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The barriers for the development of continuous monitoring of Suspended Sediment Concentration (SSC) in channels/rivers include costs and technological gaps but this paper shows that a solution is feasible by: (i) using readily available high-resolution images; (ii) transforming the images into image analytics to form a modelling dataset; and (iii) constructing predictive models by learning inherent correlation between observed SSC values and their image analytics. High-resolution images were taken of water containing a series of SSC values using an exploratory flume. Machine learning is processed by dividing the dataset into training and testing sets and the paper uses the following models: Generalized Linear Machine (GLM) and Distributed Random Forest (DRF). Results show that each model is capable of reliable predictions but the errors at higher SSC are not fully explained by modelling alone. Here we offer sufficient evidence for the feasibility of a continuous SSC monitoring capability in channels before the next phase of the study with the goal of producing practice guidelines.

ABSTRACT:Tabriz is the largest industrial city in North West of Iran and it is developing rapidly. A large proportion of water requirements for this city are supplied from dams. In this research, groundwater quality assessed through sampling 70 wells in Tabriz and its rural areas. The purposes of this study are: (1) specifying spatial distribution of groundwater quality parameters such as Chloride, Electrical Conductivity (EC), pH, hardness and sulphate (2) mapping groundwater quality for drinking purpose by employing Analytic Hierarchy Process (AHP) method in the study area using GIS and Geosatistics. We utilized an interpolation technique of ordinary kriging for generating thematic map of each parameter. The final map indicates that the groundwater quality esaeicni from North to South and from West to East of the study area. The areas located in Center, South and South West of the study area have the optimum quality for drinking purposes which are the best locations to drill wells for supplying water demands of Tabriz city. In critical conditions, the groundwater quality map as a result of this research can be taken into account by East Azerbaijan Regional Water Company as decision support system to drill new wells or selecting existing wells to supply drinking water to Tabriz city.