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On the Optimal Spatial Design for Groundwater Level Monitoring Networks

Ohmer, Marc; Liesch, Tanja; Goldscheider, Nico

Effective groundwater monitoring networks are important, as systematic data collected at observation wells provide a crucial understanding of the dynamics of hydrogeological systems as well as the basis for many other applications. This study investigates the influence of six groundwater level monitoring network (GLMN) sampling designs (random, grid, spatial coverage, and geostatistical) with varying densities on the accuracy of spatially interpolated groundwater surfaces. To obtain spatially continuous prediction errors (in contrast to point cross‐validation errors), we used nine potentiometric groundwater surfaces from three regional MODFLOW groundwater flow models with different resolutions as a priori references. To assess the suitability of frequently‐used cross‐validation error statistics (MAE, RMSE, RMSSE, ASE, and NSE), we compared them with the actual prediction errors (APE). Additionally, we defined upper and lower thresholds for an appropriate spatial density of monitoring wells. Below the lower threshold, the observation density appears insufficient, and additional wells lead to a significant improvement of the results. Above the upper threshold, additional wells lead to only minor and inefficient improvements. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000100286
Veröffentlicht am 26.11.2019
DOI: 10.1029/2019WR025728
Zitationen: 2
Web of Science
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Geowissenschaften (AGW)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 0043-1397, 1944-7973
KITopen-ID: 1000100286
Erschienen in Water resources research
Seiten 2019WR025728
Vorab online veröffentlicht am 19.11.2019
Nachgewiesen in Web of Science
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