFRI) and biodiversity assessment and its management plan (WII 2017) are the significant studies conducted on KA wetlands. Almost two decades ago one hydro-geochemistry-related study was conducted on KA wetlands with single-season (January 2005) data (Ranjan et al. 2017). Thus, the present study was carried out (i) to explore the hydro-geochemistry of the KA wetlands and to assess the seasonal (pre -monsoon and post-monsoon) influence and spatial variation on it; (ii) to identify and elaborate the sources of major ions in the KA water; and (iii) to assess the suitability of wetlands water for irrigation purposes by using irrigation water quality parameters (sodium absorption ratio, sodium% and Kelly's ratio, etc.). This study will provide scientific baseline data for proper conservation and management of the KA wetlands meeting the requirements of the local population.
MATERIALS AND METHODS
Study area
Geological and hydrogeological setting
Kusheshwar Asthan Wetlands lies between 26°27′N and 25°53′N to 86°40′E and 86°25′E in Koshi-Gandak Basin and has an altitude of 49 m above the mean sea level. KA wetland is spread over 2,921.43 ha including 14 villages within its boundary. The area lies in a hot sub-humid zone with a mean rainfall of 1,025.1 mm per year (Guhathakurta et al. 2020). KA wetlands experience summer from March to mid-June, monsoon from mid-June to September and winter from November to February. These wetlands are fed by the several channels of the perennial rivers of Kamla Balan and Jibish Dhar and by the flood waters of Kamla and Koshi rivers. The slope of the wetland is from north to the southeast which defines the flow of water in the wetland. According to the Ramsar classification system for ‘wetland type’, the wetland is classified as ‘TS-Seasonal’ or intermittent freshwater marshes (WII 2017). During the monsoon season, the wetland is inundated with rain water and flood from adjoining rivers, and more than 80% of the wetland is flooded, while during summer, the wetland shrinks, and clear patches of individual chaurs appear. The KA wetland is a Gangetic alluvial floodplain wetland. Rivers and floods bring large amounts of sand, silt and clay every year. The soil has a high amount of sand followed by clay and silt. The soil is generally rich in organic matter making it suitable for agriculture (Mandal 2010).
Environmental and cultural significance
The KA wetlands are home to plenty of winter migratory birds besides the resident water birds. Due to its importance for water birds, the wetland was declared a bird sanctuary in 1994. It was classified as an Important Bird Area (A1 category) by Bird Life International and the Royal Society for Protection of Birds, UK (Ranjan et al. 2017). IUCN red-listed species like avian fauna (Anhinga melanogaster, Ciconia episcopus, Mycteria leucocephala, Aythya nyroca, Numenius arquata) and reptiles (Python molurus) were reported in the wetland area (WII 2017). The major aquatic vegetation communities include Alternanthera, Eichhornia, Ottelia, Nymphoides, Ipomea and Vallisneria (WII 2017). Having a rich repository of flora, fauna, and fishes, the wetland is recognized as a wetland of national importance under the National Wetland Conservation and Management Programme by the Government of India (https://indianwetlands.in/). The wetland absorbs the excessive flood water from adjoining rivers and protects the area from complete inundation. Furthermore, wetland supports the livelihood of the local people. These people depend on the wetland for agriculture, fisheries, and fodder mainly. Besides this, the KA temple of Lord Shiva popularly known as ‘Kush Mahadev’ adds religious and cultural importance to the wetland area. The temple is visited by thousands of pilgrims every year.
Sample collection
The water samples were collected from 25 sites (5 sites per wetland) in pre-monsoon (March 2021) and from 32 sites in post-monsoon (October 2021). During the post-monsoon the inundated area of wetland increases due to rainfall and floods from adjoining rivers. The sampling was done according to the availability and accessibility of water across the wetland. Thus, the number of sampling sites are higher in post-monsoon (32) as compared to pre-monsoon (25). Water samples were collected in pre-washed clean 1 litre HDPE bottles. The samples were stored in the ice box and carefully transported to the laboratory for further chemical analysis. The parameters such as electrical conductivity (EC), pH, temperature, dissolved oxygen (DO), and bicarbonates were measured at the site while other parameters were further analyzed in the laboratory. Sample collection, preservation, transportation and analyses were done according to Standard Methods suggested in APHA (2017). Details of the analytical method used in the study are shown in Table 1.
Water quality parameters with their analytical methods
Water parameter . | Unit of measurement . | Instrument/Method used . | Make and model . |
---|---|---|---|
Electrical conductivity | μS/cm | Digital conductivity meter | Eutech eco Testr EC |
pH | pH units | Digital pH meter | Eutech eco Testr pH |
Temperature | °C | Thermometer | |
Total dissolved solids | mg/L | Oven drying at 105 °C | |
Dissolved oxygen | mg/L | Winkler's titrimetric method | |
N-NO3 | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Ortho-phosphate | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Sulfate | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Sodium | mg/L | Flame photometer | Systronics |
Potassium | mg/L | Flame photometer | Systronics |
Chloride | mg/L | Mohr method | |
Total hardness | mg/L | Titration method | |
Calcium | mg/L | Titration method | |
Magnesium | mg/L | Titration method | |
Bicarbonate | mg/L | Acid titration method |
