Data-Driven Estimation of Groundwater Level Time-Series at Unmonitored Sites Using Comparative Regional Analysis
Journal article, 2023

A new method is presented to efficiently estimate daily groundwater level time series at unmonitored sites by linking groundwater dynamics to local hydrogeological system controls. The proposed approach is based on the concept of comparative regional analysis, an approach widely used in surface water hydrology, but uncommon in hydrogeology. Using physiographic and climatic site descriptors, the method utilizes regression analysis to estimate cumulative frequency distributions of groundwater levels (groundwater head duration curves, HDC) at unmonitored locations. The HDC is then used to construct a groundwater hydrograph using time series from distance-weighted neighboring monitored (donor) locations. For estimating times series at unmonitored sites, in essence, spatio-temporal interpolation, stepwise multiple linear regression (MLR), extreme gradient boosting (XGB), and nearest neighbors are compared. The methods were applied to 10-year daily groundwater level time series at 157 sites in unconfined alluvial aquifers in Southern Germany. Models of HDCs were physically plausible and showed that physiographic and climatic controls on groundwater level fluctuations are nonlinear and dynamic, varying in significance from “wet” to “dry” aquifer conditions. XGB yielded a significantly higher predictive skill than nearest neighbor and MLR. However, donor site selection is of key importance. The study presents a novel approach for regionalization and infilling of groundwater level time series that also aids conceptual understanding of controls on groundwater dynamics, both central tasks for water resources managers.

regionalization

time series analysis

imputation

groundwater dynamics

multiple regression

extreme gradient boosting

Author

Ezra Haaf

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Markus Giese

University of Gothenburg

Thomas Reimann

Technische Universität Dresden

Barthel Roland

University of Gothenburg

Water Resources Research

0043-1397 (ISSN) 19447973 (eISSN)

Vol. 59 7 e2022WR033470

When, where, how? - Identifying causes of hydrogeological impacts in underground constructions

Swedish Transport Administration (TRV2019/45670), 2019-11-01 -- 2023-04-30.

Subject Categories

Geotechnical Engineering

Water Engineering

Oceanography, Hydrology, Water Resources

Probability Theory and Statistics

Control Engineering

DOI

10.1029/2022WR033470

More information

Latest update

7/17/2023