An Assessment of In-situ Water Quality Parameters and its variation with Landsat 8 Level 1 Surface Reflectance datasets

ABSTRACT The water quality represents the water’s physical, chemical and biological properties and depends on the environment, and anthropogenic influences. Recently, river water in Dehradun has subjected to immense pressure due to contamination from indecorous land use and urbanisation. In this study area, water quality assessment is carried out with the help of in situ observations and satellite surface reflectance from October 2018 to March 2019. Physicochemical and microbial qualities, namely, ambient temperature (AT), electrical conductivity (EC), water temperature (WT), potential hydrogen (pH), free carbon di oxide (CO2), biological oxygen demand (BOD), dissolved oxygen (DO), total dissolved solids (TDS), salinity (S), total Hardness (TH), calcium hardness (CH), magnesium hardness (MgH), sodium ion (Na), Potassium ion (K), nitrate (NO2), phosphate (PO4), and coliform concentrations (CC) were evaluated in the laboratory, plotted spatially in GIS environment and validated with the Indian Standards (IS). Furthermore, the Pearson correlation matrix was an established between the mean surface reflectance band values of Landsat-8 in the Google Earth Engine (GEE) and the water quality parameters are collected at each station location. The entire river water has been found an unsuitable for drinking but suitable for irrigation purposes. In future, such studies would be supportive for more effective management strategies to overcome the problems of water pollution.


Introduction
There is a well-known saying that water is life because each and every living organism need water to survive.Water not only plays a crucial role in our daily life but also supporting nutrient cycling to the ecosystem [1,2].Since the past times, human accomplished their daily needs and enjoyed the river ecosystem services without knowing about how the river ecosystem works or how to utilise it sustainably [3,4].In India, near about 64% of rural along with 37% of urban population is inaccessible to innocuous drinking water [5,6].India is facing a water shortage problem as a result of the population increase and the deprivation of natural reserves [7,8].It is the most significant element for the public as they are dependent on it for the preparation of foodstuffs, waste disposal, and other social needs [9,10].The riverine water helps in the farming, transportation, and economic development of the nation [11].Over recent decades, the inland freshwater bodies and their quality have been threatened and critically compromised by humans and environmental stressors, creating a potential threat not only on the water (surface and subsurface) but also to the entire ecological system [12].In the Himalayan region, river is the major supply of drinking water along with irrigation, but due to urbanisation, sewage discharge, and road construction, river water quality is sharply contaminated [13].The main source of river water contamination is industrial waste [14].Within 20 years, in the neighbouring areas of district Dehradun, industrialisation is gradually increased.Various industries are continuously damping-off their discharges and effluents with a large number of dyes, metals, and toxic chemicals that are solely responsible for damaging the aquatic flora and fauna.The hazardous chemicals are most harmful to water bodies, and it influences various water quality parameters [15,16].Potential contamination in inland water system disproportionately adverse impacts on human society and environment [17,18].The food-web structure of water bodies is changed due to changing the water quality.The change in physicochemical characteristics of water directly affects the productivity of primary and secondary consumers in the food-web of the water ecosystem [19].Commonly, the researcher says the term water pollution, which means its state has changed from the actual condition; therefore, its quality and function also have affected [20].
In recent years, GIS (geographic information system) and remote-sensing techniques are not only confined to some particular fields but also have shown a major involvement in the planning, development, and management of ecological assets.Therefore, it proposes a suitable technique to retrieve and merge the physicochemical data [21].Satellite imagery has great potential for regional monitoring and evaluation of the water quality.In some of the previous studies, different workers have used various models to evaluate the hydro-geochemistry quality spreading of groundwater [22,23].In the spatial interpolation and statistical methods, Geo-statistics methods are incorporated.It may be utilised to evaluate and signify the dispersal of attention whole space and period depend on the association between the sample locations, and evaluation of the irregularity of forecasting [24].Moreover, inverse distance methods (IDW) kriging techniques consider the three-dimensional association between the water sample locations points, classically working for analysis, and mapping of the spatial representation variation [25].Inverse distance weighted (IDW) method, one of the most commonly used geostatistical and mathematical interpolation techniques, has been applied to predict the target parameters in the field of hydrology science [26].It was developed for mapping and predicting spatial distribution maps, such as water quality parameters [27], methane flux [28], and rainfall intensity [29].In this study, IDW method was used to interpolate the spatial distribution of water quality scores and identify key regulatory areas of the Asan River.Numerous researchers have used spatial interpolation techniques (IDW, spline, and kriging) for the development and processing of water quality maps and data.Outcomes from the water quality mapping and processing can be utilised to tackle the accurate problems and identification of appropriate well sites, which depends upon the quality parameters of groundwater, geology, and soil.Several studies have shown that reliable empirical relations between Landsat Enhanced Thematic Mapper plus data and soil observations can be established for the water quality parameters like chlorophyll, total suspended sediments, and turbidity [30].Furthermore, water quality mapping and analysis were carried out by several workers along with policymakers using various spatial interpolation methods in the Arc GIS environment [31][32][33][34].
The Doon valley demarcates abundant drainage; however, the region suffers from rapid industrialisation near the streams.Rivers such as the Rispana, Bindal, and Suswa are almost in the moribund stage, which contains a very high load of the domestic and industrial waste in the area.In the study presented, we have tried to understand the changes in the physio-chemical characteristics of the Asan river using remote sensing and ground observational datasets.If the Asan river continues to be polluted in the same way, as per our observation, then shortly it might fall under the category of severely polluted streams.This study finds the usage of different spatial interpolation techniques to clarify regions in conjunction with elevated pollution and evaluate the productivity of the present observation of rivers quality.In India and other countries, more research has completed on the physico-chemical and microbiological aspect of the rivers but water quality parameters every seasons have been changed due to climate factors, In this view, regularly groundwater quality monitoring is important to river basin water [35][36][37][38][39][40]; however, very limited studies are found for the Asan river of Dehradun [41].Moreover, due to the rapid urbanisation in the Dehradun city, the studies pertaining to water quality needs to be done frequently, in order to properly curb its ill impact on the health of the riverine ecosystem.This will be the first study for the Asan river, in which water quality has been studied simultaneously using in situ water-quality parameters and its variation with surface reflectance datasets.

