Analysis of fragmented piezometric levels records: the ARTE (Antecedent Recharge Temporal Effectiveness) approach

Submitted: 31 March 2022
Accepted: 21 June 2022
Published: 30 June 2022
Abstract Views: 562
PDF: 373
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  • Matteo Nigro Department of Earth Sciences, University of Pisa, Italy.
  • Michele Ambrosio Af Geoscience And Technology Consulting S.r.l., San Giuliano Terme (PI), Italy.
  • Maria-Teresa Fagioli Af Geoscience And Technology Consulting S.r.l., San Giuliano Terme (PI), Italy.
  • Chiara Curcio Department of Earth Sciences, University of Pisa, Italy.
  • Roberto Giannecchini Department of Earth Sciences, University of Pisa; Institute of Geosciences and Earth Resources, IGG-CNR, Pisa; Centre for Climatic Change Impact, CIRSEC, University of Pisa, Italy.

In contrast to climatic data, piezometric records are often fragmented both in time and space continuity, despite their crucial importance in groundwater studies. This work presents a new method for analysis of groundwater level vs. recharge processes relation from fragmented piezometric data, called Antecedent Recharge Temporal Effectiveness (ARTE). The ARTE method was tested on 5 year-long (2016-2020) water table level datasets measured by three automatic piezometers located in the Lucca plain (Tuscany, Italy). For each piezometric level time series, measurements were extracted every 30, 60, and 120 days, and randomly, obtaining fragmented records inlcuding less than 3% of the complete time series. As for recharge processes of the monitored aquifer, rainfall and riverbed infiltration were selected. Hence, daily rainfall and daily mean river stage time series were acquired from different automatic raingauges and hydrometers respectively. The relationship between these recharge processes and the variation of the piezometric level from the artificially fragmented datasets were evaluated with the ARTE method. The ARTE method was potentially able to identify maximum correlation time intervals, for which the recharge processes are most likely to influence the groundwater level. Based on the analysis conducted on the fragmented piezometric datasets, the reconstruction of each piezometric time series was attempted for the study period. The simulated daily groundwater level records have RMSE values between 0.21 m and 0.73 m and NRMSE values between 0.08 and 0.16, which are satisfactory results when compared with other more complex simulation procedures, in which the training datasets are increasingly larger.

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