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Geologic Sediments

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Antifouling booster biocide extraction from marine sediments: a fast and simple method based on vortex-assisted matrix solid-phase extraction.

Environmental science and pollution research international
This paper reports the development of an analytical method employing vortex-assisted matrix solid-phase dispersion (MSPD) for the extraction of diuron, Irgarol 1051, TCMTB (2-thiocyanomethylthiobenzothiazole), DCOIT (4,5-dichloro-2-n-octyl-3-(2H)-iso...

Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks.

PloS one
Identifying land-use drivers of changes in river condition is complicated by spatial scale, geomorphological context, land management, and correlations among responding variables such as nutrients and sediments. Furthermore, variations in standard me...

A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States.

Environmental monitoring and assessment
Accurate and reliable suspended sediment load (SSL) prediction models are necessary for planning and management of water resource structures. More recently, soft computing techniques have been used in hydrological and environmental modeling. The pres...

Application of chemometric analysis and self Organizing Map-Artificial Neural Network as source receptor modeling for metal speciation in river sediment.

Environmental pollution (Barking, Essex : 1987)
Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation stud...

ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.

Environmental monitoring and assessment
The present study explores for the first time the possibility of modelling sediment concentration with artificial neural networks (ANNs) at Gangotri, the source of Bhagirathi River in the Himalaya. Discharge, rainfall and temperature have been consid...

Development of sediment load estimation models by using artificial neural networking techniques.

Environmental monitoring and assessment
This study aims at the development of an artificial neural network-based model for the estimation of weekly sediment load at a catchment located in northern part of Pakistan. The adopted methodology has been based upon antecedent sediment conditions,...

Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

Environmental science and pollution research international
The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of ...

Identifying trace metal distribution and occurrence in sediments, inundated soils, and non-flooded soils of a reservoir catchment using Self-Organizing Maps, an artificial neural network method.

Environmental science and pollution research international
The Lancang-Mekong River is a trans-boundary river which provides a livelihood for over 60 million people in Southeast Asia. Its environmental security is vital to both local and regional inhabitants. Efforts have been undertaken to identify controll...

Modeling daily suspended sediment load using improved support vector machine model and genetic algorithm.

Environmental science and pollution research international
Prediction of sediment volume and sediment load is always one of the important issues for decision-makers of watershed basins. The present study investigated the daily suspended sediment load in a watershed basin using the improved support vector mac...