Study area
The present study was conducted at different sites located in the Dehradun district ranging between Longitude 77°40ʹ to 78° 0ʹE, and Latitude 30°15ʹ to 30°27 N and lying between Lesser Himalayas from north and Siwalik Hills in the south (Figure 1).The topographic relief of the area of study fluctuates from 450 to 612 m.The Asan river defuses its water in Asan wetland at the endpoint.It is an important tributary of the river Yamuna, which flows northwest of Doon valley.Doon valley has a distinct climatic characteristic.During the summer, average temperature ranges between 17°C and 36°C, while in winter months, the temperature reaches from a maximum 24°C to a minimum 6°C.Annually, the area gets average precipitation of 2073 mm.Nearly all of the annual precipitation received during the months from June to September, however, July and August months being the rainiest.The Asan river has religious importance in the Hindu religion.According to the Hindu mythological evidence from the Rig Veda, it has an identified as the Asmavanti (presently known as the origin place of Asan river, i.e.Gautam Kund near to the Chandrabani Temple, Dehradun).

Ground sample collection
Seven locations were selected for the observations and assessment of the river water quality (Table 1).These locations were selected based on sewage discharge sources, urban areas, and forest cover (Figures 1 and 2).

Landsat 8 image processing
It is recommended to collect the on-site sample on the same day of satellite acquisition to ensure reduced error and better calibration of the estimated water quality parameters.A total number of 8 cloud-free pre-processed Landsat 8 imageries from October 2018 to March 2019 have been further analysed in the Google Earth Engine platform and graphically represented in the form of reflectance of each band concerning the acquisition period for selected stations were plotted into the system.The values obtained were scaled

