scholarly journals Application of fuzzy logic in river water quality modelling for analysis of industrialization and climate change impact on Sabarmati river

2021 ◽  
Author(s):  
Anant Patel ◽  
Karishma Chitnis
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Human Life ◽  
Surface Water Quality ◽  
Water Quality Model ◽  
Quality Data ◽  
Quality Model ◽  
Water Quality Data ◽  
Sabarmati River

Abstract Rivers are critical to human life because they are strategically significant in the world, providing primary water supplies for various purposes. Rivers are the prime importance of any country as most of the cities are settled near the river. Due to developmental activities and increase in population, it will results into huge waste generation. Surface water quality is affected because of increasing urbanization and industrialization. The aim of this research is to examine the effect of climate change and industrialization on the water quality of the Sabarmati river using a mathematical model. For this study four important town along the lower Sabarmati River have been considered and water quality data was considered from 2005 to 2015. In this study different water quality parameters were considered to derive water quality model. Results shows the water quality in downstream after Ahmedabad city is worst compare to the other location where the Maximum WQI is 0.71 at Rasikapur and average WQI is 0.50 for the same location for last 15 year. It has been observed that effect of monsoon and also by comparing time scale water quality model role of regulations for industrialization also plays important role in quality of Sabarmati river.

scholarly journals Uncertainties in selected surface water quality data

2006 ◽  
Vol 3 (5) ◽  
pp. 2991-3021 ◽  
Author(s):  
M. Rode ◽  
U. Suhr
Keyword(s):  
Water Quality ◽  
Particulate Matter ◽  
Surface Water ◽  
Suspended Particulate Matter ◽  
Surface Water Quality ◽  
Quality Data ◽  
Sampling Location ◽  
Water Quality Data ◽  
Suspended Particulate

Abstract. Monitoring of surface waters is primarily done to detect the status and trends in water quality and to identify whether observed trends arise form natural or anthropogenic causes. Empirical quality of surface water quality data is rarely certain and knowledge of their uncertainties is essential to assess the reliability of water quality models and their predictions. The objective of this paper is to assess the uncertainties in selected surface water quality data, i.e. suspended sediment, nitrogen fraction, phosphorus fraction, heavy metals and biological compounds. The methodology used to structure the uncertainty is based on the empirical quality of data and the sources of uncertainty in data (van Loon et al., 2006). A literature review was carried out including additional experimental data of the Elbe river. All data of compounds associated with suspended particulate matter have considerable higher sampling uncertainties than soluble concentrations. This is due to high variability's within the cross section of a given river. This variability is positively correlated with total suspended particulate matter concentrations. Sampling location has also considerable effect on the representativeness of a water sample. These sampling uncertainties are highly site specific. The estimation of uncertainty in sampling can only be achieved by taking at least a proportion of samples in duplicates. Compared to sampling uncertainties measurement and analytical uncertainties are much lower. Instrument quality can be stated well suited for field and laboratory situations for all considered constituents. Analytical errors can contribute considerable to the overall uncertainty of surface water quality data. Temporal autocorrelation of surface water quality data is present but literature on general behaviour of water quality compounds is rare. For meso scale river catchments reasonable yearly dissolved load calculations can be achieved using biweekly sample frequencies. For suspended sediments none of the methods investigated produced very reliable load estimates when weekly concentrations data were used. Uncertainties associated with loads estimates based on infrequent samples will decrease with increasing size of rivers.

