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oai:drum.lib.umd.edu:1903/350402026-01-27T08:47:08Zcom_1903_2243com_1903_12com_1903_2col_1903_2774col_1903_3

Prestegaard, Karen L Lastner, Alexander Joseph Digital Repository at the University of Maryland University of Maryland (College Park, Md.) Geology 2026-01-27T06:36:33Z 2025 https://doi.org/10.13016/zzlh-oahq http://hdl.handle.net/1903/35040 Hydrologic systems comprise many interacting components, making it difficult to predict how hydroclimatological change will impact water balance components. Techniques are needed that can better characterize hydroclimatology and its influence on water partitioning without requiring extensive records in a stationary climate. First, I devise a temporal concentration index (TCI) for quantifying the clustering of precipitation events in time and compare it to other indices used to quantify the temporal organization of precipitation. TCI can resolve both seasonal and non-seasonal clustering of precipitation, and trends in TCI correspond to trends in 7-day low flow across eastern CONUS. Next, I investigate minimum delay embedding dimension (De) of streamflow: a nonlinear metric of complexity hypothesized to reflect the form of precipitation generating runoff. Although streamflow De negatively correlates with fraction of precipitation as snow, I argue that the usefulness of De for characterizing basin hydroclimatology has yet to exceed conventional approaches. en DEVELOPMENT AND EVALUATION OF TECHNIQUES FOR HYDROCLIMATOLOGICAL CHARACTERIZATION Thesis Hydrologic sciences Atmospheric sciences Climate change Hydroclimatology Index evaluation Nonlinear analysis Precipitation Streamflow Temporal organization embargo