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Precise estimation of sound velocity profile and its impact on sediment classification in the tropical shallow freshwater reservoirs

机译:精确估计热带浅淡水储层中沉积物分类的声速曲线及其影响

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Tropical regions like India witness concentration of monsoons within three months of the year resulting in high rate of flow during the period. The high rate of flow manifests as high siltation in the reservoirs created for storing water for the long dry spell post monsoon. The incessant siltation during the monsoon period over the years depletes the storage capacity of the reservoirs created at very high cost. The present situation in India is really critical and urgent measures for de-siltation is called for to ensure reasonable availability of water resources for varied applications. De-siltation efforts require precise sediment classification for effective water resource management. The remote sensing followed by image analysis has been the most popular method to undertake such sediment analysis for reservoirs due to convenience. However, such methods have significant limitations in terms of inaccuracies of measurement and analysis of sediments. Acoustic methods can substantially enhance the measurement and analysis accuracies; however these techniques are highly sensitive to the medium properties of the underwater medium. The tropical Indian waters further adds to the challenges due to random fluctuations of the medium characteristics based on diurnal and seasonal variations of surface parameters including temperature, wind, etc. The deployment of acoustic methods could get limited if the medium fluctuations are not compensated and the advantages over the remote sensing methods could be neutralized. The temptation to import acoustic technology could have serious limitations in the absence of detailed study of the local conditions prior deployment. The most basic parameter for any form of acoustic analysis is the sound velocity profile (SVP) that is dependent on the temperature, salinity and pressure of the medium. The equipments used for sediment classification use default empirical equation for the computation of the SVP. These empirical equations have specif- ed limitation of their validity with respect to these parameters like temperature, salinity and pressure. It is well known that tropical waters have typical values for these parameters and also the equations valid in the sea water will not be applicable for freshwater measurements. The work attempts to highlight the variations of the commonly used empirical equations for computation of the SVP and their applicability in the tropical shallow freshwater reservoirs. The shallow water reservoirs in India ensure high multi-path interactions of the acoustic signal with the surface and the bottom, and the tropical condition cause high diurnal and seasonal fluctuations of the surface parameter. The work presents the error bound for the multiple empirical equations available in the literature namely the Wilson's, Medwin, Coppen and Leroy et.al, their validity for sediment classification in the tropical shallow freshwater. The tropical conditions in Khadakwasla lake have been used as a reference to validate the proposed difference. The simulation results have been validated with real data recording in the Lake.
机译:热带地区,如印度在一年中三个月内的季风的见证浓度,导致该期间的高流量。在为储存水季节季后遇储存水而产生的储层中的高淤积率高的流动率。多年来季风期间的不断淤积消耗了以非常高的成本创造的水库的储存能力。印度的现状是真正关键的,呼吁脱硅的紧急措施,以确保适用于各种应用的水资源。脱硅努力需要精确的沉积物分类,以获得有效的水资源管理。遥感随后是图像分析一直是最受欢迎的方法,以便由于方便起见,为储层进行这种沉积物分析。然而,这些方法在沉积物的测量和分析的不准确方面具有显着的限制。声学方法可以大大提高测量和分析精度;然而,这些技术对水下介质的介质性质非常敏感。由于基于包括温度,风等的表面参数的日元和季节参数的季节性变化,热带印度水域进一步增加了挑战。如果没有补偿介质波动,则声学方法的部署可能会受到限制。可以中和优于遥感方法的优点。导入声学技术的诱惑可能在没有对本地部署的详细研究的情况下具有严重限制。任何形式的声学分析的最基本参数是依赖于介质的温度,盐度和压力的声速曲线(SVP)。用于沉积物分类的设备使用默认经验方程来计算SVP。这些经验方程已经确定了与温度,盐度和压力等这些参数的有效性的限制。众所周知,热带水域具有这些参数的典型值,并且在海水中有效的方程也不适用于淡水测量。该工作试图突出常用经验方程的变化来计算SVP及其在热带浅淡水储层中的适用性。印度的浅水库确保了与表面和底部的声学信号的高多路径相互作用,热带条件导致表面参数的高性差和季节性波动。该工作介绍了文献中可用的多个经验方程的错误,即威尔逊,Medwin,Coppen和Leroy et.al,它们在热带浅淡水中对沉积物分类的有效性。 Khadakwasla Lake的热带条件已被用作验证拟议差异的参考。模拟结果已通过湖中的真实数据录制验证。

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