TY - JOUR
T1 - A multi-hydrogeophysical study of a watershed at Kaiwi Coast (Oʻahu, Hawaiʻi), using seismic ambient noise surface wave tomography and self-potential data
AU - Grobbe, Niels
AU - Mordret, Aurélien
AU - Barde-Cabusson, Stéphanie
AU - Ellison, Lucas
AU - Lach, Mackenzie
AU - Seo, Young Ho
AU - Viti, Taylor
AU - Ward, Lauren
AU - Zhang, Haozhe
N1 - Publisher Copyright:
© 2021. The Authors.
PY - 2021/4
Y1 - 2021/4
N2 - We study a watershed containing an old stream valley at the Kaiwi Coast on Oʻahu, Hawaiʻi. The study site has undergone significant hydrogeological changes throughout its history, and at present displays complex interactions of a variety of geological formations. We highlight an innovative and efficient combination of two hydrogeophysical methodologies for studying groundwater systems: ambient noise surface wave tomography (ANSWT), and self-potential (SP) measurements. We collected (1) 5 days of continuous seismic data, using a total of 54 autonomous seismic nodes, exploiting both ocean wave and traffic noise sources and (2) 386 SP measurements with an average 20 m spacing, in the same area. We showcase how these two data sets complement each other in a joint-interpretation framework. The SP data display the distribution of groundwater in the region, as well as zones of higher infiltration and/or flow rates. Using ANSWT, we identify the structural contact between the older Koʻolau basalt formation and the younger post-erosional Honolulu volcanics, as well as the distribution of sedimentary valley fill and coastal deposits. The joint interpretation of the SP and seismic data clearly illustrates that groundwater flow occurs in the identified paleo-channels at the erosional surface of the basaltic bedrock. Furthermore, it highlights that the basaltic bedrock of the ridges likely forms an important groundwater flow unit. Some flow may occur in the shallower valley fill material. Complementing SP data with seismic data enables us to place groundwater flow inferences, as made from SP data, at depth.
AB - We study a watershed containing an old stream valley at the Kaiwi Coast on Oʻahu, Hawaiʻi. The study site has undergone significant hydrogeological changes throughout its history, and at present displays complex interactions of a variety of geological formations. We highlight an innovative and efficient combination of two hydrogeophysical methodologies for studying groundwater systems: ambient noise surface wave tomography (ANSWT), and self-potential (SP) measurements. We collected (1) 5 days of continuous seismic data, using a total of 54 autonomous seismic nodes, exploiting both ocean wave and traffic noise sources and (2) 386 SP measurements with an average 20 m spacing, in the same area. We showcase how these two data sets complement each other in a joint-interpretation framework. The SP data display the distribution of groundwater in the region, as well as zones of higher infiltration and/or flow rates. Using ANSWT, we identify the structural contact between the older Koʻolau basalt formation and the younger post-erosional Honolulu volcanics, as well as the distribution of sedimentary valley fill and coastal deposits. The joint interpretation of the SP and seismic data clearly illustrates that groundwater flow occurs in the identified paleo-channels at the erosional surface of the basaltic bedrock. Furthermore, it highlights that the basaltic bedrock of the ridges likely forms an important groundwater flow unit. Some flow may occur in the shallower valley fill material. Complementing SP data with seismic data enables us to place groundwater flow inferences, as made from SP data, at depth.
KW - groundwater
KW - hydrogeophysics
KW - seismic ambient noise surface wave tomography
KW - self-potential
KW - volcanic islands
KW - water resources
UR - http://www.scopus.com/inward/record.url?scp=85105766259&partnerID=8YFLogxK
U2 - 10.1029/2020WR029057
DO - 10.1029/2020WR029057
M3 - Article
AN - SCOPUS:85105766259
SN - 0043-1397
VL - 57
JO - Water Resources Research
JF - Water Resources Research
IS - 4
M1 - e2020WR029057
ER -