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Een analyse van grondwaterstanden die beïnvloed worden door de getijdebeweging *
Author(s) -
Stol Ir. Ph. Th.
Publication year - 1965
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1965.tb00966.x
Subject(s) - water table , amplitude , groundwater , water level , correlation coefficient , hydrology (agriculture) , table (database) , phase (matter) , precipitation , environmental science , mathematics , geology , meteorology , geotechnical engineering , statistics , physics , geography , cartography , quantum mechanics , computer science , data mining
Summary In hydrology and water management research knowledge of the cause of changes in groundwater levels often is of great importance. Changes of ground‐waterlevel can be caused by precipitation and evaporation, by positive ‐ or negative seepage, by polder‐discharge and local discharges for industrial needs: along tidal‐rivers also by the influence of the tides. The effect of the tide (R) and of local discharges (P) together, give several types of groundwater level‐curves (Jig. 2). The propagation of the tide takes place with a shift in phase (t t in ( I )) and a damping of the amplitude (fig. 6). To determine in an empirical way the rate with which the phase shifts, in connection with the distance ( x )from the banks of the river, a simple regression model (2) is recalculated several times, shifting mutually the series of data before each calculation. This work can easily be done by means of a computer, loading in sequence the data of the test‐wells (W) located in the region under discussion (fig. I). That shift which results in the highest multiple correlation‐coefficient is used to determine the difference in phase with reference to the tide present in the river (table 1, giving the effect of increasing phase shift (t B ) on the correlation coefficients, with in the columns: phase shift in hours; mult. corr. coeff.; time in degrees; corr. with river level). The results, for instance the numerical values of the correlation between each test well and the river, critical values of deviations from the model, the regression coeff. (b 2 ) for local effects, are represented in maps (Jig. 3, 4, 5), and may serve to determine the magnitude of soil‐physical constants.