How To Identify And Prioritize Watershed Pollution Sources? ------ Case Studies of Transform Water Quality Data into Decision Making Tool

2016 ◽  
Vol 2016 (8) ◽  
pp. 3265-3273
Author(s):  
Ting Lu ◽  
James Schlaman ◽  
Leisha Pica ◽  
MaryLynn Lodor ◽  
Gérald Checco ◽  
...  
Keyword(s):  
Water Quality ◽  
Decision Making ◽  
Case Studies ◽  
Pollution Sources ◽  
Quality Data ◽  
Water Quality Data ◽  
Decision Making Tool

SPATIAL CHARACTERIZATION AND IDENTIFICATION SOURCES OF POLLUTION USING MULTIVARIATE ANALYSIS AT TERENGGANU RIVER BASIN, MALAYSIA

2015 ◽  
Vol 77 (1) ◽  
Author(s):  
Ahmad Firdaus Kamaruddin ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Sharifuddin Md Zain ◽  
Mohd Nordin Abdul Rahman ◽  
...  
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Organic Pollution ◽  
Agricultural Runoff ◽  
Pollution Sources ◽  
Anthropogenic Sources ◽  
Quality Data ◽  
Water Quality Data ◽  
Hierarchical Agglomerative Cluster ◽  
Sources Of Pollution

The spatial water quality data (281x22) obtained from 12 sampling stations located along the Terengganu River and its main tributaries were evaluated with environmetric methods. Principal component analysis was used to investigate the origin of each variable due to land use and human activities based on the three clustered regions obtained from the hierarchical agglomerative cluster analysis. Six principal components (PCs) were obtained, where six varimax factor (VF) of values more than 0.70 that considered strong loading are discussed. The possible pollution sources identified are of anthropogenic sources, mainly municipal waste, surface runoff, agricultural runoff, organic pollution and urban storm runoff. As a conclusion, the application of environmetric methods could reveal important information on the spatial variability of a large and complex river water quality data in order to control pollution sources.

scholarly journals Network-Based Topological Exploration of the Impact of Pollution Sources on Surface Water Bodies

2022 ◽  
Vol 9 ◽  
Author(s):  
Viktor Sebestyén ◽  
Tímea Czvetkó ◽  
János Abonyi
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Wastewater Treatment Plants ◽  
Pollution Sources ◽  
Water Bodies ◽  
Quality Data ◽  
Critical Surface ◽  
Water Quality Data ◽  
Surface Water Bodies ◽  
The Impact

We developed a digital water management toolkit to evaluate the importance of the connections between water bodies and the impacts caused by pollution sources. By representing water bodies in a topological network, the relationship between point loads and basic water quality parameters is examined as a labelled network. The labels are defined based on the classification of the water bodies and pollution sources. The analysis of the topology of the network can provide information on how the possible paths of the surface water network influence the water quality. The extracted information can be used to develop a monitoring- and evidence-based decision support system. The methodological development is presented through the analysis of the physical-chemical parameters of all surface water bodies in Hungary, using the emissions of industrial plants and wastewater treatment plants. Changes in water quality are comprehensively assessed based on the water quality data recorded over the past 10 years. The results illustrate that the developed method can identify critical surface water bodies where the impact of local pollution sources is more significant. One hundred six critical water bodies have been identified, where special attention should be given to water quality improvement.

Editing and Sharing Water Quality Data in Yukon Alaska

2012 ◽  
Author(s):  
Gregg Breton
Keyword(s):  
Water Quality ◽  
Quality Data ◽  
Water Quality Data

Ground-Water Quality Data in the San Francisco Bay Study Unit, 2007: Results from the California GAMA Program

Data Series ◽  
10.3133/ds396 ◽  
2009 ◽  
Author(s):  
Mary C. Ray ◽  
Justin T. Kulongoski ◽  
Kenneth Belitz
Keyword(s):  
Water Quality ◽  
Ground Water ◽  
San Francisco ◽  
San Francisco Bay ◽  
Quality Data ◽  
Ground Water Quality ◽  
Water Quality Data ◽  
Study Unit

Ground-Water Quality Data in the Coastal Los Angeles Basin Study Unit, 2006: Results from the California GAMA Program

Data Series ◽  
10.3133/ds387 ◽  
2008 ◽  
Author(s):  
Timothy M. Mathany ◽  
Michael Land ◽  
Kenneth Belitz
Keyword(s):  
Water Quality ◽  
Los Angeles ◽  
Ground Water ◽  
Quality Data ◽  
Ground Water Quality ◽  
Los Angeles Basin ◽  
Water Quality Data ◽  
Study Unit

Water-quality data collected at Lake Anne, Reston, Virginia, 1997-1999

2000 ◽  
Author(s):  
Kathryn M. Conko ◽  
Margaret M. Kennedy ◽  
Karen C. Rice
Keyword(s):  
Water Quality ◽  
Quality Data ◽  
Water Quality Data
Sign in / Sign up

Export Citation Format

Share Document