Review of the methodologies used to derive groundwater characteristics for a specific area in The Netherlands

Abstract

In this paper, we analyze the methods that are used in The Netherlands to upscale in-situ groundwater measurements in time and in space, and how the selected combinations of upscaling methods affect the resulting groundwater characteristic. In The Netherlands, a three-step approach is used to obtain groundwater characteristics for a specific area: (1) in-situ monitoring of the water table depth; (2) temporal upscaling; and (3) spatial interpolation and aggregation. The three-step approach is, however, not standardized, but a combination of the following methods is used: (i) four methods to measure/monitor the phreatic water table; (ii) four methods for temporal aggregation; and (iii) four methods for spatial interpolation and/or aggregation. Over the past sixty years, several combinations of these methods have been used. Our review shows that the use of these different combinations in the approach to measure and interpret water table depths has resulted in significant systematic differences in the corresponding groundwater characteristics and that there are many sources of potential error. Error in the in-situ measurement of the water table depth can be as high as 1 meter. Errors in the temporal aggregation are in the range of 10 to 20 cm and for the spatial interpolation between 20 to 50 cm. We show that there has been no systematic assessment of how these errors influence the resulting groundwater characterization. Thus, we cannot answer the question of whether drought stress in The Netherlands is under-or overestimated. Based on these findings we give recommendations for a systematic approach to groundwater characterizations studies that can minimize the impact of errors.

Effect of microrelief and water-table on vegetation dynamics in silty loam saline soils of coastal areas

“…WT depth varies in time and space based on pedological and hydrological processes [53], and the processes of macroaggregation and structural porosity are enhanced under higher soil surface roughness [54]. Moreover, very small changes in MR caused significant changes in moisture and other soil properties.…”

Mapping water table depths in wetlands and polder areas by probability sampling

“…From the selected time series the WTD-characteristics the Mean Highest (MHW) and Mean Lowest (MLW) Watertable are estimated according to Ritzema et al (2018). First, for each hydrological year, measures for the upper and lower bounds of the seasonal fluctuation are calculated, i.e.…”

“…Next, the MHW and MLW are estimated. The MHW (MLW) is defined as: average of the HW3 (LW3) over a period of 30 years under the given climatic and hydrological conditions (Ritzema et al, 2018). It is assumed that MHW and MLW can be estimated from observed series with lengths of at least four years in polder areas, since in these areas the seasonal fluctuation depends more on water level management than on seasonal fluctuation of precipitation and evapotranspiration.…”

“…We refer to these characteristics as WTD-characteristics. These WTD-characteristics are for instance the average upper and lower bounds of the yearly seasonal fluctuation, summarized with averages of the yearly highest (shallowest) and lowest (deepest) water tables (MHW and MLW), see Ritzema et al, 2018 for definitions. In wetlands and ditch-dissected polder areas most of the spatial variation of WTD-characteristics occurs within the fields between the ditches.…”