Spatial modelling approach to water pollution monitoring in the sugar belt of Maharashtra along the Krishna river

This paper on the GIS Development site highlights the findings of a study taken up for the monitoring, identification and suggesting preliminary measures of water pollution control in the Satara-Sangli stretch (stretch-I) of the Krishna basin in Maharashtra with the help of Geographic Information System (GIS). The stretch-I, also known as the country's sugar-belt, has been identified by CPCB and MPCB (Maharashtra Pollution Control Board) for the restoration of water quality under the National River Action Plan (NRAP).

This is in the context of the initiative taken up by the Central Pollution Control Board (CPCB), which in 1976, initiated a series of integrated river basin studies all over the country. CPCB in collaboration with the State Pollution Control Boards (SPCB) established the Water Quality Monitoring (WQM) network in the country. The CPCB has identified river stretches all over the country, which have been polluted to the maximum extent. The Krishna river, which is one such polluted rivers of the country, flows in the states of Maharashtra, Karnataka and Andhra Pradesh. 

GIS was utilised in the storage and retrieval of attribute data such as water quality parameters (pollution loads), population density and fertiliser consumption over the spatial database (map) of Satara-Sangli stretch in the Krishna basin. This database was useful in motoring the trend of pollution load and population growth in the entire watershed between 1984 to 1997. With the aid of map comparison utility in GIS, pollution map could be compared with the population, fertiliser and industry location maps.

The study found that, the Satara-Sangli stretch of the Krishna river is polluted grossly by the human-induced activities in the subwatersheds. The factors for acute pollution of water are:

• The intensive use of fertilisers and pesticides in the agricultural land, growth of medium to big size sugar and distillery factories and very high growth of population leading to high domestic load from urban setup.
• Turbidity values increased and the same results were witnessed after 1990 for chemical parameters such as BOD, COD, Na, Mg, Ca, Cl, TKN and sulphate.
• Of all sources, the share of agriculture to water consumption and water pollution was the highest. Agricultural sources contributed to 91% of total waste discharge while the same for domestic and industrial sources were 4.5% each.

The study suggests that some standard economically feasible technologies could be adopted to mitigate and reciprocate the process of water quality degradation, and restore the quality back to its normal. The river zonation suggested in this paper on the basis of subwatershed approach is fairly better in terms of a real coverage and pollution control.