Water parameter . | Unit of measurement . | Instrument/Method used . | Make and model . |
---|---|---|---|
Electrical conductivity | μS/cm | Digital conductivity meter | Eutech eco Testr EC |
pH | pH units | Digital pH meter | Eutech eco Testr pH |
Temperature | °C | Thermometer | |
Total dissolved solids | mg/L | Oven drying at 105 °C | |
Dissolved oxygen | mg/L | Winkler's titrimetric method | |
N-NO3 | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Ortho-phosphate | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Sulfate | mg/L | Spectrophotometer | PerkinElmer Lamba25 |
Sodium | mg/L | Flame photometer | Systronics |
Potassium | mg/L | Flame photometer | Systronics |
Chloride | mg/L | Mohr method | |
Total hardness | mg/L | Titration method | |
Calcium | mg/L | Titration method | |
Magnesium | mg/L | Titration method | |
Bicarbonate | mg/L | Acid titration method |
Comparison of the average concentration of major ions (in mg/L) of KA wetlands with selected freshwater wetlands of India
Wetland . | Na+ . | Ca2+ . | Mg2+ . | K+ . | HCO3- . | SO42- . | Cl- . | NO3- . | PO43- . | Reference . |
---|---|---|---|---|---|---|---|---|---|---|
KA wetlands (pre-monsoon) | 37.28 | 21.46 | 10.28 | 3.45 | 110.72 | 18.22 | 14.51 | 0.0472 | 0.021 | Present study |
KA wetlands (post-monsoon) | 25.43 | 17.87 | 7.70 | 3.58 | 93.28 | 2.65 | 27.93 | 0.072 | 0.029 | Present study |
Saman wetland, Uttar Pradesh | 91.5 | 23 | 21.5 | 16.5 | 119 | 108.5 | 49 | 54.5 | NA | (Khan et al. 2022) |
Loktak Lake, India (pre-monsoon) | 7.28 | 13.05 | 8.11 | 2.66 | 55.8 | 0.01 | 29.36 | 0.171 | 0.092 | (Mayanglambam & Neelam 2022) |
Loktak Lake, India (post-monsoon) | 6.53 | 9.06 | 7.31 | 2.85 | 58.5 | 0.21 | 16.62 | 0.339 | 0.407 | (Mayanglambam & Neelam 2022) |
Bhindawas Bird Sanctuary, Haryana, India | 31.3 | 18.8 | 17.3 | 2.4 | 100 | 85.3 | 58.2 | 14.2 | 4.9 | (Shan et al. 2021) |
Kabar Tal, Bihar, India (pre-monsoon) | 3.2 | 13.7 | 5.7 | 0.5 | 11.2 | 18.40 | 86.5 | 1.10 | 0.047 | (Gupta et al. 2021) |
Kabar Tal, Bihar, India (post-monsoon) | 4.1 | 22.7 | 12.9 | 4.8 | 17.4 | 47.7 | 37.8 | 0.80 | 0.028 | (Gupta et al. 2021) |
Kabar Tal, Bihar, India (July to November) | NA | 28.34 | 6.34 | NA | 219 | 30.92 | 25.74 | 2.583 | 0.06 | (Singh et al. 2020) |
Gogabil, Bihar, India | NA | NA | NA | NA | NA | NA | 4.77 | 0.037 | 0.034 | (Adhishwar & Chaudhary 2020) |
Deepor Beel, Assam | 24.43 | 94.10 | 3.09 | 17.08 | 101.03 | 56.61 | 63.57 | 15.05 | 2.49 | (Dash et al. 2020) |
Ropar wetland, Punjab | NA | 27.71 | 114.77 | NA | 99.225 | 2.71 | 24.89 | 0.11 | 0.12 | (Akhter & Brraich 2020) |
Renuka Lake (pre-monsoon) | 24.78 | 54.81 | 44.12 | 3.032 | 201.4 | 159.0 | -- | 02.60 | NA | (Kumar et al. 2019) |
Renuka Lake (post-monsoon) | 24.85 | 94.44 | 47.32 | 3.105 | 353.6 | 121.8 | -- | 6.911 | NA | (Kumar et al. 2019) |
Kanjli wetland, Punjab (pre-monsoon) | NA | 30.53 | 7.031 | NA | NA | NA | 22.49 | 4.77 | 0.57 | (Singh et al. 2017) |
Kanjli wetland, Punjab (post-monsoon) | NA | 40.39 | 11.46 | NA | NA | NA | 30.64 | 1.65 | 0.28 | (Singh et al., 2017) |
Nainital Lake, India | 13.1 | 32.7 | 59.3 | 3.7 | 351 | NA | 15.3 | NA | NA | (Das et al., 2005) |
Wetland . | Na+ . | Ca2+ . | Mg2+ . | K+ . | HCO3- . | SO42- . | Cl- . | NO3- . | PO43- . | Reference . |
---|---|---|---|---|---|---|---|---|---|---|
KA wetlands (pre-monsoon) | 37.28 | 21.46 | 10.28 | 3.45 | 110.72 | 18.22 | 14.51 | 0.0472 | 0.021 | Present study |
KA wetlands (post-monsoon) | 25.43 | 17.87 | 7.70 | 3.58 | 93.28 | 2.65 | 27.93 | 0.072 | 0.029 | Present study |
Saman wetland, Uttar Pradesh | 91.5 | 23 | 21.5 | 16.5 | 119 | 108.5 | 49 | 54.5 | NA | (Khan et al. 2022) |
Loktak Lake, India (pre-monsoon) | 7.28 | 13.05 | 8.11 | 2.66 | 55.8 | 0.01 | 29.36 | 0.171 | 0.092 | (Mayanglambam & Neelam 2022) |
Loktak Lake, India (post-monsoon) | 6.53 | 9.06 | 7.31 | 2.85 | 58.5 | 0.21 | 16.62 | 0.339 | 0.407 | (Mayanglambam & Neelam 2022) |
Bhindawas Bird Sanctuary, Haryana, India | 31.3 | 18.8 | 17.3 | 2.4 | 100 | 85.3 | 58.2 | 14.2 | 4.9 | (Shan et al. 2021) |
Kabar Tal, Bihar, India (pre-monsoon) | 3.2 | 13.7 | 5.7 | 0.5 | 11.2 | 18.40 | 86.5 | 1.10 | 0.047 | (Gupta et al. 2021) |
Kabar Tal, Bihar, India (post-monsoon) | 4.1 | 22.7 | 12.9 | 4.8 | 17.4 | 47.7 | 37.8 | 0.80 | 0.028 | (Gupta et al. 2021) |
Kabar Tal, Bihar, India (July to November) | NA | 28.34 | 6.34 | NA | 219 | 30.92 | 25.74 | 2.583 | 0.06 | (Singh et al. 2020) |
Gogabil, Bihar, India | NA | NA | NA | NA | NA | NA | 4.77 | 0.037 | 0.034 | (Adhishwar & Chaudhary 2020) |
Deepor Beel, Assam | 24.43 | 94.10 | 3.09 | 17.08 | 101.03 | 56.61 | 63.57 | 15.05 | 2.49 | (Dash et al. 2020) |
Ropar wetland, Punjab | NA | 27.71 | 114.77 | NA | 99.225 | 2.71 | 24.89 | 0.11 | 0.12 | (Akhter & Brraich 2020) |
Renuka Lake (pre-monsoon) | 24.78 | 54.81 | 44.12 | 3.032 | 201.4 | 159.0 | -- | 02.60 | NA | (Kumar et al. 2019) |
Renuka Lake (post-monsoon) | 24.85 | 94.44 | 47.32 | 3.105 | 353.6 | 121.8 | -- | 6.911 | NA | (Kumar et al. 2019) |
Kanjli wetland, Punjab (pre-monsoon) | NA | 30.53 | 7.031 | NA | NA | NA | 22.49 | 4.77 | 0.57 | (Singh et al. 2017) |
Kanjli wetland, Punjab (post-monsoon) | NA | 40.39 | 11.46 | NA | NA | NA | 30.64 | 1.65 | 0.28 | (Singh et al., 2017) |
Nainital Lake, India | 13.1 | 32.7 | 59.3 | 3.7 | 351 | NA | 15.3 | NA | NA | (Das et al., 2005) |
Statistical analysis
Statistical analysis of the water samples (maximum, minimum, mean, and standard deviation) and irrigation parameters, Gibbs diagram, and plots related to water samples were prepared by Microsoft Excel 2019. Pearson's correlation was analyzed by using SPSS 20. Piper diagram and Durov plot were prepared by Grapher software. Wilcox diagram and USSL diagram were processed by Diagrammes software. Map of the study area and interpolation was done by Arc GIS.
