Interdisciplinary Centre for Water Research (ICWaR)
https://etd.iisc.ac.in/handle/2005/30
2024-03-28T09:47:30Z
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Anthropogenic Influence on River Water Quality
https://etd.iisc.ac.in/handle/2005/6024
Anthropogenic Influence on River Water Quality
Santy, Sneha
Anthropogenic factors such as climate change, land use land cover change and industrial and population growth can influence river water quality. Climate change affects water quality due to changes in stream temperature and streamflow due to increased air temperature and varied precipitation patterns associated with warming. Land use land cover influences water quality mainly from the agricultural runoff, which carries the pollutants from fertilizers and pesticides and reaches the nearby water body. Population growth can increase the water demand and sewage generated hence aggravating pollution. Industrial growth has the potential to affect water quality through increased effluent loads. The work presented in this thesis contributes to quantifying such anthropogenic influences on river water quality using a coupled hydrological-water quality simulation model. The study area considered is a 238km stretch of Ganga river in India from Ankinghat to Shahzadpur, passing through Kanpur, which is identified as the most polluted stretch of Ganga river by the Central Pollution Control Board of India.
Sensitivity studies with forcings such as climate change and land use are extremely important for any management decision on water quality. In the initial part of the thesis, the sensitivity of nine water quality parameters to climate change and land use change is assessed using idealized scenarios and a standalone water quality simulation model, QUAL2K. The key input model parameters contributing to model uncertainty and key locations are identified using first order reliability analysis. The water quality parameters considered are DO, BOD, ammonia, nitrate, total nitrogen, organic-, inorganic-, and total phosphorous and faecal coliform. The non-point source pollution is quantified using the export coefficient method, in which pollutants from all land use classes are considered. Eight climate change and six land use land cover scenarios are framed based on historical data analysis to assess their sensitivity to water quality parameters. DO is the most sensitive indicator to the climate change scenarios considered, while nutrients and faecal coliform are more sensitive to the land use scenarios. In general, the water quality parameters are found to improve with a rise in air temperature and deteriorate with a reduction in streamflow. An increase in the agricultural land area leads to higher nutrient concentration, while an increase in the built-up area causes an increase in faecal coliform concentration. An increase in forest land shows better water quality in terms of all water quality parameters. The key input variables contributing to the uncertainty of water quality simulation are the head water discharge, point and non-point pollution loadings, water temperature, and corresponding reaction rates. The key locations identified using first order reliability analysis are Kanpur downstream and Jajmau downstream.
Risk assessment studies on water quality for future scenarios are limited in the literature. In the next part of the thesis, the effect of climate change on water quality, the risk of eutrophication and fish kill for the mid-and end of the 21st century for this river stretch are assessed. The risk of eutrophication and fish kill are quantified using simulated concentrations of nutrients and DO, respectively. Downscaled climate change projections for two climate change scenarios (RCP4.5 and RCP8.5) are used to drive a hydrological model coupled with a water quality simulation model. The simulations indicate a potential deterioration of water quality in this stretch in the mid-21st century, with a potential increase in pollutant concentration by more than 50% due to climate change alone. The risk of reduced dissolved oxygen and increased organic and nutrient pollution, and the risk of eutrophication and fish kills increase with warming due to the rise in the frequency of low-flow events and a reduction in streamflow during low-flow events. However, the risk of nitrate and microbial pollution is reduced due to increased denitrification and pathogen decay rates with warming. The risk of eutrophication and fish kill is found to increase by 43.5% and 15% due to climate change alone by the mid-21st century. The risk of eutrophication is found to increase by 6% due to land use change which can be attributed to an increase in nutrient loading with land use change.
