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An automated toolkit for hyetograph-hydrograph analysis

Understanding the nature of streamflow response to precipitation inputs is at the core of applied hydrological applications such as flood forecasting and water resource management. Indices such as the runoff ratio, recession constant and response time of a watershed retain an important place in hydrology decades after their establishment as metrics to compare watersheds and understand the impact of human activity, geology, geomorphology, soils and climate on precipitation-runoff relations. Extracting characteristics of the hyetograph-hydrograph relationship is often done manually, resulting in subjective and inconsistent results that require considerable time. In addition, there are a large number of metrics proposed to analyze the hyetograph-hydrograph relationship and hydrograph shape that are typically subjective in application. The objective of this research is to develop an automated and flexible toolkit for rainfall-runoff analysis. Using the MATLAB language, a series of inter-related functions are created to extract rainfall-runoff events from time-series of rainfall and streamflow data and compute commonly used characteristics of the hyetograph-hydrograph relationship. Furthermore, a number of input parameters are introduced to add flexibility to the toolkit. This toolkit has been applied successfully to four watersheds in Canada and Scotland. A subsequent analysis was performed assessing the sensitivity of parameter selection on the toolkit performance, and a number of suggestions for users provided. It is anticipated that this toolkit will provide hydrologists with a rapid objective method of analyzing rainfall and runoff data where in the past manual procedures resulted in considerable subjectivity in results. / Thesis / Master of Science (MSc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/16443
Date19 November 2014
CreatorsTang, Weigang
ContributorsCarey, Sean, Geography
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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