Sampling and water quality analysis
Standard APHA methods were followed to study the physicochemical characteristics of the water samples [7].At the time of experimental analysis of water quality, we have taken three replicates to avoid any extraneous error, and the mean values were recorded.The drinking water quality is an influential environmental determining factor for Health [4].Water samples were collected for the study of river quality because nowadays, so many anthropogenic activities are active near the surrounding area of the river.For the study of water quality, we have designated various physicochemical parameters like air temperature, water temperature, TDS (Total Dissolved Solids), pH, BOD (Biological Oxygen Demand), Salinity, TH (Hardness), CaH (Calcium Hardness), MgH (Magnesium Hardness), Sodium ion, Potassium ion, NO 3 (Nitrate), and PO 4 (Phosphorus) (Figure 3).The collection of water samples was done for the month of October till March 2019.Samples from the mid-channel of the streams were collected to avoid the neighbouring nonhomogeneousness alongside the river bank.All samples were collected in 500 ml.Pyrex glass specimen bottles and stored for further use.Before use, sampling bottles were saturated in the solution of 1 M nitric acid and washed properly with deionised water.During water sampling, the collection timing was similar for each selected site.The measurement of ambient temperature, dissolved oxygen, and pH was done immediately after sample collection at the site [42], whereas; remaining parameters were evaluated at the lab.The inverse distance weighted (IDW) other spatial interpolation techniques were used for the generation of river quality maps.Geographical Information System (GIS) techniques were utilised to spatially prepare thematic maps and creating spatial comparisons of river quality data [43].The different physicochemical parameters estimation was carried out through spatial interpolation methods in the Arc-GIS 10.3 software [44].The standard guideline values recommended by the [43] were used to compare the physio-chemical parameters of the analytical results and were correlated with the satellite observations.In this study, the method of spatial interpolation like IDW (Inverse Distance Method) was an incorporated to estimate the water quality values between the measurements [45].The better outcomes from spatial interpolation methods are determined when sample location points are satisfactorily large to denote the limited changes [15,22,44,46,47].In this study, sampling of the river water was done by using a drainage map.The drainage map was derived from the Survey of India toposheets (No. 53 F/11, 53 F/15, 53J03) and Landsat 8 satellite data (Figure 3) [48,49].The satellite data and toposheets were rectified using the coordinate system-Universal Transverse Mercator (UTM) and the World Geodetic System (WGS) 1984 datum 43 zones using ERDAS software.Satellite data were atmospherically and radiometrically corrected in the ERDAS 2014 software.Satellite image classification was carried out by assigning per-pixel signatures and distinguishing them into the land use types based on the origin of the exact digital number (DN) value of various landscape basics.The spectral signature of earth surface features was identified on the Landsat data for preparation of the land use and land cover mapping.This land-use map was prepared based on the random forest classification technique.This correction depends on the AOI.Data.This land-use mapping provides better information about the landscape of the study area [50].

Total viable count (T.V.C.)
TVC was estimated on the basis of standard microbiological procedures [51].Water samples were diluted in a 1:9 ratio with the help of sterile 0.85% saline.Inoculated the diluted water samples on nutrient agar (Hi-Media) Petri plates in triplicate.Then, incubated the plates for 24 hours at 25°C temperatures in Incubator.Calculated the bacterial colonies unit (CFU/ ml.) as the colony number per plate and multiplied it by the dilution factor.

Presumptive coliform test
A multiple-tube fermentation experiment was done for the Presumptive coliform test [52].For the coliform isolation, Lauryl Tryptose Broth (L.T.B., HiMedia) was used as a differential medium.Five tube series of L. T. broth were prepared.The first tube series encompassing five tubes with double strength broth and the remaining two series containing 10 tubes with single strength broth.Tubes were then inoculated with 10 ml., 1 ml., and 0.1 ml. of water in the ratio of 5:5:5, respectively.The tubes were incubated at 37°C temperature and observed after 24 and 48 hours.The presumptive tests are said to be positive for coliform if the production of acid and gas in Durham tubes took place (Figure 4).

Confirmatory test
The confirmatory test was performed to ensure the coliform bacteria.A loopful inoculum from a positive tube of the presumptive test was transferred into a BGLB tube (Brilliant Green Lactose Bile Broth, Hi-Media) with a Durham tube.Then, the BGLB tubes with Durham tube were incubated for 24 to 48 hours at 37°C temperatures for the total coliform while for the faecal coliform the incubation temperature was 44.5°C and finally, observed the gas production.

