HR: 0800h
AN: H41E-0463    [Abstracts]
TI: Numerical Simulations of River Stage/Precipitation Tomography
AU: * Xiang, J
EM: xjw@hwr.arizona.edu
AF: University of Arizona, Department of Hydrology and Water Resources 1133 E. North Campus Drive Harshbarger Bldg., Tucson, az 85721 United States
AU: Yeh, T J
EM: ybiem@mac.hwr.arizona.edu
AF: University of Arizona, Department of Hydrology and Water Resources 1133 E. North Campus Drive Harshbarger Bldg., Tucson, az 85721 United States
AB: Inverse modeling is an ultimate quantitative approach for characterizing parameters of watershed or basin-scale hydrologic models. Tomographic surveys make an inverse problem better posed because each survey cross-validates the others so that the modeling result approaches reality. Tomographic surveys using different types of energy provide coverage and perspectives of a watershed or basin at difference scales. Fusion of different tomographic surveys expands and enhances the capability of a particular type of survey, provides cross-validation, and drives new sampling strategies. Watershed or basin scale tomographic surveys require energy sources of great strengths. Spatially and temporally varying natural stimuli (i.e., precipitation, barometric pressure, river stage, lightning, earthquakes, etc.) are ideal energy sources for this purpose. In this study, we explore the possibility of using spatial and temporal variations in precipitation and river stages as energy sources of basin-scale subsurface tomographic surveys. Specifically, we use numerical models to simulate effects of spatial and temporal variations in precipitation and river stage on groundwater responses in a hypothetical groundwater basin. Our successive linear estimator, an iterative geostatistical inverse model, then exploits the relation between temporal and spatial variations of well hydrographs and precipitation or river stage to image subsurface heterogeneity in groundwater basins. The results are encouraging. The concept of using naturally recurrent stimuli for characterizing groundwater basin or calibrating a groundwater model may be the future of geohydrology.
DE: 1800 HYDROLOGY
DE: 1829 Groundwater hydrology
DE: 1869 Stochastic hydrology
SC: Hydrology [H]
MN: Fall Meeting 2005