Modeling hydraulic heads with impulse response functions in different environmental settings of the Baltic countries

Abstract

Study region:: The Baltic countries (Estonia, Latvia, Lithuania), North Eastern Europe. Study focus:: Time series models are a convenient tool for modeling hydraulic head time series due to their parsimonious parameterization and quick calculation time. However, it is unclear how the model structure and the outcome relate to the respective site characteristics. Time series modeling with impulse response functions was used to model the head time series. The correlations between the model performance and the environmental settings and between the model parameters and the environmental settings were analyzed using Spearman rank correlation and Random Forest regression analyses. New hydrological insights:: From the 460 analyzed head time series, 145 were modeled with satisfactory goodness-of-fit in the calibration period, using only precipitation, potential evaporation, and temperature as model inputs. This number decreased to 68 time series with a satisfactory fit in the validation period. Including additional drivers in wells where a substantial influence is characteristic could improve modeling results. The model results suggest that snow processes are affecting head dynamics in many wells in the Baltic countries. Most correlations between the model performance and the environmental setting were observed with the geological and climatic setting of the site. Models performed best in monitoring wells with shallow groundwater and lower precipitation seasonality.

Keywords

• Time series models
• IRF
• Hydraulic head
• SHAP values
• Environmental variables