Three-dimensional characterization of caves within the Grand Canyon's deep karst aquifer.

Saved in:
Bibliographic Details
Title: Three-dimensional characterization of caves within the Grand Canyon's deep karst aquifer.
Authors: LaSala, Blase, Sankey, Temuulen Tsagaan, Nebel, Mark, Springer, Abraham E., Mildice, Aria
Source: Scientific Reports; 8/30/2025, Vol. 15 Issue 1, p1-10, 10p
Subject Terms: KARST hydrology, LIDAR, STRUCTURAL geology, THREE-dimensional modeling, KARST, GEOLOGIC faults, GROUNDWATER flow
Geographic Terms: GRAND Canyon National Park (Ariz.), GRAND Canyon (Ariz.)
Abstract: Understanding groundwater movement within karst aquifers remains challenging because flow-defining conduit and fracture networks are both complex and inaccessible. In Grand Canyon National Park, dye tracers have been used to establish flow paths for springs that support ecosystems and park operations. Unfortunately, these point-to-point studies are limited when attempting to extrapolate flow paths over thousands of square kilometers. We introduce a mobile lidar-based methodology that resolves groundwater flow-defining structures from actively-discharging stream caves within the aquifer. This methodology enabled efficient collection of centimeter-scale 3D data from over 10 km of remote caves from the Redwall (Mississippian) and Muav (Cambrian) limestones in the North Rim of the Grand Canyon. Our methodology achieved total compounding errors of less than 0.5% and shows strong agreement with traditional cave maps. We find geologic structures exposed within these caves are consistent across kilometers of cave passages, indicating groundwater flow exploits joint sets and bedding dip direction. These patterns suggest that present-day flow paths within the North Rim of Grand Canyon National Park are, in part, a product of regional faulting and uplift. This lidar-derived structural characterization enables karst network flow pattern identification that would be otherwise unavailable from traditional methods. [ABSTRACT FROM AUTHOR]
Copyright of Scientific Reports is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Be the first to leave a comment!
You must be logged in first