RESULTS AND DISCUSSIONS
Hydro-geochemistry of KA wetland
The water quality of wetland is a reliable indicator of the environmental changes that depend upon various factors including topography, seasons (Kumari & Sharma 2019), soil type, precipitation, surface runoff, evapotranspiration, flooding frequency, nutrient and sediment loading (Ajorlo et al. 2013).
(a) Spatial distribution of temperature in pre-monsoon and post-monsoon in KA wetland. (b) Spatial distribution of pH in pre-monsoon and post-monsoon in KA wetland. (c) Spatial distribution of electrical conductivity in pre-monsoon and post-monsoon in KA wetland. (d) Spatial distribution of dissolved oxygen in pre-monsoon and post-monsoon in KA wetland. (e) Spatial distribution of Ca in pre-monsoon and post-monsoon in KA wetland. (f) Spatial distribution of Mg in pre-monsoon and post-monsoon in KA wetland. (g) Spatial distribution of Na in pre-monsoon and post-monsoon in KA wetland. (h) Spatial distribution of potassium in pre-monsoon and post-monsoon in KA wetland. (i) Spatial distribution of HCO3 in pre-monsoon and post-monsoon in KA wetland. (j) Spatial distribution of chloride in pre-monsoon and post-monsoon in KA wetland. (k) Spatial distribution of nitrate in pre-monsoon and post-monsoon in KA wetland. (l) Spatial distribution of sulfate in pre-monsoon and post-monsoon in KA wetland. (m) Spatial distribution of PO4 in pre-monsoon and post-monsoon in KA wetland.
(a) Spatial distribution of temperature in pre-monsoon and post-monsoon in KA wetland. (b) Spatial distribution of pH in pre-monsoon and post-monsoon in KA wetland. (c) Spatial distribution of electrical conductivity in pre-monsoon and post-monsoon in KA wetland. (d) Spatial distribution of dissolved oxygen in pre-monsoon and post-monsoon in KA wetland. (e) Spatial distribution of Ca in pre-monsoon and post-monsoon in KA wetland. (f) Spatial distribution of Mg in pre-monsoon and post-monsoon in KA wetland. (g) Spatial distribution of Na in pre-monsoon and post-monsoon in KA wetland. (h) Spatial distribution of potassium in pre-monsoon and post-monsoon in KA wetland. (i) Spatial distribution of HCO3 in pre-monsoon and post-monsoon in KA wetland. (j) Spatial distribution of chloride in pre-monsoon and post-monsoon in KA wetland. (k) Spatial distribution of nitrate in pre-monsoon and post-monsoon in KA wetland. (l) Spatial distribution of sulfate in pre-monsoon and post-monsoon in KA wetland. (m) Spatial distribution of PO4 in pre-monsoon and post-monsoon in KA wetland.
pH regulates the biochemical processes within the aquatic environment (Jalal & Kumar 2013; Palit et al. 2018; Deep et al. 2020). The pH in the pre-monsoon ranged from 7.5 to 8.2 and 7.6 to 8.8 in the post-monsoon. Lesser values of pH were observed in the northern part of the wetland. Still there was no major change in the pH of water all over the wetland (Figure 2(b)). The sites having lower pH values were proximate to the human settlements releasing organic waste and their further degradation is linked to formation of decomposition originated acids; however, the higher pH sites were densely populated by wetlands macrophytes. The vigorous growth of phytoplankton cause increase in the pH value (William et al. 1970; Olsen & Summerfield 1977). Decay of organic matter (Langmuir 1997) and the use of agrochemicals for agricultural purposes (Chegbeleh et al. 2020) can contribute to lowering the pH of the wetland in pre-monsoon; at the same time high photosynthesis of macrophytes in wetlands can contribute to higher pH (Gupta et al. 2021). The overall pH of both seasons reflects the alkaline nature of wetland water. The presence of bicarbonates in wetland water may be a reason for its alkaline nature (Tank & Chippa 2013; Kumar et al. 2018). Dissolved oxygen (DO) ranged from 5.6 mg/L to 10.5 mg/L during pre-monsoon. It was 5.8 mg/L to 12 mg/L in post-monsoon. A good spatial variation in the DO was observed at KA wetland. The northern part had relatively lesser DO as grey water was being discharged from the community. Higher DO was recorded in the western part of the wetland, especially in post-monsoon, where abundance of macrophytes was also observed (Figure 2(d)). A similar pattern of DO in pre-monsoon and post-monsoon was observed by Gupta et al. (2021), at Kabar Taal wetland, Bihar and by Singh et al. (2022) at selected Ramsar wetlands of Punjab. Total hardness in water is present due to carbonates, bicarbonates, sulfates and chlorides of magnesium and calcium. Total hardness was observed in the range of 72 mg/L to 128 mg/L in pre-monsoon and 50 mg/L to 100 mg/L in post-monsoon. The minimum and maximum concentrations of calcium in pre-monsoon and post-monsoon were 13.27 mg/L and 28.56 mg/L and 8.41 mg/L to 25.23 mg/L respectively (Figure 2(e)). Calcium is one of the dominant cations in surface water and its major source can be geogenic or it may have entered the wetland from the adjoining streams flowing over rocks composed of gypsum and limestone (Bhateria & Jain 2016). The presence of calcium ions can be due to weathering of silicate rocks containing plagioclase minerals (Kadam et al. 2021). Magnesium, which is naturally present in surface water, is derived from weathering of rocks containing magnesium minerals like biotite, olivine, and augite (Kadam et al. 2021). The concentration of magnesium remains lower than the calcium (Tulsankar et al. 2020). It is an important micronutrient for the algae and macrophytes and for phytoplankton it is a limiting factor for their growth (White & Brown 2010; Dijkstra et al. 2019). The concentration of magnesium ranged from 6.32 to 17.84 mg/L and 2.92 to 14.22 mg/L in pre- and post-monsoon respectively (Figure 2(f)). The average concentration of magnesium was 10.28 mg/L in pre-monsoon and 7.70 mg/L in post-monsoon. The range of calcium and magnesium is similar to the findings of Ranjan et al. (2017) and Singh et al. (2017). Sodium ranged from 17.54 mg/L to 59.28 mg/L in pre-monsoon and 20.12 mg/L to 34.07 mg/L in post-monsoon (Figure 2(g)). A relatively high concentration of sodium was also reported in Bhindawas wetland (Shan et al. 2021) and Saman wetland (Khan et al. 2022). Chemical dissolution of minerals and cation exchange can be ascribed to the increased concentration of sodium. The concentration of potassium was found to be 1.84 mg/L to 6.11 mg/L in pre-monsoon and 2.90 mg/L to 4.73 mg/L in post-monsoon (Figure 2(h)). The concentration of potassium in KA wetlands was similar to most other freshwater wetlands (Table 2) except Deepor Beel, which receives landfill leachate and industrial waste (Dash et al. 2020). The major source of sodium and potassium in natural water may be attributed to the weathering and dissolution of silicate minerals like feldspars (Arulbalaji & Gurugnanam 2017), agricultural activities (Kumar et al. 2018), cation-anion exchange (Khan et al. 2022) and sewage discharge from localities (Dixit et al. 2021). A relatively lower value in post-monsoon can be due to dilution of ions through monsoon showers.
