Rapid urbanization, especially in developing countries like India, ... Water quality index is one of the most effective tools to communicate information on the.
Ground Water Quality Index Assessment in Parts of Unnao, India
AB RAQEEB RATHER Aligarh Muslim University , Aligarh.
CHAPTER 1 INTRODUCTION 1.1 GENERAL: Drinking water is an important resource that needs to be protected from pollution and biological contamination. Underground water is clean but it depends upon quality and quantity of materials dispersed and dissolved in it. Water picks up impurities in during its flow, which are harmful to man and vegetation. The reason for contamination and pollution of water in the natural surroundings and in the storage are pesticides, fertilizers, industrial wastes, inorganic and organic salts from top soil and geological strata (Nanoti, 2004). Groundwater is used for domestic, industrial, water supply and irrigation all over the world. In the last few decades, there has been a tremendous increase in the demand for fresh water due to rapid growth of population and the accelerated pace of industrialization. Human health is threatened by unsanitary conditions through open drain carrying and disposing waste water into natural water bodies. Rapid urbanization, especially in developing countries like India, has affected the availability and quality of groundwater due to its overexploitation and improper waste disposal, especially in urban areas. As per the latest estimate of Central Pollution Control Board, about 29,000 million litre/day of wastewater generated from class-I cities and class-II towns out of which about 45% (about 13000 MLD) is generated from 35 metro-cities alone. According to WHO organization, about 80% of all the diseases in human beings are caused by water. Once the groundwater is contaminated, its quality cannot be restored back easily and to device ways and means to protect it. Water quality index is one of the most effective tools to communicate information on the quality of water to the concerned citizens and policy makers. The concept of Water Quality Index (WQI) to represent gradation in water quality was first proposed by Horton. WQI indicates a single number like a grade that expresses the overall water quality at a certain area and time based on several water quality parameters. The use of GIS technology has greatly simplified the assessment of natural resources and environmental concerns, including groundwater. In groundwater studies, GIS is commonly used for site suitability analyses, managing site inventory data, estimation of groundwater vulnerability to contamination, groundwater flow modelling, modelling solute transport and
leaching, and integrating groundwater quality assessment models with spatial data to create spatial decision support systems (Engel and Navulur 1999). The objective of this work is to evaluate the significance and applicability of a GQI generated using GIS approach for the assessment of groundwater quality in a part of Unnao district.
1.2 GROUNDWATER SCENARIO IN INDIA: Out of 5723 assessment units (blocks/mandals/talukas/watersheds) in the country, 839 are categorized as "Over-Exploited" where the stage of development exceeds annual replenishment. As many as 226 blocks/watersheds are categorized “Critical” where groundwater development has reached a high level of development (Romani et al. 2006). The unplanned and non-scientific development of ground water resources, mostly driven by individual initiatives has led to an increasing stress on the available resources. The adverse impacts can be observed in the form of long-term decline of ground water levels, desaturation of aquifer zones, increased energy consumption for lifting water from progressively deeper levels and quality deterioration due to saline water intrusion in coastal areas in different parts of the country. On the other hand, there are areas in the country where ground water development is still at low-key in spite of the availability of sufficient resources. Similarly the canal command areas suffer from problems of water logging and soil salinity due to the gradual rise in ground water levels. Groundwater is the most preferred source of water in various user sectors in India on account of its near universal availability, dependability and low capital cost. The increasing dependence on groundwater as a reliable source of water has resulted in indiscriminate extraction in various parts of the country without due regard to the recharging capacities of aquifers and other environmental factors. On the other hand, there are areas in the country, where groundwater development is sub-optimal in spite of the availability of sufficient resources, and canal command areas suffering from problems of water logging and soil salinity due to the gradual rise in ground water levels. As per the latest assessment, the annual replenishable groundwater resource of country has been estimated as 433 billion cubic meters (bcm), out of which 399 bcm is considered to be available for development for various uses. The irrigation sector remains the major consumer of ground water, accounting for 92% of its annual withdrawal. Problems related to uneven and unplanned development of groundwater resources, overexploitation, lack of clear managerial policies with respect to harnessing groundwater reservoirs and sloppiness in implementing Government policies and directions in spite of the
existence of Groundwater Departments at the State level and also federal organizations, such as, Central Groundwater Board (CGWB) and National Groundwater Authority, are further compounded by ever increasing deterioration of quality of groundwater to such an extent that it is rendered undrinkable in many regions.
1.3 PRESENT STUDY: The present study was taken with an intention that it will add more dimensions to overall understanding of the hydrochemistry of parts of Unnao district in the Central Ganga Plain. Indiscriminate use of surface and groundwater for irrigation purposes without considering the status of groundwater level enhances the formation of saline soil in the study area. The rising groundwater trend would eventually accelerate the formation of saline (usar or reh) soil in the study area. Moreover, the wastes (both solid and liquid) generated from tanneries and their unplanned surface and subsurface disposal has caused deterioration not only in groundwater quality but has also degraded the quality of soil in the area. These explanations are not universally applicable but definitely hold good for the study area selected and may also be applicable to areas characterized by similar or comparable geological, geomorphological and hydrological settings.
1.4 OBJECTIVES: The investigation, the results of which are being presented here, has been carried out with the following objectives: 1. Evaluation of the chemistry of groundwater system (major cations and anions) in terms of roles
of
aquifer-related
processes,
water-rock
interaction,
precipitation/dissolution
mechanisms, mixing of two or more waters and various anthropogenic processes/factors. 2. To study the chemistry of groundwater system and evaluate its suitability for drinking and irrigational uses. 3. Assessment of groundwater quality index using GIS for a better understanding of the spatial variation of the chemistry of groundwater and to study the cumulative effect of different water quality parameters in the study area.
