COMPARATIVE EVALUATION OF THE MODELS USED FOR THE CALCULATION OF RE-AERATION COEFFICIENT OF SURFACE WATER BODIES (A CASE OF DEEZIM CREEK, KHANA L.G.A., RIVERS STATE, NIGERIA)

Project Abstract

<p> </p><p>The various models (equations) used for the calculation of re-aeration coefficient of rivers/streams were evaluated. The evaluation was carried out by fitting data obtained from Deezim Creek in Khana Local Government Area of Rivers State. The results of the re-aeration coefficients obtained from the various models were verified using linear regression model and correlation. The model with the highest root mean square (R2) was adopted as the best model for calculating re-aeration coefficient for the creeks.</p><br> <br><p></p>

Project Overview

<p> </p><p><strong>1.1 Background of Study</strong></p><p>Self-purification is a natural process by which surface water bodies (rivers, streams, lakes etc) get rid of wastes. This process aids surface water to regain their original conditions or state despite the introduction of pollutants into the water bodies (Ledogo and Akatah, 2011; Agunwamba, 2001). Self-purification is a complex process which involves physical, chemical and biological processes working simultaneously. The self-purification of water bodies is largely dependent on the de-oxygenation rate constant and the re-aeration rate constant. The ratio of the re-aeration rate constant (coefficient) to the de-oxygenation rate constant (coefficient) is called the self-purification factor, f.</p><p>The most important parameters for water quality modeling and self-purification capacity studies are the de-oxygenation coefficient and the re-aeration coefficient. The re-aeration rate constant (coefficient) is a function of the rate at which surface water bodies absorbs atmospheric oxygen. When the existing dissolved oxygen in surface water body is used for BOD loading, the DO level decreases sharply and may cause the water body to become septic. For the water body to recover from its polluted state, the water body will trap and dissolve atmospheric oxygen at a rate greater than the rate at which the water body losses oxygen during BOD loading (Omole, 2011, Omole and Longe, 2008). Re-aeration rate constant was first studies in the United States of America. &nbsp;Though, it was first studied in the US, several researches have been carried out in different countries. These studies or researches were carried out to find out the <a target="_blank" rel="nofollow" href="https://www.modishproject.com/predicting-students-academic/">customized models </a>for predicting reaeration coefficient in such countries. Principal among these researches are Al-Zboom and Al-Suhaili, 2009; Agunwamba et al, 2007; Ugbebor, 2011; Omole, 2011; Mehrdadi et al, 2006, etc. The reason for the customized studies is premised on the fact that climatic conditions affects re-aeration rate constant and the climatic conditions differ with countries and continents. The most important climatic factor in the study of re-aeration coefficient, K2 is temperature. Temperature determines the rate at which atmospheric oxygen dissolves in surface water bodies (Omole, 2011; Agunwamba et al, 2007).Apart from temperature, other factors or variables that affect re-aeration rate are stream velocity, hydraulic radius, stream depth, water surface area dispersive nature, river bed friction (Alam et al, 2007; Jha et al, 2005; Garg, 2006). The above named variables are usually similar in all countries but temperature varies widely in different countries.</p><p>K2 models are mostly expressed using the general expression:</p><p>K2 = &nbsp; C Vn/Hm &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; </p><p>Where V is Velocity of flow (Stream Velocity) in m/s or ft/s, H is Stream depth or hydraulic radius in m or ft. and c, n and m = constants with specific values.</p><p>Several <a target="_blank" rel="nofollow" href="https://www.modishproject.com/effect-of-models-and-charts-on-students-academic-performance-in-basic-science-in-calabar-municipality-cross-river-state-nigeria/">re-aeration models </a>have been developed in different countries. Some of the models as related to the countries (nations) include the Nigerian models, the Indian models, the Chilean models, the British models, the Chinese model and the US models. In this work, some of these re-aeration models will be used to determine the re-aeration coefficient of the creek.</p><p><strong>1.2 &nbsp; &nbsp; Statement of Problem</strong></p><p>The issue of self-purification of surface water is a major issue in the universe. Researches have revealed the de-oxygenation and re-aeration play a key role in the prediction or determination of self-purification of stream. Because of the important role played by re-aeration in self-purification studies, several models or equations have been developed by researchers. Some of the models include O’connor and Dobbins (1958), Agunwamba et al (2007), Ugbebor et al, 2011, Omole and Longe (2012), Jha et al (2001), etc.These models may be stream based or may not be suitable for the prediction of re-aeration coefficient in some stream or rivers. Hence, this work seeks to find out the best equation or model that can be used to predict or determine the re-aeration coefficient of Deezim creek in Khana Local Government Area of Rivers State.</p><p><strong>1.3 &nbsp; &nbsp; Aim and Objectives of the Study</strong></p><p>The main aim of this study is to evaluate the various re-aeration models and use the models to determine the re-aeration coefficient of Deezim Creek in Khana Local Government Area of Rivers State. The specific objectives of the study include;</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determine the re-aeration coefficient of Deezim Creek in Khana LGA using different models.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determine evaluate the models.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Select the best model for prediction of re-aeration constant of Deezim creek.</p><p><strong>1.4 &nbsp; &nbsp; Scope of Study</strong></p><p>The scope of this study includes:</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Reconnaissance visit to the creek.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determination of stream velocity.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determination of bed slope and water depths.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determination of hydraulic radius.</p><p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Determination of re-aeration constant using different models.</p><p>&nbsp;Selection of the best model for the determination of re-aeration constant for the stream.</p> <br><p></p>