In the final part of the thesis, the individual effects of climate change, land use land cover change, population and industrial growth on river water quality are assessed with a coupled hydrological-water quality simulation model and the predominant factor contributing to pollution is identified. Also, the future water quality is projected for mid 21st century considering climate change, land use projections, population and industrial growth, and the proposed treatment for the stretch considered using socio-environmental scenarios. The effectiveness of the proposed treatment to offset the reduction in water quality from anthropogenic forcings is also assessed. The climate change effect is found to have a larger effect on water quality than other drivers, with a percentage contribution of above 70% because of the considerable sensitivity of water quality parameters to the amount of streamflow. Climate change projections combined with socio-environmental scenarios imply that the large increase in pollution due to climate change, land use land cover, industry, and population growth cannot be controlled by the current treatment proposals for 2050 by the authorities. However, providing adequate STPs to meet the population of 2050, and allowing only domestic sewage to reach STPs can help in achieving the objective of the Ganga Action Plan in the mid-21st century.
The thesis comprises of five chapters. An introduction to the problem addressed, and the objectives of the work presented in the thesis are provided in Chapter 1. Details of the case study and analysis of the sensitivity of water quality parameters to climate change and land use with idealized future scenarios are discussed in Chapter 2. In Chapter 3, the risk assessment of low water quality, eutrophication and fish kill under changing climate and land use land cover is presented. Chapter 4 presents the analysis of the individual effects of all external forcings, including climate change, land use change, population and industrial growth. Conclusions drawn from the study are presented in Chapter 5.
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An Investigation of the Characteristics of Monsoon Low Pressure Systems in the Present Climate and their Sensitivity to Topography and Climate Change
https://etd.iisc.ac.in/handle/2005/5965
An Investigation of the Characteristics of Monsoon Low Pressure Systems in the Present Climate and their Sensitivity to Topography and Climate Change
Thomas, Tresa Mary
Monsoon Low-Pressure Systems (LPS) are synoptic-scale tropical disturbances that periodically form over the Indian subcontinent during the summer monsoon season (June-September). Apart from being a lifeline to agriculture, the LPS-triggered precipitation could cause catastrophic floods. This thesis investigates the large-scale factors that influence LPS characteristics under the current and future climate change scenarios. In the early part of the thesis, a new approach is developed to track the formation and propagation of LPS over the Indian subcontinent. A detailed statistical and visual comparison is made between LPS tracks generated using our approach applied to ERA-Interim reanalysis data and tracks obtained in previous studies. Furthermore, extreme rainfall at locations in the vicinity of LPS is analyzed which could be valuable for flood risk assessment during the monsoon season in central India.
In the latter part of the thesis, a fully coupled version of the Community Earth System Model (CESM 1.2.2) is run at 0.9°×1.25° spatial resolution, and 6-hourly output is generated for track analysis. The model’s ability to simulate the characteristics of LPS is first assessed by performing a present-day control simulation. Simulations to study the sensitivity of LPS statistics to topographical features in the south Asian region (presence or absence of southeast Asian mountains and the height of Tibetan and Himalayan Orography (THO)) and the change in LPS characteristics under climate change are also performed. Simulations without the southeast Asian mountains enable determining the influence of these mountains on the downstream amplified systems (remnants of Pacific tropical cyclones) over the Bay of Bengal. The sensitivity analysis on the influence of the height of THO shows an interesting result: while a decrease in monsoon precipitation with a reduction in the height of THO is simulated, the number of LPS increases. A detailed analysis of the dynamic factors leading to this counter-intuitive result is performed. Finally, the change in LPS characteristics and the associated large-scale SST and circulation anomalies in the Indian Ocean and south Asian region are assessed for the RCP8.5 emissions scenario. It is found that the monsoon circulation is weakened, summer monsoon precipitation over India is enhanced, and the number of LPS remains nearly unchanged in a warmer world.
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Optimization of Wastewater Treatment Process in a Bioreactor Through Hydrodynamic-biokinetic Modeling and Experimental Studies
https://etd.iisc.ac.in/handle/2005/6059
Optimization of Wastewater Treatment Process in a Bioreactor Through Hydrodynamic-biokinetic Modeling and Experimental Studies
Reshma Mohan, T
Membrane bioreactor has emerged as one of the leading technologies for treating municipal and industrial wastewater due to its efficiency in producing high-quality effluents. One of the significant challenges in bioreactors is the high energy and operating costs. The diffused aeration process of a bioreactor is the most energy-intensive operation amounting to 45-75% of the plant energy costs. This study attempts to optimize the wastewater treatment (WWT) process in a bioreactor through modeling and experimental studies. The overall aim is to develop efficient models which can be used to reduce the treatment costs of the WWT process while increasing the treatment efficiency.