Modeling water quality in an oil sands compensation lake

2015 ◽  
Vol 42 (11) ◽  
pp. 901-909 ◽  
Author(s):  
Jianhua Jiang ◽  
Jerry Vandenberg ◽  
Ian Halket ◽  
Kasey Clipperton ◽  
Richard J. Kavanagh ◽  
...  
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Water Temperature ◽  
Oil Sands ◽  
Fish Habitat ◽  
Environmental Modeling ◽  
Water Quality Model ◽  
Quality Data ◽  
Quality Model ◽  
Water Quality Data

Surface mining in the oil sands region of Alberta, Canada, often requires that mining operators drain lakes or divert streams to access the underlying ore. “Compensation lakes” can be constructed to create new fish habitat to offset the loss of fish habitat due to mining activity and to satisfy conditions under a project’s Fisheries Act Authorization. The design of these lakes requires prediction of future water temperature and dissolved oxygen levels to determine the suitability of the new habitat for fish. These predictions are made using a calibrated hydrodynamic and water quality model. Until recently, there were not any built compensation lakes in the region with enough measured water quality data that could be used to calibrate such a model. This paper uses measured data from Horizon Lake, a recently built compensation lake, to calibrate Generalized Environmental Modeling System of Surfacewaters (GEMSS), a three-dimensional hydrodynamic and water quality model, used to model the lake. Horizon Lake was built in 2008 by Canadian Natural Resources Ltd. and water quality in the lake has been monitored for the last seven years. The results of the model calibration to observed water temperature and dissolved oxygen provide rates and coefficients, notably sediment oxygen demand, that can be used to improve model applications to other planned compensation lakes.

scholarly journals Assessment of Water Quality of Brahmani River using Correlation and Regression Analysis

2020 ◽  
Author(s):  
Saroj Nayak
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Correlation Coefficient ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Chemical Parameters ◽  
Water Quality Data

This work evaluates the surface water quality in terms of physico-chemical parameters of the Brahmani River, Odisha using statistical analysis involving the calculation of correlation coefficient and regression equation. Besides this, the work also highlights and draws attention towards the “Water Quality Index” in a simplified format which may be used at large and could represent the reliable picture of water quality. Surface water quality data is taken from OSPCB of various location i.e. Panposh D/S, Rourkela D/S, Rengali, Talcher U/S, Kamalanga D/S, Bhuban, Pattamundai and was assessed for summer, monsoon, winter for the years 2011, 2012, 2013, 2014 and 2015. Average of values, minimum of values and maximum of values of water quality parameters were obtained seasonally over the above mentioned years. Besides this, the standard deviation for the water quality parameters was also obtained for water quality parameters namely pH, Temperature, DO, TDS, Alkalinity, EC, Na+, Ca2+, Mg2+, K+, F-, Cl-, NO3-, SO42- and PO42-. Seasonal changes in various physical and chemical parameters were analysed.The values obtained were compared with the guideline values for drinking water by Bureau of Indian Standard (BIS). A systematic correlation and regression study is carried out for three seasons, showed linear relationship among different water quality parameters. This provides an easy and rapid method of monitoring water quality. Highly significant (0.8< r <1.0), moderately significant (0.6< r <0.8) and significant (0.5< r <0.6) correlations between the parameters have been worked out. High correlation coefficient has been observed between TDS,EC-Na+, Ca2+, Cl-, SO42- ; Na+- Cl-. From the collected quantities, certain parameters were selected to derive WQI for the variations in water quality of each designated sampling site. WQI of Brahmani River ranged from 36.7 to 44.1 which falls in the range of good quality of water.Panposh D/S and Rourkela D/S showed poor water quality in summer and winter season. It is shown that WQI may be a useful tool for assessing water quality and predicting trend of variation in water quality at differentlocations in the Brahmani River.

scholarly journals Evolution of Drought–Flood Abrupt Alternation and Its Impacts on Surface Water Quality from 2020 to 2050 in the Luanhe River Basin

2019 ◽  
Vol 16 (5) ◽  
pp. 691 ◽  
Author(s):  
Wuxia Bi ◽  
Baisha Weng ◽  
Zhe Yuan ◽  
Yuheng Yang ◽  
Ting Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Surface Water ◽  
River Basin ◽  
Surface Water Quality ◽  
Quality Data ◽  
Simultaneous Occurrence ◽  
Water Quality Data ◽  
Luanhe River Basin ◽  
Extreme Climate

