HR: 0800h
AN: H21F-1095    [Abstracts]
TI: Using Spectral Analysis to Relate Climate and Land-Use Changes to Processes Influencing Stream Flow
AU: * Kendall, A D
EM: kendal30@msu.edu
AF: Department of Geological Sciences, 206 Natural Sciences Michigan State University, East Lansing, MI 48824 United States
AU: Hyndman, D W
EM: hyndman@msu.edu
AF: Department of Geological Sciences, 206 Natural Sciences Michigan State University, East Lansing, MI 48824 United States
AU: Phanikumar, M S
EM: phani@msu.edu
AF: Department of Geological Sciences, 206 Natural Sciences Michigan State University, East Lansing, MI 48824 United States
AU: Pijanowski, B C
EM: bpijanow@purdue.edu
AF: Department of Frestry and Natural Resources, 195 Marsteller Street Purdue University, West Lafayette, IN 47907 United States
AB: Stream flows are influenced by changes in both climate and land use. Understanding these factors is essential to accurately predict changes in future water resources. For instance, large-scale urbanization, reforestation, and climatic cycles alter peak, mean, and minimum annual flows-three key stream behavior indicators. Analyses of long-term hydrograph data in Michigan have revealed distinct trends in these indicators. For instance, in several regional Michigan watersheds, mean and minimum flows have increased over the last 70 years while peak flows have declined. These indicators, as well as the precise shape of the hydrographs, are governed by the interplay of hydrologic processes influenced by climate and land-use. Efforts at interpreting hydrographs often focus on characteristics of hydrograph peaks and recession curves and on extracting baseflow contributions from groundwater. These methods are all are limited by the complexities of the processes involved, as well as by the fact that some changes that may be ascribed to land-use effects rather than competing climatic effects. Spectral analysis can extract information about processes that influence stream flow by transforming time-series data into the frequency domain via algorithms such as the Fast Fourier Transform (FFT) or wavelet analyses. In this study, spectral analysis is performed on stream flow, precipitation, and groundwater head data from two regional watersheds in Michigan. The fluctuations in the forcing functions of stream flow, precipitation and groundwater, are then related to the stream flow spectrum. Additionally, climatic cycles, trends, and land-use change data from a Land-Transformation Model (LTM) are incorporated in order to explain super-annual trends in the spectral data.
DE: 1803 Anthropogenic effects
DE: 1829 Groundwater hydrology
DE: 1860 Runoff and streamflow
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting