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Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment

Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment
Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment

Statistical techniques can be used in groundwater pollution problems to determine the relationships among observed contamination (impacted wells representing an occurrence of what has to be predicted), environmental factors that may influence it and the potential contamination sources. Determination of a threshold concentration to discriminate between impacted or non impacted wells represents a key issue in the application of these techniques. In this work the effects on groundwater vulnerability assessment by statistical methods due to the use of different threshold values have been evaluated. The study area (Province of Milan, northern Italy) is about 2000 km2 and groundwater nitrate concentration is constantly monitored by a net of about 300 wells. Along with different predictor factors three different threshold values of nitrate concentration have been considered to perform the vulnerability assessment of the shallow unconfined aquifer. The likelihood ratio model has been chosen to analyze the spatial distribution of the vulnerable areas. The reliability of the three final vulnerability maps has been tested showing that all maps identify a general positive trend relating mean nitrate concentration in the wells and vulnerability classes the same wells belong to. Then using the kappa coefficient the influence of the different threshold values has been evaluated comparing the spatial distribution of the resulting vulnerability classes in each map. The use of different threshold does not determine different vulnerability assessment if results are analyzed on a broad scale, even if the smaller threshold value gives the poorest performance in terms of reliability. On the contrary, the spatial distribution of a detailed vulnerability assessment is strongly influenced by the selected threshold used to identify the occurrences, suggesting that there is a strong relationship among the number of identified occurrences, the scale of the maps representing the predictor factors and the model efficiency in discriminating different vulnerable areas.

Groundwater vulnerability assessment, Milan, Nitrate, Statistical method, Threshold
0048-9697
3836-3846
Masetti, Marco
c3d261b3-da8c-4040-8fea-bc4389542c42
Sterlacchini, Simone
0704090e-e01f-49f7-b19b-4d5f4a2661c8
Ballabio, Cristiano
6cd34adb-9ab2-4b39-a0c4-e5ddbd398071
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
Poli, Simone
5bbc18ad-1b8a-4655-bff1-394af8edab4a
Masetti, Marco
c3d261b3-da8c-4040-8fea-bc4389542c42
Sterlacchini, Simone
0704090e-e01f-49f7-b19b-4d5f4a2661c8
Ballabio, Cristiano
6cd34adb-9ab2-4b39-a0c4-e5ddbd398071
Sorichetta, Alessandro
c80d941b-a3f5-4a6d-9a19-e3eeba84443c
Poli, Simone
5bbc18ad-1b8a-4655-bff1-394af8edab4a

Masetti, Marco, Sterlacchini, Simone, Ballabio, Cristiano, Sorichetta, Alessandro and Poli, Simone (2009) Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment. Science of the Total Environment, 407 (12), 3836-3846. (doi:10.1016/j.scitotenv.2009.01.055).

Record type: Article

Abstract

Statistical techniques can be used in groundwater pollution problems to determine the relationships among observed contamination (impacted wells representing an occurrence of what has to be predicted), environmental factors that may influence it and the potential contamination sources. Determination of a threshold concentration to discriminate between impacted or non impacted wells represents a key issue in the application of these techniques. In this work the effects on groundwater vulnerability assessment by statistical methods due to the use of different threshold values have been evaluated. The study area (Province of Milan, northern Italy) is about 2000 km2 and groundwater nitrate concentration is constantly monitored by a net of about 300 wells. Along with different predictor factors three different threshold values of nitrate concentration have been considered to perform the vulnerability assessment of the shallow unconfined aquifer. The likelihood ratio model has been chosen to analyze the spatial distribution of the vulnerable areas. The reliability of the three final vulnerability maps has been tested showing that all maps identify a general positive trend relating mean nitrate concentration in the wells and vulnerability classes the same wells belong to. Then using the kappa coefficient the influence of the different threshold values has been evaluated comparing the spatial distribution of the resulting vulnerability classes in each map. The use of different threshold does not determine different vulnerability assessment if results are analyzed on a broad scale, even if the smaller threshold value gives the poorest performance in terms of reliability. On the contrary, the spatial distribution of a detailed vulnerability assessment is strongly influenced by the selected threshold used to identify the occurrences, suggesting that there is a strong relationship among the number of identified occurrences, the scale of the maps representing the predictor factors and the model efficiency in discriminating different vulnerable areas.

Full text not available from this repository.

More information

Accepted/In Press date: 22 January 2009
e-pub ahead of print date: 5 April 2009
Published date: 1 June 2009
Keywords: Groundwater vulnerability assessment, Milan, Nitrate, Statistical method, Threshold

Identifiers

Local EPrints ID: 433081
URI: http://eprints.soton.ac.uk/id/eprint/433081
ISSN: 0048-9697
PURE UUID: 6679f2e1-8feb-4142-882b-08c57b663e10
ORCID for Alessandro Sorichetta: ORCID iD orcid.org/0000-0002-3576-5826

Catalogue record

Date deposited: 07 Aug 2019 16:30
Last modified: 17 Dec 2019 01:35

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