Home Articles Terrain mapping unit of Bharatpur district

Terrain mapping unit of Bharatpur district

Saif ud din, Iqbaluddin and Mukhtar Ahmad
Remote Sensing Application Centre for Resource Evaluation and Geo-engineering
Aligarh Muslim University
Aligarh, U. P.

The surface water bodies like lakes and rivers are endangered due to indiscriminate dumping of domestic and industrial wastes. It is found that nutrients from these wastes are causing algal bloom and prolific growth of macrophytes. These can be mapped using satellite data in 0.52 – 0.59 um. Chlorophyll – a concentration is a god indicator to quantitatively estimate the presence of Phytoplankton biomass. The present case study deals with Upper Lake, Bhopal. The methodology adopted is an integration of remote sensing, conventional laboratory analysis, global positioning system and geographic information system. ILWIS 2.1 GIS package has been used in the present analysis to accomplish the task of integration and production of chlorophyll – a map of the lake.

Water is one of the prime necessity for the survival of any civilisation. Surface streams and lakes are the main sources of fresh water. In recent years, one of the major problem being faced by our country is the pollution of surface streams and lakes. The reasons for this are rapid urbanisation and industrialisation, as these fresh water bodies are being used for dumping the sewage and industrial wastes. There are regulations and regulatory bodies to monitor the pollution in surface streams. But they are finding it too difficult or rather impossible to implement the regulations in absence of quick and cost effective monitoring techniques. Thus, there is a need to develop a monitoring techniques for the water quality frequently and take remedial measures to preserve these fresh water bodies. The term water quality refers to the chemical, physical and biological characteristics of water. The chemical characteristics include total dissolved solids, turbidity, colour, taste, odour, and temperature. The biological community present in the water body (Peavy et al, 1985). The trophic status of a lake is an important aspect to be monitored frequently as it indicates the effect of incoming sewage and other wastes in it. The test to determine the trophic status of the lake is the measurement of phytoplankton biomass (OECD 1982). Lakes enriched with nutrients exhibit excessive growth of phytoplankton (Vollenwieder 1968, Harper 1992). An excess of phytoplankton can create numerous problems such as clogging the water body and reduction in the water availability for human consumption. It is observed that lake area gets depleted with dead macrophytes and total storage capacity of the reservoir is adversely affected. In addition it also hinders the recreational activities and reduces the aesthetic beauty. Phytoplankton biomass is traditionally estimated by filtering water samples and then extracting the photosynthetic pigment – chlorophyll-a.

Aim of the Study:
The conventional point sampling methods are very accurate but they are time consuming and do not display the spatial and temporal variations. In this regard remote sensing techniques, using airborne or spaceborne sensors providing multispectral and repetitive data offers a great scope for regional monitoring with the advantage of providing synoptic view and better estimate of spatial distribution. The aim of the present study is to provide an alternate solution to conventional point sampling method of estimating water quality parameters using the tools of Remote Sensing and GIS. Here we have taken chl-a as the pollution parameter to be determined as a case study.

Study Area:
Upper lake-Bhopal make the western periphery of the Bhopal city. It is a large lake having a water spread area of 30.72 sq. km. and serves as the main source of water supply to the Bhopal city (Tamot and Srivastava, 1987). This lake has many outfalls dumping untreated city sewage and other wastes in it. From adjoining agricultural fields the fertilisers and other biomass also find their way into the lake during rainy season. These incoming wastes provide nutrients and cause algal boom.

Satellite Data:
For this study IRS-IC LISSIII image has been obtained from Nov 7, 1997 from NRSA, Hyderabad. Images of three bands i.e. band2 (0.52-0.59um), band3 (0.62-0.68um), band4 (0.77-0.86um) have been taken. The scene centre lies at 770 22′ 56”E and 230 15′ 00”N.

Field Sampling:
Field sampling in the lake has been conducted on Nov 7, 1997. The date was fixed keeping in mind the pass of the satellite over the study area during field sampling so that accurate relationship of chlorophyll -a with sensor records may be established. IRS-IC passes over the same area after 24 days.
Water samples were collected from various points inside the lake and brought for laboratory sampling. To accurately mark the location of sampling station inside the lake, a Global Positioning System (GPS) (SOKKIA-Spectrum) was used. Water samples from 45 different locations were collected. These samples were then tested in laboratory for chl-a concentration. The chl-a concentration has been determined by the spectrophotometric method (APHA-AWWA-WPCF, 1985).

In this study ILWIS 2.1 GIS package has been used. Different bands of IRS-IC data were initially geo-referenced with the help of Survey of India (SOI) toposheet (1:50,000) of Bhopal. The lake from toposheet is digitized using ALTEK A0 size digitizer. This map is overlain on digital image data and the portion of the lake is extracted for each band. Knowing the co-ordinates (lattitude, longitude) of the sampling stations from the GPS observations, reflectance values were extracted for a 2*2 grid of pixels and the mean value was taken for all the mean reflectance values of the four bands and the correspondence chl-a concentrations at the corresponding location. Of the three bands it was found that chl-a gives best correlation with band 2 (0.52-0.58um). The image of the lake in band 2 (green band) is shown in the Figure 1. Green band has also been found to give best correlation for determination of chl-a in productive lakes by George (1987). The model obtained is of the form

Chl-a=3.73565 R2 – 230.6679
Where, chl-a is chlorophyll -a concentration in mg/cu.m. and R2 is reflectance in band2. This model has offered coefficient of correlation of 0.895. The model was found to yield satisfactory result at 5 percent confidence level in Chi-square test.

The Chlorophyll model was applied on the band2 image of the lake. This produced a map of the lake (Figure 2) with chl-a values at every point. This map was then density sliced to give four zones of chlorophyll -a distribution.

As can be seen in the Figure 2, the highly polluted zones are appearing in red colour. The areas showing high concentration of chl-a are the areas which are receiving untreated sewage from a hospital (Hamidia hospital) and some densely populated slum dwellings (in Karbala, Koh-e-fiza, and Khanugaon area) of adjoining areas of lake. It is also observed that near the outfalls severe algal bloom occurs. The prolific growth of macrophytes are observed near upper left banks of lake due to agricultural runoff. It is observed that a large area in middle right portion of the lake is showing very low chlorophyll – a concentration as it is away from point and non – point sources of incoming nutrients.
The conventional GIS approach of mapping chl-a distribution may be the point interpolation method. But, it is realised that this method gives poor results for points situated at a larger distance from the sampling station. Hence to get an accurate estimate fairly large number of samples are required . Whereas the methodolgy adopted in this study is based on satellite sensor records and needs fewer sampling points and offers very accurate regional picture of the whole lake for chl-a distribution.
Similarly other water quality parameters such as SSC, total dissolved solids (TDS) and several other chemicals may be modelled and a regional map may be generated using the reflectance data from spaceborne sensors.

Authors are grateful to Sri S. K. Katiyar, Lecturer, MACT Bhopal for rendering useful help during fieldwork. Authors also thank for the kind help offered by Mrs Leela Ayyagar , Senior Scientific Officer, IIT Kanpur in carrying out chemical Laboratory analysis.


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