Remote Sensing (May 2023)

Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process

  • Edgar J. Guerrón-Orejuela,
  • Kai C. Rains,
  • Tyelyn M. Brigino,
  • William J. Kleindl,
  • Shawn M. Landry,
  • Patricia Spellman,
  • Coowe M. Walker,
  • Mark C. Rains

DOI
https://doi.org/10.3390/rs15102630
Journal volume & issue
Vol. 15, no. 10
p. 2630

Abstract

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Understanding where groundwater recharge occurs is essential for managing groundwater resources, especially source-water protection. This can be especially difficult in remote mountainous landscapes where access and data availability are limited. We developed a groundwater recharge potential (GWRP) map across such a landscape based on six readily available datasets selected through the literature review: precipitation, geology, soil texture, slope, drainage density, and land cover. We used field observations, community knowledge, and the Analytical Hierarchy Process to rank and weight the spatial datasets within the GWRP model. We found that GWRP is the highest where precipitation is relatively high, geologic deposits are coarse-grained and unconsolidated, soils are variants of sands and gravels, the terrain is flat, drainage density is low, and land cover is undeveloped. We used GIS to create a map of GWRP, determining that over 83% of this region has a moderate or greater capacity for groundwater recharge. We used two methods to validate this map and assessed it as approximately 87% accurate. This study provides an important tool to support informed groundwater management decisions in this and other similar remote mountainous landscapes.

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