Water managers often have a large amount of data distributed in space and time. Berendrecht Consultancy applies a wide range of statistical techniques to extract the required information from these data including spatial and temporal variability, trends, and correlations. We also use statistical techniques to interpolate measurement data in space and time, making it possible to provide estimates at unobserved locations and/or timeframes.
Groundwater time series analysis
Berendrecht Consultancy is a specialist in the field of time series analysis. With time series analysis we calculate and evaluate the dynamics of a variable (for example, the water table or water level) at one or more locations. This statistical method has many useful applications including detection of measurement errors, estimation of missing observations, assessing the influence of explanatory variables (e.g. precipitation, evaporation, groundwater abstractions, hydrological interventions), and trend detection. We have developed techniques for the modeling of non-equidistant time series (varying measurement interval), and non-linear time series. Moreover, we use multiple time series analysis to analyse time series simultaneously. This allows us to distinguish common dynamic factors from unique dynamic factors, which can be used to detect spatial patterns, to fill gaps in time series, and to better value the uniqueness of observations obtained from a measurement location. The latter is very helpful to optimize monitoring networks.
Validating and processing data
High-quality and validated data are crucial in hydrological studies. Commonly used hydrological data include measurements of surface water levels, groundwater, precipitation, evaporation, and surface level. These data may be obtained from in-situ measurements as well as from remote sensing. We analyze and validate the data and further process it so that it can be used in, for example, hydrological models.