Abstract

Nowadays, several methodologies, implemented for satellite or terrestrial surveys, reveal that daily and weekly site-positioning time series can exhibit linear trends plus seasonal oscillations. Such periodic components affect the evaluation of subsidence rates and, thus, they must be recognized and properly modelled. In this work, the periodic component of vertical land motion in Po Delta (Northern Italy) is estimated by a multi-component and multi-source procedure recently proposed by some of the authors for studying land subsidence in delta areas. First, land vertical motion data, acquired in the central part of the Po Delta over a six-year time interval, were compared with hydro-meteorological and climate datasets collected from nineteen stations distributed over the entire Delta. Then, four physically based models of the test site were implemented to verify the water pressure- and water mass-dependent processes inferred from the analytical phase. Modelling results show that the annual ground oscillation is better explained by soil moisture change, although river water mass variation gives a relevant contribution to land deformation, especially in the wet periods. Finally, to account for intra-annual processes, the joint contributions of all the inferred sources were treated as a nonlinear problem and solved applying the generalized reduced gradient method. The obtained combination is well supported by statistical parameters and provides the best agreement with the geodetic observations.

Highlights

  • Surface distortional deformations computed in the second numerical model (Section 4.3.2), which considers the loading history induced by the river water mass change during the analyzed time interval, simulate well the sequence of peaks and troughs at interand intra-annual scales exhibited by the geodetic signal

  • Multi-component and multi-source approach, based on multi-disciplinary comparative analyses and physically based modelling, was applied in the Po Delta to produce a better understanding of the physical mechanisms responsible for the periodic ground level oscillations observed at the TGPO site in the period April 2011–June 2017

  • The mean annual values from two piezometers located north-east and south-west of the TGPO site correlate well with the mean annual values of the Po River level, suggesting that the river–aquifer exchange flow combined with the expansion/compression of terrains may drive land-surface deformation

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Summary

Introduction with regard to jurisdictional claims in

In the last few decades, vertical land motion (VLM) monitoring has evolved according to the technological development in land surveying techniques passing from the traditional levelling method to the Global Navigation Satellite System (GNSS) and, to Synthetic Aperture Radar Interferometry (InSAR) [1]. Since the seasonal signals vary from year to year due to different physical mechanisms, some authors analyze the periodic oscillations in terms of time-varying artificial patterns by using different approaches, like the singular spectrum analysis (e.g., [11]), the Kalman filter [12,13], the seasonal signal filter (e.g., [14]) or the Chebyshev polynomials [15] Such methods do not take into account the physical nature of the observed seasonal variations, i.e., the source(s) responsible for the annual and semi-annual variations exhibited in the geodetic time series, such as surface mass redistribution (e.g., [16,17]), local environmental effects such as temperature and rain (e.g., [18,19]), thermal expansion of ground and monuments (e.g., [20]), and groundwater withdrawal (e.g., [21]). The study area was historically affected by significant land subsidence (e.g., [25]) and, in recent decades, has been covered by accurate GNSS monitoring data and InSAR data (e.g., [26,27,28]) These satellite-derived time series are normally used for monitoring the permanent component of vertical land movements. It consists of 38 pumping stations and a drainage net 700 km long with a water extraction capability of 180 m3 /s [30]

Data Presentation
Geodetic Time Series
Application of the Multi-Component and Multi-Source Approach
Step 1
Step 2
Step 3
Groundwater–Surface Water Interaction
Mechanical Modelling via FEM
Joint Contribution of the Proposed Sources
Discussion
Conclusions

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