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Post, V. E. A., Houben, G. J., & van Engelen, J. (2018). What is the Ghijben-Herzberg principle and who formulated it? Hydrogeology Journal, 26(6), 1801–1807.
Abstract: It has been suggested in a number of historical notes that it was neither Willem Badon Ghijben nor Alexander Herzberg who formulated the famous principle now carrying their name, which relates the water-table elevation to the depth of the freshwater saltwater interface in coastal aquifers. In this paper, a systematic review of the literature pre-dating the publication of their work is presented. The aim is to establish to what extent these previous works captured the essence of the Ghijben-Herzberg principle, that is, the combination of a correct conceptual model of the hydrogeological conditions with a quantitative relationship. It was found that references to coastal fresh groundwater reserves can be traced back to Roman times, while the earliest detailed descriptions of a freshwater lens that could be found dates from the eighteenth century. The correct understanding of the hydrostatic equilibrium between fresh and salt groundwater is evident in works from the early nineteenth century. However, it was Badon Ghijben and Herzberg who combined this with the correct understanding of the groundwater conditions of a freshwater lens. It was further found that Herzberg had already recorded his findings in 1888 in a hand-written report, confirming speculation that such a report might exist.
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Post, V. E. A. (2018). Annotated translation of “Nota in verband met de voorgenomen putboring nabij Amsterdam [Note concerning the intended well drilling near Amsterdam]” by J. Drabbe and W. Badon Ghijben (1889). Hydrogeology Journal, 26(6).
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Conde, J. E., & Sanz Alaejos, M. (1997). Selenium concentrations in natural and environmental waters. Chemical Reviews, 97(6), 1979–2004.
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Nas, B. (2009). Geostatistical approach to assessment of spatial distribution of groundwater quality. Polish J. of Environ. Stud., 18(6), 1073–1082.
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Kisi, O., Heddam, S., Parmar, K. S., Yaseen, Z. M., & Kulls, C. (2024). Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data. Stochastic Environmental Research and Risk Assessment, 38(6), 2489–2519.
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