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

Research output: Contribution to journalResearch articleContributedpeer-review


  • Ezra Haaf - , Chalmers University of Technology (First author)
  • Markus Giese - , University of Gothenburg (Author)
  • Thomas Reimann - , Chair of Groundwater Systems (Author)
  • Roland Barthel - , University of Gothenburg (Author)


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.


Original languageEnglish
Article numbere2022WR033470
Number of pages18
JournalWater Resources Research
Volume59 (2023)
Issue number7
Publication statusPublished - 12 Jun 2023

External IDs

Scopus 85163824560
Mendeley dcde00fe-33f6-3369-8905-1bd2f07f357b
WOS 001042091200001
ORCID /0000-0002-4259-0139/work/142252579


Research priority areas of TU Dresden

Sustainable Development Goals

ASJC Scopus subject areas


  • Extreme gradient boosting, Groundwater dynamics, Imputation, Multiple regression, Regionalization, Time series analysis

Library keywords