Maps of runoff-depth have been found to be useful tools in a variety of water resource applications. Producing such maps can be a challenging and expensive task. One of the standard methods of producing these maps is to use a manual procedure based on gaged runoff data, topographic and past runoff-depth maps, and the expert opinion of hydrologists. This thesis examined five new automated procedures for producing runoff-depth contour maps to see if the maps produced by these procedures had similar accuracy and characteristics when compared to the manual procedure. An uncertainty analysis was used to determine the accuracy of the automated procedure maps by withholding gaged runoff data from the creation of the contour maps and then interpolating estimated runoff back to these sites from the maps produced. Subtracting gaged runoff from estimated runoff produced interpolation error values. The mean interpolation error was used to define the accuracy of each map and was then compared to a similar study by Rochelle, et al., (1989) conducted on a manual procedure map.

The development and rapid growth of computer mapping has led to many discussions concerning the accuracy of techniques used to generate these computer representations. The purpose of this study is to analyze the accuracy of thinning methods applied to scanned map data, which is only one in a series of processes used to accomplish digital conversion of conventional maps. In preliminary tests, nine thinning methods based on the successive layer removal process are evaluated. Seven raster images are thinned using these methods. The raster results are compared based on the number of pixels deleted and on the number of retained pixels that fall either on or off the medial axis of the original matrix. The four algorithms that produce the best results are then used for final testing. For the final tests, 25 digital lines are plotted and scanned. The raster images are thinned using the four successive layer removal methods and a line following method developed for this study. The raster output is evaluated using the preliminary testing method. The final vector output is compared to the original input based on line length, anchor line length, and fractal dimension. / Master of Science

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