With increasing model complexity there is a pressing need for new methods that can be used to mine information from large volumes of model results and available data. This work explores strategies to identify and evaluate the causes of discrepancy between models and data related to hydrologic processes, and to increase our knowledge about watershed input-output relationships. In this context, we evaluate the performance of the abcd monthly water balance model for 764 watersheds in the conterminous United States. The work required integration of the Hydro-Climatic Data Network dataset with various kinds of spatial information, and a diagnostic approach to relating model performance with assumptions and characteristics of the basins. The diagnostic process was implemented via classification of watersheds, evaluation of hydrologic signatures and the identification of dominant processes. Knowledge acquired during this process was used to test modifications of the model for hydrologic regions where the performance was "poor".

Human alteration of the landscape for agricultural and urban land use has been linked to the degradation of streams and stream biota. Natural physical and climatic characteristics, or physiographic template, are important for determining natural land cover and constraining human land use, and are strongly related to stream habitat and stream biotic assemblages. Since the physiographic template differs among watersheds and is an important determinant of the processes being studied, it is important to account for these natural differences among watersheds so that the relationship between land cover and streams can be properly understood. The purpose of this thesis is to develop and assess the utility of a regional framework that classifies watersheds based on physical and climatic predictors of land cover. In Chapter 1, I identified physical and climatic predictors of land cover and classified watersheds into Land cover Distinguished Physiographic Regions (LDPRs) based on these predictors. I was able to identify and create classes based off eight climatic and landform characteristics that determined natural land cover and human land use patterns for both the Eastern and Western U.S. In Chapter 2, I utilized LDPRs to stratify a study region and investigated whether the relationships between land cover and stream fish assemblages varied between these regions. Five commonly used metrics covering trophic, reproductive and taxonomic groupings showed significant variation in their response to agricultural land use across LDPRs. The results suggest that the physiographic differences among LDPRs can result in different pathways by which land cover alterations impact stream fish communities. Unlike other commonly used regional frameworks, the rationale and methods used to develop LDPRs properly accounts for the causal relationship between physiography and land cover. Therefore, I recommend the use of LDPRs as a tool for stratifying watersheds based on physiography in future investigations so that the processes by which human land use results in stream degradation can be understood. / Master of Science

Twelve stream segments in the Silvies River drainage system were classified in the fall of 1993 and again in 1994, using a morphological classification of natural rivers (Rosgen 1994). Bankfull flow of stream channels is the key feature of this system. Measurement of bankfull is used in the calculation of entrenchment ratio and width/depth ratio. Analysis of the differences of the averages between years in bankfull measurements showed that despite being consistently repeated at the same locations along the channel, the measurements were found to be different (p=0.000163 for entrenchment ratios and p = 0.0208 for width/depth ratios). Bankfull was found to be a non-repeatable field measure, therefore, a poor benchmark for a classification scheme. Historical information collected for the study area indicated a history of domestic livestock use that dates back as far as the mid-nineteenth century. Although grazed by livestock for several years, settlement of the Bear and Silvies Valleys occurred mostly around the turn of the twentieth century after the stockgrower's homestead acts were passed. Ownership today is dominated by large (relative to the homestead days) ranches. / Graduation date: 1996

This master’s thesis is focused on automating the process of differential leukocyte count in peripherial blood using image processing. It deals with the design of the processing of digital images - from scanning and image preprocessing, segmentation nucleus and cytoplasm, feature selection and classifier, including testing on a set of images that were scanned in the context of this work. This work introduces used segmentation methods and classification procedures which separate nucleus and the cytoplasm of leukocytes. A statistical analysis is performed on the basis of these structures. Following adequate statistical parameters, a set of features has been chosen. This data then go through a classification process realized by three artificial neural networks. Overall were classified 5 types of leukocytes: neutropfiles, lymphocytes, monocytes, eosinophiles and basophiles. The sensitivity and specificity of the classification made for 4 out of 5 leukocyte types (neutropfiles, lymphocytes, monocytes, eosinophiles) is higher than 90 %. Sensitivity of classiffication basophiles was evaluated at 75 % and specificity at 67 %. The total ability of classification has been tested on 111 leukocytes and was approximately 91% successful. All algorithms were created in the MATLAB program.