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Spatial modelling approach to water pollution monitoring in the sugar belt of Maharashtra along the Krishna river
Fertiliser and Pesticide
Consumption
To get higher yields in the cultivated land, farmers apply
more and more of chemical fertilizers. Table 2 shows the fertilizer consumption
in the districts of Satara and Sangli since 1980. The total chemical fertilizer
consumption in Satara and Sangli during 1995-96 was 50390 and 83153 tonnes. With
intensification of agriculture, particularly since introduction of higher
yielding but low pest-resistant varieties of crops, the use of pesticides and
biocides has been increasing steadily. The total pesticide consumption in
Maharashtra is 711 MT/Year, of which 7% is consumed in Satara and 6.4% in
Sangli. In these two basin districts organo-chlorine share is the highest. The
application rate per hectare is about 0.09.
Water Consumption and
Effluent Discharge
The state of Maharashtra is ranked first in terms of
industrial investment in the country. Major industrial sectors are in power,
fertiliser, sugar and cement industries. In satara and Sangli fifteen medium to
large size sugar industries are located. There are many liquor factories located
along the stretch-I. The quantity of water that is consumed for domestic,
industrial and irrigation uses are respectively 66, 18 and 3366 MCM.
Correspondingly, the amount of effluent that is being discharged from urban,
industrial and irrigation are 29, 14 and 673 MCM. From the sugar factories and
its surrounding domestic locations about 13400 and 1525 cubic meter of effluents
are being discharged everyday.
A Framework for Monitoring Water
Quality in GIS
River water quality monitoring is the process of regular
study of parameters related to river water. It helps determining the quality
trend and hence the threshold values for the restoration of water quality to its
normal. Different factors those affect the water quality are physical, chemical
and socio-economic parameters of the river basin. A detailed monitoring
framework is shown in the figure 1. The present case study is followed up as per
this framework. Using GIS, the database on pollution load, the relationship
between pollution load with population, fertiliser consumption and factory
location, and the river zonation have been assessed and graphically presented.
The techniques of river zonation has been reviewed and modified. The prime
objectives of using GIS over traditional methods are :
- Effective storage and analysis system for spatial and temporal databases
such as maps on geology, geomorphology, soils, landuses and attributes on
meteorology, population, water quality etc.,
- Spatial analysis on depicting the source-pollutant relationship,
- Graphical presentations, visual impacts and spatial distribution of
graphical outputs on water quality changes, pollution load and relationship with
sources and
- Management of river basins by generating buffer zones on the basis of water
quality criteria.
Water Quality and Pollution Load at
Stretch-I
The stretch-I is about 180 kms. This stretch, covering a total
area of 13065.22 km2, is subdivided into three sub-watersheds SW1 (1705.17), SW2
(3545.4) and SW3 (7814.65) km2. A WQM station accompanies each one of these
sub-watersheds. The WQMs 1194, 36 and 37 respectively fall within the
sub-watersheds SW1, SW2 and SW3. The coverage of Krishna channel within these
subwatersheds are respectively 40.92, 300.84 and 531.10 Km2. About 19 water
quality parameters, the physical parameters temperature, run-off and turbidity
and the chemical parameters pH, hardness, conductivity, alkalinity, DO, BOD,
COD, Fcoli, Total Coliform, Nitrogen, Chlorine, Sulphur, Sodium, Calcium,
Magnesium and TKN, were studied from their monsoon and non-monsoon readings.
While computing the pollution load (Table 3) it was assumed that the river flows
in the stretch 365 days a year (a perennial river). The exposure of total
population to pollution load in each subwatershed as shown in this table is to
correlate their growth trend.
Generally along the stretch-I, turbidity
and the chemical parameters BOD, COD, Na, Mg, Ca, Cl, TKN and Sulphate show
slightly increasing trend over the years (1984-1997) in the downstream direction
of river flow. Parameters like pH, N and DO don't show much of variation from
the mean. However, the water quality readings of Fcoli and Tcoli are slightly
decreasing along the downstream direction. In the individual WQM station the
trend in BOD and COD loads, the indicators of organic pollution, show positive
and the COD values are quite higher than BOD. The minimum and maximum BOD values
during 1997 were 227 and 13241 tonnes year-1 whereas the COD values were 655 and
33453 tonnes year-1. The BOD and COD loads of the stretch, are showing sharp
positive trend from 1990 onwards (figure 2 a,b,c,d). These indicated that the
inflow of pollutants to river has been increasing after 1990. Amongst all the
chemical parameters, the load of magnesium was the maximum. The highest Mg-load
obtained was 224416 tonnes year-1 in 1988 for SW3. If the load of each pollutant
is listed in terms of their total contribution in an year, the sequence in
descending order for these pollutants will be Mg, Ca, Na, Sulphate, Cl, N, COD
and BOD. First five major pollutants in the sequence are generally from the
agricultural sources and the last two are both from both domestic and industrial
sources.
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