The cationic trend follows the order of Na+ > Ca2+ >Mg2+ >K+ in both seasons at KA wetlands. Bhindawas bird sanctuary, Haryana and Saman Wetland, Uttar Pradesh, have a similar order of cation concentrations to that of KA wetland (Table 2).
The concentration of chloride in KA wetland varied from 10.78 mg/L to 19.96 mg/L in pre-monsoon and 21.99 mg/L to 33.99 mg/L in post-monsoon (Figure 2(j)). Chloride in surface water comes from rocks, runoff from agricultural fields, or the discharge of sewage from surrounding areas (Singh et al. 2022). The increase in concentration of chloride in post-monsoon can be due to runoff from adjoining areas in monsoon. A similar trend for chloride ions (pre-monsoon and post-monsoon) was found in Kanjli Wetland (Singh et al. 2017) (Table 2). Bicarbonates were observed to be higher in pre-monsoon than post-monsoon. It was reported to be 88.0 mg/L to 146.0 mg/L and 60 mg/L to 105 mg/L in pre-monsoon and post-monsoon respectively (Figure 2(i)). The data hints that there is intense weathering of silicate and carbonate minerals and decomposition of organic matter in pre-monsoon (Mayanglambam & Neelam 2022). Its source can be also linked to the dissolution of carbonates (Kumar et al. 2021). Similar values of bicarbonates were reported in Saman Wetland, Uttar Pradesh and Ropar wetland, Punjab (Table 2).
The phosphate content at KA wetlands was observed in the range of 0.01 mg/L to 0.09 mg/L in pre-monsoon and 0.01 mg/L to 0.06 mg/L in post-monsoon. The spatial variation of the phosphate is presented in Figure 2(m). Weathering of rocks containing phosphorus and decomposition of organic matter are some of the natural sources of phosphate in surface water (Dixit et al. 2021), whereas intensive use of phosphate fertilizers is one of the most common anthropogenic sources of phosphate in surface water (Khan et al. 2012). The phosphate concentration in the KA wetland water is similar to the other wetlands of Bihar like Kabar Tal and Gogabil (Table 2). The concentration of nitrate varied from 0.01 mg/L to 0.09 mg/L in pre-monsoon and 0.04 mg/L to 0.10 mg/L in post-monsoon (Figure 2(k)). The natural sources of nitrate include nitrification processes and weathering of igneous rocks (Stadler et al. 2012; Dixit et al. 2021), whereas anthropogenic sources include agricultural runoff or animal wastes (Arulbalaji & Gurugnanam 2017). Similar nitrate content has been reported in the Gogabil wetland of Bihar (Table 2). Nitrate and phosphate are important parameters that indicate the pollution status of wetland water. Higher concentration of nitrate and phosphate can lead to eutrophication (Prashant et al. 2022). KA wetlands are surrounded by 14 nearby villages. The discharge of untreated municipal waste directly into wetland area and the use of urea, diammonium phosphate (DAP) and other fertilizers for increasing crop productivity are some of the major sources of nitrate and phosphate. Sulfate is found naturally in almost all kinds of water resources. The key sources of sulfate are weathering of rocks like gypsum and pyrite (Ranjan et al. 2017), atmospheric deposition, and the use of sulfate-rich fertilizers (Arulbalaji & Gurugnanam 2017). Pre-monsoon data showed an elevated concentration of sulfates compared with post-monsoon. It ranged from 2.21 mg/L to 34.12 mg/L in pre-monsoon and 0.56 mg/L to 5.5 mg/L in post-monsoon (Figure 2(l)). The sulfate content of KA wetland and Kabar Taal wetland has similar values during pre-monsoon (Table 2). The KA wetlands remain inundated for nearly six months annually. A single season crop (mostly maize) is cultivated within the wetland area during dry periods. The central and southern parts of the wetland are agricultural infested areas. The higher values of phosphate and sulfate in the central and southern parts is ascribed to fertilizer usages to enhance crop productivity (Figure 2(m) and 2(l)). The dominance of anions in the wetland follows the trend of HCO3− > SO42− > Cl− > NO3− > PO43− in pre-monsoon and HCO3− > Cl− > SO42− > NO3− > PO43− in post-monsoon. The central part and southern part of the wetland are fed by more than one river stream (Kamla Balan and Jibish dhar). Sometimes, flood water of Koshi river also joins the area, whereas the western part is being fed by flooded Kamla alone. The site has relatively less water than the other sites. This can be one of the reasons for the relatively different behavior of the site.
Table 3 depicts physicochemical composition of KA wetland water during pre-monsoon and post-monsoon.
