Modelling of Escherichia coli concentrations in bathing water at microtidal coasts

Palazón, Antonio; López, Isabel; Aragonés, Luís; Villacampa, Yolanda; Navarro-González, Francisco J.

doi:10.1016/j.scitotenv.2017.03.161

Cited by 23 publications

(11 citation statements)

References 51 publications

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“…Numerical methodologies are important due to their application in science and engineering processes where it is not possible to represent relationships by mathematical equations. Some numerical methodologies developed by the authors have been successfully applied in the modelling of different problems [27][28][29][30]. These methodologies are based on the generation of a geometrical model of finite elements.…”

Section: Mathematical Modellingmentioning

confidence: 99%

Modelling Faba Bean (Vicia faba L.) Biomass Production for Sustainability of Agricultural Systems of Pampas

et al. 2020

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The Pampas region is characterized by a high complexity in its productive system planning and faces the challenge of satisfying future food demands, as well as reducing the environmental impact of the activity. Climate change affects crops and farmers should use species capable of adapting to the changed climate. Among these species, faba bean (Vicia faba L.) cv. ‘Alameda’ has shown good adaptation to weather variability and, as a winter legume, it can help maintain the sustainability of agricultural systems in the area. The main purpose of this research was to select the models which describe the production characteristics of the ‘Alameda’ bean by using the least number of variables. Experimental and agrometeorological data from the cultivation of the ‘Alameda’ in Azul, Buenos Aires province, Argentina were used to generate mathematical models. Several modelling methodologies have been applied to study the production characteristics of the faba bean. The prediction of the models generated was analyzed by randomly disturbing the experimental data and analyzing the magnitude of the errors produced. The models obtained will be useful for predicting the biomass production of the faba bean cv. ‘Alameda’ grown in the agroclimatic conditions of Azul, Buenos Aires province, Argentina.

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Section: Mathematical Modellingmentioning

confidence: 99%

Modelling Faba Bean (Vicia faba L.) Biomass Production for Sustainability of Agricultural Systems of Pampas

et al. 2020

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“…In [4], the model is built from a physical analogy that solves some problems on the linear system. One approach more on the line of the original FEM can be seen in [5] and applied by an example in [6,7]. Although different modifications of the initial algorithm have been developed, see [8] in order to improve the computing speeds for the regression model, the basic methodology can be resumed as follows.…”

Section: Introductionmentioning

confidence: 99%

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

et al. 2020

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Estimation problems are frequent in several fields such as engineering, economics, and physics, etc. Linear and non-linear regression are powerful techniques based on optimizing an error defined over a dataset. Although they have a strong theoretical background, the need of supposing an analytical expression sometimes makes them impractical. Consequently, a group of other approaches and methodologies are available, from neural networks to random forest, etc. This work presents a new methodology to increase the number of available numerical techniques and corresponds to a natural evolution of the previous algorithms for regression based on finite elements developed by the authors improving the computational behavior and allowing the study of problems with a greater number of points. It possesses an interesting characteristic: Its direct and clear geometrical meaning. The modelling problem is presented from the point of view of the statistical analysis of the data noise considered as a random field. The goodness of fit of the generated models has been tested and compared with some other methodologies validating the results with some experimental campaigns obtained from bibliography in the engineering field, showing good approximation. In addition, a small variation on the data estimation algorithm allows studying overfitting in a model, that it is a problematic fact when numerical methods are used to model experimental values.

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“…solar radiation, salinity, temperature, pH, and nutrient availability) are almost stable, the assessment of the E.C. concentration can be obtained performing only specific microbiological analyses [13], [14]. Among fecal coliforms, E.C.…”

Section: Introductionmentioning

confidence: 99%

Methodological Approach for the Delimitation of “No Bathing Areas” in Marine Coastal Zones Close to the Outlets of Natural and Artificial Water Courses in Basilicata Region, Italy

Greco

Ungaro²,

Caricato³

et al. 2020

WIT Transactions on Ecology and the Environment

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The Basilicata coasts, both Tyrrhenian and Ionian, are characterised by a considerable number of water courses both natural and artificial, which represent critical points for influence on marine bathing water quality. In such a context, according to the Water Framework Directive (2000/60/EC) and Water Bathing Directive (2006/7/EC), it has been necessary to carry out a systematic water quality check integrating the ordinary monitoring activity lead by the Regional Environmental Protection Agency of Basilicata (ARPAB) in order to provide a preliminary characterization of the marine waters for bathing purposes. The adopted methodological approach suggests to apply a 1-D model for pollutant transport and diffusion/dispersion in water bodies in order to perform a preliminary assessment of the width of the "no bathing area," including the watercourse mouth. Calibration has been provided using episodic data collected in some of the artificial and natural water courses flowing into the Basilicata seas. Moreover, the assessment of the longshore width of these "no bathing areas" is generally aligned with the middle axis of the water course mouths. It has been obtained by simulating the diffusion/dispersion plume using episodic data and systematically collected ones during the bathing seasons, starting from 2011. In such a framework, the model results suggest a differentiation between Ionian and Tyrrhenian coasts due to the local littoral morphology as well as to the natural deltas and artificial outlets. Therefore, in "no bathing areas" of the Ionian coast, the methodological approach proposes a width of 40 m for artificial water course outlets and 100 m for natural water course outlets. However, the proposed "no bathing area" of the Tyrrhenian coast is 20 m wide with only one artificial water course outlet.

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Modelling of Escherichia coli concentrations in bathing water at microtidal coasts

Cited by 23 publications

References 51 publications

Modelling Faba Bean (Vicia faba L.) Biomass Production for Sustainability of Agricultural Systems of Pampas

Modelling Faba Bean (Vicia faba L.) Biomass Production for Sustainability of Agricultural Systems of Pampas

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

Methodological Approach for the Delimitation of “No Bathing Areas” in Marine Coastal Zones Close to the Outlets of Natural and Artificial Water Courses in Basilicata Region, Italy

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