Processes influencing groundwater in the coastal aquifer of Troia Portugal

2021 ◽  
Author(s):  
Marlin Juchem ◽  
Maria da Conceição Neves ◽  
Amélia Dill
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Salt Water ◽  
Karst Aquifer ◽  
Time Lag ◽  
Barometric Pressure ◽  
Influential Factor ◽  
Sea Level Changes ◽  
Ongoing Research ◽  
Tidal Cycles

<p>Groundwater fluctuation in coastal aquifers depends on a number of processes which interact with each other in a complex way. In this work, we analyzed the response of the groundwater’s quality and quantity indicators of Troia costal aquifer to several forcing factors. Troia peninsula is underlayed by a multi-layer aquifer consisting of an upper phreatic layer freshwater porous aquifer, a salt water sandy layer with interbeded clay lenses and a deeper semi-confined karst aquifer. This study focuses on the upper aquifer region (10m depth), where influences of oceanic and atmospheric drivers are expected to be strongest. Groundwater data was collected from a borehole located approx. 200m from the shoreline. Hourly records of the piezometric level, conductivity, and temperature data from the hydrological year 2006-2007 were related to data of barometric pressure, rainfall and tides using correlation and singular spectral analytical methods. All variables (precipitation, barometric pressure and tidal cycles) uniquely affect the groundwater’s level and quality with different magnitudes and time scales. Regarding the long-term and larger scales, precipitation seems to be the most influential factor, contributing to 46 % of the variability of the groundwater time series. This percentage of variabillity is due the seasonality of the water cycle, with 29% related to the semi-annual cycle and 17% related to the quarterly cycle. The barometric pressure seems to affect the groundwater in similar scales as the precipitation, however tidal cycles have a much smaller impact. The tidal data was modelled with WxTides software with an interval of 15 minutes. The cyclic patterns of semidiurnal and fortnightly tidal-induced sea level changes can clearly be observed in the records of the groundwater level throughout the entire time series. Tides and groundwater level present a maximum positive correlation coefficient of 0.58 in the month of August, when other forcing factors, such as precipitation, are the lowest. Groundwater level displays a 16-day time lag with the precipitation, a two-day time lag with the barometric pressure and a two-hour time lag with the modelled tides. The correlations and lags found in this study are being used as a basis for ongoing research on the complexity of groundwater level oscillations in littoral zones. The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – IDL.</p>

scholarly journals Visibility Graph Complex Network Analysis on Seismic-Induced Variation in Groundwater Level of Nanxi Well, China

2020 ◽  
Vol 15 (6) ◽  
pp. 905-911
Author(s):  
Jian Yu ◽  
Hongbiao Gu ◽  
Baoming Chi ◽  
Weifeng Shan ◽  
Mingyuan Wang
Keyword(s):  
Time Series ◽  
Seismic Response ◽  
Groundwater Level ◽  
Complex Dynamics ◽  
Time Windows ◽  
Barometric Pressure ◽  
Scale Free ◽  
Degree Correlation ◽  
Topological Features ◽  
Well Water Level

Groundwater level in wells, i.e., well water level (WWL) is an important index in hydrological monitoring during earthquakes. Due to the complex dynamics of groundwater, the WWL might change under seismic actions. This paper attempts to identify the long-term correlation between WWL and earthquakes, and disclose the topological features of groundwater dynamics. Taking Nanxi Well as an example, the authors conducted state space analysis on the raw series and trend of WWL to eliminate interferences like barometric pressure, rainfall, and solid tide, creating the trend time series. Then, the raw series and trend time series were converted into the raw visible graph (VG) network and trend VG network, respectively. Further, the global period was divided into five local time windows, and the two VG networks were compared by global aspect, local aspect, and topological properties of complex networks. The results show that the nodes of high degrees are closely related to the seismic response of the WWL in Nanxi Well; all VG networks are scale free and hierarchical; the seismic response of the WWL in the well is reflected by degree correlation; the community division of raw VG network was basically the same as that of trend VG network. The research findings provide insights to the seismic response of WWL and the dynamic fluctuation of groundwater level.

scholarly journals Correlation between tides of northern Adriatic sea and hydrodynamics of the karstic aquifer in the Pozzo dei Protei di Monfalcone (Classical Karst)

2020 ◽  
Vol 49 (1) ◽  
Author(s):  
Rino Semerraro ◽  
Federico Valentinuz ◽  
Maurizio Tavagnutti
Keyword(s):  
Electrical Conductivity ◽  
Groundwater Level ◽  
Adriatic Sea ◽  
Salt Water ◽  
Karst Aquifer ◽  
Chloride Ion ◽  
Northern Adriatic Sea ◽  
Northern Adriatic ◽  
The North ◽  
Mineralized Water

The Pozzo dei Protei di Monfalcone (northeast Italy) is a cavity developed in Cretaceous limestones (Cenomanian-Turonian) situated near the contact of the north-western zone of the Classical Karst with the Lower Plain of the Isonzo/Soča River. At the bottom of the cave is the groundwater at an average altitude of 1.89 m a.s.l. In consideration of the proximity of the cave with the Adriatic Sea, the possible effects of the tides on the karst aquifer were investigated monitoring groundwater level, electrical conductivity (EC, K25) and water temperature using a CTD diver. Groundwater level daily oscillations show a lag of 4–4.5 hours compared to tides. The electrical conductivity variations that can be correlated to tides are 2–5 μS/cm. Excluding that the cave, given the altimetry, is directly affected by the saltwater wedge, the cyclical variations of the EC would derive from the dispersion at the salt water and fresh water interface and from the mobilization of more mineralized water coming from the rock mass. The hypothesis of mixing fresh and salt water and saline fossil waters in the caves of the area has been verified by a general increase in the chloride ion in this area of the karst aquifer compared to the internal areas of Classical Karst.

