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Arsenic Mapping for North 24- Pargana District of West Bengal –using GIS and Remote Sensing technology


Analysis :
From the various process as described above, the following analysis have been derived.
  1. The contour map of arsenic concentration of each block was derived using weighted average of the arsenic concentration value. A thematic map was generated to form a classified output with five ranges. The classified output was converted into layer to get an idea of the total area affected.
  2. The matrix modeling was performed using arsenic concentration values and the depth of occurrence of arsenic values. In the present scenario high arsenic value at a shallow depth was considered to be unsuitable for drinking water and low value at shallow depth was considered to be safe for drinking water. With the help of matrix overlay, the two thematic maps were algebraically mapped to bring out five classified areas in an index scale of five, higher index means unsuitable and lower means safe.

    Arsenic break values 0.01 0.05 1.5 2.00 2.85
        0 1 2 3 4 5
    Depth 0 0 0 0 0 0 0
    112.31 1 0 0 5 5 5 5
    261.29 2 0 4 4 4 4 5
    410.27 3 0 3 3 3 4 4
    559.25 4 1 2 3 3 4 4
    708.23 5 0 1 1 1 1 2

  3. Multi-criterion modeling was performed using three impacts to find out an area which can be consider to a highly sensitive zone or danger zone. The presence of arsenic alone over the district is not important; the other related issues like population density and the depth at which it is occurring are also very important considerations to bring out the most danger prone zone. Here also the raster GIS concept of map algebra was used to co-relate the individual weight ages of arsenic concentration, population density and depth. Arsenic was given the highest weightage and it’s further subdivisions were again scaled and given scores. The second important factor considered was population of that area and the third parameter was the depth at which it was present. In a scale of 100, arsenic concentration was given a weightage of 50, the population density of that distric was given a weightage of 30 and depth at which it occurs was given 20. In this way the further subdivisions was given due scores, so effectively the quantitative values was given a qualitative preference to bring out from the whole areas those blocks which can be considered as danger zones or safe zones. An index map was generated and a legend developed to show those regions of danger and arsenic free zones. The multi-criteria map was generated using the following table

    Arsenic Concentration Weightage 50
    Values Scores
    0.01 1
    0.05 2
    1.5 3
    2.0 4
    2.86 5

    Population Density Wightage 30
    Values Scores
    30 1
    40 2
    50 3
    60 4
    70 5

    Depth of water level Weightage 20
    Values Scores
    112.31 5
    261.29 4
    410.27 3
    559.25 2
    708.23 1

