Saved in:
| Main Author: | |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidad Nacional Autónoma de México
2004
|
| Subjects: | |
| Online Access: | https://www.redalyc.org/articulo.oa?id=56843404 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- Aquifer vulnerability mapping and GIS: A proposal to monitor uncertainty associated with spatial data processing Valérie Murat Alfonso Rivera Jacynthe Pouliot Marcelo Miranda Salas Martine M. Savard Ciencias de la Tierra GIS DRASTIC model groundwater resources Uncertainty monitoring vulnerability analysis An aquifer assessment was undertaken by the Geological Survey of Canada to estimate the sustainability and aquifer vulnerabilityin the St. Lawrence Lowlands of south western Quebec. The DRASTIC model and GIS was used to calculate and producevulnerability maps. A detailed monitoring of data processing was performed to control the accuracy of the vulnerability maps.Overall estimates involved identifying errors and uncertainty associated with spatial and descriptive data used to run the model.The data analysed was related to wells, drillings, thematic maps, and also multiple processing data including errors and uncertaintyattributed to calculations of the hydraulic conductivity, data interpolations, intersections of spatial data layers, etc. A categorizationsystem using the Unified Modeling Language (UML) was proposed to categorize spatial data with respect to the degreeand sources of possible uncertainties. This article presents the categorization system used, an example of an application for anstudy area and a discussion around its usefulness in controlling data processing (GIS and model integration). This work shows thatuncertainty associated with spatial data processing and integrating data to a numerical system can be very significant, the mainambiguity occurring when cleaning data, interpolating, classifying and overlaying. Uncertainty characterization on the data processeswas a valuable source of information. Monitoring the uncertainty associated with spatial data processing is almost moreimportant to assemble than the model itself. However uncertainty monitoring may be complex and subjective and in fact it israrely done on a regular basis mainly because it requires much more efforts compare to simply running the model. 2004 artículo científico 0016-7169 https://www.redalyc.org/articulo.oa?id=56843404 en http://www.redalyc.org/revista.oa?id=568 Geofísica Internacional application/pdf Universidad Nacional Autónoma de México Geofísica Internacional (México) Num.4 Vol.43