Completed test
Completed tests are required to avoid any extraneous errors confronted during the confirmatory test.To obtain the pure colonies, a loopful inoculum was streaked on E.M. B. Agar (Eosin Methylene Blue Agar, HiMedia) plate from each positive tubes of the confirmatory test.Then, incubated the plates for 24 to 48 hours at 37°C temperatures.Green colonies with metallic gleam were detected.Noted down the MPN (most probable number) per 100 ml. of the water sample.The rich population of bacteria is the consequence of the inflow of washed organic substances in the river from the adjacent suburban areas.

Results and discussion
This paper focuses on the measurement water quality of the river by using various parameters for water quality assessment and surface reflectance of satellite imageries; these parameters are useful for the planning and management of the environment and water quality.In this study, water quality and field attribute databases were established to generate thematic maps of important parameters of river water quality viz.EC, pH, TDS, the temperature of the water and ambient temperature, etc. River water quality thematic maps were prepared, where an appropriate position in the river for the use of drinking and non-pollution water was visualised.All water quality data were analysed using spatial interpolation methods.Furthermore, the variation of surface reflectance of satellite observations was graphed with the ground observation for further analysis.This outcome of the thematic maps and satellite observation of river water quality helps us to identify the current problems and the potential of water quality conditions in the river as well as in the region.

Ambient temperature
The temperature of the surface determines the air temperature.Commonly it is measured as a weather parameter.In particular, temperature defines the kinetic energy or motion energy of the gases that make up air.The gas movement would be quick as air temperature rises.In the present study, the minimum recorded temperature was 16.2°C in February 2019 at Site-1, and the maximum temperature recorded was 24.55°C in December 2018 at Site-1.The temperature of the water fluctuates concerning air temperature, which ultimately affects water hotness or coolness (Figure 5).

Water temperature
The water temperature is very crucial for its influence on the biological, biochemical, and chemical parameters of the aquatic system.It is one of the most essential attributes that significantly influence the patterns and trends of water quality shift together with the metabolism of water life.The range of water temperature enriches the microbial growth and changes the colour, odour, taste, and causes corrosions [53].The temperature of water usually follows the ambient temperature closely, but the range differs depending on the geology, the coverage of vegetation, and the pollutant load in the water system.In addition, water volumes, depth, and direct solar radiation also influence the river water temperature.The present finding reveals that the monthly variations of temperature fluctuated between 14.17°C and 21.37°C.The minimum temperature was recorded at 14.17°C in January 2019 at Site-1, and the maximum temperature was recorded at 21.37°C in October 2018 at Site-VII (Figure 6).During this study, it was found that the instabilities in the river temperature depend generally on the climatic factors, sampling time, and the temperature of the effluents that spills over into the river [49].

Potential of Hydrogen
In river chemistry, pH plays a critical role.The water pH affects the solubility of metals, various toxic and nutritive substances, and may impair the availability of aquatic species.Extraordinary changes in pH or rapid pH may cause stress or destroy aquaculture.Several animals experience even minor deviations from acceptable pH requirements [19].A reduction in pH (increased acidity) will increase the supply of metals and increase organism absorption and may trigger physiological harm to water life [13].The toxicity of cyanides and sulphides also increases with a decrease in pH.Conversely, due to a trivial increment in pH, ammonia comes to be more toxic.The presence of carbonates and hydrogen carbonates in river water is usually more alkaline.Surface water is less buffering and thus are more shifting with the pH [21].Usually, surface waters have a pH of nearly 6.5 to 8.5 and never exceed the range of 4 to 9. In the present study, the pH of the Asan river fluctuated from 5.79 to 8.19.The minimum pH was recorded 5.79 in October 2018 at Site-II, and the maximum pH was recorded in 8.19 in December 2018 at Site-III (Figure 7).The analysis revealed that the pH values for alkaline in river water did not differ considerably due to the high temperature that allows CO 2 solubility to be decreased [33].

Electrical conductivity (EC)
Electrical conductivity is a measurement of the capacity of water to convey the electrical current expressed in μmho/cm [34].Water EC impacts inorganic solid dissolution (ion with a negative or positive charge).The effects of organic material decomposition and mineralisation will enhance EC and cation levels [9].Rates were strongly positive for all parameters except dissolved oxygen, total solids, and total solids.In the present study, the EC of the river water fluctuated between 0.15 and 0.90 µmho/cm.The minimum EC was recorded 0.15 in November 2018 at Site-IV, while the maximum EC was recorded 0.90 in October 2018 at Site-I (Figure 8).The higher EC suggests a higher degree of mineralisation and the influence of strong anthropogenic activities in the Asan river charging environment.