    An output was generated with an index of 5 being the safe zone and index 1 as the danger zone.
  4. The wells where Iron and Ph values were measured are also saved into layer. It is generally observed that wells with high Iron values are having low Arsenic values. Though this predictive conclusion does not bear any correlation in terms of regression formula, it will require more data sets to reach at any conclusion whatsoever.
  5. From the multi-criterion map that has been generated by using Multi-criterion modeling using three parameters, the different zones were obtained as raster classes. Using GIS technology, these layers were converted into vector layers and we obtain the area that is affected by each class. Hence we get the percentage of area that falls into danger zone of safe zone or intermediate zones.
Results and Discussion:
From the work that has been concluded for the particular district, the following results and discussions can be concluded.
  1. The geocoded satellite images of the area is perfectly overlaid on the base map, and it is observed that each natural feature exactly coincides with the image even at a scale of 1: 10000, this indicates that when the block boundaries are overlaid, we get the exact amount of actual earth surface within that block. Any observation on the land use and land cover within a block is very clearly observed, hence the changes that might occur in the coming few years in terms of surface water or urbanization can or natural features can clearly be measured for changes in actual earth co-ordinates over a period of time.
  2. The image has been classified using supervised classification technique with Maximum Likelihood classifier algorithm. The whole area has been classed into Water bodies, Forest areas, Urban areas, Wetland, Rural Areas, Arable Land and Fallow Land. The total area covered under surface water is 0.86% of the total land and covers around 129 sq kms. The Urban area constitutes around 6.3% whereas rural area is around 1.5% of the district, thus around 950 sq.kms is Urban area and 224sq kms of rural areas. The detail classification report was given earlier. Hence we see that this district has a sizable amount of urban and rural population.
  3. From the zonation map that has been created from the multi-criterion modeling has 6 classes namely Safe Zone, Below Affected level, Moderately affected, highly affected and Danger Zone. The area covered under “Danger Zone” is around 7 square kilometers and Highly affected zone is around 27 square kilometers. On overlaying the block map over the zones it has been found that the eastern region of Barasat I block falls under danger zone and western region of Deganga block, North Western region of Barrakpur II, middle region of Barasat I, southern region of Habra –II and North Eastern region of Amdanga falls under highly affected zone.
  4. From the classified satellite images it is being observed on overlaying the zonation map that the “danger Zone” falls mainly on the arable land and certain regions of urban land in the east Barasat - I block and portions of fallow land and wetlands.on … and the moderately affected zone falls on the arable land and certain regions on the urban and fallow land.
  5. The map obtained from Matrix over lay shows the various zones safe for drinking water. The result of Matrix Modeling shows that the area safe for drinking water . This area falls in the blocks Sandeshkhali-I, some region of Hingalganj, major area in the block Minakhan. It is also found that the safe zones fall mainly on the rural areas and fallow lands.
  6. Thus it can be concluded from the above that the danger prone zone is urban areas and arable land where shallow pumps are extensively used for extracting groundwater thereby raising the water table. The reason for such an increased effect of arsenic is now open to diverse research for finding out a plausible cause for such an effect in such areas.
Reference:
  • Astolfi, E., Maccagno, A., Fernandez, J.C.G., Vaccara, R. and Stimola, R., 1981. Relation between arsenic in drinking water and skin cancer. Biological Trace Element Research. 3, 133-143. Auden, J.B. 1949. Geological discussion of the Satpura hypotheses and Garo-Rajmahal gap. Proceeding, National Institute of Science India, 15, 315-340.
  • Borgono, J.M. and Greiber, R. 1971. Epidemiological study of arsenicism in the city of Antofagasta. Trace Substances in Environmental Health, 5, 13-24.
  • Cebrian, M.E., Albores, A., Aguilar, M. and Blakely, E. 1983. Chronic arsenic poisoning in the north of Mexico. Human Toxicology, 2, 121-133.
  • Chakraborti, D., Das, D., Chatterjee, A., Jin, Z. and Jiang, S.G. 1992. Direct determination of some heavy metals in urban air particulates by electro- thermal atomic absorption spectrometry using Zeeman back-ground correction after simple acid decomposition. Part iv:Applications to Calcutta air particulates. Environmental Technology, 13, 95-100.
  • Chakraborti, D., Burguera, M. and Burguera, J.L.1993. Analysis of standard reference materials after microwave- oven digestion in open vessels using graphite furnace atomic absorption spectrophotometry and Zeeman-effect background correction. Fresenius Journal of Analytical Chemistry, 347, 233-237.
  • Chatterjee, A., Das, D. and Chakraborti, D. 1993. A study of ground water contamination by arsenic in the residential area of Behala, Calcutta due to industrial pollution. Environmental Pollution, 80(1), 57-65.
  • Chatterjee, A., Das, D., Mandal, B.K., Roy Chowdhury, T., Samanta, G. and Chakraborti, D., 1995. Arsenic in groundwater in six districts of West Bengal, India, The biggest arsenic calamity in the world. Part-1. Arsenic species in drinking water and urine of the affected people. Analyst, 120, 643-650. Committee on Medical and Biologic Effects of Environmental Pollutants 1977. Medical and Biologic Effects of Environmental Pollutants Arsenic, pp. 8, 18. National Academy of Sciences, Washington, D.C.
  • Das, D., Chatterjee, A., Mandal, B.K., Samanta, G., Chanda, B. and Chakraborti, D. 1995. Arsenic in ground water in six districts of West Bengal, India, The biggest arsenic calamity in the world. Part-2. Arsenic concentration in drinking water, hair, nail, urine, skin-scale and liver tissue (biopsy) of the affected people. Analyst, 120, 917-924. PCI USER Manual on Geomatica V 8.2
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