An Overview of Water Quality Modeling in India: A Case Study - Kori , Basappa B; Saranadagoudar , Rajani (An Overview of Water Quality Modeling in India: A Case Study, 2024)
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.