It has become a hot issue to study extreme climate change and its impacts on water quality. In this context, this study explored the evolution characteristics of drought–flood abrupt alternation (DFAA) and its impacts on total nitrogen (TN) and total phosphorous (TP) pollution, from 2020 to 2050, in the Luanhe river basin (LRB), based on the predicted meteorological data of the representative concentration pathways (RCPs) climate scenarios and simulated surface water quality data of the Soil and Water Assessment Tool (SWAT) model. The results show that DFAA occurred more frequently in summer, with an increasing trend from northwest to southeast of the LRB, basically concentrated in the downstream plain area, and the irrigation area. Meanwhile, most of the DFAA events were in light level. The incidence of TN pollution was much larger than the incidence of TP pollution and simultaneous occurrence of TN and TP pollution. The TN pollution was more serious than TP pollution in the basin. When DFAA occurred, TN pollution almost occurred simultaneously. Also, when TP pollution occurred, the TN pollution occurred simultaneously. These results could provide some references for the effects and adaptation-strategies study of extreme climate change and its influence on surface water quality.

scholarly journals Analysis of agricultural pollution by flood flow impact on water quality in a reservoir using a three-dimensional water quality model

2012 ◽  
Vol 15 (4) ◽  
pp. 1061-1072 ◽  
Author(s):  
Chen Zhang ◽  
Xueping Gao ◽  
Liyi Wang ◽  
Yuanyuan Chen
Keyword(s):  
Water Quality ◽  
Driving Forces ◽  
Surface Wind ◽  
Three Dimensional ◽  
Water Quality Model ◽  
Quality Data ◽  
Agricultural Pollution ◽  
Quality Model ◽  
Water Quality Data ◽  
Yuqiao Reservoir

This study presents the Yuqiao Reservoir Water Quality Model (YRWQM), a three-dimensional hydrodynamic and water quality model of the Yuqiao reservoir, China. The YRWQM was developed under the environmental fluid dynamics code (EFDC) model and was calibrated and verified to hydrodynamic and water quality data, using two sets of observed data from January 1 to December 31, 2006 and from May 1 to October 31, 2007, respectively. The primary hydrodynamic and transport driving forces are inflows/outflows and surface wind stresses. Considering effects of water transfer and wind on the advection-dispersion processes, the model results showed better agreements with observed data in the reservoir. The YRWQM predicted the variations of water quality resulting from agricultural pollution which flowed into the reservoir with floods lasting for 12 days in 2009. The results indicated that the concentrations of chemical oxygen demand and total nitrogen were increased 225 and 314%, respectively. Considering the interactions between chlorophyll-a and nitrogen in the model, the results indicated the reservoir was not a nitrogen-limited environment. We suggest the management should focus on agricultural pollution strategies for the reservoir during the flood period. The YRWQM could be a useful tool for water sources management in the reservoir.

Spatiotemporal variation of surface water quality for decades: a case study of Huai River System, China

2013 ◽  
Vol 68 (6) ◽  
pp. 1233-1241 ◽  
Author(s):  
Wei Ji ◽  
Dafang Zhuang ◽  
Hongyan Ren ◽  
Dong Jiang ◽  
Yaohuan Huang ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Water Quality ◽  
River System ◽  
Spatiotemporal Variation ◽  
Quality Data ◽  
Main Stream ◽  
Water Quality Data ◽  
Huai River

