Six main public domain water quality models which are presently available for Rivers and streams are being captured in this article. These main models could produce important results if they are used in the correct manner, because they are different in terms of assumptions, strength and weaknesses, processes they represent, modeling capability and data input requirements. The Model review discussed includes, water quality analysis simulation program (WASP7), simulation catchment (SIMCAT), quality simulation along Rivers (QUASAR), and the temporal overall model for catchment (TOMCAT), QUAL2KW, QUAL2EU. The models are described individually according to a consistent set of criteria-conceptualization, model capability, model strengths, limitations, input data and how it utilized. The outcome showed that TOMCAT and SIMCAT are important in ASSESSING effect of point sources in a very simple way. The QUAL2KW, unlike the QUAL2EU where macrophytes play a major interaction, it can convert algal death to carbonaceous Biochemical Oxygen Demand (CBOD), thereby making it more suitable. In addition to the extensive requirement of data, it is expensive and time consuming to set up these complex models such as QUASAR and WASP7. Therefore, one model cannot be used for all the required functionalities. Choosing a model would depend on a specific application, financial cost and time availability. This article may be of help in choosing a suitable model for a specific water quality problem.
The focus of this research was to calculate initial beam characteristics of a 6 MV X-rays with flattening filter (FF) from Elekta Versa-HD linear accelerator (Linac) using the Tool for Particle Simulation (TOPAS) Monte Carlo (MC) simulation code. TOPAS 3.6 simulated data was compared with the measured data. During simulation, all the main component were simulated including Linac head, Multi-Leaf Collimators (MLCs), and uniform water phantom, while the SNC 3D scanner phantom and SNC125c Chamber were used for measurements. At collimator sizes of 5x5, 10x10, and 20x20 cm2, the depth dose scans (PDD) distribution and beam profiles (BP) were measured. The estimated tissue phantom ratio (TPR20,10) was 0.669, which was -1.1 percent lower than the measured TPR20,10 of 0.681. The obtained results show that the simulated and measured data were in good agreement, with gamma rate analysis of 3%/3 mm criteria reaching 95% and 99 % for PDD and BP respectively.
The ability of a water body to self-purify itself is dependent on its re-aeration rate (Ka). This rate is necessary to calculate the dissolved oxygen content in the waterbody. This rate also depends on some variables that include the stream velocity, stream bed slope, cross section area, water depth, frictional velocity, discharge rate, Froude’s number and a number of other things. For the purpose of this study, thirteen empirical equations are considered when evaluating the performance of the re-aeration rates. This is done with respect to the size of the Tungabhadra river. Observation of the re-aeration rate for this study was done using mass balance approach. The data needed for this was gotten from field investigation data obtained from 288 separate samples (6 different sites) between the period March, 2017 to December, 2018. The performance evaluation of the re-aeration equation was done via the implementation of least square techniques. The following statistical error methods were applied in due course; standard error, normal mean method and mean multiplicative method. The results of the methods are 0.16, -0.0006 and 2.75. The coefficient of correlation for this was 0.91 and by interpretation, it shows an efficient outcome.
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