CHAPTER 2 THE STUDY AREA 2.1 LOCATION AND ACCESSIBILITY: The study area, north-western part of Unnao district, lies in the central part of Uttar Pradesh, bounded on the north-east by Sai river and on the south-west by river Ganga. The area falls in Survey of India Toposheets no. 63B/5 and 63B/6 on 1:50,000 scale. It lies between 26°30/ to 27°00/ N latitude and 80°15/ to 80°30/ E longitude and covers an area of about 950 km2 (Figure-2.1). Almost all villages are well connected by motarable roads from district headquarters. Unnao district is well connected with adjoining districts and towns, such as, Lucknow, Hardoi and Rai Bareli. It is connected to state capital Lucknow by national Highway No. 25. Besides, a large number of metalled roads connect different parts of the district to the Unnao city. It is an important rail head of Northern railway on Delhi-Lucknow broad gauge line. Agriculture is playing pivotal role in the economy of the local people and also it is the main job of the people. The principal crops of the region are wheat, barley, gram, masoor, paddy, jwar, urad, sugarcane and groundnut. Unnao industrial area is having about 50 industries at present comprising mainly of leather industries (http://unnao.nic.in/industry.htm). Tanning is the biggest industry in Unnao, being well known for its leather industry and its leather goods. There are also numerous small industries dealing with manufacturing of agricultural machines
Figure-2.1: Location map of the study area.
2.2 CLIMATE AND RAINFALL: The climate of the area falls under the warm temperate type with dry winters (Cwg type) or C1 type of climate i.e., dry sub-humid type of climate (Ahmad, 1999). There are four distinct climatic seasons in the district, viz. winter, summer, monsoon and receeding-monsoon. The winter season generally extends from November to March and experiences lowest temperature and humidity and high atmospheric pressure. The wind speed in this season remains very slow due to atmospheric pressure. The summers generally extend from April to June and have very high temperature and low atmospheric pressure. This season experiences hot speedy winds, which are also termed as ‘Loo’. In the mid of June or July, the monsoon enters the area with south-westerlies winds and generally extends up to the end of September. During this season the rains occur in the area and humidity goes to its maximum. The receding monsoon season extends up to the end of September to October month. The summer temperature generally shoots up to 47°C. January is the coldest month during which the temperature drops to 4°C. The rainfall in study area often shows erratic nature and many times the area experiences long dry spells also. The average annual rainfall of the
district is 838 mm. Almost 90% of annual precipitation occurs during the period mid June to September (Faruqi, 2002). Winds are generally light to moderate in the district. From October to April winds blow mostly from directions between west and north-west, while from May onwards northeasterly and southeasterly winds blow.
2.4 TOPOGHRAPHY: Unnao district represents flat topography with a general elevation of 98 m (322 ft.) covering an area of 4558 km2. By virtue of its geographic setting in the great (Ganga) plains, the land is highly fertile. The soil is mostly alluvial. The district is mainly drained by the river Ganga and its tributaries Kalyani, Khar, Loni and Marahai in the western part of the district and by Sai river in the eastern part of the district. All these rivers are perennial in nature. About 87% area of the net sown area (3,00,000 hectares) is irrigated both by surface water (Sharda Canal network system) and ground water through shallow and moderately deep tubewells. The share of surface water irrigation is 48% while that of ground water is 52%. 2.5 GEOMORPHOLOGY: Geologically Unnao district lies in Ganga plain, one of the most densely populated regions, one of the largest ground water repositories and one of the largest fluvial systems on Earth wherein, monsoon rain causes large scale sediment-water movement and reworking of sediments. The area is beset with alluvium of Quaternary age consisting of older alluvium of middle to upper Pleistocene and newer alluvium of Holocene. The climate of the study area is semi-arid type. Geomorphologically, the Plain shows a south to southeasterly sloping planar surface in the northern part, formed due to contraction and expansion of alluvial fans in response to the climatic changes during the Quarternary (Ghosh and Singh, 1988). There is a regional plateau or upland surface (T2) sloping towards east and south-east. Another regional surface (T1) is developed within the major river valleys. These surfaces have developed in response to sealevel and climatic changes during Quarternary period (Singh, 1987). It is observed that in rivers flowing NW-SE, the southern bank shows prominent cliffs, while in the north, broad flood planis are developed (Singh and Rastogi, 1973). The present-day Ganga river near Unnao-Kanpur is a 2-3 km wide distinctly braided stream with only one or two braid bars across the channel. These braid bars / sand flats have shifted downstream as well as accreted vertically. Vertically accretion has lead to the development of permanent sandy islands, which become vegetated, as they are not inundated by average
annual floods. The river is undergoing vertical accretion at a rate of about 25cm/10 years (Singh et al., 1990). A comparison of the area of active channel, active sand bar, vegetated bar has shown that over a period of 60 years, there has been a 57% reduction in the active channel area and a substantial increase in the area of active sand bar and vegetated bar. The sand of the river channel is micaceous and very fine (Singh et al., 1990). Geomorphology and drainage type combined with sedimentation processes play a substantial role on dispersion and transport patterns of metals bound to sediments and soils. It has been divided into five independent geochemical domains on the basis of sedimentgeomorphic, hydrological and geochemical characters. The monsoon hydrography and physicochemical parameters (pH, conductivity) of the river and urban drain waters play a prominent role in
40000
r ive iR Sa
45000
regulating the concentrations and behavior of the metals in the aquatic system of the Plain.
