Optimal design of groundwater-level monitoring networks
Author(s) -
Fahimeh Mirzaie-Nodoushan,
Omid BozorgHaddad,
Hugo A. Loáiciga
Publication year - 2017
Publication title -
journal of hydroinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 50
eISSN - 1465-1734
pISSN - 1464-7141
DOI - 10.2166/hydro.2017.044
Subject(s) - groundwater , kriging , inverse distance weighting , sorting , genetic algorithm , weighting , interpolation (computer graphics) , aquifer , network planning and design , environmental science , computer science , engineering , multivariate interpolation , algorithm , artificial intelligence , machine learning , geotechnical engineering , medicine , motion (physics) , computer network , computer vision , bilinear interpolation , radiology
Groundwater monitoring plays a significant role in groundwater management. This study presents an optimization method for designing groundwater-level monitoring networks. The proposed design method was used in the Eshtehard aquifer, in central Iran. Three scenarios were considered to optimize the locations of the observation wells: 1) designing new monitoring networks, 2) redesigning existing monitoring networks, and 3) expanding existing monitoring networks. The kriging method was utilized to determine groundwater levels at non-monitoring locations for preparing the design data base. The optimization of the groundwater monitoring network had the objectives of 1) minimizing the root mean square error and 2) minimizing the number of wells. The non-dominated sorting genetic algorithm (NSGA-II) was applied to optimize the network. Inverse distance weighting interpolation was used in NSGA-II to estimate the groundwater levels while optimizing network design. Results of the study indicate that the proposed method successfully optimizes the design of groundwater monitoring networks that achieve accuracy and cost-effectiveness.
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