Characterization of spatiotemporal variation of water quality is a basic environmental issue with implications for public health in China. Trends in the temporal and spatial distribution of water quality in the Huai River System (HRS) were analyzed using yearly surface water quality data collected from 1982 to 2009. Results showed that the water quality of the main stream deteriorated in the 1990s and early 2000s but has been ameliorated since 2005. The sections that were classified as severely polluted from the monitoring data were located largely in the middle reach. The water quality of HRS fluctuated during the period 1997–2009; it has improved and stabilized since 2005. In terms of spatialized frequency of serious pollution, heavily polluted regions were mostly concentrated in the area along several tributaries of the Ying, Guo and New Sui Rivers as well as the area north of Nansi Lake. These regions decreased from 1997 to 2009, especially after 2005. Our analysis indicated that water pollution in HRS had a close relation with population and primary industry during the period 1997–2009, and implied that spatiotemporal variation of surface water quality could provide a scientific foundation for human health risk assessment of the Huai River Basin.

scholarly journals Water quality modeling for determination of suitability of water for shrimp farming in tidal rivers

2018 ◽  
Vol 54 (1) ◽  
pp. 34-46
Author(s):  
Navid Dolatabadi Farahani ◽  
Hamid Taheri Shahraiyni ◽  
Reza Sheikhi
Keyword(s):  
Water Quality ◽  
Water Channels ◽  
Water Quality Modeling ◽  
Shrimp Farming ◽  
Quality Data ◽  
Quality Model ◽  
Water Quality Data ◽  
Shrimp Culture ◽  
Standard Values

Abstract In this study, the water quality of the Bahmanshir River and its water channels where Choebdeh Shrimp Farms (the largest shrimp culture complex in Iran) are located were simulated using MIKE11 software. First, an integrated hydraulic and salinity model of the river and its water channels was developed. Then, Manning and dispersion coefficients of the river were calibrated and validated. The most important parameters in the water quality model were determined by sensitivity analysis and these parameters were calibrated using in situ measured water quality data. The errors of salinity, temperature, nitrate, ammonia and dissolved oxygen (DO) models in the verification step were 7.9, 1.2, 0.34, 0.79 and 12%, respectively. Then, two scenarios were applied to the river and the effects of these scenarios on the water quality of the river and its channels were evaluated. The results demonstrated that the site selection of the shrimp culture complex had been performed well because different scenarios could not affect the water quality in the channels. Finally, the water quality in the channels was compared with the standard values of shrimp survival parameters. All of the parameters in the channels were in the range of standard values except DO, which was slightly under the standard value.

scholarly journals Modeling Biological Oxygen Demand Load Capacity in a Data-Scarce Basin with Important Anthropogenic Interventions

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2379
Author(s):  
Alejandra Zurita ◽  
Mauricio Aguayo ◽  
Pedro Arriagada ◽  
Ricardo Figueroa ◽  
María Elisa Díaz ◽  
...  
Keyword(s):  
Water Quality ◽  
Carrying Capacity ◽  
Stream Water ◽  
Oxygen Demand ◽  
Biological Oxygen Demand ◽  
Water Quality Model ◽  
Quality Data ◽  
Quality Model ◽  
Anthropogenic Pressures ◽  
Water Quality Data

Most water bodies are currently used as receptors for pollutants coming mainly from the industrial and domestic sectors. The Biobío river is subjected to multiple anthropogenic pressures such as industrial water supply, drinking water, hydroelectric power generation, agriculture, and the final receptor body of a large amount of industrial and urban waste, pressures that will intensify due to the decrease in water flow as a result of climate change. In this context, organic contamination has been found mainly from sewage discharges and oxidizable waste discharges generated by industrial processes. In this sense, the objective of this research is to determine the Biological Oxygen Demand Loading Capacity (LC) in a basin with a low density of water quality data subjected to strong anthropogenic pressures. To estimate the carrying capacity in a section of the Biobío River, the water quality model River and Stream Water Quality Model- Qual2K version 2.11b8, developed by Chapra, was used. This model solves the Streeter–Phelps equation, proposing an analytical expression to relate the dissolved oxygen (DO) and biochemical oxygen demand (BOD5) variables. These variables were modeled for different critical scenarios of minimum flows in return periods of 5, 50, and 100 years, determining that the studied section of the Biobío river would have a high carrying capacity to not be affected by its organic matter pollution.

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