Development and Application of Exceedance Model for Surface Water Quality Parameters

Abstract

Surface water quality is continuously changing due to anthropogenic activities and natural causes. The drinking water treatment technology can be expensive and ineffective if implemented without identifying the patterns of parameter exceedances. The objectives of this paper were to: (i) develop a mean exceedance model; (ii) apply the model for identification of the exceeded parameters; (iii) obtain the exceedance patterns of parameters; and (iv) obtain decision making on the treatment of parameters. The mean exceedance model was developed by utilizing cluster database of 12 major Canadian rivers. The clusters were developed on the basis of normalization model, principal component analysis, total exceedance model and Canadian Water Quality Index. On application of mean exceedance model, the parameters were identified, which exceeded the water quality guidelines. The output of mean exceedance model was utilized for making decision on treatment of parameters. The normalized water quality data of 17 parameters was used to develop a mean exceedance model to obtain exceedance level for water quality parameters. The mean exceedance for the parameters increased as the cluster number increased from low to high for all the rivers. Overall, the mean exceedance was higher for fecal coliforms, turbidity, total phosphorus, total nitrogen, true colour, dissolved oxygen, iron and manganese. The exceedance in fecal coliforms, turbidity, total phosphorus, total nitrogen, true colour, dissolved oxygen could be related to anthropogenic activities of landuse/landcover (LULC). The exceedance in iron and manganese could be associated to natural mineralization. The mean exceedance model was found useful for obtaining the specific parameters with their exceedance levels. The parameter exceedance patterns

Assessing and modelling drinking water quality at the railway stations of Tripura, India, with a possible strategic solution

“…Drinking water quality varies due to natural, quasi-natural, and anthropogenic activities and causes (Akbar et al 2021 ). The causality of diversified quality of drinking water varies due to geological structure (Pant et al 2021 ; Shroder et al 2021 ; Baba and Gundur 2017 ), physiographic characteristics (Qadir and El-Rawy 2021 ; Wu and Lu 2021 ; Taka et al 2015 ), soil properties (Wu et al 2022 ; Shahadha et al 2019 ; George et al 2017 ), micro-regional land use pattern (Rimba et al 2021 ; Tahlru et al 2020 ; Hua 2017 ), agricultural practices (Spitsov et al 2020 ; Sasakova et al 2018 ; Nikolaidis et al 2008 ), industrial development (Zou et al 2021 ; Edwards and Crabb 2020 ), and anthropogenic activities (Akhtar et al 2021 ; Kulk et al 2021 ; Khatri and Tyagi 2014 ).…”