Physicochemical composition of KA wetland water during pre-monsoon and post-monsoon
Parameters . | Pre-monsoon . | Post-monsoon . | ||||||
---|---|---|---|---|---|---|---|---|
Minimum . | Maximum . | Mean . | Standard deviation . | Minimum . | Maximum . | Mean . | Standard deviation . | |
Temperature | 26 | 28.2 | 27.40 | 0.55 | 25 | 26.50 | 25.83 | 0.52 |
EC | 250 | 540 | 380.4 | 74.08 | 101.5 | 222.39 | 165.85 | 31.83 |
pH | 7.5 | 8.2 | 7.87 | 0.186 | 7.60 | 8.80 | 8.09 | 0.28 |
DO (mg/L) | 5.6 | 10.5 | 7.968 | 1.044 | 5.80 | 12 | 8.38 | 1.58 |
TH (mg/L) | 72 | 128 | 98.96 | 13.07 | 50 | 100 | 76.28 | 15.87 |
Ca2+ (mg/L) | 13.27 | 28.56 | 21.46 | 4.50 | 8.41 | 25.23 | 17.87 | 3.87 |
Mg2+ (mg/L) | 6.32 | 17.84 | 10.28 | 2.35 | 2.92 | 14.22 | 7.70 | 2.62 |
Na + (mg/L) | 17.54 | 59.28 | 37.28 | 12.43 | 20.12 | 34.07 | 25.43 | 2.80 |
K + (mg/L) | 1.84 | 6.11 | 3.45 | 1.34 | 2.90 | 4.73 | 3.58 | 0.371 |
HCO3− (mg/L) | 88 | 146 | 110.72 | 17.40 | 60 | 105 | 93.28 | 2.072 |
SO42− (mg/L) | 2.21 | 34.23 | 18.22 | 11 | 0.56 | 5.5 | 2.65 | 1.14 |
PO43− (mg/L) | 0.01 | 0.03 | 0.021 | 0.007 | 0.01 | 0.061 | 0.029 | 0.015 |
NO3− (mg/L) | 0.01 | 0.09 | 0.0472 | 0.02 | 0.045 | 0.108 | 0.072 | 0.019 |
Cl− (mg/L) | 10.78 | 19.96 | 14.51 | 2.58 | 21.99 | 33.99 | 27.93 | 3.57 |
Parameters . | Pre-monsoon . | Post-monsoon . | ||||||
---|---|---|---|---|---|---|---|---|
Minimum . | Maximum . | Mean . | Standard deviation . | Minimum . | Maximum . | Mean . | Standard deviation . | |
Temperature | 26 | 28.2 | 27.40 | 0.55 | 25 | 26.50 | 25.83 | 0.52 |
EC | 250 | 540 | 380.4 | 74.08 | 101.5 | 222.39 | 165.85 | 31.83 |
pH | 7.5 | 8.2 | 7.87 | 0.186 | 7.60 | 8.80 | 8.09 | 0.28 |
DO (mg/L) | 5.6 | 10.5 | 7.968 | 1.044 | 5.80 | 12 | 8.38 | 1.58 |
TH (mg/L) | 72 | 128 | 98.96 | 13.07 | 50 | 100 | 76.28 | 15.87 |
Ca2+ (mg/L) | 13.27 | 28.56 | 21.46 | 4.50 | 8.41 | 25.23 | 17.87 | 3.87 |
Mg2+ (mg/L) | 6.32 | 17.84 | 10.28 | 2.35 | 2.92 | 14.22 | 7.70 | 2.62 |
Na + (mg/L) | 17.54 | 59.28 | 37.28 | 12.43 | 20.12 | 34.07 | 25.43 | 2.80 |
K + (mg/L) | 1.84 | 6.11 | 3.45 | 1.34 | 2.90 | 4.73 | 3.58 | 0.371 |
HCO3− (mg/L) | 88 | 146 | 110.72 | 17.40 | 60 | 105 | 93.28 | 2.072 |
SO42− (mg/L) | 2.21 | 34.23 | 18.22 | 11 | 0.56 | 5.5 | 2.65 | 1.14 |
PO43− (mg/L) | 0.01 | 0.03 | 0.021 | 0.007 | 0.01 | 0.061 | 0.029 | 0.015 |
NO3− (mg/L) | 0.01 | 0.09 | 0.0472 | 0.02 | 0.045 | 0.108 | 0.072 | 0.019 |
Cl− (mg/L) | 10.78 | 19.96 | 14.51 | 2.58 | 21.99 | 33.99 | 27.93 | 3.57 |
Note: In pre-monsoon (n = 25) and in post-monsoon (n = 32).
Hydrochemical facies
Piper diagram
Piper diagram showing different hydrochemical classifications for pre-monsoon and post-monsoon of KA wetland.
Piper diagram showing different hydrochemical classifications for pre-monsoon and post-monsoon of KA wetland.
Durov plot
Gibbs diagram
(a) log TDS vs Cl/(Cl + HCO3), (b) log (TDS) vs (Na + K)/(Na + K + Ca) for pre-monsoon and post-monsoon.
(a) log TDS vs Cl/(Cl + HCO3), (b) log (TDS) vs (Na + K)/(Na + K + Ca) for pre-monsoon and post-monsoon.
Plots of (a) Mg2+/Na+ vs Ca2+/Na+ and (b) HCO3− vs Ca2+/Na+ representing the end-member diagram for identification of type of weathering prevailing in KA wetland.
Plots of (a) Mg2+/Na+ vs Ca2+/Na+ and (b) HCO3− vs Ca2+/Na+ representing the end-member diagram for identification of type of weathering prevailing in KA wetland.
Correlation matrix
To understand the interrelationship between different physicochemical parameters, a Pearson-correlation analysis was conducted in the study area (Table 4).
Correlation matrix for (a) pre-monsoon and (b) post-monsoon
Correlations . | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | Temp . | pH . | EC . | DO . | TH . | Ca . | Mg . | Na . | K . | Cl . | NO3 . | PO4 . | SO4 . | HCO3 . |
(a) Pre-monsoon | ||||||||||||||
Temp | 1 | |||||||||||||
pH | −0.092 | 1 | ||||||||||||
EC | −0.195 | −0.334 | 1 | |||||||||||
DO | −0.446* | 0.502* | −0.312 | 1 | ||||||||||
TH | −0.348 | 0.372 | 0.642** | 0.099 | 1 | |||||||||
Ca | −0.07 | 0.463* | 0.109 | 0.171 | 0.500* | 1 | ||||||||
Mg | −0.24 | −0.2 | 0.670** | −0.197 | 0.525** | −0.349 | 1 | |||||||
Na | −0.124 | −0.322 | 0.961** | −0.282 | 0.597** | 0.03 | 0.732** | 1 | ||||||
K | −0.385 | −0.199 | 0.874** | −0.097 | 0.647** | 0.075 | 0.750** | 0.905** | 1 | |||||
Cl | −0.408* | −0.164 | 0.763** | 0.003 | 0.648** | 0.283 | 0.526** | 0.762** | 0.848** | 1 | ||||
NO3 | 0.038 | 0.332 | 0.408* | 0.025 | 0.471* | 0.511** | 0.09 | 0.441* | 0.442* | 0.421* | 1 | |||
PO4 | 0.05 | 0.319 | 0.348 | 0.064 | 0.611** | 0.765** | −0.094 | 0.259 | 0.242 | 0.407* | 0.516** | 1 | ||
SO4 | −0.297 | −0.06 | 0.775** | −0.133 | 0.523** | 0.113 | 0.535** | 0.807** | 0.811** | 0.665** | 0.599** | 0.229 | ||
HC03 | − 0.317 | − 0.038 | 0.877** | − 0.024 | 0.817** | 0.289 | 0.699** | 0.869** | 0.850** | 0.784** | 0.481* | 0.463* | 0.747** | 1 |
Temp | pH | EC | DO | TH | Ca | Mg | Na | K | Cl | PO4 | NO3 | SO4 | HCO3 | |
(b) Post-monsoon | ||||||||||||||
Temp | 1 | |||||||||||||
pH | −0.292 | 1 | ||||||||||||
EC | −0.271 | −0.307 | 1 | |||||||||||
DO | −0.133 | 0.624** | −0.225 | 1 | ||||||||||
