scholarly journals Increasing confidence in model prediction: A case study on water quality data collation for model validation in the Great Barrier Reef catchments

2011 ◽  
Keyword(s):  
Water Quality ◽  
Great Barrier Reef ◽  
Model Validation ◽  
Model Prediction ◽  
Quality Data ◽  
Barrier Reef ◽  
Water Quality Data ◽  
Data Collation

scholarly journals Longitudinal River Monitoring and Modelling Substantiate the Impact of Weirs on Nitrogen Dynamics

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 189
Author(s):  
Geovanni Teran-Velasquez ◽  
Björn Helm ◽  
Peter Krebs
Keyword(s):  
Water Quality ◽  
Nitrogen Dynamics ◽  
Low Flow ◽  
Quality Data ◽  
Quality Model ◽  
Spatiotemporal Resolution ◽  
Water Quality Data ◽  
River Monitoring ◽  
The Impact

The fluvial nitrogen dynamics at locations around weirs are still rarely studied in detail. Eulerian data, often used by conventional river monitoring and modelling approaches, lags the spatial resolution for an unambiguous representation. With the aim to address this knowledge gap, the present study applies a coupled 1D hydrodynamic–water quality model to a 26.9 km stretch of an upland river. Tailored simulations were performed for river sections with water retention and free-flow conditions to quantify the weirs’ influences on nitrogen dynamics. The water quality data were sampled with Eulerian and Lagrangian strategies. Despite the limitations in terms of required spatial discretization and simulation time, refined model calibrations with high spatiotemporal resolution corroborated the high ammonification rates (0.015 d−1) on river sections without weirs and high nitrification rates (0.17 d−1 ammonium to nitrate, 0.78 d−1 nitrate to nitrite) on river sections with weirs. Additionally, using estimations of denitrification based on typical values for riverbed sediment as a reference, we could demonstrate that in our case study, weirs can improve denitrification substantially. The produced backwater lengths can induce a means of additional nitrogen removal of 0.2-ton d−1 (10.9%) during warm and low-flow periods.

scholarly journals Challenges in Quantifying Air‐Water Carbon Dioxide Flux Using Estuarine Water Quality Data: Case Study for Chesapeake Bay

2020 ◽  
Vol 125 (7) ◽  
Author(s):  
Maria Herrmann ◽  
Raymond G. Najjar ◽  
Fei Da ◽  
Jaclyn R. Friedman ◽  
Marjorie A. M. Friedrichs ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Chesapeake Bay ◽  
Carbon Dioxide Flux ◽  
Quality Data ◽  
Estuarine Water ◽  
Water Quality Data ◽  
Estuarine Water Quality

Chemometric Analysis of Surface Water Quality Data: Case Study of the Gorganrud River Basin, Iran

2011 ◽  
Vol 17 (4) ◽  
pp. 411-420 ◽  
Author(s):  
Roohollah Noori ◽  
Abdulreza Karbassi ◽  
Amir Khakpour ◽  
Mohammadreza Shahbazbegian ◽  
Hassan Mohammadi Khalf Badam ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
River Basin ◽  
Surface Water Quality ◽  
Chemometric Analysis ◽  
Quality Data ◽  
Water Quality Data

A construction of water quality index considering physicochemical properties for drinking purposes in a rural settlement: a case study of Gajraula region, Ganga River Basin (North India)

2012 ◽  
Vol 12 (6) ◽  
pp. 818-828 ◽  
Author(s):  
Bineet Singh ◽  
Jaspal Singh Chauhan ◽  
Anuraag Mohan
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Rating Scale ◽  
Rural Settlement ◽  
North India ◽  
Quality Data ◽  
Rapid Urbanization ◽  
Water Quality Data

A simple methodology based on several key variables of groundwater chemistry is used to create a water quality index (WQI), with the aim of monitoring the influence of industrial and rapid urbanization on a typical rural settlement. The applicability of the constructed indices as an assessment and communication tool is evaluated in a case study of Gajraula and its suburb of JP Nagar district in northern India. The water quality data from 2007 to 2009 were analysed for 12 different locations surrounding Gajraula for two seasons, i.e. wet and dry. Five point rating scale was used to classify water quality for each of the study locations. Rating curves were drawn based on the tolerance limits of drinking waters. In the present study, the WQI demonstrated a modest increase in wet seasons (August to November) than dry seasons (February to June) for all locations with a few exceptions. Hardness, total dissolved solids, NO3−, biochemical oxygen demand, and Fe in most cases were found to be responsible for the decline in seasonal WQI for various locations. However, the WQI around Gajraula varied from 50.6 to 87.7 and was found to be satisfactory except for some locations.