Free CO 2
The atmospheric water interface of carbon dioxide (CO 2 ) enters the water and is, of consequence, the solution as metabolism by-product of the hydrobiological analysis of the Dahikhuta reservoir as defined by [54].Along with the downstream, the free carbon dioxide content of water increased [25].reported similar findings while studying the  pollution status analysis of the Moirang river of Manipur.The heavy inflow of organic waste leads to a high concentration of free CO 2 .CO 2 rise reflects the increase in the volume of emissions [24].In the present study, water-free carbon oxide values fluctuated between 0.83 and 7.89 mg/l.The minimum free CO 2 was recorded 0.83 mg/l in March 2019 at Site-IV, and maximum free CO 2 was recorded in 7.89 mg/l in December 2018 at Site-III (Figure 9).

Dissolved oxygen (DO)
Dissolved oxygen is one of the key criteria for water quality evaluation.The temperature depends on the average concentration of oxygen that can be absorbed into water and therefore, DO water content can change globally and occasionally [55].A diversity of life forms in the water sources are essential to preserve.A low DO level indicates a heavy load of emissions.DO variations are often caused by water temperature changes, as well as the introduction of oxygen requiring waste [24,56].found that the high amount of organic matter in the waste greatly impacts the oxygen balance of the river and adversely affects the water and the consistency of the sediment.During October and November months, increased DO value was observed while the decreased DO value was observed in January, February, and March.DO depends on several factors, including rainfall, water salinity, water erosion, plant life in the water, riverbed type of rock, and the presence of contaminants.The Central Pollution Control Board (CPCB) specifies the drinking water dissolved oxygen limit for wildlife and fisheries to be 4 mg/l or more dissolved oxygen.In the present study, Dissolve oxygen fluctuated between 4.37 and 11.46 mg/l.The minimum DO was recorded 4.37 mg/l in February 2019 at Site-II, and the maximum DO was recorded in 11.46 mg/l in October 2018 at Site-III (Figure 10).

Biological oxygen demand (BOD)
The BOD is used to quantify the organic material quantity in an aquatic environment that promotes microorganism growth.BOD is the rate at which dissolved oxygen is used by bacteria and other microorganisms for the decomposition of organic matter.BOD is an indirect evaluation of the biodegradable content in the water.The BOD for water and waste water is the volume of molecular oxygen needed for aerobic oxidative activity to stabilise decomposable organic matter in water.Elevated organic matter in river waters increases the BOD to oxidise the organic matter.In the present study, BOD fluctuated from 1.70 to 7.06 mg/l.The minimum BOD was recorded at 1.70 mg/l in March 2019 at Site-I, and the maximum BOD was recorded in 7.06 mg/l in November 2018 at Site-V (Figure 11).It is indicating that the river is moderately polluted.

Total dissolved solids (TDS)
TDS in the water is predominantly composed of different organic matters, salts, and salt particles like bicarbonates, nitrates, carbonates, phosphates, chlorides, sulphates of calcium, magnesium, manganese, potassium, and sodium [33].The residue left after evaporation of the filtered sample determines the Total dissolved solids and is reported in mg/l.According to BIS Standard, the desired TDS must be 500 mg/l, and during the unavailability of the healthier source of water, it may be 2000 mg/l [11].The corresponding criterion is 'hardness measured as CaCO3' where the acceptable limit is 200 mg/l and the maximum allowable limit is 600 mg /l.In our study, total dissolved solids fluctuated between 210.37 and 582.25 mg/l.The minimum TDS was recorded 210.37 mg/l in November 2018 at Site-IV, and the maximum TDS was recorded in 582.25 mg/l in October 2018 at Site-IV (Figure 12).

Salinity
Salinity is the indicator of all salts that have been dissolved in water.In surface and groundwater streams, the salts are strongly soluble and can be moved with water flow.Salt is usually measured in parts per thousand (ppt).The permissible limit of salinity for rivers and lakes is 0.5 ppt or 500 mg/l [11].In the present study, the Salinity of river water fluctuated between 0.18 and 0.81 mg/l.The minimum Salinity was recorded at 0.18 mg/l in January 2019 at Site-II, and maximum salinity was recorded in 0.81 mg/l in January and March 2019 at Site-III (Figure 13).The data of salinity in our study period revealed that salinity is below the permissible limit for drinking water.

