International Journal of Engineering Research

Sameer Arora ¹, Ashok K. Keshari ²

Affiliations
1 G D Goenka University, Gurgaon-122103, Haryana, IN
2 Indian Institute of Technology Delhi, New Delhi-110016, IN

Abstract

To model and to allocate the waste load in a stream, it is necessary to estimate the re-aeration coefficient (k₂). Re-aeration rate coefficient as compared to loads, sources and sinks, cannot be measured under natural conditions. Indirect measurement with the calculation provide the efficient methodology for the estimation of re-aeration rate coefficient. Natural aeration system of river depending upon its assimilation capacity decomposes the organic matter which is mainly controlled by the flow rate and wastewater load. Currently, available k₂ when applied to different stream conditions as compared to their developed conditions produces poor estimate, because they were derived from small databases composed of potentially highly inaccurate measurements. In the present study, the re-aeration model for the different reaches of Yamuna river have been developed. Most commonly used predictive equation developed earlier have been tested and results obtained from these equation are compared with the field observation. A new predictive equation have been developed using Multivariate Linear Regression (MLR) with different flow conditions. The results of these studies are found with 95% level of significance with observed values and indicate that the modified re-aeration equation is a useful tool for measuring the atmospheric re-aeration rate coefficient.

Keywords

Environmental Flow, Assimilation Capacity, Re-Aeration, Multivariate Regression.

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Amarsinh B. Landage ¹, Ashok K. Keshari ²

Affiliations
1 Govt. Engineering College, Karad-415124, Maharashtra, IN
2 Department of Civil Engineering, IIT Delhi, New Delhi-110016, IN

Abstract

Groundwater management is very necessary due to scarcity of surface water sources and has heavy stress on its utilization for different purposes. Contamination of water either on surface or in ground is crucial problem. Now days various models are developed to assess groundwater quality. When the contaminant is subject to chemical constituent that follows a non-linear sorption isotherm, the resulting differential equation is non-linear. Analytical solution of non-linear differential equation is difficult. In present paper, main focuses have been made on sorption of contaminant species in groundwater. Finite difference models were developed to assess the groundwater quality for different sorption isotherms namely, Freundlich and Langmuir with linear and non linear conditions. Results of numerical model were compared with available analytical model. It is found that all results are comparable and matches approximately. A combined study for plumes behavior for sorption and no sorption situations has carried out for spatial and temporal variation. Such kind of study would be useful for finding contaminant species interactions with groundwater when it subject to sorption for wide range of field conditions with regard to dispersion and source definition.

Keywords

Groundwater Modelling, Sorption Isotherm, Freundlichs, Langmuir, Finite Difference Model.

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N. Patidar ¹, Ashok K. Keshari ¹

Affiliations
1 Department of Civil Engineering, Indian Institute of Technology, Delhi, IN

Abstract

With the advancement of earth observing satellites, remote sensing has become an important tool in monitoring and managing natural resources. Substantial research has been carried out in the field of hydrology to obtain wide range of information from remote sensing data. In particular, use of remote sensing data in estimating evapotranspiration, snow cover mapping, and flood-plain mapping, monitoring of sediment and water pollution and estimating soil moisture have been topics of intense interest during the past three decades. In the present paper, various remote sensing approaches to extract information for hydrological modelling are examined. Discussions are focused on the remote sensing data, land use and land cover (LULC) classification techniques and retrieval of leaf area index and surface albedo. The literature review suggested that major approaches during the past decade include LULC classification using traditional pixel based approaches for hydrological modelling. In addition to this, there has been a lag between the development of techniques of land surface parameter determination from remote sensing and application of these techniques in hydrological modelling.

Keywords

Hydrological Modelling, Land Use and Land Cover, Leaf Area Index and Surface Albedo.

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