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This file includes the data published in: Malenda, H.F., Sutfin, N.A., Stauffer, S., Guryan. G., Rowland, J.C., Williams, K.H., and Singha, K. (2019). From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology, geophysics, and remote sensing. Earth Surface and Planetary Landforms, doi:10.1002/esp.4613.
Floodplain stratigraphy, a major structural element of alluvial aquifers, is a fundamental component of floodplain heterogeneity, hydraulic conductivity, and connectivity. Watershed-scale hydrological models often simplify floodplains by modeling them as largely homogeneous, which inherently overlooks natural floodplain heterogeneity and anisotropy and their effects on hydrologic processes such as groundwater flow and transport and hyporheic exchange. This study, conducted in the East River Basin, Colorado, USA, combines point-, meander-, and floodplain-scale data to explore the importance of detailed field studies and physical representation of alluvial aquifers. We combine sediment core descriptions, hydraulic conductivity estimates from slug tests, ground-penetrating radar (GPR), historical maps of former channels, LiDAR-based elevation and Normalized Difference Vegetation Index data to infer 3-D fluvial stratigraphy. We compare and contrast stratigraphy of two meanders with disparate geometries to explore floodplain heterogeneity and connectivity controls on flow and transport. We identify buried point bars, former channels, and overbank deposits using GPR, corroborated by point sediment descriptions collected during piezometer installment and remotely sensed products. We map heterogeneous structural features that should control resultant flow and transport; orientation and connectivity of these features would control residence times important in hydrologic models.
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Malenda, H.F., Sutfin, N.A., Stauffer, S., Guryan. G., Rowland, J.C., Williams, K.H., and Singha, K. (2019). From Grain to Floodplain: Evaluating heterogeneity of floodplain hydrostatigraphy using sedimentology, geophysics, and remote sensing. Earth Surface and Planetary Landforms, doi:10.1002/esp.4613.
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National Science Foundation
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The U.S. Department of Energy (DOE), Office of Science, Office of Biological Env. Research (BER)
Comments
Jackie Randell 5 years, 4 months ago
Remote Sensing Data owned by Los Alamos National Laboratory (LANL)
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