TH | −0.596** | 0.246 | 0.478** | 0.106 | 1 | |||||||||
Ca | −0.406* | 0.208 | 0.488** | −0.027 | 0.747** | 1 | ||||||||
Mg | −0.511** | 0.174 | 0.263 | 0.181 | 0.798** | 0.195 | 1 | |||||||
Na | −0.059 | −0.251 | 0.475** | −0.24 | 0.28 | 0.124 | 0.301 | 1 | ||||||
K | −0.123 | −0.088 | 0.023 | 0.181 | 0.174 | −0.148 | 0.392* | 0.116 | 1 | |||||
Cl | −0.414* | 0.298 | 0.348 | 0.18 | 0.654** | 0.511** | 0.501** | 0.380* | −0.093 | 1 | ||||
PO4 | −0.413* | 0.348 | 0.207 | 0.116 | 0.661** | 0.505** | 0.517** | 0.081 | 0.009 | 0.473** | 1 | |||
NO3 | 0.18 | 0.035 | −0.106 | −0.044 | −0.144 | 0.04 | −0.25 | −0.177 | −0.589** | −0.177 | 0.231 | 1 | ||
SO4 | 0.003 | 0.157 | −0.011 | 0.347 | 0.135 | 0.158 | 0.056 | 0.248 | 0.172 | 0.203 | 0.23 | 0.077 | 1 | |
HCO3 | −0.373* | −0.086 | 0.509** | −0.382* | 0.504** | 0.462** | 0.324 | 0.268 | −0.204 | 0.378* | 0.243 | 0.093 | −0.123 | 1 |
Correlations . | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
. | Temp . | pH . | EC . | DO . | TH . | Ca . | Mg . | Na . | K . | Cl . | NO3 . | PO4 . | SO4 . | HCO3 . |
(a) Pre-monsoon | ||||||||||||||
Temp | 1 | |||||||||||||
pH | −0.092 | 1 | ||||||||||||
EC | −0.195 | −0.334 | 1 | |||||||||||
DO | −0.446* | 0.502* | −0.312 | 1 | ||||||||||
TH | −0.348 | 0.372 | 0.642** | 0.099 | 1 | |||||||||
Ca | −0.07 | 0.463* | 0.109 | 0.171 | 0.500* | 1 | ||||||||
Mg | −0.24 | −0.2 | 0.670** | −0.197 | 0.525** | −0.349 | 1 | |||||||
Na | −0.124 | −0.322 | 0.961** | −0.282 | 0.597** | 0.03 | 0.732** | 1 | ||||||
K | −0.385 | −0.199 | 0.874** | −0.097 | 0.647** | 0.075 | 0.750** | 0.905** | 1 | |||||
Cl | −0.408* | −0.164 | 0.763** | 0.003 | 0.648** | 0.283 | 0.526** | 0.762** | 0.848** | 1 | ||||
NO3 | 0.038 | 0.332 | 0.408* | 0.025 | 0.471* | 0.511** | 0.09 | 0.441* | 0.442* | 0.421* | 1 | |||
PO4 | 0.05 | 0.319 | 0.348 | 0.064 | 0.611** | 0.765** | −0.094 | 0.259 | 0.242 | 0.407* | 0.516** | 1 | ||
SO4 | −0.297 | −0.06 | 0.775** | −0.133 | 0.523** | 0.113 | 0.535** | 0.807** | 0.811** | 0.665** | 0.599** | 0.229 | ||
HC03 | − 0.317 | − 0.038 | 0.877** | − 0.024 | 0.817** | 0.289 | 0.699** | 0.869** | 0.850** | 0.784** | 0.481* | 0.463* | 0.747** | 1 |
Temp | pH | EC | DO | TH | Ca | Mg | Na | K | Cl | PO4 | NO3 | SO4 | HCO3 | |
(b) Post-monsoon | ||||||||||||||
Temp | 1 | |||||||||||||
pH | −0.292 | 1 | ||||||||||||
EC | −0.271 | −0.307 | 1 | |||||||||||
DO | −0.133 | 0.624** | −0.225 | 1 | ||||||||||
TH | −0.596** | 0.246 | 0.478** | 0.106 | 1 | |||||||||
Ca | −0.406* | 0.208 | 0.488** | −0.027 | 0.747** | 1 | ||||||||
Mg | −0.511** | 0.174 | 0.263 | 0.181 | 0.798** | 0.195 | 1 | |||||||
Na | −0.059 | −0.251 | 0.475** | −0.24 | 0.28 | 0.124 | 0.301 | 1 | ||||||
K | −0.123 | −0.088 | 0.023 | 0.181 | 0.174 | −0.148 | 0.392* | 0.116 | 1 | |||||
Cl | −0.414* | 0.298 | 0.348 | 0.18 | 0.654** | 0.511** | 0.501** | 0.380* | −0.093 | 1 | ||||
PO4 | −0.413* | 0.348 | 0.207 | 0.116 | 0.661** | 0.505** | 0.517** | 0.081 | 0.009 | 0.473** | 1 | |||
NO3 | 0.18 | 0.035 | −0.106 | −0.044 | −0.144 | 0.04 | −0.25 | −0.177 | −0.589** | −0.177 | 0.231 | 1 | ||
SO4 | 0.003 | 0.157 | −0.011 | 0.347 | 0.135 | 0.158 | 0.056 | 0.248 | 0.172 | 0.203 | 0.23 | 0.077 | 1 | |
HCO3 | −0.373* | −0.086 | 0.509** | −0.382* | 0.504** | 0.462** | 0.324 | 0.268 | −0.204 | 0.378* | 0.243 | 0.093 | −0.123 | 1 |
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
The results showed that pH has no significant relation with other parameters except DO (r > 0.5) in both seasons. Total hardness (TH) and Mg2+ has a moderate (r = 0.5 to 0.6) correlation with EC whereas Na+, Mg2+, K+, Cl−, SO42− and HCO3−(r > 0.7) have a very strong correlation with EC. The result indicates weathering process in pre-monsoon. Na+ had a strong relationship with almost all parameters except pH, EC, DO, and Ca2+ in pre-monsoon, and it was 0.96 for EC and 0.905 for K+. Na did not show any significant correlation with other parameters in post-monsoon except a weak correlation with EC (0.47). HCO3− had strong to moderate positive correlations with EC, Mg2+, Na+, K+, Cl− and SO42− invariably in pre-monsoon. Cl− had very strong correlations with K+ (0.848), HCO3− (0.784) and Na+ (0.76), while it had moderate correlation with SO42− (0.66) and Mg2+ (0.53) in the pre-monsoon, and in post-monsoon it had moderate correlation with total hardness (0.65) and good correlation with Ca2+ (0.51) and Mg2+ (0.50) only with PO43− (0.59) in the post-monsoon. The correlation between Cl−, Na+, K+, and Mg2+ hints at a derivation from a common source. PO43− showed positive correlations with TH, Ca2+, and NO3− in pre-monsoon and with TH, Ca2+, and Mg2+ in post-monsoon. It was observed that nitrate had a good correlation with SO42−, Ca2+, and PO43− (r = 0.5 to 0.6). SO42− was strongly correlated with Na+, K+, and EC in pre-monsoon and moderately correlated with TH, SO42−, Mg2+, and NO3−. NO3− did not show any significant correlation with other parameters in post-monsoon. The correlation between nitrate and sulfate can be ascribed to use of fertilizers in wetland area and disposal of municipal waste (Khan et al. 2022).
