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Tomografia di resistività elettrica per la caratterizzazione dei mezzi porosi un’esperienza di laboratorio
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An electrical resistivity tomography system for imaging at laboratory scale
No full textOver the past century, there has been an increase in the use of electrical resistivity tomography in environmental research for subsurface characterization. Although commercial devices emphasize robustness and measurement quality, their lack of flexibility and high cost make them unsuitable for budget-constrained applications like research and educational purposes. This paper presents a low-cost DC resistivity meter that provides an adaptable tool for small-scale research in both laboratory and field environments. The proposed device is built around an Arduino Due board integrated with a four-channel 16-bit analog-to-digital converter. In addition, two custom shields are incorporated for signal conditioning and multiplexing. The firmware system allows users to configure key parameters, including array sequences, the number of repetitions, reverse measurements, acquisition frequency, and delays between measurements. Repetitive and reverse measurements contribute significantly to the accurate characterization of measurement errors. Its compact, cost-effective, and fully customizable design makes it particularly innovative in overcoming the limitations of current commercial alternatives. Laboratory tests validated the efficacy and reliability of the proposed device. Comparative analysis with a commercial resistivity meter (Iris Syscal R1) further reinforced these findings, revealing an excellent agreement (R2 = 0.999) between measurements acquired by the two instruments. These results highlight the system's optimal performance and the remarkable consistency of its measurements
Impacts of climate change on groundwater droughts by means of standardized indices and regional climate models
Full text linkThis paper investigates the impacts of climate change on groundwater droughts making use of regional projections and standardized indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Groundwater Index (SGI). The method adopted, using historical precipitation and temperature data and water levels collected in monitoring wells, first investigates the possible correlations between meteorological and groundwater indices at each well. Then, if there is a correlation, a linear regression analysis is used to model the relationships between SGIs and SPIs, and SGIs and SPEIs. The same relationships are used to infer future SGIs from SPI and SPEI projections obtained by means of an ensemble of Regional Climate Models (RCMs), under different climate scenarios (RCP 4.5 and RCP 8.5). This methodology has been applied to data collected in northern Tuscany (Italy) in an area served by a water company, where historical series of daily climate variables (since 1934) and daily records for 16 wells, covering the period 2005–2020, are available. The impacts on groundwater have been computed in the short- (2006–2035), medium- (2036–2065) and long-term (2066–2095). The analysis indicates that, in the historical period and for most of the monitoring wells, there is a good correlation between SGIs and SPIs or SPEIs. The results point out that making use of the SGI-SPI relationships, slight variations in the availability of groundwater are expected in the future. However, in a global warming scenario, the influence of temperature on evapotranspiration phenomena cannot be overlooked and, for this reason, the SGI-SPEI relationships seem more suitable to forecast groundwater droughts. According to these relationships, negative effects on groundwater levels in almost all wells are estimated for the future. For the RCP 4.5 scenario, the largest decline in groundwater level is expected in the medium-term, while for the RCP 8.5 scenario future SGIs will significantly decrease over the long-term. Due to the type of data required and its simplicity, this methodology can be applied to different areas of interest for a quick estimate of groundwater availability under climate change scenarios
Hydrogeophysical inversions using ensembled smoother with multiple data assimilation
No full textEnvironmental pressure on groundwater systems has intensified during the past
century because of the massive development of industrial and agricultural activities.
The effective and safe management of the groundwater environment represents a
significant challenge to modern society, requiring a detailed understanding of the
systems involved. In hydrogeology, direct measurements of subsurface geology are
often limited. Recently, more attention has been paid to inverse hydrogeophysics
modelling for the spatial prediction of hydrogeological subsurface properties.
In this work, electrical resistivity tomography (ERT) data and pollutant con centrations measured sparsely at borehole locations were jointly used to predict
the hydraulic conductivity field using the Ensemble Smoother with Multiple Data
Assimilation (ES-MDA). A synthetic case that simulates a heterogeneous aquifer
was developed to assess the efficacy of the approach. The ES-MDA is an itera tive data assimilation approach that allows the estimation of unknown parameters
using observed data and a forward model that relates model parameters and ob servations. One of the advantages of the ES-MDA is its capability to assimilate
multiple data sources simultaneously. The hydraulic conductivity field is estimated
using the ERT data and concentrations as observations in this case. The forward
model is represented by laws that establish the relationship between observed data
and parameters to be estimated. The method workflow begins with an initialization
phase, in which an initial ensemble of parameter realizations is defined, followed by
an iterative phase consisting of a forecast and update steps. During the forecast
step, the forward model provides predictions corresponding to the available observa tions for each parameter realization. Then, the algorithm updates the ensemble of
parameters based on the misfit between predictions and observations. In ES-MDA,
all available observations are assimilated multiple times during the iterative process.
The results demonstrate the potential of ES-MDA for hydrogeophysical inver sion using both ERT data and concentrations concurrently for subsurface charac terization while accounting for the uncertainty of the predictions. Furthermore, the
ES-MDA assimilates multiple data sources, which can significantly improve the ac curacy of the estimated conductivity field. As a future development, it is planned
to use data collected in a laboratory experiment under fully controlled conditions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Coupled hydrogeophysical inversion through ensemble smoother with multiple data assimilation and convolutional neural network for contaminant plume reconstruction
Full text linkIn the field of groundwater, accurate delineation of contaminant plumes is critical for designing effective remediation strategies. Typically, this identification poses a challenge as it involves solving an inverse problem with limited concentration data available. To improve the understanding of contaminant behavior within aquifers, hydrogeophysics emerges as a powerful tool by enabling the combination of non-invasive geophysical techniques (i.e., electrical resistivity tomography-ERT) and hydrological variables. This paper investigates the potential of the Ensemble Smoother with Multiple Data Assimilation method to address the inverse problem at hand by simultaneously assimilating observed ERT data and scattered concentration values from monitoring wells. A novelty aspect is the integration of a Convolutional Neural Network (CNN) to replace and expedite the expensive geophysical forward model. The proposed approach is applied to a synthetic case study, simulating a tracer test in an unconfined aquifer. Five scenarios are compared, allowing to explore the effects of combining multiple data sources and their abundance. The outcomes highlight the efficacy of the proposed approach in estimating the spatial distribution of a concentration plume. Notably, the scenario integrating apparent resistivity with concentration values emerges as the most promising, as long as there are enough concentration data. This underlines the importance of adopting a comprehensive approach to tracer plume mapping by leveraging different types of information. Additionally, a comparison was conducted between the inverse procedure solved using the full geophysical forward model and the CNN model, showcasing comparable performance in terms of results, but with a significant acceleration in computational time
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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