Total hardness (TH)
Total hardness is a water content metric used to characterise the impact of the dissolved mineral that defines water solubility for residential, industrial and potable purposes due to the inclusion of calcium and magnesium bicarbonates, sulphate, chloride, and nitrates.TH concentration of metal ions represented in terms of mg/l of equivalent CaCO 3 .The Hardness of water indicates water quality, essentially in the relation of calcium and magnesium, but it is not a parameter for pollution indication.The acceptable limit of TH as   CaCO 3 is 200 mg/l [11].In the present study, TH of river water fluctuated between 57.67 and 481.90 mg/l.The minimum Hardness was recorded 57.67 mg/l in November 2018 at Site-IV, and the maximum hardness was recorded in 481.90 mg/l in January 2019 at Site-III.

Calcium hardness (CaH)
The amount of all the calcium dissolved in water (limestone, gypsum dolomite, and gypsum ferrous) is considered the hardness of calcium.CaH is most generally expressed as an equivalent of Mg Calcium Carbonate equivalent per litre.Calcium is important since high levels are unstable and much more unstable when the pH or overall alkalinity is greater than average levels.These imbalances will contribute to scaling and cloudy water.If the temperature of the water raises, calcium is more prone to precipitate.Usually, water containing CaCO 3 at concentrations below 60 mg/l is considered as soft; 60-120 mg/l, moderately hard; 120-180 mg/l, hard; and more than 180 mg/l, very hard [53].In the present study, CaH of river water fluctuated between 37.87 and 143.5 mg/l.The minimum CaH was recorded 37.87 mg/l in October 2018 at Site-Ⅶ, and the maximum CaH was recorded in 143.5 mg/l in December 2018 at Site-Ⅴ.A similar trend was observed by [8].

Magnesium hardness
Calcium and magnesium are primarily found in the form of ions (i.e.Ca 2+ and Mg 2+ ) in low and medium mineralised underground and surface waters (as drinking water).The amount of magnesium usually is lesser than calcium in the water, which can easily understand that magnesium found in the earth's crust has much lower amounts as compared to calcium.In the present study, magnesium hardness of river water fluctuated between 6.70 and 63.75 mg/l.The minimum Mg hardness was recorded 6.70 mg/l in November 2018 at Site-II while the maximum Mg Hardness was recorded 63.75 mg/l in February 2019 at Site-III.

Sodium-ion
Sodium is one of the most significant natural cations, with amounts typically smaller than calcium and magnesium in natural waters.The primary cause of sodium in natural waters is the weathering of various rocks.Many agricultural waste and domestic sewage are high in sodium and raise their concentration after discharge in natural waters.In the natural world, sodium is a normal ingredient and also contained in water.In water, sodium may occur naturally or as a consequence of the use of road salt, water chemicals or softening agents for ion exchange.The EPA suggests that sodium from drinking water should not exceed 20 mg/ l.EPA endorses that sodium concentrations in drinking water should not exceed 30 to 60 mg/l to avoid the antagonistic impacts on taste, a threshold for taste-sensitive population fragments.The permissible limit of the sodium ion is 200 mg/l [11,43].The data of sodium ion in our study period revealed that the sodium ion is below the permissible limit.

Potassium ion
Potassium is significantly less prevalent than sodium, in igneous rocks but in all sedimentary rocks potassium is more plentiful.This point to somewhat distinct actions of natural environments of these two alkali metals.Potassium is slightly harmful owing to its low transformation ability and strong water mobility.Potassium plays an important function in plant development and growth.Potassium from the dead and decaying plant as well as animal material is often bound to earthen minerals in soils earlier and gets dissolves in water.Permissible limits of potassium ion for drinking water are 12 mg/l [11,43].The data of Potassium Ion in our study period revealed that the Potassium Ion is below the permissible limit for drinking water.