APPRAISAL OF KA WETLAND WATER SUITABILITY FOR AGRICULTURAL PRACTICES
The concentration of different ions determines the quality of water and governs its suitability for various purposes, such as agriculture, the sector which is the largest consumer of fresh water. Thus, it is of utmost importance that irrigation water should be potent for crop growth and crop yield. Otherwise, a poor irrigation water quality can harm crop and soil characteristics due to either nutrient deficiency or excessive toxicity. Hence, in the present study different irrigation water quality parameters have been accounted for determining the suitability of wetland water for irrigation. The irrigation water quality of the KA wetlands was assessed on the basis of irrigation water quality parameters (Table 5).
Different irrigation parameters used in the study
Sl. No. . | Irrigation water quality parameters . | References . |
---|---|---|
01 | Salinity hazard | Bryan et al. (2007) |
02 | Sodium adsorption ratio (SAR) | Todd & Mays (1980); Richards (1954) |
03 | Sodium percentage (Na %) | Wilcox (1955) |
04 | Magnesium adsorption ratio (MAR) | Raghunath (1987) |
05 | Residual sodium carbonate (RSC) | Richards (1954); Eaton (1950) |
06 | Kelly's ratio (KR) | Kelley (1963) |
07 | Chloride hazard | Ayers & Wescot (1985) |
Sl. No. . | Irrigation water quality parameters . | References . |
---|---|---|
01 | Salinity hazard | Bryan et al. (2007) |
02 | Sodium adsorption ratio (SAR) | Todd & Mays (1980); Richards (1954) |
03 | Sodium percentage (Na %) | Wilcox (1955) |
04 | Magnesium adsorption ratio (MAR) | Raghunath (1987) |
05 | Residual sodium carbonate (RSC) | Richards (1954); Eaton (1950) |
06 | Kelly's ratio (KR) | Kelley (1963) |
07 | Chloride hazard | Ayers & Wescot (1985) |
Salinity hazard
Classification of irrigation water based on salinity hazard
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Salinity hazard (EC)(μs/cm) | <250 | Excellent | Nil | 100% |
250–750 | Good | 100% | Nil | |
750–2,000 | Permissible | Nil | Nil | |
2,000–3,000 | Poor | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Salinity hazard (EC)(μs/cm) | <250 | Excellent | Nil | 100% |
250–750 | Good | 100% | Nil | |
750–2,000 | Permissible | Nil | Nil | |
2,000–3,000 | Poor | Nil | Nil |
Sodium adsorption ratio
Irrigation water quality of wetland water based on SAR
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post -monsoon . | |||
SAR | <10 | Excellent | 100 | 100 |
10–18 | Good | Nil | Nil | |
18–26 | Medium | Nil | Nil | |
>26 | Bad | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post -monsoon . | |||
SAR | <10 | Excellent | 100 | 100 |
10–18 | Good | Nil | Nil | |
18–26 | Medium | Nil | Nil | |
>26 | Bad | Nil | Nil |
(a) USSL diagram for pre-monsoon; (b) USSL diagram for post-monsoon.
The USSL diagram plot SAR against EC C1 to C4 represents low salinity to high salinity range whereas S1 to S4 represents low to high SAR value (USSL 1954). The USSL diagram (Figure 9(a) and 9(b)) for the present study illustrates that most of the water samples of pre-monsoon and post-monsoon fall in C1S1 and C2S2 categories, indicating lower salinity and low SAR hazard and medium salinity and low SAR hazard, respectively, and are suitable for irrigation purpose.
Sodium percentage
Sodium percentage (%Na) (Equation (2)) is widely used in assessing the suitability of water for irrigation purposes. It is expressed as
Na% is a representation of sodium content with respect to other cations in water (Wilcox 1955). Sodium is limited concentration and is beneficial for various biological activities. Higher sodium content clogs the soil pores and reduces the permeability of soil (Mukiza et al. 2021). It disturbs the osmotic pressure and thus reduces the absorption of essential nutrients by crops (Singaraja et al. 2014). It may stun the growth of plants. The classification of water samples based on Na% values is shown in Table 8.
Irrigation water quality of wetland water based on Na%
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Na% | <20% | Excellent | Nil | Nil |
20–40% | Good | 12% | 16% | |
40–60% | Permissible | 76 | 84 | |
60–80% | Doubtful | 12% | Nil | |
>80% | Unsuitable | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Na% | <20% | Excellent | Nil | Nil |
20–40% | Good | 12% | 16% | |
40–60% | Permissible | 76 | 84 | |
60–80% | Doubtful | 12% | Nil | |
>80% | Unsuitable | Nil | Nil |
The majority of the samples of pre-monsoon and post-monsoon fall under the permissible range. The Na% ranged from 36% to 62.7% and 35% to 58% in pre-monsoon and post-monsoon respectively.
Residual sodium carbonate
Residual sodium carbonate (RSC) is another tool to assess the suitability of irrigation water. It represents the toxicity of carbonates and bicarbonates over calcium and magnesium. Carbonates and bicarbonates are important constituents of irrigation water and affect soil properties. High carbonates and bicarbonates cause precipitation of Ca2+ and Mg2+ (Rawat et al. 2018) and intensify the sodium hazard which is generally not reflected by SAR (Chaudhary & Satheeshkumar 2018). Higher RSC leads to an increase in adsorption of sodium in soil (Hedjal et al. 2018).
Irrigation water quality of wetland water based on residual sodium carbonate (RSC)
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
RSC | <1.25 | Good | 100% | 100% |
1.25–2.5 | Doubtful | Nil | Nil | |
>2.5 | Unsuitable | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
RSC | <1.25 | Good | 100% | 100% |
1.25–2.5 | Doubtful | Nil | Nil | |
>2.5 | Unsuitable | Nil | Nil |
Irrigation water quality of wetland water based on magnesium adsorption ratio (MAR)
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
MAR | ≤50 | Unsuitable | 4% | Nil |
≥50 | Suitable | 96% | 100% |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
MAR | ≤50 | Unsuitable | 4% | Nil |
≥50 | Suitable | 96% | 100% |
Magnesium adsorption ratio (MAR)
Magnesium present in excess increases soil alkalinity, reduces the infiltration and thus disturbs the growth of crops (Raghunath 1987). MAR (Equation (4)) measures the toxicity of magnesium ions over calcium ions.
