Impact of Coal Mining on River Sediment Quality in the Sydney Basin, Australia

The environmental impacts arising from mining activities affect the air, water, and soil quality. Impacts may result in unexpected and adverse environmental outcomes. This study reports on the impact of coal production on sediment in Sydney region of Australia. The sediment samples upstream and downstream from the discharge points from three mines were taken, and 80 parameters were tested. The results were assessed against sediment quality based on presence of metals. The study revealed the increment of metal content in the sediment downstream of the reference locations. In many cases, the sediment was above the Australia and New Zealand Environment Conservation Council and international sediment quality guidelines value (SQGV). The major outliers to the guidelines were nickel (Ni) and zinc (Zn).

Mechanical Characterization and Impact Study on the Environment of Raw Sediments and Sediments Dehydrated by Addition of Polymer

Large volumes of river sediments are dredged each year in Europe in order to maintain harbour activities and prevent floods. The management of this sediment has become increasingly complex. Several European projects were implemented to find environmentally sound solutions for these materials. The main objective of this study is to show the ability of river sediment to be used in road. Since sediments contain a high amount of water, then a dehydrating treatment by addition of the flocculation aid has been used. Firstly, a lot of physical characteristics are measured and discussed for a better identification of the raw sediment and this dehydrated sediment by addition the flocculation aid. The identified parameters are, for example, the initial water content, the density, the organic matter content, the grain size distribution, the liquid limit and plastic limit and geotechnical parameters. The environmental impacts of the used material were evaluated. The results obtained show that there is a slight change on the physical-chemical and geotechnical characteristics of sediment after dehydration by the addition of polymer. However, these sediments cannot be used in road construction.

Physicochemical Characterizations of Marine and River Sediments in the North of France

This work is undertaken to develop a methodology to enhance the management of dredged marine and river sediments in the North of France. The main objective of this study is to determine the main characteristics of these sediments. In this order, physical, mineralogical and chemical properties of both types of sediments are measured. Moreover, their potential impacts on the environment are assessed throughout leaching tests. From the obtained results, the potential of their use in road engineering is discussed.

Tidal River Sediment Management–A Case Study in Southwestern Bangladesh

The problems of severe drainage congestion and water logging in the southwestern Bangladesh have been solved by an innovative concept, Tidal River Management (TRM). TRM involves the uniform raising of the land inside a tidal basin (beel) while simultaneously maintaining the proper drainage capacity in the river. The present practice of TRM is to link the river with the selected beel by constructing a link canal at the entrance of which most of the sedimentation takes place. This localized sedimentation also creates drainage congestion and water logging making it unattractive to landowners who participate in the program. In this paper a functional sediment management plan is presented to get rid of this problem

A Study of Flow and Sedimentation at the Basins of Khoozestan Province Rivers: A Case Study of Boneh Basht Pumping Station

The present paper is a case study about exploitation of Kheir Abad river (Khoozestan, Iran) water resources and the problems caused by river sediments around the pumping stations. The weak points and strong points of Boneh Basht pumping station have been studied by experienced experts, work teams, and consulting engineers and technical and executive solutions have been suggested. Therefore, the suggestions of this article are based on the performed studies and are proposed in order to evaluate the logical solutions. Rather complicated processes resulting from the interaction of water flows and sediments observed at Boneh Basht pumping station occur at other pumping stations in almost the same way. Therefore, Boneh Basht pumping station can be selected as a sample (pilot) and up-to-date theories and experiences can be applied to this station and the results can be offered to other stations.

A Study of Methods for Preservation of River Banks in order to Reduce Sediments

Reducing river sediments through path correction and preservation of river walls leads to considerable reduction of sedimentation at the pumping stations. Path correction and preservation of walls is not limited to one particular method but, depending on various conditions, a combination of several methods can be employed. In this article, we try to review and evaluate methods for preservation of river banks in order to reduce sediments.

Artificial Neural Networks Modeling in Water Resources Engineering: Infrastructure and Applications

The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.