Geospatial water quality assessment system for the Sg. Buloh river basin in Malaysia

被引：0
|
作者：
Rowshon, M.K. [1 ]
Mbaruk, M.M. [2 ]
Marriott, Martin J. [3 ]
Amin, M.S.M. [1 ]
Ahsan, Amimul [4 ]
Loh, Eric W.K. [5 ]
机构：
[1] Department of Biological and Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), 43400 UPM Serdang, Selangor,DE, Malaysia
[2] Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), 43400 UPM Serdang, Selangor,DE, Malaysia
[3] School of Architecture Computing and Engineering, Docklands Campus, University of East London, London E16 2RD, United Kingdom
[4] Department of Civil Engineering, Institute of Advanced Technology, Universiti Putra Malaysia (UPM), 43400 UPM Serdang, Selangor,DE, Malaysia
[5] School of Civil Engineering, Linton University College, Bandar Universiti Teknologi Legenda (BUTL), Negeri Sembilan,71700, Malaysia
来源：
International Journal of Water | 2014年 / 8卷 / 04期
关键词：
Biochemical oxygen demand - User interfaces - Dissolved oxygen - Risk assessment - Water pollution control - Watersheds - Decision making - River pollution;
D O I：
10.1504/IJW.2014.065795
中图分类号：
学科分类号：
摘要：
Assessment of pollution risk requires the assimilation of spatio-temporally variable data on water quality parameters. This paper describes a GIS user-interface program coupled with a water quality index (WQI) model that was developed and built to assess water quality in the Sg. Buloh river basin. Fifty-two water sampling stations were selected for this study, and the WQI model considers parameters such as pH, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total suspended solids and ammonia nitrogen, as used by the Department of Environment in Malaysia. The spatial pattern of each parameter was analysed, and WQI values were calculated, ranging from 4.48 to 76.8 on a scale with 100 representing the highest pristine quality. A map of WQI is provided, which will help planners and decision makers to develop water pollution control strategies, and the model is capable of extension with further data to address pollution risk. Copyright © 2014 Inderscience Enterprises Ltd.
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页码：401 / 421
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