Nitrate (NO 3 )
Nitrate is a water-soluble molecule made up of nitrogen and oxygen.As a result of anthropogenic activities like disposal of wastewater, sewerage, excreta from animals and humans, excessive use of nitrogenous manures, and fertilisers in agricultural fields, nitrates can spread to surface and groundwater.The concentrations of surface water nitrates may shift rapidly because of the surface runoff of fertilisers, phytoplankton ingestion and bacterial denitrification, but groundwater levels normally display reasonably slow changes [43].The high concentration of nitrates can result in algal blooms and the release of toxic substances (cyanotoxins), which causes the death of fishes [16].The permissible limit of nitrate for the drinking water is 45 mg/l [11].The data of nitrate in our study period revealed that the NO 3 is below the permissible limit for drinking water.

Phosphate (PO 4 )
Phosphorus is considered to be the main limiting nutrient for primary production in most freshwater aquatic systems, and therefore, its determination in natural water may yield significant conclusions regarding water quality [54].The major sources of phosphate in rivers are municipal sewage, industrial wastes, synthetic detergents and agricultural runoff, domestic sewage generally yields organic phosphates, while orthophosphate (inorganic phosphate) comes through detergents, fertilisers, and similar substances.The high phosphate concentration is always suggestive of eutrophic conditions [55].

Microbiological assessment
A widely used indicator of pathogenic organisms for microbial water contamination is the coliform group of bacteria.Coliforms are useful because they resided in the intestinal tract of mammals.Contamination by anthropogenic activities like human and animal waste in water bodies causes waterborne diseases like diarrhoea, hepatitis, and typhoid [56, 57 and 43].Therefore, the presence of coliforms in the waterbody specifies the possibility of faecal contamination, and therefore, water is hazardous for consumption.According to BIS, the coliform count should be <10 colonies/100 ml.In the course of the laboratory analysis, we observed a wide range of total and faecal coliform count.During the months of January, February, and March the average total coliform count in the water samples was found to be in the wide range of 24 to 109 and faecal coliform varied from 3 to 27 colonies/100 ml.Similarly, during the months of October, November, and December the average total coliform count was found to be 3 to 18 and faecal coliform varied from 26 to 95 colonies/100 ml.The investigated data revealed the contamination of total and faecal coliforms in the Asan river.In the water samples of Asan river, the intense level of coliform counts signifies a contaminated source, unsatisfactory and unhealthy management of solid wastes.There must be some solid planning and management to surmount the above-said problem for the Asan river.

Variation of surface reflectance with in-situ water quality parameters
In the present study, mean spectral reflectance value of LANDSAT 8 Level-1 product for all the study sites i.e.S1, S2, S3, S4, S5, S6, and S7 were correlated with the values of each in-situ water quality parameters and shown in Figure 14.It was found that the plot of ambient temperature and water temperature were negatively correlated with the surface reflectance for all the stations and having maximum negative values at S6 (−0.96) and S1 (−0.63) for AT and WT, respectively.In majority of the location the pH was found to be positively correlated having maximum correlation at S6 (0.76) followed by S7 (0.73).Theconductivity showed negative correlation for majority of the stations with maximum negative correlation at S7 (−0.8).The free CO 2 showed positive correlation at station S4, S5 and S6 with maximum value at S5 (0.87) and negative correlation at S1,S2,S3 and S7 with maximum negative value at S2 (−0.77).The DO, BOD, TDS, showed negative correlation at majority sites with maximum negative value at S1 (−0.77),S6 (−0.45), and S5 (−0.36) for DO, BOD, and TDS respectively.The salinity showed positive correlation at station S3, and S7 with maximum value at S7 (0.96) and negative correlation at S1,S2,S5 and S6 with maximum negative value at S2 (−0.64).The TH showed positive correlation at station S1, S2 and S3 with maximum value at S3 (0.86) and negative correlation at S4, S5, S6 and S7 with maximum negative value at S4 (−0.5).The Ca showed positive correlation at station S1, S2, S3 and S7 with maximum value at S2 (0.37) and negative correlation at S4, S5 and S6 with maximum negative value at S4 (−0.28).The Mg showed positive correlation at station S1, S2 and S5 with maximum value at S2 (0.83) and negative correlation at S3, S4, S6 and S7 with maximum negative value at S7 (−0.65).The Na showed positive correlation at station S2, S5 and S6 with maximum value at S6 (1.0) and negative correlation at S1, S3, S4 and S7 with maximum negative value at S7 (−0.5).The K showed positive correlation at station S4, S5 and S6 with maximum value at S4 (0.44) and negative correlation at S1, S3, S7 with maximum negative value at S3 (−0.5).The NO 3 showed positive correlation at station S1, S4, S5 and S7 with maximum value at S7 (0.39) and negative correlation at S2, S3, S6 with maximum negative value at S6 (−0.37).The PO 4 showed positive correlation at station S1, S2, S3 and S4 with maximum value at S1 (0.13) & S4 (0.13) and negative correlation at S4, S5, S6 with maximum negative value at S5 (−0.49).These correlation plot signifies the variation of each water quality parameters with the surface reflectance and help in determining the proper reflectance bands for each parameter.So that, in the absence of in-situ datasets, the satellite observation could by itself reveal the nature and trend of water quality.