Making management decisions in the face of uncertainty: a case study using the Burdekin catchment in the Great Barrier Reef

2018 ◽  
Vol 69 (8) ◽  
pp. 1187 ◽  
Author(s):  
P. M. Kuhnert ◽  
D. E. Pagendam ◽  
R. Bartley ◽  
D. W. Gladish ◽  
S. E. Lewis ◽  
...  
Keyword(s):  
Water Quality ◽  
Great Barrier Reef ◽  
Hot Spots ◽  
Decision Makers ◽  
Barrier Reef ◽  
Target Setting ◽  
Making A Difference ◽  
The Face ◽  
Modelling Data

Modelling and monitoring pollutants entering into the Great Barrier Reef (GBR) lagoon remain important priorities for the Australian and Queensland governments. Uncertainty analysis of pollutant load delivery to the GBR would: (1) inform decision makers on their ability to meet environmental targets; (2) identify whether additional measurements are required to make confident decisions; and (3) determine whether investments into remediation activities are actually making a difference to water quality and the health of the GBR. Using a case study from the Upper Burdekin catchment where sediment concentrations are the focus, herein we explore and demonstrate different ways of communicating uncertainty to a decision maker. In particular, we show how exceedance probabilities can identify hot spots for future monitoring or remediation activities and how they can be used to inform target setting activities. We provide recommendations for water quality specialists that allow them to make more informed and scientifically defensible decisions that consider uncertainty in both the monitoring and modelling data, as well as allowing the calculation of exceedances from a threshold.

scholarly journals A comparative analysis of the effects of landfills on water quality: a case study of two locations in New Jersey

2019 ◽  
Vol 4 (2) ◽  
pp. 9-13
Author(s):  
Casilda Saavedra
Keyword(s):  
Water Quality ◽  
New Jersey ◽  
Comparative Analysis ◽  
Inorganic Material ◽  
Quality Data ◽  
Water Quality Data ◽  
Quality Of Water ◽  
The Town

Leachate is a liquid generated by mixing of water with organic and inorganic material found in landfills. This liquid accumulates at the bottom of the landfill and has the potential to percolate through the soil to enter groundwater or other water bodies. Leachate contains various contaminants and toxins that can significantly diminish the quality of water it enters, which can become hazardous to humans and the environment. In this article, the water quality of two towns: Egg Harbor and Middle Township, New Jersey were analyzed and compared. Egg Harbor Township has a landfill located within the town, while the closest landfill to Middle Township is approximately 10 miles away. Water supply for both towns comes from the same aquifer, known as the Kirkwood-Cohansey water table system. The water quality results from community wells within Egg Harbor Township were compared to those of Middle Township. Water quality data for this study is from New Jersey American Water database. Based on the results, the water quality of Egg Harbor Township varies significantly from Middle Township. The levels of contaminants in Egg Harbor Township are much higher compared to Middle Township. Therefore, it can be concluded that communities near landfills, even well monitored and managed ones, are prone to have poorer water quality than those farther away from the landfill.

scholarly journals Evaluation of Different WQI Methods for Drinking Water Assessment with a Case Study of Groundwater from Vizianagaram District, AP, India

2021 ◽  
pp. 28-46
Author(s):  
A. G. S. Reddy ◽  
K. S. Sastry ◽  
Guru Raghavendra
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Water Chemistry ◽  
Simple Calculation ◽  
Quality Data ◽  
Index Method ◽  
Water Quality Data ◽  
Weighted Arithmetic ◽  
Acceptable Method

Application of Water Quality Index (WQI) to assess the water quality for drinking water suitability and intensity of contamination is in practice worldwide. Many WQI methods have been in use since their conceptualization, and some are country-specific or use-specific. A generalized and widely acceptable method that can project ground truths in non-dimensional numerical form to evaluate the water quality, especially for drinking uses, is lacking. Complexity and disagreement among different methods are adding to incongruence among the scientists. The concept and a simple calculation method of WQI are deliberated. Five different WQI methods using water chemistry results of Vizianagarm District are discussed. The WQI output obtained from these methods displays discrepancies in the proper projection of water quality. Some samples show similarities in WQI values obtained from two to four methods. However, the suitability status of water for drinking purposes could not be precisely ascertained from these indices. Since the water chemistry results and WQI values are incompatible, the output from these methods could be red herring. Few issues are identified among the studied methods which need improvisation. The use of ideal value in the weighted arithmetic index method and arbitration in assigning Weight for each parameter gives scope for speculation. Non-uniformity in the categorization of water and the suitability statuses of drinking water are discouraging factors. The WQI is an effective tool in screening the vast database for identifying and addressing the issues in water quality. Since drinking water standards and water supply are government-sponsored, an institutional intervention is required to standardize the WQI computation procedure. Such an initiative is necessary for the practical application of water quality data to contain water-borne diseases.

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