Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Contamination Predictive Model for Escherichia coli in Rural Communities Dug Shallow Wells
In Brazilian rural communities, the lack of treated water leads their residents to seek individual and alternative solutions, in which dug shallow wells (DSW) are quite widespread. However, water quality may not be fitted for human consumption. For this reason, the current study aimed to predict the contamination of DSW water in rural communities in the Brazilian state of Goiás. For this, secondary data related to water quality, the distance to possible contamination sources, structural conditions, and local geology were evaluated. Therefore, a generalized linear model was applied, and its predictors were evaluated by stepwise methods (Akaike information criterion—AIC and Bayesian information criterion—BIC), generating an intermediate model. After the analysis, turbidity parameter was chosen to be removed resulting in a final, submitted to leave-one-out cross-validation method, and its performance was measured by a confusion matrix. The final model resulted in four predictive variables: well diameter, contour paving width, poultry, and swine husbandry existence. The model accuracy was 82.61%, with a true positive predictor of 82.18% and a negative predictor of 85.71%.
A Contamination Predictive Model for Escherichia coli in Rural Communities Dug Shallow Wells
In Brazilian rural communities, the lack of treated water leads their residents to seek individual and alternative solutions, in which dug shallow wells (DSW) are quite widespread. However, water quality may not be fitted for human consumption. For this reason, the current study aimed to predict the contamination of DSW water in rural communities in the Brazilian state of Goiás. For this, secondary data related to water quality, the distance to possible contamination sources, structural conditions, and local geology were evaluated. Therefore, a generalized linear model was applied, and its predictors were evaluated by stepwise methods (Akaike information criterion—AIC and Bayesian information criterion—BIC), generating an intermediate model. After the analysis, turbidity parameter was chosen to be removed resulting in a final, submitted to leave-one-out cross-validation method, and its performance was measured by a confusion matrix. The final model resulted in four predictive variables: well diameter, contour paving width, poultry, and swine husbandry existence. The model accuracy was 82.61%, with a true positive predictor of 82.18% and a negative predictor of 85.71%.
A Contamination Predictive Model for Escherichia coli in Rural Communities Dug Shallow Wells
Hítalo Tobias Lôbo Lopes (Autor:in) / Luis Rodrigo Fernandes Baumann (Autor:in) / Paulo Sérgio Scalize (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Locating Escherichia coli contamination in a rural South Carolina watershed
Online Contents | 2007
Evaluation of methods for diagnosing contamination in rural wells
| Tema Archiv | 1998
| Wiley | 1925
Simple Technology of Shallow Wells
| Taylor & Francis Verlag | 1983