DEVELOPMENT AND EVALUATION OF TECHNIQUES FOR HYDROCLIMATOLOGICAL CHARACTERIZATION

Abstract

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.