Conclusion and recommendation
The study accomplishes that the river water quality assessment depends on many factors like hydrological conditions along with natural or anthropogenic activities.This study presented a basic condition of water quality of the Asan river with the help of in-situ measurements and satellite surface reflectance datasets.Uncontrolled urbanisation and industrialisation in close proximity of the river side may deteriorate the microbiological and physicochemical status.If such type of circumstances remains in the future, pollution may get poorer and create potential health hazards.This study also unveiled that the existence of a raised level of the bacterial population that indicates the pollution state of the Asan river.According to the permissible limit, as defined by WHO [58], the concentration of the different physicochemical parameters exceeds.Consequently, direct water intake, domestic uses may directly pose a high risk to human health.The current study estimated that the Asan river in Dehradun is most polluted, and the data produced on physicochemical and microbiological water quality parameter components give a clue for the need for urgent management approaches for its protection.Thus, it can be determined that the Asan river is heavily polluted by untreated wastewater and by waste from point-to-point sources from pesticides and insecticides employed on the farms.Since the development of many hospitals, housing waste, road building waste, factories (in Selaqui), the pollution rates in the Asan river further increased.Analysis of water samples from different areas has shown that the contamination rates of the river and river bodies were more by large amounts of sewage, agricultural waste, and cremation at Badowala Bridge, Khushalpur, and Naya Gaon.Heavy contamination of coliforms revealed that river water is under pollution from sewerages and also through overspills from the areas of open excretion near the river banks.The water quality analysis for drinking purposes also determined that water was found inappropriate for drinking and irrigation purposes.It is further emphasised that appropriate sanitation services must be delivered in the neighbouring areas of the river system to regulate the microbial contamination.The correlation plot of surface reflectance datasets with the in-situ water quality parameters reveals that, in the absence of in-situ datasets, the remote sensing observation could also be utilised for the approximate estimation of water quality variations.These results highlight the quality of water in the Asan river, which could be utilised by the policymakers to take necessary action, and eradicate the water contaminations.Along with this, the establishment of proper urban drainage systems and rainwater harvesting in the region can reduce the dissemination of contamination from agricultural runoff, industries, and urban areas in the Asan river.

Figure 1 .
Figure 1.Study area map with sampling points using Landsat 8 (FCC) data.

to a factor of 10
,000.The images have mainly eight spectral bands viz.Band 1 (coastal/ aerosol), Band 2 (blue), Band 3 (green), Band 4 (red), Band 5 (near-infrared, NIR), Band 6 and Band 7 (SWIR1 and SWIR2) and Band 9 (cirrus) with a spatial resolution of 30 m; Band 10 and Band 11 (TIR-1 and TIR-2) have a resolution of 100 m, while Band 8 (panchromatic) has a resolution of 15 m.To estimate the correlation between the surface reflectance values and observed water quality parameters plotted the graph.

Figure 2 .
Figure 2. Drainage map of study area with sampling points using toposheet.

Figure 3 .
Figure 3. Outline of the methodology used in the study.

Figure 5 .
Figure 5. Thematic map of ambient temperature.

Figure 6 .
Figure 6.Thematic map of water temperature.

Figure 9 .
Figure 9. Thematic map of Free Carbon Dioxide.

Figure 14 .
Figure 14.Obtained values of correlation coefficient and mean surface reflectance at each station location.

Table 1 .
River water quality sampling location.