St. John's Harbour water quality model

1984 ◽  
Vol 11 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Raymond J. Dewey ◽  
Merv D. Palmer

A dynamic two-dimensional numerical water quality model was developed for St. John's Harbour, Newfoundland, to assist in providing direction for a water quality enhancement program. The model input parameters were adjusted until the model outputs of water levels, currents, and water quality concentrations matched collected field data which included measurements of the sewer discharges. The tidal stage for the most degraded harbour water quality was identified. This stage was used to compare the harbour water quality enhancements and degradations for different management scenarios which included combining and relocating discharges, partial treatment of some discharges, and some direct ocean discharge. By using the model in a comparative manner, the requirements for model verification are reduced as are some of the errors in the modelling process. Key words: St. John's Harbour, dynamic numerical water quality model.

The River has got religious importance in India. The Bhima River is beginning from Bhimashankar hill and it flows through some parts of Maharashtra and Karnataka state. The assessment of water quality for the development of the places near the bank of River is important. These is controlled by various manmade activities. The quality of river water resources is facing problems because of the continuous agricultural runoff, development and urbanization. Due to mixing of nutrients causes algal blooms, which results eutrophication. The modeling of water quality can be deliberated as useful tool for assessing river water. Bhima River is demarcated as a major and important water body located in Pandharpur, dist. Solapur, Maharashtra. As Pandharpur is having historical background and known as one of the famous Holly places in Maharashtra, this place is facing huge population fluctuation due to migrated pilgrims and rapid growth of urbanization. These two things detrimentally affect River water quality. The main objective of current study was to develop a hydrodynamic model combined with river water quality model for the Bhima River to measure and recognize the processes harmful for the River. For Bhima River a hydrodynamic model was constructed using the HEC-RAS 4.1 software combined with a river water quality model to estimate the amount, distribution and sources of algae, nitrate and temperature. The river model has standardized with the help of previous water levels near the Pandharpur region. It has standardized and calibrated for the assessed parameters by competing them with the present data. The result showed a relationship between DO and temperature range. DO level in Pandharpur and Gopalpur were observed to be fluctuating with respective temperature and during Vari season. However, wastewater discharge from Nalha in sample station 3 i.e. Goplapur shows slit changes in DO and due to this there is necessity to learn other parameters also.


2009 ◽  
Vol 42 (11) ◽  
pp. 798-803 ◽  
Author(s):  
M.K. Yetik ◽  
M. Yüceer ◽  
R. Berber ◽  
E. Karadurmuş

1985 ◽  
Vol 12 (1) ◽  
pp. 236-237
Author(s):  
Raymond J. Dewey ◽  
Merv D. Palmer

Author(s):  
Soobin Kim ◽  
Yong Sung Kwon ◽  
JongChel Pyo ◽  
Mayzonee Ligaray ◽  
Joong-Hyuk Min ◽  
...  

2021 ◽  
Vol 193 (1) ◽  
Author(s):  
Cássia Monteiro da Silva Burigato Costa ◽  
Izabel Rodrigues Leite ◽  
Aleska Kaufmann Almeida ◽  
Isabel Kaufmann de Almeida

2021 ◽  
Vol 13 (1) ◽  
pp. 454-468
Author(s):  
Yumeng Song ◽  
Jing Zhang

Abstract We integrated hyperspectral and field-measured chlorophyll-a (Chl-a) data from the Kristalbad constructed wetland in the Netherlands. We developed a best-fit band ratio empirical algorithm to generate a distribution map of Chl-a concentration (C chla) from SPOT 6 imagery. The C chla retrieved from remote sensing was compared with a water quality model established for a wetland pond system. The retrieved satellite results were combined with a water quality model to simulate and predict the changes in phytoplankton levels. The regression model provides good retrievals for Chl-a. The imagery-derived C chla performed well in calibrating the simulation results. For each pond, the modeled C chla showed a range of values similar to the Chl-a data derived from SPOT 6 imagery (10–25 mg m−3). The imagery-derived and prediction model results could be used as the guiding analytical tools to provide information covering an entire study area and to inform policies.


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