کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4576633 1629972 2013 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
The multivariate statistical structure of DRASTIC model
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
The multivariate statistical structure of DRASTIC model
چکیده انگلیسی

SummaryAn assessment of aquifer intrinsic vulnerability was conducted in the Sordo river basin, a small watershed located in the Northeast of Portugal that drains to a lake used as public resource of drinking water. The method adopted to calculate intrinsic vulnerability was the DRASTIC model, which hinges on a weighted addition of seven hydrogeologic features, but was combined with a pioneering approach for feature reduction and adjustment of feature weights to local settings, based on a multivariate statistical method. Basically, with the adopted statistical technique-Correspondence Analysis-one identified and minimized redundancy between DRASTIC features, allowing for the calculation of a composite index based on just three of them: topography, recharge and aquifer material. The combined algorithm was coined vector-DRASTIC and proved to describe more realistically intrinsic vulnerability than DRASTC. The proof resulted from a validation of DRASTIC and vector-DRASTIC by the results of a groundwater pollution risk assessment standing on the spatial distribution of land uses and nitrate concentrations in groundwater, referred to as [NO3-]-DRASTIC method. Vector-DRASTIC and [NO3-]-DRASTIC portray the Sordo river basin as an environment with a self-capability to neutralize contaminants, preventing its propagation downstream. This observation was confirmed by long-standing low nitrate concentrations in the lake water and constitutes additional validation of vector-DRASTIC results. Nevertheless, some general recommendations are proposed in regard to agriculture management practices for water quality protection, as part of an overall watershed approach.


► Neutralize redundancy between DRASTIC features using multivariate statistics.
► Automatically adjust DRASTIC feature weights to local settings.
► Validate a pioneering method of vulnerability mapping with pollution risk assessment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 476, 7 January 2013, Pages 442–459
نویسندگان
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