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

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

doi:10.3390/rs15102630

Open AccessArticle

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

by

Edgar J. Guerrón-Orejuela

^1,*

,

Kai C. Rains

¹,

Tyelyn M. Brigino

¹,

William J. Kleindl

²,

Shawn M. Landry

¹,

Patricia Spellman

¹,

Coowe M. Walker

^3,4 and

Mark C. Rains

¹

School of Geosciences, University of South Florida, Tampa, FL 33620, USA

²

Land Resources and Environmental Sciences, Montana State University, Bozeman, MT 59717, USA

³

Kachemak Bay National Estuarine Research Reserve, Homer, AK 99603, USA

⁴

Alaska Center for Conservation Science, University of Alaska, Anchorage, AK 99508, USA

^*

Author to whom correspondence should be addressed.

Remote Sens. 2023, 15(10), 2630; https://doi.org/10.3390/rs15102630

Submission received: 14 April 2023 / Revised: 12 May 2023 / Accepted: 16 May 2023 / Published: 18 May 2023

(This article belongs to the Special Issue Remote Sensing Approaches to Groundwater Management and Mapping)

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Abstract

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.

Keywords: Alaska; Analytic Hierarchy Process (AHP); GIS; groundwater mapping; Kenai lowlands; recharge

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MDPI and ACS Style

Guerrón-Orejuela, E.J.; Rains, K.C.; Brigino, T.M.; Kleindl, W.J.; Landry, S.M.; Spellman, P.; Walker, C.M.; Rains, M.C. Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process. Remote Sens. 2023, 15, 2630. https://doi.org/10.3390/rs15102630

AMA Style

Guerrón-Orejuela EJ, Rains KC, Brigino TM, Kleindl WJ, Landry SM, Spellman P, Walker CM, Rains MC. Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process. Remote Sensing. 2023; 15(10):2630. https://doi.org/10.3390/rs15102630

Chicago/Turabian Style

Guerrón-Orejuela, Edgar J., Kai C. Rains, Tyelyn M. Brigino, William J. Kleindl, Shawn M. Landry, Patricia Spellman, Coowe M. Walker, and Mark C. Rains. 2023. "Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process" Remote Sensing 15, no. 10: 2630. https://doi.org/10.3390/rs15102630

APA Style

Guerrón-Orejuela, E. J., Rains, K. C., Brigino, T. M., Kleindl, W. J., Landry, S. M., Spellman, P., Walker, C. M., & Rains, M. C. (2023). Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process. Remote Sensing, 15(10), 2630. https://doi.org/10.3390/rs15102630

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

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