Background: Rivers are susceptible to pollution and water pollution is a growing problem in low- and middle-income countries (LMIC) with rapid development and minimal environmental protections. There are universal pollutant threshold values, but they are not directly linked to river activities such as sand mining and aquaculture. Water quality modelling can support assessments of river pollution and provide information on this important environmental issue.
Objectives: The objective of the present study was to demonstrate water quality modelling methodology in reviewing existing policies for Malaysian river catchments based on an example case study.
Methods: The MIKE 11 software developed by the Danish Hydraulic Institute was used to model the main pollutant point sources within the study area - sand mining and aquaculture. Water quality data were obtained for six river stations from 2000 to 2015. All sand mining and aquaculture locations and approximate production capacities were quantified by ground survey. Modelling of the sand washing effluents was undertaken with the advection-dispersion module due to the nature of the fine sediment. Modelling of the fates of aquaculture deposits required both advection-dispersion and Danish Hydraulic Institute ECO Lab modules to simulate the detailed interactions between water quality determinants.
Results: According to the Malaysian standard, biochemical oxygen command (BOD) and ammonium (NH4) parameters fell under Class IV at most of the river reaches, while the dissolved oxygen (DO) parameter varied between Classes II to IV. Total suspended solids (TSS) fell within Classes IV to V along the mid river reaches of the catchment.
Discussion: Comparison between corresponding constituents and locations showed that the water quality model reproduced the long-term duration exceedance for the main body of the curves. However, the water quality model underestimated the infrequent high concentration observations. A standard effluent disposal was proposed for the development of legislation and regulations by authorities in the district that could be replicated for other similar catchments.
Conclusions: Modelling pollutants enables observation of trends over the years and the percentage of time a certain class is exceeded for each individual pollutant. The catchment did not meet Class II requirements and may not be able to reach Class I without extensive improvements in the quality and reducing the quantity of both point and non-point effluent sources within the catchment.
Competing Interests: The authors declare no competing financial interests.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.