As a first objective, a multiphase mixture computational fluid dynamics (CFD) model was developed using k-𝜺 turbulence closure equations and a discrete population balance model (PBM) add-on with specific bubble classes to predict the oxygen mass transfer in synthetic water. The validated model was extended for sensitivity analysis for a diffused aeration system in a bench-scale aeration tank. Results show that the volumetric oxygen mass transfer coefficient increased by 15 %, with a decrease in air bubble size by 10 %. In a diffuse aeration system, the air bubbles had a wider distribution, with a larger diameter near the bottom of the bioreactor, and narrow distribution, with a smaller bubble size at the top of the bioreactor.
As a second objective, an integrated model was developed by combining the multiphase CFD model, the PBM sub-model, an activated sludge submodel, and a combined extracellular polymeric substance (EPS) – soluble microbial product (SMP) (CES) submodel to investigate the oxygen uptake rate, the aeration efficiency, and treatment efficiency in bioreactors. Three different scale bioreactors, namely, i) case 1- laboratory, ii) case 2 – pilot, and iii) case 3- full-scale system, were studied. The model predictions on water quality were validated well with the experimental results. The validated model was used for sensitivity analysis to identify optimum conditions. The maximum percentage reduction in chemical oxygen demand and total nitrogen were 17 % and 18 %, respectively, for case 3. Also, a reduction of 32 % in the cost of aeration was observed when the bubble size was reduced to 5 mm (from the current value of 7 mm).
The third objective focused on developing a multiphase CFD – porous- CES model to investigate the effect of hydrodynamics on biofouling and the effect of the EPS and SMP on the cake layer formation. The developed model was validated with experimental observations from the laboratory-scale ultrafiltration hollow fiber membrane setup. Observations showed that as the filtration time increased, the transmembrane pressure (TMP) increased, and the permeate flux decreased. Furthermore, in experimental set 2 (synthetic wastewater with sludge seeding), the effect of cake deposition on TMP and permeate flux was 17% and 1.5% higher, respectively, compared to experimental set 1 (synthetic wastewater with yeast sludge). The validated model was then used to investigate the sensitivity of the CES submodel by comparing it with the sectional resistance submodel. It was observed that the sectional resistance model underpredicted the mass of cake deposited by 13 % and overpredicted the limiting flux by 4 %. The results suggest the importance of accounting for the influence of EPS and SMP on the cake layer formation and biofouling.
The fourth objective of this thesis reports a BioWin©- ASM for optimizing the biological nutrient removal (BNR) in a 55 million liters per day sewage treatment plant (STP). The proposed modification was to incorporate an intermediate virtual anoxic zone to achieve simultaneous nitrification-denitrification and total dissolved phosphorus (TDP as PO4) removal. The hydraulic residence time (HRT), dissolved oxygen (DO), and mixed liquor suspended solids (MLSS) of the bioreactor were varied to identify the optimum operating conditions. The optimum DO and MLSS levels were identified as 4 mg/L and 4000 mg/L, respectively, and the optimum HRT was found to be 2 h. in the aeration zone, 1 h. in anoxic, and 3 h. in the reaeration zone. Implementing these modifications in the STP, with minimal operational interventions and no capital costs, improved its performance as predicted by the model. The total nitrogen and TDP (as PO4) reduced from 20 mg/L to 8 mg/L and 3.5 mg/L to 0.9 mg/L, respectively, and met the revised discharge standards. This intervention gave a cost saving of approximately 5.6 million USD.
This work has demonstrated that the numerical models can be successfully used to optimize the treatment efficiency while reducing the capital (membrane replacement) costs and operating (aeration) costs of a bioreactor. The time and efforts required for identifying the optimum conditions through numerical modeling are significantly less than physically characterizing the bioreactor (and varying the conditions to optimize them).