Irrigation water quality of wetland water based on Mg/Ca
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Mg/Ca | <1.5 | Safe | 100% | 100% |
1.5–3.0 | Moderate | Nil | Nil | |
>3.0 | Unsafe | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Mg/Ca | <1.5 | Safe | 100% | 100% |
1.5–3.0 | Moderate | Nil | Nil | |
>3.0 | Unsafe | Nil | Nil |
Spatial distribution of Kelly's ratio in pre-monsoon and post-monsoon.
Spatial distribution of chloride hazard in pre-monsoon and post-monsoon.
The irrigation water quality ratings based on the Mg/Ca ratio shows that all the samples of pre-monsoon and post-monsoon belonged to the safe category (Table 11). Figure 14 shows the spatial distribution of Mg/Ca in pre- and post-monsoon.
Irrigation water quality of wetland water based on Kelly's ratio
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Kelly's ratio | <1 | Suitable | 60% | 75% |
>1 | Unsuitable | 40% | 25% |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Kelly's ratio | <1 | Suitable | 60% | 75% |
>1 | Unsuitable | 40% | 25% |
Kelly's ratio
A value greater than one is not considered safe for irrigation as it denotes a higher sodium concentration leading to poor growth of crops.
Irrigation water quality of wetland water based on chloride hazard
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Chloride hazard | <2 | Low hazard | 100% | 100% |
2–4 | Medium hazard | Nil | Nil | |
4–10 | High hazard | Nil | Nil | |
>10 | Very high hazard | Nil | Nil |
. | Range . | Water Class . | % of samples . | |
---|---|---|---|---|
Pre-monsoon . | Post-monsoon . | |||
Chloride hazard | <2 | Low hazard | 100% | 100% |
2–4 | Medium hazard | Nil | Nil | |
4–10 | High hazard | Nil | Nil | |
>10 | Very high hazard | Nil | Nil |
Kelly's ratio ranged from 0.58 to 1.8 for pre-monsoon and 0.68 to 1.50 for post-monsoon, respectively; 60% of the samples were detected suitable for pre-monsoon while 75% of the samples were detected suitable for post-monsoon (Table 12). Spatial map of Kelly's ratio for pre-monsoon and post-monsoon is illustrated in Figure 15.
Chloride hazard
Chloride is a micronutrient and plays an imperative role in the growth and development of plants. Adsorption of chloride by soil is less and it is absorbed by plants. Excessive chloride accumulates in leaves and causes leaf burn or necrosis (www.fao.org). In irrigation water, the concentration of chloride should not be more than 2 meq/l (Sreedevi et al. 2019). The observed range of chloride ions was 0.3 meq/l to 0.56 meq/l and 0.61 meq/l to 0.96 meq/l for pre-monsoon and post-monsoon respectively, suggesting its suitability for agriculture (Table 13). The spatial map of chloride hazard for pre- and post-monsoon is illustrated in Figure 16.
A comprehensive summary of different irrigation water quality parameters in pre-monsoon and post-monsoon is presented in Table 14.
Comprehensive summary of different irrigation water quality parameters in pre-monsoon and post-monsoon
Sl. No. . | Irrigation water quality parameters . | Pre-monsoon . | Post-monsoon . |
---|---|---|---|
01 | Salinity hazard | 100% good | 100% excellent |
02 | SAR | 100% suitable | 100% suitable |
03 | Sodium % | 76% permissible | 84% permissible |
04 | RSC | 100% suitable | 100% suitable |
05 | MAR | 96% suitable | 100% suitable |
06 | KR | 60% suitable | 75% suitable |
07 | Mg/Ca | 100% suitable | 100% suitable |
08 | Chloride hazard | 100% suitable | 100% suitable |
Sl. No. . | Irrigation water quality parameters . | Pre-monsoon . | Post-monsoon . |
---|---|---|---|
01 | Salinity hazard | 100% good | 100% excellent |
02 | SAR | 100% suitable | 100% suitable |
03 | Sodium % | 76% permissible | 84% permissible |
04 | RSC | 100% suitable | 100% suitable |
05 | MAR | 96% suitable | 100% suitable |
06 | KR | 60% suitable | 75% suitable |
07 | Mg/Ca | 100% suitable | 100% suitable |
08 | Chloride hazard | 100% suitable | 100% suitable |
CONCLUSION
This study focused on comprehensive analysis of hydro geochemistry of KA wetland water and its suitability for agricultural purposes. The wetlands water is alkaline in nature as reflected by the pH values. EC, TH, Na+, Ca2+, SO42− and HCO3− were relatively high, and temperature, DO, Mg2+ and Cl− were lower in pre-monsoon than post-monsoon. There was no major change in the concentration of nitrate and phosphate over both the seasons. Gibb's diagram reveals that the weathering of rocks in pre-monsoon and rock weathering along with precipitation in post-monsoon are the major sources of ions in wetland. Silicate weathering is the dominant contributor for ions in the wetland. The Piper diagram represents Na + K type and mixed type for cations and HCO3− for anions. The concentration of major cations was in order of Na+ > Ca2+ > Mg2+ > K+ and concentration of anions was in order of HCO3− > SO42− > Cl− > NO3− > PO43− in pre-monsoon and HCO3− > Cl− > SO42− > NO3− > PO43− in post-monsoon. Irrigation parameters like salinity hazard, SAR, Na%, KR, MAR, RSC, Mg/Ca and chloride hazard were applied to assess the wetland water suitability for irrigation. As per SAR standards, all samples were found to be suitable for both seasons. The majority of samples were with in the permissible limit for Na%. RSC was found to be good for both seasons. MAR was found to be suitable for both seasons (60% of the samples were found suitable in pre-monsoon and 75% in post-monsoon). There was less chloride hazard in both seasons. The wetlands water recedes in the summer season and during this period the dry land is used for agriculture purposes. Use of fertilizer during this period has been observed. In monsoon the dry land is inundated, thus causing mixing of the fertilizer residues. The agriculture activity in the wetlands catchments and human settlements are sources of nutrient enhancement to the wetlands. Overall, it is stated that the water quality of KA wetlands is suitable for agriculture purposes where there is abundance of water. The seasonal variation and anthropogenic activities are major contributors to the hydrochemistry of the wetlands.
ACKNOWLEDGEMENTS
The authors are grateful to Union Grant Mission for financial assistance in terms of a fellowship for one for the authors. The authors are grateful to the Principal Chief Conservator of Forests, Government of Bihar and Divisional Forest Officer, Darbhanga, Bihar for granting permission to carry out research work in KA wetlands. The authors wish to thank the anonymous reviewers for their valuable suggestions and comments which improved the quality of the paper.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.