Decoupling of modeling and measuring interval in groundwater time series analysis based on response characteristics

A state-space representation of the transfer function-noise (TFN) model allows the choice of a modeling (input) interval that is smaller than the measuring interval of the output variable. Since in geohydrological applications the interval of the available input series (precipitation excess) is often smaller than the interval of the output series (groundwater head), the state-space model opens the way to a more detailed description of the system. This paper evaluates the influence of the reduction of the modeling interval on the performance of the state-space time series model while keeping the measuring interval fixed. In order to obtain general conclusions of the relation between the modeling interval and the model performance, a large number of groundwater time series are generated and modeled with the state-space time series model. The results show that a reduction of the modeling interval noticeably improves the model performance. The degree of improvement depends on aspects like the response time of the system, the length of the time series and the amount of noise. A case study illustrates the effect of reducing the modeling interval as well as that of adding high-frequency measurements to the time series.