Simulation of point and non-point source pollution in mahanadi river system lying in odisha, India

Guru, Nibedita (2012) Simulation of point and non-point source pollution in mahanadi river system lying in odisha, India. MTech thesis.



Assessment of point and non-point source pollution in a river system plays an important role for proper water resources management/utilization/protection, reducing environmental/health degradation, suitable waste load allocation and decision-making for pollution monitoring networks. It has been observed that most of the water resources have been utilized for the disposal of municipal and industrial wastes since early days in addition to influx of non-point source pollution. To address the non-linearity, subjectivity, transfer and transformation rule of the pollutants and complexity of the cause-effect relationships between water quality variables and water quality status, development and use of water quality model is of utmost importance. Since the concentration of the quality constituents is reliant on the quantity of flow, entry of point and non-point source pollutants, reaction kinetics, etc., it is essential to supervise and use suitable mathematical models for predicting water quality variables. Owing to the random discharge of point and non-point pollution from various sources has not only rendered such water bodies eutrophic but also their advantageous uses such as water supply, irrigation, recharge of ground water, recreation and habitat for flora and fauna have been adversely affected.
Oxygen-demanding substances are major contaminants in domestic and municipal wastewater. The main indicators of river pollution which deals with the oxygen domestic conditions of the river are Biochemical oxygen demand (BOD) and dissolved oxygen (DO).To manage the quality of natural water bodies that are subjected to pollutant inputs; one must be able to predict the degradation in quality that results from such inputs. The non-point source pollution is another imperative variable responsible for increasing pollutant load in a stream/river. Recognizing the magnitude of assessing non-point source pollution in river system, copious studies intended at understanding the processes controlling nutrient concentration, fluxes in the river systems and the quantification of the nutrient loads of rivers have been proficient in past.
In the present study, attempts have been made to use different water quality models for Mahanadi river system lying in Odisha, establish model parameters values and test the
applicability of the model for different Spatio-temporal conditions. Different water quality data namely, discharge, BOD, DO, water temperature, pH, turbidity, electrical conductivity, nitrate a
Most commonly used BOD-DO model have been used to simulate the point source pollution at different reaches of Mahanadi river system lying in Odisha and model parameters deoxygenation coefficient (k1) and reaeration rate coefficient (k2) have been established. Various empirical equations used for estimating and reaeration rate coefficient were used and a modified equation suitable for estimating reaeration rate coefficient has been derived.
Further, the Multi-layer Perceptron (MLP) neural network techniques was used to estimate for the analysis of point source pollution in terms of BOD and DO concentration and the neural network model is developed using the data collected from the upstream and downstream stations on Mahanadi river system lying in Odisha. The accuracy performance of training, validation and prediction of seasonal water quality parameters has been tested.
Another important variable responsible for increasing pollutant load in the river system is non-point source pollution. For recognizing the importance of influx of nutrients (nitrate and ortho-phosphate) from non point sources and their simulation, an analytical model has been used and non-point source pollution entering the river has been estimated.
To test the validity of generalized model and ANN model, different statistical errors, the root mean square error (RMSE), mean multiplicative errors (MME), correlation coefficient (R) were used.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Point Source, Non-Point Source, Bod, Do, Ann,Remote Sensing And Gis
Subjects:Engineering and Technology > Civil Engineering > Water Resources Engineering
Divisions: Engineering and Technology > Department of Civil Engineering
ID Code:4026
Deposited On:04 Jun 2012 15:54
Last Modified:13 Jun 2012 16:44
Supervisor(s):Jha, R

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