Spatiotemporal assessment of water quality monitoring network in a tropical river

Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropri...

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Main Authors: Moriken, Camara, Jamil, Nor Rohaizah, Abdullah, Ahmad Fikri, Hashim, Rohasliney
Format: Article
Language:English
Published: Springer 2019
Online Access:http://psasir.upm.edu.my/id/eprint/82224/
http://psasir.upm.edu.my/id/eprint/82224/1/Spatiotemporal%20assessment%20of%20water%20quality%20monitoring%20network%20in%20a%20tropical%20river.pdf
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author Moriken, Camara
Jamil, Nor Rohaizah
Abdullah, Ahmad Fikri
Hashim, Rohasliney
author_facet Moriken, Camara
Jamil, Nor Rohaizah
Abdullah, Ahmad Fikri
Hashim, Rohasliney
author_sort Moriken, Camara
building UPM Institutional Repository
collection Online Access
description Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall’s coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall’s coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network.
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spelling upm-822242020-10-17T06:57:36Z http://psasir.upm.edu.my/id/eprint/82224/ Spatiotemporal assessment of water quality monitoring network in a tropical river Moriken, Camara Jamil, Nor Rohaizah Abdullah, Ahmad Fikri Hashim, Rohasliney Managers of water quality and water monitoring programs are often faced with constraints in terms of budget, time, and laboratory capacity for sample analysis. In such situation, the ideal solution is to reduce the number of sampling sites and/or monitored variables. In this case, selecting appropriate monitoring sites is a challenge. To overcome this problem, this study was conducted to statistically assess and identify the appropriate sampling stations of monitoring network under the monitored parameters. To achieve this goal, two sets of water quality data acquired from two different monitoring networks were used. The hierarchical agglomerative cluster analysis (HACA) were used to group stations with similar characteristics in the networks, the time series analysis was then performed to observe the temporal variation of water quality within the station clusters, and the geo-statistical analysis associated Kendall’s coefficient of concordance were finally applied to identify the most appropriate and least appropriate sampling stations. Based on the overall result, five stations were identified in the networks that contribute the most to the knowledge of water quality status of the entire river. In addition, five stations deemed less important were identified and could therefore be considered as redundant in the network. This result demonstrated that geo-statistical technique coupled with Kendall’s coefficient of concordance can be a reliable method for water resource managers to identify appropriate sampling sites in a river monitoring network. Springer 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/82224/1/Spatiotemporal%20assessment%20of%20water%20quality%20monitoring%20network%20in%20a%20tropical%20river.pdf Moriken, Camara and Jamil, Nor Rohaizah and Abdullah, Ahmad Fikri and Hashim, Rohasliney (2019) Spatiotemporal assessment of water quality monitoring network in a tropical river. Environmental Monitoring and Assessment, 191 (12). art. no. 729. pp. 1-14. ISSN 0167-6369; ESSN: 1573-2959 https://link.springer.com/article/10.1007/s10661-019-7906-1 10.1007/s10661-019-7906-1
spellingShingle Moriken, Camara
Jamil, Nor Rohaizah
Abdullah, Ahmad Fikri
Hashim, Rohasliney
Spatiotemporal assessment of water quality monitoring network in a tropical river
title Spatiotemporal assessment of water quality monitoring network in a tropical river
title_full Spatiotemporal assessment of water quality monitoring network in a tropical river
title_fullStr Spatiotemporal assessment of water quality monitoring network in a tropical river
title_full_unstemmed Spatiotemporal assessment of water quality monitoring network in a tropical river
title_short Spatiotemporal assessment of water quality monitoring network in a tropical river
title_sort spatiotemporal assessment of water quality monitoring network in a tropical river
url http://psasir.upm.edu.my/id/eprint/82224/
http://psasir.upm.edu.my/id/eprint/82224/
http://psasir.upm.edu.my/id/eprint/82224/
http://psasir.upm.edu.my/id/eprint/82224/1/Spatiotemporal%20assessment%20of%20water%20quality%20monitoring%20network%20in%20a%20tropical%20river.pdf