Role of error propagation for integrating multisource data within spatial models: the case of the DRASTIC groundwater vulnerability model

Michelle Fortin; Keith P. B. Thomson; Geoffrey Edwards

doi:10.1117/12.298159

30 December 1997 Role of error propagation for integrating multisource data within spatial models: the case of the DRASTIC groundwater vulnerability model

Michelle Fortin, Keith P. B. Thomson, Geoffrey Edwards

Author Affiliations +

Proceedings Volume 3222, Earth Surface Remote Sensing; (1997) https://doi.org/10.1117/12.298159
Event: Aerospace Remote Sensing '97, 1997, London, United Kingdom

Abstract

As part of our ongoing multisource data research program a groundwater vulnerability model was implemented within Arc/Info^TM, for the Lachute Area, near Montreal in Quebec, Canada. The model used was the DRASTIC model, initially developed in the United States and now recognized by Canadian and American government agencies (Aller et al., 1987). The objective of the present project was to develop an error propagation model for the evaluation of the reliability of the DRASTIC model. DRASTIC uses seven different parameters which influence groundwater vulnerability. These parameters are: depth to water, recharge, aquifer media, soil type, impact of the vadose zone and hydraulic conductivity. Each element is weighted according to its own influence on vulnerability. The DRASTIC index is obtained by the weighted summation of the rating attributed to the different parameters according to the relations incorporated in the DRASTIC model. For a homogeneous area: Index equals D_wD_r plus R_wR_r plus A_wA_r plus S_wS_r plus T_wT_r plus I_wI_r plus C_wC_r where X_w is the weight attributed to each parameter and X_r is the rating attributed to each parameter according to DRASTIC charts. The necessary data used for evaluating each model parameter originates from various sources including point data from drill holes, digitized maps, a digital elevation model and a Landsat TM image classification. As a final product, a vulnerability surface of the area in raster format is obtained. Two different approaches could have been considered for the characterization of error: a stochastic simulation of the model or analytical error propagation. In this paper, the second approach is presented because the DRASTIC type of model contains too many parameters for straightforward simulation.

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Michelle Fortin, Keith P. B. Thomson, and Geoffrey Edwards "Role of error propagation for integrating multisource data within spatial models: the case of the DRASTIC groundwater vulnerability model", Proc. SPIE 3222, Earth Surface Remote Sensing, (30 December 1997); https://doi.org/10.1117/12.298159

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