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Title: Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types

Here, a recent assessment that quantified potential impacts of solar energy development on water resources in the southwestern United States necessitated the development of a methodology to identify locations of mountain front recharge (MFR) in order to guide land development decisions. A spatially explicit, slope-based algorithm was created to delineate MFR zones in 17 arid, mountainous watersheds using elevation and land cover data. Slopes were calculated from elevation data and grouped into 100 classes using iterative self-organizing classification. Candidate MFR zones were identified based on slope classes that were consistent with MFR. Land cover types that were inconsistent with groundwater recharge were excluded from the candidate areas to determine the final MFR zones. No MFR reference maps exist for comparison with the study’s results, so the reliability of the resulting MFR zone maps was evaluated qualitatively using slope, surficial geology, soil, and land cover datasets. MFR zones ranged from 74 km2 to 1,547 km2 and accounted for 40% of the total watershed area studied. Slopes and surficial geologic materials that were present in the MFR zones were consistent with conditions at the mountain front, while soils and land cover that were present would generally promote groundwater recharge. Visual inspection ofmore » the MFR zone maps also confirmed the presence of well-recognized alluvial fan features in several study watersheds. While qualitative evaluation suggested that the algorithm reliably delineated MFR zones in most watersheds overall, the algorithm was better suited for application in watersheds that had characteristic Basin and Range topography and relatively flat basin floors than areas without these characteristics. Because the algorithm performed well to reliably delineate the spatial distribution of MFR, it would allow researchers to quantify aspects of the hydrologic processes associated with MFR and help local land resource managers to consider protection of critical groundwater recharge regions in their development decisions.« less
Authors:
 [1] ;  [1] ;  [2]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
  2. Univ. of Illinois at Chicago, Chicago, IL (United States)
Publication Date:
Grant/Contract Number:
AC02-06CH11357
Type:
Accepted Manuscript
Journal Name:
Journal of Water Resource and Protection
Additional Journal Information:
Journal Volume: 06; Journal Issue: 08; Journal ID: ISSN 1945-3094
Publisher:
Scientific Research Publishing, Inc.
Research Org:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC); Department of the Interior, Bureau of Land Management
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; Arid environment; Geographic information system (GIS); Groundwater recharge; Mountain front; Water resources
OSTI Identifier:
1392675

Bowen, Esther E., Hamada, Yuki, and O’Connor, Ben L.. Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types. United States: N. p., Web. doi:10.4236/jwarp.2014.68072.
Bowen, Esther E., Hamada, Yuki, & O’Connor, Ben L.. Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types. United States. doi:10.4236/jwarp.2014.68072.
Bowen, Esther E., Hamada, Yuki, and O’Connor, Ben L.. 2014. "Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types". United States. doi:10.4236/jwarp.2014.68072. https://www.osti.gov/servlets/purl/1392675.
@article{osti_1392675,
title = {Mapping Mountain Front Recharge Areas in Arid Watersheds Based on a Digital Elevation Model and Land Cover Types},
author = {Bowen, Esther E. and Hamada, Yuki and O’Connor, Ben L.},
abstractNote = {Here, a recent assessment that quantified potential impacts of solar energy development on water resources in the southwestern United States necessitated the development of a methodology to identify locations of mountain front recharge (MFR) in order to guide land development decisions. A spatially explicit, slope-based algorithm was created to delineate MFR zones in 17 arid, mountainous watersheds using elevation and land cover data. Slopes were calculated from elevation data and grouped into 100 classes using iterative self-organizing classification. Candidate MFR zones were identified based on slope classes that were consistent with MFR. Land cover types that were inconsistent with groundwater recharge were excluded from the candidate areas to determine the final MFR zones. No MFR reference maps exist for comparison with the study’s results, so the reliability of the resulting MFR zone maps was evaluated qualitatively using slope, surficial geology, soil, and land cover datasets. MFR zones ranged from 74 km2 to 1,547 km2 and accounted for 40% of the total watershed area studied. Slopes and surficial geologic materials that were present in the MFR zones were consistent with conditions at the mountain front, while soils and land cover that were present would generally promote groundwater recharge. Visual inspection of the MFR zone maps also confirmed the presence of well-recognized alluvial fan features in several study watersheds. While qualitative evaluation suggested that the algorithm reliably delineated MFR zones in most watersheds overall, the algorithm was better suited for application in watersheds that had characteristic Basin and Range topography and relatively flat basin floors than areas without these characteristics. Because the algorithm performed well to reliably delineate the spatial distribution of MFR, it would allow researchers to quantify aspects of the hydrologic processes associated with MFR and help local land resource managers to consider protection of critical groundwater recharge regions in their development decisions.},
doi = {10.4236/jwarp.2014.68072},
journal = {Journal of Water Resource and Protection},
number = 08,
volume = 06,
place = {United States},
year = {2014},
month = {6}
}