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UBC Theses and Dissertations

Quantifying drainage basin comparisons within a knowledge-based system framework Cheong, Anthony Leonard


Because of the subjectivity in previous methods of drainage basin comparisons, there is a need to quantify such procedures. This is in order to be make objective comparisons and to transfer results among different studies. Quantification is best effected within the framework of a knowledge-based system. Three types of drainage basin characteristics may be identified: morphometric, biogeophysical and historical. These data exist in nominal, ordinal, interval and ratio form. Quantification of morphometric information appears to be the most straightforward and should probably play a dominant role in any similarity comparison as many processes are related to these characteristics. These variables can be analysed using a procedure which incorporates alllevels of information; nominal and ordinal information are used as filters while interval and ratio information are used to calculate dissimilarity—a form of euclidean distance measure. Because much of this information is available in digital form—morphometry from digital terrain models, for example—the similarity procedure is best developed within a knowledge-based system framework. With the use of a pseudo-relational information base and search procedures formalised through artificial intelligence theory, knowledge can be stored within the system and used to effect the analysis. Thirty one characteristics are measured of 65 drainage basins in the Queen Charlotte Islands, British Columbia. Dissimilarities between the basins are calculated for both untransformed and transformed information. Because of the non-normality of variables, the tests are carried out on both sets of information to assess the robustness of the various statistical procedures. Two tests are performed:

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