30000 25000
SAFIPUR
20000
Northing in metres
35000
BANGARMAU
15000
LEGEND Flood Plain
10000
Ganga River
Paleao/Abandoned Channel Meander Scar Point bar Ox bow Lake
5000
Alluvial plane Younger/Lower Channel bar
0
0
5 Km
UNNAO Alluvial plane Older/Upper
Scale 5000
10000 15000 Easting in metres
20000
Figure-2.3: Geomporphological map of the study area (http://gis.up.nic.in:8080/srishti/#
2.6 LAND USE AND LAND COVER: Land use and land cover studies serve as a decision making tool not only in planning and management activities regarding the use of land surface, but also a crucial parameter in hydrological investigations of a given area for assessing the qualitative and quantitative aspects of available water resources. The area covered by various land use categories are given in Table-2.2. From this table it is clear that agricultural land is the dominant land use category followed by plantation and settlements.
Table-2.2: Land Use and Land Cover classification of Sai-Ganga Interfluve region Land
use/Land
cover Area
S/No. catagories
(km2)
1
Agriclutural land
877.31
2
Plantation
36.1
3
Settlement
24.24
4
Saline area (Usar or reh)
11.87
5
Water bodies
0.5
6
Total Area
950.02
2.7 SURFACE AND SUB-SURFACE GEOLOGY: The Ganga Plain is an active foreland basin formed as result of the continental collision between the Indian plate and the Eurasian plate. A fairly detailed account of the subsurface geology and basement tectonics of the Ganga plain is given by Sastri et al. (1971) and Rao (1973) and depositional model is given by Singh (1996, 2004). The study area forms parts of the Ganga basin, which is one of the physiographic units of India. Geologically, the area is underlain by Quaternary alluvium which consists of alternate layers of sand and clay with occasional calc concretions (kankar). The Quaternary period is represented by two cycles of sedimentation. The older one, ranging in age from Late to Middle Pleistocene, resulted in the deposition of Varanasi Alluvium. The younger one, ranging in age from Late Pleistocene to Holocene is referred to as Newer Alluvium (Kumar, 2005).
Through time, the Gangetic Plain has expanded southwards in response to thrust-fold loading in the Himalaya. The subsurface data in the alluvium of the southern marginal plain shows that above the basement, there is a succession of sediment derived from the Peninsular region, dominated by pink-colored arkoses sands. This zone is capped by a sequence of sediments from Himalayan source, which are essentially grey coloured, micaceous subgreywacke type (Singh and Bajpai, 1989). In Kanpur (& Unnao) region, Ganga river flows along NW-SE trending weak zone (a tectonic lineament) showing a prominent escarpment on the southern side and well-developed flood plain in the northern side (Singh and Rastogi, 1973). This weak zone has also controlled the subsurface stratigraphy in the alluvium (Singh and Bajpai, 1989). The area lies in the Central Ganga plain, consisting mostly of Alluvial sediments of Ganga basin, which have been classified into Older Alluvium and Newer Alluvium; the former consists of sediments which were formed in distant past and are partly undergoing denudation, while the latter is under its process of formation. The Older Alluvium is made up of massive beds of clay of pale reddish brown colour, very often yellowish with kanker (calcrete) present in between the clay layers. The Newer Alluvium is light coloured and poor in calcareous matter. The major part of the Central Ganga plain is composed of Older Alluvium (Khanna, 1992). The Jal Nigam, U.P. State Govt, and CGWB have put many bore holes in the district for the delineating sub-surface geology and for exploration of groundwater; the deepest hole is made at Panna Lal Park in the Unnao city area. It was drilled down to a depth of 569.27 m bgl, but could not encounter the bed rock and three granular zones were reported (Faruqi, 2002). In addition to drilling data, a map of the Ganga Plain showing sub-surface basement high and thickness of the foreland sediment is published (Singh, 2004). Unnao, in this map, lies between contours of 1.5 and 1.0 km. Therefore the probable thickness of alluvium in the study area is likely to be more than 1000 m.
Table-2.3: Probable Geological Succession in the Study Area (After CGWB, 2002) Age Holocene
Litho Unit
Sedimentary Constitution
Newer Alluvium
Channel Alluvium Levee Alluvium
----------------------------------Disconformity-----------------------------------Middle
to
Upper Varanasi Older Alluvium
Pleistocene
Clayey Facies Sandy Facies
--------------------------------------Unconformity-------------------------------------(Basement Rock) ???
Figure-2.4: Map of the Ganga Plain Showing Sub-Surface Basement High and Thickness of Foreland Sediments (in km) Based on Studies of Agarwal (1977), Karunakaran and Rao (1979) and Singh (2004).
