Characterizing Heterogeneity in Infiltration Rates During Managed Aquifer Recharge |
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| Authors: | Chloe Mawer Andrew Parsekian Adam Pidlisecky Rosemary Knight |
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| Institution: | 1. Engineering Research Center for Re‐Inventing the Nation's Urban Water Infrastructure (ReNUWIt), National Science Foundation, Stanford, CA 94305;2. Geology and Geophysics, University of Wyoming, Laramie, WY 82071;3. Civil and Architectural Engineering, University of Wyoming, Laramie WY 82071;4. Geosciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada;5. Geophysics, Stanford University, Stanford, CA 94305 |
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| Abstract: | Infiltration rate is the key parameter that describes how water moves from the surface into a groundwater aquifer during managed aquifer recharge (MAR). Characterization of infiltration rate heterogeneity in space and time is valuable information for MAR system operation. In this study, we utilized fiber optic distributed temperature sensing (FO‐DTS) observations and the phase shift of the diurnal temperature signal between two vertically co‐located fiber optic cables to characterize infiltration rate spatially and temporally in a MAR basin. The FO‐DTS measurements revealed spatial heterogeneity of infiltration rate: approximately 78% of the recharge water infiltrated through 50% of the pond bottom on average. We also introduced a metric for quantifying how the infiltration rate in a recharge pond changes over time, which enables FO‐DTS to be used as a method for monitoring MAR and informing maintenance decisions. By monitoring this metric, we found high‐spatial variability in how rapidly infiltration rate changed during the test period. We attributed this variability to biological pore clogging and found a relationship between high initial infiltration rate and the most rapid pore clogging. We found a strong relationship (R2 = 0.8) between observed maximum infiltration rates and electrical resistivity measurements from electrical resistivity tomography data taken in the same basin when dry. This result shows that the combined acquisition of DTS and ERT data can improve the design and operation of a MAR pond significantly by providing the critical information needed about spatial variability in parameters controlling infiltration rates. |
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