scholarly journals Forecasting sea level changes applying data mining techniques to the Cristobal Bay time series, Panama

2016 ◽  
Vol 8 (1) ◽  
pp. 89-101 ◽  
Author(s):  
José A. Simmonds ◽  
Juan A. Gómez ◽  
Agapito Ledezma
Keyword(s):  
Data Mining ◽  
Time Series ◽  
Sea Level ◽  
Cross Validation ◽  
Sequence Data ◽  
Time Lag ◽  
Sea Level Changes ◽  
Data Mining Techniques ◽  
Lag Period ◽  
Using Data

Time series forecasting using data mining models applied to various time sequence data of a wide variety of domains has been well documented. In this work, time series of water level data recorded every hour at ‘Cristobal Bay’ in Panama during the years 1909–1980 are employed to construct a model(s) that can be suitable for predicting changes in sea level patterns. Four time lag assemblages of variable combinations of the time series information are fully explored to identify the optimal combinations for the dataset using a data mining tool. The results, based on the assessment using time series of Cristobal data, show that in general using cross-validation and a longer time lag period of the time series led to more accurate forecasting of the model than that of a shorter lag period of the time series. The study also suggests that data mining techniques using cross-validation and the aid of an attribute evaluator can be effectively used in modeling time series for changes in sea level at coastal areas, and changes in ecosystems that by their nature are characterized by nonlinearity and presentation of chaotic climatic changes in their physical behavior.

Analysis and prediction of groundwater level time series with Autoregressive Linear Models

2016 ◽  
Vol 39 ◽  
pp. 109-112
Author(s):  
Mirko Ginocchi ◽  
Giovanni Franco Crosta ◽  
Marco Rotiroti ◽  
Tullia Bonomi
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Linear Models

scholarly journals Identifying the sensitivity of GPS to non-tidal loadings at various time resolutions: examining vertical displacements from continental Eurasia

GPS Solutions ◽  
2021 ◽  
Vol 25 (3) ◽  
Author(s):  
Anna Klos ◽  
Henryk Dobslaw ◽  
Robert Dill ◽  
Janusz Bogusz
Keyword(s):  
Time Series ◽  
Seasonal Changes ◽  
System Modeling ◽  
Sea Level Changes ◽  
Observation Level ◽  
Earth System Modeling ◽  
Atmospheric Loading ◽  
Modeling Group ◽  
Vertical Displacements ◽  
Almost All

AbstractWe examine the sensitivity of the Global Positioning System (GPS) to non-tidal loading for a set of continental Eurasia permanent stations. We utilized daily vertical displacements available from the Nevada Geodetic Laboratory (NGL) at stations located at least 100 km away from the coast. Loading-induced predictions of displacements of earth’s crust are provided by the Earth-System-Modeling Group of the GFZ (ESMGFZ). We demonstrate that the hydrological loading, supported by barystatic sea-level changes to close the global mass budget (HYDL + SLEL), contributes to GPS displacements only in the seasonal band. Non-tidal atmospheric loading, supported by non-tidal oceanic loading (NTAL + NTOL), correlates positively with GPS displacements for almost all time resolutions, including non-seasonal changes from 2 days to 5 months, which are often considered as noise, intra-seasonal and seasonal changes with periods between 4 months and 1.4 years, and, also, inter-annual signals between 1.1 and 3.0 years. Correcting the GPS vertical displacements by NTAL leads to a reduction in the time series variances, evoking a whitening of the GPS stochastic character and a decrease in the standard deviation of noise. Both lead, on average, to an improvement in the uncertainty of the GPS vertical velocity by a factor of 2. To reduce its impact on the GPS displacement time series, we recommend that NTAL is applied at the observation level during the processing of GPS observations. HYDL might be corrected at the observation level or remain in the data and be applied at the stage of time series analysis.

scholarly journals A novel deseasonalized time series model with an improved seasonal estimate for groundwater level predictions

2019 ◽  
Vol 2 (1) ◽  
pp. 25-44 ◽  
Author(s):  
S. Mohanasundaram ◽  
G. Suresh Kumar ◽  
Balaji Narasimhan
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Moving Average ◽  
Seasonal Component ◽  
Univariate Time Series ◽  
Level Data ◽  
Proposed Model ◽  
Interval Approach ◽  
Prediction And Forecasting ◽  
Observation Wells

Abstract Groundwater level prediction and forecasting using univariate time series models are useful for effective groundwater management under data limiting conditions. The seasonal autoregressive integrated moving average (SARIMA) models are widely used for modeling groundwater level data as the groundwater level signals possess the seasonality pattern. Alternatively, deseasonalized autoregressive and moving average models (Ds-ARMA) can be modeled with deseasonalized groundwater level signals in which the seasonal component is estimated and removed from the raw groundwater level signals. The seasonal component is traditionally estimated by calculating long-term averaging values of the corresponding months in the year. This traditional way of estimating seasonal component may not be appropriate for non-stationary groundwater level signals. Thus, in this study, an improved way of estimating the seasonal component by adopting a 13-month moving average trend and corresponding confidence interval approach has been attempted. To test the proposed approach, two representative observation wells from Adyar basin, India were modeled by both traditional and proposed methods. It was observed from this study that the proposed model prediction performance was better than the traditional model's performance with R2 values of 0.82 and 0.93 for the corresponding wells' groundwater level data.

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