CHAPTER 3 HYDROCHEMISTRY GENERAL: Although water is commonly thought of as simply H2O, literally thousands of other substances are dissolved in it in the environment. Most of these substances occur naturally, and many are present in water in only small quantities. Water acquires very small quantities of some solutes from dust and gases when it falls through the atmosphere as precipitation, but it typically acquires the majority of its solutes once it reaches the land surface. Solutes that were already present in the water increase in concentration because of the processes of evaporation and transpirationprocess that, for the most part, remove water while leaving the solutes behind (Plumer et al. 2003). Groundwater acquires major and minor cations primarily through solid-water interaction (Bartarya, 1993; Subba Rao, 1993). The concentrations of the major ions and the other dissolved species in groundwater reflect the availability of various constituents to the system and the solubility of solids that may limit solution concentration (Deutch, 1997). That rocks the groundwater remains in contact with contribute chemical species through dissolution is discernible in the form of a direct relationship between the type of lithology and relative abundances of cations (Faure, 1998). For example, in carbonate rock terrain, groundwater is characterized by the abundance of Ca + Mg over Na + K, whereas this trend is reversed in areas with granitic lithology (Alam, 2010). The hydrogeochemical processes and hydrogeochemistry of the ground water vary spatially and temporally, depending on the geology and chemical characteristics of the aquifer. Fresh groundwaters flowing through different aquifers may be identified and differentiated by their characteristic salinity levels and ionic ratios (Rosenthal, 1987). The composition of groundwater in upper reaches of catchments is close to that found in rain falling on recharge areas. The groundwater chemistry undergoes a significant alteration during the course of its flow away from the recharge 136 area. The least mineralized water is found closest to the
main recharge zones and the salinity of the water increases significantly away from recharge areas (Hidalgo and Sanjulian, 2001). Changes in chemical characteristics of groundwater in different aquifers over space and time often serve as an important technique in deciphering a geochemical model of the hydrological system (Cheboterev, 1955; Hem, 1959; Back and Hanshaw, 1965; Gibbs, 1970; Srinivasamoorthy, 2005; Srinivasamoorthy et al. 2008; Dehnavi et al. 2011). An understanding of geochemical evolution of groundwater is important for a sustainable development of water resources for any regions. In this connection, an attempt was made to assess the hydrochemical characteristics of groundwater in the study area.
3.2 PHYSICO-CHEMICAL ATTRIBUTES OF GROUND WATER: The summary of physico-chemical parameters of water samples analyzed including pH, electrical conductivity (EC), total dissolved solids (TDS), are given below.
3.2.1 Hydrogen Ion Concentration (pH): Values of pH were measured at well sites, which range between 6 to 7.6 and 6.8 to 8.5 during pre-monsoon 2010 and post-monsoon 2010, respectively. The groundwater thus is mildly acidic to slightly alkaline in nature. As far as human consumption is concerned, all the samples may be considered fit, as they are neither acidic nor strongly alkaline.
3.2.2 Electrical Conductivity: Electrical conductivity is an important parameter in groundwater quality assessments for drinking and irrigation, since it is related to the concentration of charged particles in water. The presence of charged particles in the water increases its conductivity. In the study area, EC values ranges between 600-1600 μS/cm during June 2010. The EC values during November 2010 were reported in between 400- 1400 μS/cm. On the basis of Electrical conductance, groundwater is classified (Table- 3.1) as given by Sarma and Narayanaswamy (1981).
Table-3.1: Classification of groundwater samples on the basis of EC EC (µS/cm o
Class
at 25 C)
Low Conductivity Medium
Pre-monsoon
Post-monsoon
2010
2010
< 500
0
7% (1 Samples)
Conductivity 500- 1000
40% (6 Samples)
60% (9 Samples)
Conductivity 1000- 3000
60% (9 Samples)
33% (5 Samples)
Class I Medium Class II High Conductivity Class > 3000
0
0
III
3.3.3 Total Dissolved Solids (TDS): In natural waters, dissolved solids consists mainly of inorganic salts such as carbonates, bicarbonates, chlorides, sulphates, phosphates and nitrates of calcium, magnesium, sodium, potassium, iron etc. and small amount of organic matter and dissolved gases. In the present study the values of total dissolved solids (TDS) in the groundwater varies from 652 to 1434 mg/l during pre-monsoon season (June 2010). Seven out of 15 samples have values of >1000 mg/l, the average value for the samples being 1017 mg/l. The TDS values during November 2010 range between 761 to 2384 mg/l with an average value of 1461 mg/l, indicating high mineralization in the study area in both the seasons. During postmonsoon season, 87% of groundwater samples have TDS value of >1000 mg/l (Table-3.2). It may be concluded that there is more mineralization of groundwater during post-monsoon season. Water containing more than 500 mg/l of TDS is not considered desirable for drinking water supplies, though more highly mineralized water is also used where better water is not available. For this reason, 500 mg/l as the desirable limit and 2000 mg/l as the maximum permissible limit has been suggested for drinking water. Water containing TDS more than 500 mg/l causes gastrointestinal irritation (BIS, 1991).
Table-3.2: Classification of groundwater based on TDS Category
Pre-
monsoon Post-
2010
2010
53% (8 Samples)
13% (2 Samples)
Brackish water 1,000- 10,000
47% (7 Samples)
87% (13 Samples)
Saline water
10,000- 100,000
0
0
Brine water
> 100,000
0
0
Fresh water
TDS (mg/l)
0- 1,000
monsoon
3.3.4Hardness: During June 2010, the hardness in the study area varies from 124 – 360 mg/l with an average value of 242 mg/l. Values above desirable limit (> 300 mg/l) were recorded at Riyamau and Sarmba (Table-3.3). During November 2010, hardness ranges between 100-612 mg/l with an average value of 356 mg/l. Samples 2, 3, 8, and 11 show the value above desirable limit, constituting about 27% of the total analyzed samples. Thus groundwater during both the seasons, viz. June 2010 and November 2010 falls in the realm of moderately hard to very hard. However, except samples 3(shadipur) collected in November 2010, all the samples analyzed are indicated to be with in the permissible limit of drinking water standard (BIS, 1991).
