Today, most of the rivers all over the globe have been
transferred into open sewers, due to industrialization, agricultural
activities, and population explosion. Water pollution problems are more serious
in the third world countries. The problem of not adopting better sanitation
system, non implementation of statutory rules by the authorities concerned are
the major causes of river and reservoir pollution here, in India. Most of the
rivers in India are under the serious threat of pollution due to industrial and
sewage discharges. These rivers are becoming unsuitable not only for human
consumption but also for agricultural purposes. Karanja River is one among the
polluted rivers in North Karnataka. Till date, no scientific data are available
on the quality of Karanja River, even though it provides water for domestic,
industrial and agricultural purposes. Hence, it is proposed to undertake a
systematic study of Karanja reservoir and river.
To understand the present status of Karanja reservoir and
river in terms of its pollutional sources and degree of pollution, nine
sampling points were selected (five in the reservoir and four along the river
stretch). Overall twenty-two physico-chemical characteristics were analysed for
two years from December -2007 to November-2009. The samples were collected at
an interval of one month.
The water quality index (WQI) has been calculated for
intended purpose of drinking using basic parametric values, the WQI thus
indicates that the water quality of the reservoir in the rainy season is much
better compared with the summer and winter seasons. The water quality index
value is greater at sampling point D-2 and D-4. This indicates that water
quality is poor in these stations. The main reason for poor water quality at
sampling points D-2 and D-4 is the discharge of industrial wastewater.
Similarly, the water quality index of the river water has also been carried
out. In this study, the fuzzy logic formulation has also been used to assess
the river water quality by developing a water quality index based on fuzzy
reasoning. On the other hand, comparison has been made between FWQ and the
conventional WQI index; there exists an agreement between the methods during
summer and winter seasons.
The monitoring data was used to study the spatial
distribution of water quality of Karanja reservoir and river. In this study, in
order to analyze the data determining water quality, a GIS software package of
GIS 9.0 and ARCGIS Geostatistical analyst extension were used. An interpolation technique called ordinary
Kriging was used to produce the spatial distribution of water quality
parameters over the reservoir and the river.
In this study an attempt has been made to apply the EPA
supported water quality model QUAL2Kw which was used to simulate the Karanja
river water quality. The calibrated pre-monsoon and validated post monsoon
results produce the minimum RMSE value of important parameters such as
dissolved oxygen and biochemical oxygen demand. Hence, the pre-monsoon
calibrated model was used for further study. From the result it is clear that,
the Karanja river water is not yet highly affected. The calibrated and
validated results are acceptable especially for developing countries like India
where financial resources for frequent monitoring are limited. The calibrated
model was applied to develop several management scenarios by changing the model
input parameters during pre-monsoon period to maintain the targeted water
quality criteria. Model sensitivity analysis has also been carried out in order
to identify the parameters of the river water quality that have the greatest
effect on the model output. Similarly, another model (MIXPIPOX) was used to
compare both observed and predicted dissolved oxygen.
Finally, an attempt has been made to compare the observed
data with QUAL2Kw and MIXPIPOX models. It was observed that both models
provided satisfactory forecasting results for dissolved oxygen. But the QUAL2Kw
modeling approach was recommended for forecasting of water quality parameters
of the river, because in the case of QUAL2Kw model the conversion of algal
death to BOD, fixed plant DO and the dentrification were considered, these
effects were not considered in the case of MIXPIPOX model. Hence, QUAL2Kw model
was recommended for prediction of river water quality.
Author(s) Details:
Basappa B Kori,
Department of Civil Engineering, Guru Nanak Dev Engineering College,
Bidar-585403, Karnataka, India.
Rajani
Saranadagoudar,
Department of Civil Engineering, Guru Nanak Dev Engineering College,
Bidar-585403, Karnataka, India.
Please see the link here: https://stm.bookpi.org/AOWQMIACS/article/view/13602\
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