Water Quality Assessment of Jharia Coal Field in Dhanbad district Using Geospatial Tools

*Gaurav Chakrabarty **Ritesh Kumar *Msc Geoinformatics, BIT Mesra Ranchi

gaurav_chakrabarty2004@yahoo.com **Scientist CIFMR Dhanbad

ritesh13@rediffmail.com

Abstract Jharia coalfield spread over an area of 450 sq. km. and contains 40 identified coal horizons and has one of the highest coal densities in the world The coalfield has a vast number of streams and Damodar river is the main drain of the area. The mining and associated activities have altered the surface drainage pattern of the coalfield to a great extent and in the last century more than 100 km of the natural streams/drains have vanished from the coalfield area. Damodar river is considered to be one of the most polluted river in the country In this study an attempt has made to assess the surface water turbidity using Remote Sensing and GIS technique. In this study LANDSAT ETM+ data has been used to obtain an optical measure of water colour and turbidity Remote sensing offers considerable advantages for the study of large areas, determination of water current and water circulation patterns, and monitoring of sedimentation, water productivity, and eutrophication. Further, water turbidity data from CIMFR and MADA has been used to prepare Water Quality Index Map of JCF. Introduction

Jharia coalfield (JCF) is probably one of the most talked about coal mining area not only in the country but also in many countries abroad due to its typical characteristics and unique status and problems. Mining in the coal field started in the year 1894 and most of the mining was underground until the nationalization of the coal mines in the country in 1971 and 1973. Opencast mining was done only in the areas having outcrops of the seam. The mining operation carried out by various companies is approximately in 450 sq. km. area The major source of Water Pollution in the coal mines is the carry over of the suspended solids in the drainage system of the mine sump water and storm water drainage. The impact of mining on water resources may range from minimal through to severe. The effects depend on the location of the mine, the hydrology and climate of an area, and the

physical and chemical properties of the coal, associated strata, and reject materials.

In this study LANDSAT ETM+ data has been used to obtain an optical measure of water colour and turbidity. Colour increases the absorption of light in water and decreases the remotely sensed signal; turbidity increases the backscatter of light. For low concentrations of suspended materials, spectral reflectance is determined mostly by the absorptance characteristics of water. For higher concentrations, the absorptance characteristics of suspended particles are the most important factor. Remote sensing offers considerable advantages for the study of large areas, determination of water current and water circulation patterns, and monitoring of sedimentation, water productivity, and eutrophication. Further, water turbidity data from CIMFR and MADA has been used to prepare Water Quality Index Map of JCF.

Measuring Water Turbidity using satellite data

The feasibility of measuring water colour and turbidity from satellites can be

assessed by considering light and water interaction processes and by evaluating the

effects of atmospheric and hydrological variables. Water parameters that affect the energy levels detected by a camera or scanner are colour and turbidity. Differences in water colour and turbidity affect signals in the visible and very near ultraviolet and infra-red wavelengths. An increase in water colour decreases the energy flux reaching a sensor, because more of the sun's energy is absorbed in the water. An increase in turbidity increases the energy flux reaching a sensor, because more solar energy is reflected or backscattered by the particles that produce turbidity. An increased signal also occurs, however, in clear, shallow water where some solar energy is reflected from the bottom. If the solar energy that reaches a water surface is represented by Io, the interaction is expressed by:

where, ISR is the solar flux that is specularly reflected at the water surface (the mirror

effect), IA is the flux absorbed by the water, and IB is the flux backscattered to the water surface and thereby available for remote detection. Specular reflection is equal at all wavelengths, but absorption and backscatter produce distinctive spectral signatures.

Pollutants generally affect the colour, turbidity, temperature, or microwave emissivity of water to be detectable by remote sensing. Dissolved coloured materials increase light absorption in water but do not affect their initial light scattering characteristics. Nevertheless, the spectral distribution of backscattered energy is affected by additional absorption. A brown water, for example, backscatters much less blue light and slightly less green and red light than a clear water. The average path length for light in coloured water is the same as in clear water. Table 1 lists the relative turbidity as seen from different bands in LANDSAT data.

Table 1: Relative Turbidity from different Bands in LANDSAT Data

Tone of Image Relative Turbidity Band 4 Band 5 Band 6 Band 7

None Dark Dark Black Black Slight Medium Dark Black Black Moderate Light Medium Dark Black Heavy Light Light Medium Dark Very Heavy Light Light Light Medium

Source: Moore K.G. ,Satellite remote sensing of water turbidity, Hydrological Sciences-Bulletin-

des Sciences Hydrologiques, 25, 4, 12/1980 Methodology Adopted

In this research LANDSAT ETM+ data of JCF has been used and separately the Band 4, Band 5, Band 6 and Band 7 data have been analysed in detail using ERDAS IMAGINE. However, since the resolution of band 4, band 5 and band 7 is 30m and that of band 6 is 60m, so it was very difficult to

predict turbidity in small water resources like small ponds or reservoirs. For those water resources, non-spatial turbidity data obtained from CIMFR and MADA is used in conjunction with image interpretation. Further, water quality index map has been generated using both spatial and non-spatial data.

Results and Discussion

The LANDSAT ETM+ band 4, band 5, band 6 and band 7 geo-rectified images are shown in Figure 1 . These images are analysed in detail and the concept of image interpretation as given in Table 1 is applied to find out the Turbidity content in various parts of Damodar river and other water resources in the coal mining area. However, as stated

before, with the resolution of LANDSAT ETM+ data, it is not possible to obtain the turbidity content in small ponds and other water resources like small drainage or nala in the coalfield, so for those places the non-spatial data obtained from CIMFR and MADA is used to generate the final Water Quality Index Map.

Figure1. LANDSAT ETM+ Images of Band 4, Band 5,Band 6 & Band 7

Band 4 Band 5

Band 6 Band 7

While generating the water quality index map the quality has been categorized into four divisions from the data obtained from CIMFR

and MADA. The quality index so used is tabulated in Table 2.

Table 2: Quality Index

Water Quality Turbidity (mg/L) Slight Less than 100 Moderate 100-200 Heavy 200-300 Very Heavy Greater than 300 Using the categorization of Water Quality as given in Table 2, Water Quality Index Map and the geo-database of water quality is prepared in ArcGis. The Water Quality Index Map is given in Figure 2. It was found from the final analysis that the mining and its allied area with a distant about 50m experience the highest degree of water pollution. The fact there of is that the suspended particulate

matter (SPM) due to mining which is the major source of turbidity in the JCF can carry by air generally to a distance of 40-60 m. On the other hand when different small streams nearby mining area also becomes a source of turbidity carrier to other parts of Jharia. This is one of the biggest reasons for the pollution of Damodar River

Conclusion The water pollution in JCF is a great

threat to the people including mine as well as non-mine workers. Since the turbidity content in surface water is very high, generally underground water is used. But, with the continuous extraction of ground water has

resulted scarcity of water, especially in summer season when the water level drops below.In those periods, the surface water is being used and as a result many chronic diseases have emerged out in this area, making the life of people really pity

.

Figure 2: Water Quality Index Map of JCF

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