HR: 09:15h
AN: H41I-06    [Abstracts]
TI: Fractal Interpolation and Monte Carlo Simulations to Address Aliasing in Well Hydrographs
AU: * Evans, D G
EM: dave_evans@csus.edu
AF: California State University, Department of Geology 6000 J Street, Sacramento, CA 95819-6043, United States
AU: Anderson, W P
EM: andersonwp@appstate.edu
AF: Appalachian State University, Department of Geology, Boone, NC 28608-2067, United States
AB: Calibrating transient models to time-series observations is a challenge in many aspects of hydrology due to incomplete or inadequate time-series data. For example, when calibrating groundwater models to well hydrographs researchers must account for a time scales ranging from minutes to years. In such cases, aliasing is an inherent problem because it is often impractical to measure water levels in wells for extended periods of time at a rate greater than the highest-frequency stress on the aquifer. (Aliasing refers to spurious low-frequency components of a signal introduced by an inadequate sampling rate.) To address the aliasing problem for well hydrographs it is necessary to interpolate water level data so that sufficiently high frequency components are present in the calibration signal. This can be achieved using Monte Carlo simulations in which stochastic hydrographs are generated that (1) match the data points on the observed (low frequency) hydrograph, and (2) have a fractal dimension consistent with that of the observed time series. We tested the inversion method by generating synthetic recharge signals to generate synthetic water-table hydrographs. Because the method works well with the synthetic data, we have applied these methods to water- table hydrographs measured on Hatteras Island, North Carolina.
DE: 1829 Groundwater hydrology
DE: 1839 Hydrologic scaling
DE: 1847 Modeling
DE: 1872 Time series analysis (3270, 4277, 4475)
SC: Hydrology [H]
MN: 2007 Fall Meeting