Table-3.3: Hardness classification of groundwater Hardness of CaCO3 (mg/l)
Water Class
Pre- monsoon 2010
Post- monsoon 2010
0 – 75
Soft
0
0
75 – 150
Moderately hard 27% (4 Samples)
20% (3 Samples)
150-300
Hard
60% (9 Samples)
53% (8 Samples)
> 300
Very hard
13% (2 Samples)
27% ( 4 Samples)
3.4 CLASSIFICATION OF GROUNDWATER To see the changes in groundwater chemistry at different locations and zones and the extent of water rock interaction, major ion data of water samples of both the time periods were plotted on Piper Trilinear diagram shown in Figure-3.1a and 3.1b.
3.4.1 Piper’s Trilinear Diagram: Piper diagrams are broadly used in hydrogeology as they illustrate the hydrochemical characteristics of groundwater by representing the percentage of anions and cations in meq L─1 in separate triangular diagrams (Freeze and Cherry, 1979; Helena et al. 1998). Geochemically similar waters are clustered in clearly defined areas, indicating water mixing phenomena, precipitation, dissolution, etc. All groundwater samples collected from the study area have been plotted in a Piper diagram (Figure-3.1a). Based on the interpretation of the Piper diagram of pre-monsoon 2010, the following hydrochemical considerations can be pointed out:
So far as the relative abundance of cations are concerned, 80% are alkalis and 20% exhibit no dominant signature.
Among anionic species, 33% fall in no dominant field, 61% are bicarbonate type and the remaining 6% samples are chloride type.
Figure-3.1a: Chemical facies identified on Piper’s Diagram in groundwater samples collected in June 2010 In post-monsoon samples (Figure-3.1b), the observed trend on Piper’s Diagram in terms of relative abundance of cationic and anionic species is as follows:
Alkalis represent the most dominant group, comprising 100% of the samples.
Among anions, 13% of the samples do not have any dominant anionic signature, followed by 87% with relative abundance of bicarbonates.
Figure-3.1b: Chemical facies identified on Piper’s Diagram in groundwater samples collected in November 2010 The majority of the samples, therefore, are “alkali-bicarbonate” and “alkali bicarbonate-chloride type” with Na having an overwhelming abundance over K. The remaining samples exhibit mixed character with composition varying from mixed alkali bicarbonate to alkali bicarbonate calcium chloride type.
3.4.2 L-L Diagram: To evaluate the chemical evolution of groundwater in the study area, the major ion chemistry of both pre-monsoon and post-monsoon period has been summarized in the form of the Langelier and Ludwig (1942) L-L diagram shown in Figure-3.2a and 3.2b. None of the samples qualify to be called a typical Ca-Mg-HCO3 type of local meteoric water (LMW). Pre-monsoon 2010 plot (Figure-3.2a) helps in identifying three different chemical types of groundwater. Group I, comprising (47%) 7 samples has higher concentrations of Cl─ + SO42─ and Na++ K+ and thus exhibit Na++ K+- Cl─ + SO42─ type chemical characteristics.This group is called as”alkali-chloride-sulphate type”. Group II groundwater samples (33%) have higher concentration of Na++ K+ and HCO3─, in which the former ions constitute the average of 39% and the later constitute 45% of the total ion chemistry. The HCO3─ and Cl─ differentiate the fresh and contaminated water environments respectively. This group is named as “alkali-bicarbonate type”. Group III (14%) 2 samples occur in the central portion of L-L diagram. This group is named as “mixed type”.
The post-monsoon diagram presents a different scenario where more than 90% of the samples are concentrated in a single group. Except for sample 5 collected from Utmanpur which lies in the centre of L-L diagram, others belong to the group named as “alkali-chloridesulphate type”. This group is dominated by Na++ K+ - Cl─ and SO42-
Figure-3.3a: Langelier and Ludwig (L-L) diagram of June 2010 samples
Figure-3.3b: Langelier and Ludwig (L-L) diagram of November 2010 samples
From above discussion, it can be concluded that chemical characteristics of the groundwater in the study area has evolved through a series of events and primordial chemical characteristics of the meteoric water has been completely obliterated. Most of the groups seem to have acquired their major ion chemistry as a result of various processes which may be attributed to the combined action of geogenic and anthropogenic activities.
3.6 SUITABILITY OF WATER FOR IRRIGATION PURPOSES Groundwater in the study area finds intensive use in irrigation. In Unnao district, of which study area is a part, agriculture is very important income source, comprising about 66% of the whole district. About 88% of the net cultivated area in Unnao district is falling under irrigated category, of which 69% irrigation is being done by groundwater (CGWB, 2002). The suitability of groundwater for agricultural purposes depends on the effect of mineral constituents of water on both plants and soil. Effects of salts on soils causing changes in soil structure, permeability and aeration indirectly affect plant growth. Wilcox (1955) and US Salinity Laboratory Staff (1954) proposed irrigational specifications for evaluating the suitability of water for irrigation use. There is a significant relationship between sodium adsorption ratio (SAR) values for irrigation water and the extent to which sodium is adsorbed by the soils. If water used for irrigation is high in sodium and low in calcium, the cation exchange complex may become saturated with sodium, which can destroy the soil structure owing to dispersion of clay particles (Singh, 2002; Tyagi et al. 2009). The electrical conductivity is a measure of salinity hazard to crop as it reflects the TDS in the groundwater. Parameters such as sodium absorption ratio (SAR) and residual sodium carbonate (RSC) were estimated to assess the suitability of groundwater for irrigation. The salt present in the water, besides affecting the growth of plants directly also affects soil structure permeability and aeration, which indirectly affect plant growth (Mohan et al. 2000; Umar et al. 2001).
3.6.1 Sodium Adsorption Ratio (SAR) Criterion: Sodium absorption ratio is the measurement of sodium content relative to calcium and magnesium in soil-water medium which influences soil properties and plant growth. The total soluble salt content of irrigation water generally is measured either by determining its electrical conductivity (EC), reported as micromhos per centimeter, or by determining the actual salt content in parts per million (ppm). Normally, irrigation water with an EC of < 700
μmhos cm-1 causes little or no threat to most crops while EC > 3000 μmhos cm-1 may limit their growth (Tijani, 1994; Khodapanah et al. 2009).
The sodium or alkali hazard in the use of water for irrigation is determined by the absolute and relative concentration of cations and is expressed as the sodium adsorption ratio (SAR).The following formula is used to calculate SAR:
SAR =
Na Ca Mg 2
Ions in the equation are expressed in milliequivalent per liter (meq/l). There is a significant relationship between SAR values of irrigation water and the extent to which sodium is absorbed by the soils. Continued use of water with a high SAR value leads to a breakdown in the physical structure of the soil caused by excessive amounts of colloidally absorbed sodium. This breakdown results in the dispersion of soil clay that causes the soil to become hard and compact when dry and increasingly impervious to water penetration due to dispersion and swelling when wet. Fine-textured soils, those high in clay, are especially more vulnerable to this action. The calculated value of SAR in the study area ranges from 1.76-10.48 with an average of 4.02 during pre-monsoon 2010, where as in post-monsoon 2010; it varies from 1.59 to 11.64 with an average of 5.71 in groundwaters. SAR of all the samples lie below 10, except sample 14 collected during June 2010 from Barikhera. So far as this sample is concerned, water from this dug-well is not used for irrigation purposes at all as it is located far away from the agricultural fields. The SAR values of June 2010 when plotted on the US salinity diagram (Richards, 1954), show that 80% samples fall in C3-S1, 13% in C2-S1 and7% in C2S2 (Figure-3.3a). Samples falling in C3-S1 are not advisable to the soils with scarce drainage and the prerequisite for samples falling in C2-S1 to be used for irrigation is that the soil must encompass through moderate leaching.
Figure-3.3a: SAR versus E.C. (June 2010) During November 2010, 4 samples (27%) fall in C3-S2 (high salinity and moderate sodium water) and 1 sample fall in C2-S2 (moderate salinity and moderate sodium water) (Figure3.3b). Therefore, 5 samples exhibit medium sodium hazard. Such water can show adverse effect in fine textured soils where frequent cation exchange occurs, application of gypsum in agricultural fields can overcome this problem. When the options are limited, these waters can be used in coarse-grained soils where sizable pore-spaces do not allow cation exchange to take place (Karanth, 1987). The remaining samples fall in C2-S1 (53%) and C3-S1 (13%) for which the necessary requisites have already been discussed. The quality classification of groundwater is given below in Table-3.6 (USSL, 1954).
Table-3.6: Quality Classification of Irrigation Water (after USSL, 1954) Water
Salinity
Hazard
E.C SAR Value
(Micromhos/cm at 250 C) Excellent
26
Figure-3.4b: SAR versus E.C. (November 2010)
3.6.2 Residual Sodium Carbonate (RSC) Parameter: Calcium and magnesium has a tendency to precipitate as carbonate, when there is high percentage of bicarbonate in the groundwater. To quantify this effect, an experimental parameter termed as Residual Sodium Carbonate can be used. The concept of residual sodium carbonate (RSC) is employed for evaluating high carbonate waters and is calculated by the formula given below: RSC = (CO32─ + HCO3─) ─ (Ca2+ + Mg2+) Where, the concentrations are reported in meq/l. RSC gives an account of calcium and magnesium in the water sample as compared to carbonate and bicarbonate ions. RSC value less than 1.25 indicates low hazard, whereas a value of 1.25- 2.5 indicates medium hazard and more than 2.5 indicates high hazard to crop growth (Kaur and Singh, 2011). The classification of irrigation water according to the RSC value is presented in Table-3.7.
Table-3.7: Quality of Groundwater Based on Residual Sodium Carbonate (RSC)
RSC (meq/l)
Quality
Pre-Monsoon 2010
Post-Monsoon 2010
Representative
Representative
Samples
Samples
2.5
Unsuitable
1
9
The value of residual sodium carbonate (RSC) have been calculated for both the seasons (Table-6.9) and compared with the above classification. It was found that during premonsoon 2010, 2 (13%) samples, where as during November 2010, 13 (87%) of the samples fall in doubtful to unsuitable quality. The remaining samples are of good quality from irrigation point of view. An important note-worthy point here is that when RSC is > 2.5, a salt layer called ‘Reh’ gets formed. A close study of the analytical data of water samples in both the seasons indicate that water showing high RSC values are associated with high fluoride concentration at most of the places.
CHAPTER 4 GROUND WATER QUALITY INDEX ASSESSMENT 4.1 GENERAL: Groundwater chemistry has been utilized as a tool to outlook water quality for various purposes (Rao, S.N., 2006). Calculation of water quality index (WQI) is an important technique for demarcating groundwater quality and its suitability for drinking purposes (Tiwari, T.N. et. al., 1985). WQI is defined as a technique of rating that provides the composite influence of individual water quality parameters on the overall quality of water for human consumption (Mitra, B.K., 1998). WQI indicates a single number like a grade that expresses the overall water quality at a certain area and time based on several water quality parameters. WQI reflects a composite influence of contributing factors on the quality of water for any water system. WQI a well known method as well as one of the most effective tools to express water quality that offers a simple, stable, reproducible unit of measure and communicate information of water quality to the policy makers and concerned citizens. It thus, becomes an important parameter for the assessment and management of ground water. Water quality of different sources has been communicated on the basis of calculated water quality indices. The effects of urban development on groundwater quality have been studied by many authors (e.g. Atwood and Barber 1989; Pelc 1990; Hirschberg 1991). Barber et al. (1993) have collected and analyzed existing data on trends in GW quality in relation to land use changes in order to determine the long-term impacts of urban developments. A GIS-based study was carried out by Barber et al. (1996) to determine the impact of urbanization on groundwater quality in relation to land-use changes. Nas and Berktay 2008 have mapped urban groundwater quality in Koyna, Turkey, using GIS. Vinten and Dunn (2001) studied the effects of land use on temporal changes in well water quality. Ahn and Chon (1999) investigated groundwater contamination and spatial relationships among
groundwater quality, topography, geology, land use, and pollution sources using GIS in Seoul, Korea. Ducci (1999) produced groundwater contamination risk and quality maps using GIS in Italy. Fritch et al. (2000) developed an approach to evaluate the susceptibility of groundwater in north-central Texas to contamination. Ben Hammou (1995) integrated groundwater geochemistry and cartography using GIS (Arc/Info) techniques. From Indian perspective, GQI was studied by many workers eg. Shivasharanappa et al(2010) studied Bidar city and its industrial area in Karnataka. Their analysis reveals that the groundwater quality status of the study area is excellent, but it also needs to be protected from the perils of future contamination by giving certain degree of treatment viz., disinfection. Reza and Singh(2010) studied GQI in Orissa state and their study revealed that the values of WQI have been affected mainly by the concentration of dissolved ions (F , NO , Ca and Mg ) in ground water. The values of WQI of the samples were found in the range of 14-57 in summer season while it was 19-67 in post-monsoon season. The higher concentration of dissolved solids during post monsoon samples exhibits poor quality of water as compared to summer season. It may be due to more seepage and movement of ground water during post-monsoon. Kalra (2012) studied Bojhpur area of Bihar and revealed that the ground water of the Koilwar block needs some treatment before consumption and it is also needs to be protected from contamination. Rao et al. (1973) applied the WQI in the assessment of ground water quality in Meghadrigedda watershed, Visakhapatnam district, Andhra Pradesh, India. Tyagi et al,2009. used the WQI in the study of spatial and temporal water quality trends of the pristine river Kshipra, Madhya Pradesh. WQI was used by Kakati and Sarma,1981 in the study of drinking water of Lakshimpur district, Assam. The quality of ground water in Tumkur Taluk, Karnataka state, was assessed by Ramakrishnaiah et al using WQI. Swarna Latha et al. used the WQI in water quality assessment at village level, S. Kota, Vizianagaram district.
4.2 GROUND WATER QUALITY INDEX ASSESSMENT: To generate the index, seven parameters listed in World Health Organization guidelines (WHO 2004) for drinking water quality were selected from the main dataset. Six parameters (Cl-, Na+, Ca2+, Mg2+, SO42-, and TDS) can be categorized as chemically derived contaminants that could alter the water taste, odour, or appearance and affect
its ‘‘acceptability’’ by consumers (WHO 2004). Thresholds for maximum desired concentrations have been proposed for these chemicals, but fixed guidelines have not been established. NO3- was categorized under chemicals that might inflict ‘‘potential health risk’’ and a guideline value of 50 mg/l was assigned (WHO 2004). The abovementioned groundwater quality parameters are also good indicators of changing landuse conditions on the surface. The following sub-sections describe the steps leading to the formulation of the GQI. The process involves the generation of representations for the spatial variability of the originally scattered measurements and the multiple transformations of groundwater quality data into a corresponding index rating value related to groundwater quality.
4.2.1. The primary map I: Concentration maps representing the “primary map I” was constructed for each parameter from the point data using mainly Kriging interpolation. Unlike other point interpolation methods (nearest point or moving average) Kriging is built on a statistical method. The Kriging method performs a weighted averaging on point values where the output estimates equal the sum of product of point values and weights divided by the sum of weights. The weight factors in Kriging are determined by using a user-defined semi-variogram model based on the output of the spatial correlation operation and the pattern analysis (ITC-ILWIS, 2001).
4.2.2. The primary map II: In order to relate the data to universal norm, the measured concentration, X’, of every pixel in the “primary map I” was related to its desired WHO standard value, X (Table 1), using a normalized difference index: C= (X’-X)/ (X’+X) The resultant “primary map II” thus displays for each pixel a contamination index values ranging between −1 and 1. This is close to the contamination index approach which is calculated as the ratio between the measured concentration of contaminant and the prescribed maximum acceptable contaminant level (Melloul and Collin, 1998; Praharaj et al., 2002; Babiker et al., 2004) however the normalized difference index used here provides fixed upper and lower limits for the contamination level.
4.2.3. The rank map: The contamination index (primary map II) was then rated between 1 and 10 to generate the “rank map”. The rate 1 indicates minimum impact on groundwater quality while the rate 10 indicates maximum impact. The minimum contamination index level (−1) was set equal to 1, the median level (0) was set equal to 5 and the maximum level (1) was set equal to 10. The following polynomial function can thus be used to rank the contamination level (C) of every pixel between 1 and 10: r= (0.5 * C2) + (4.5 * C) + 5 where C stands for the contamination index value for each pixel and r stands for the corresponding rank value.
4.2.4. Groundwater Quality Index The GQI was calculated as follows: GQI = 100 – ((r1w1 + r2w2 + ....... + rnwn)/N) r, stands for the rate of the rank map (1–10); w, stands for the relative weight of the parameter which corresponds to the “mean” rating value (r) of each rank map (1–10) and to the “mean r + 2” (r ≤ 8) in the case of parameters that have potential health effects (e.g. nitrate); N is the total number of parameters used in the suitability analyses. The main part of the GQI represents an averaged linear combination of factors. The weight (w) assigned to each parameter indicating its relative importance to groundwater quality, corresponds to the mean rating value of its “rank map”. Parameters that inflict higher impact over groundwater quality (high mean rate) are assumed to be similarly more important in evaluating the overall groundwater quality. Particular emphasis was given to contaminants that posses potential risk to human health (w = mean r + 2). This helps to reduce subjectivity associated with assigning weights of importance to the different parameters involved in the index computation. Dividing by the total number of parameters involved in the computation of the GQI averages the data and limits the index values between 1 and 100. In this way the impact of individual parameters is greatly reduced and the index computation is never limited to a certain number of chemical parameters. The “100” in the first part of the formula was incorporated to directly project the GQI value such that high index values close to 100 reflect high water quality and index values far below 100 (close to 1) indicate low water quality.
Fig.4.1 GQI Map of the study area. Fig 4.1 shows the groundwater quality index map for pre-monsoon 2010 season. Dark shade represents high GQI and good groundwater quality. In the study area, the GQI values suggest good groundwater quality. However, the relative spatial variation of groundwater quality is represented by GQI map. The GQI values range from 85.66 to 89.08. The GQI map shows low values in the central and south-western part corresponding to relatively poor groundwater quality. The west, north and some parts in the south show high GQI and thus relatively good quality.
CHAPTER 5 CONCLUSION The following conclusions are derived from the hydrogeochemical study of the area: ● The study area, a part of the vast central Ganga Plain, occasionally characterized by the development of depositional terraces, is covered by over 1000 m thick alluvial deposits of Quaternary age comprising at least 3 major aquifers intervened by poorly permeable to impermeable horizons. ● Bulk of the groundwater supply for the region comes through dug wells, hand pumps and shallow tube wells tapping the first aquifer, which being the shallowest is vulnerable to pollution due to anthropogenic activities and descent of water soluble surface material with recharging fluids. ● Bulk of the samples are moderately hard to hard with 41% samples being very hard during November 2010. TDS values are high, averaging >1000 mg/l for both the sets of samples, post-monsoon value being higher. ● On Piper’s Trilinear plot, it is clear that alkalis are most dominant among cations and bicarbonates among anions. On the basis of L-L diagram, samples could be segregated in to 3 clusters during pre-monsoon and one group during post-monsoon. All the clusters have Na + K > Ca + Mg,except group III of pre-monsoon having dominance of mixed ion concentration. Such chemical characteristics could be due to interaction of various natural and anthropogenic processes rather than water rock interaction alone. ● Based on SAR, bulk of June, 2010 samples fall in good to excellent category for irrigation but 33% of November 2010 samples exhibit medium sodium hazard. On the basis of RSC values, 13% and 86% of June 2010 and November 2010 samples, respectively fall in doubtful
to unsuitable category for irrigation. Samples with high RSC values are interestingly associated with high F values. ● TDS values are strikingly high in both the seasons, averaging > 1000 mg/l. High TDS values are confined to central, western and some parts adjacent to Sai-river. Post-monsoon TDS values are higher than those of Pre-monsoon period. ● Signatures of the meteoric origin of groundwater (Ca – Mg – HCO3 Type) have been completely obliterated and for a groundwater system there is anomalously high concentration of major ions, particularly, HCO3, Na, K, SO4 and Cl which is associated with relative deficiency of Ca and F. ● Not even a single sample collected from 15 locations in the study area of > 950 km2 may be considered perfect, in all respects, for human consumption. This deterioration in quality has occurred both with respect to major ions and trace metals. ● Unique chemical characteristics of groundwater are the outcome of several natural and anthropogenic processes. The groundwater regime is detrimentally affected profoundly both in qualitative and quantitative terms. Acquisition of chemical species in the groundwater is the result of a combination of processes, such as: 1. Water-rock interaction 2. Cation exchange 3. Dissolution of surface saline encrustations 4. Dissolution and precipitation of carbonates 5. Application of fertilizers 6. Influent and effluent behavior of surface discharges 7. Descent of household and industrial wastes to groundwater level 8. Industrial pollution due to leather tanneries and brick kilns.
The role of water-rock interaction is trivial and it is very difficult to identify the role of various processes in solute acquisition in quantitative terms. ● Major ions, particularly, Na, K, Cl and SO4 show rather anomalous concentrations which are difficult to be explained invoking water-rock interaction alone. Possible sources of these
ions could be speculated on the basis of their mutual relationships available, literature and information on local industries and agricultural practices. ● Ca and Mg are the only two ions whose average concentration does not seem to have increased significantly in the intervening period of June and November 2010. The depletion in the concentration of Ca can be partly attributed to the precipitation of carbonate and resultant decrease in Ca and HCO3 concentration levels in groundwater. Mg has not been involved in precipitation of carbonate and therefore its concentration levels are probably acquired through interaction in clay zones that have been retained. ● The entire area can be called as ‘calcium deficit’ as only 29% of the samples exhibit Ca level above the lowest desirable limit in both sets of samples. Ca deficiency may be responsible for many diseases of bones and teeth.
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