Electrical Conductivity Data Research Articles

Artificial Neural Network Modeling to Predict Electrical Conductivity and Moisture Content of Milk During Non-Thermal Pasteurization: New Application of Artificial Intelligence (AI) in Food Processing

This study proposed applying artificial intelligence (AI) to predict the actual electrical conductivity (EC) of raw and pasteurized milk using moderate electric field (MEF) based on the electric field strength (EFS) and mass flow rate (MFR) along with modeling moisture content (MC) based on the EC. To this end, an artificial neural network (ANN) was implemented for conventionally (CP) and non-thermally (NP) pasteurized milk. The findings indicated no significant difference (p > 0.05) between the experimental and predicted data for EC and MC. The MFR and EFS affected the actual EC. The raw milk samples had an EC of 0.468812–0.46913 S/m and MC of 87.3218–87.35941%, while these values in NP pasteurized milk were 0.457441–0.638224 S/m and 87.33986–87.40851%. With correlation coefficients (R) of 0.736478106–0.951840323 and mean square errors (MSE) of 0.005539–0.0064, the ANN accurately predicted the raw and pasteurized milk MC based on the EC using the sixth-order polynomial model and the EC based on the EFS and MFR using a quadratic model. The EC of pasteurized milk by NP was significantly (p < 0.05) lower than that of CP and raw dairy by 15.44% and 11.30%, respectively. The results show that the EFS and MFR might be used for the online assessment of milk’s physical attributes (e.g., EC), followed by using the assessed parameter to determine other properties (e.g., MC) by developing AI approaches based on optimized models. These observations showcase the innovative use of ANN-based AI to predict milk’s EC and MC accurately. Integrating such AI platforms into non-thermal food processing could eventually develop more sustainable food production and enhance food security and quality through process innovation and sustainable manufacturing, contributing to the industrial revolution and sustainable development goals.

Prediction of mechanical properties of polymer composites with carbon fillers based on low-frequency electrical conductivity data

Prediction of mechanical properties of polymer composites with carbon fillers based on low-frequency electrical conductivity data

Dynamics of soil water, temperature, and salt and their coupled effects in Haloxylon ammodendron forests of different ages in an arid desert oasis ecotone

Study regionThe study region is a typical desert oasis ecotone of the Hexi Corridor, Northwest China. Study focusBased on four years of in situ observational data of soil water, temperature, and electrical conductivity obtained from three Haloxylon ammodendron (H. ammodendron) forests (20, 30 and 50 years) in a typical desert oasis ecotone (DOE) of the Hexi Corridor, in this study, the mechanisms of change and coupled effects of water, heat, and salt in frozen desert soils along a long-term shrub plantation in a typical desert oasis ecotone are presented. New hydrological insights for the regionThis study revealed that changes in soil water, heat, and salt and their coupling effects were completely different between shallow (0–80 cm) and deep (160–200 cm) depths. At 0–80 cm, soil water gradually decreased in the 50-year-old H. ammodendron plot, but soil salt first increased in the 30-year plot and then decreased in the 50-year plot. When the freezing process occurred in the 0–80 cm depth interval, the soil water and salt contents decreased nonlinearly with the absolute value of the soil temperature (|T|), following a power function and logarithmic function, respectively. For the thawing process in the 0–80 cm depth interval, soil water and salt increased with increasing temperature, and there was a significant linear relationship between soil water and salt (P<0.01). In the 160–200 cm layer, soil water and salt significantly increased after 30–50 years during the growing season.

High temperature setup for measurement of Hall coefficient and electrical conductivity of thermoelectric materials.

An experimental setup has been developed for the simultaneous measurement of the Hall coefficient (RH) and electrical conductivity (σ) of thermoelectric (TE) specimens in the temperature range of 300-700K. The van der Pauw geometry is utilized for the RH and σ measurements. The sample holder geometry has been designed for diverse TE specimen dimensions and easy sample mounting. A special feature of the holder geometry is that the same sample can be used for other relevant thermoelectric measurements such as the Seebeck coefficient and thermal diffusivity. This minimizes measurement errors associated with compositional or doping inhomogeneities. In the absence of high temperature standard reference materials for Hall coefficient measurements, silicon samples with different doping concentrations have been used to verify the accuracy of the instrument. Additionally, the electrical conductivity data have been validated by measurements on the same samples in a calibrated setup. Repeat measurements indicate a maximum standard deviation of ±3% and ±0.5% for the RH and σ data in the studied temperature range. Furthermore, comparisons with the calibrated setup indicate deviations within ±3% for the σ data. The suitability of the measurement setup for TE specimens has been demonstrated using measurements on n-type (Mg2Sn) and p-type (Mg3Sb2) specimens with carrier concentrations in the range of 1019-1020cm-3.

“Stick–slip” fluctuations in local electrical conductivity maps on graphite surfaces: A revisit

Electrical conductivity images of graphite surfaces are routinely obtained using scanning probe microscopy. Although the acquired conductivity maps often display a trigonal pattern with smooth variations, a “stick–slip” type of fluctuation has also been reported, where the local conductivity inversely correlates with the friction force during probe scanning. In this work, we revisit the lattice-resolved variations in local conductivity on graphite surfaces and reveal a new series of behaviors. Unlike previous observations, we demonstrate that local conductivity can exhibit in-phase, out-of-phase, or mixed-mode correlations with “stick–slip” lateral force signals. These behaviors are attributed to the cross-talk effect between interface contact conductivity and lateral force, induced by the inhomogeneous conductivity of the tip apex. This mechanism is experimentally validated, showing that local conductivity variations can switch within a single scan due to spontaneous changes in the conductivity of the tip. Our findings enhance the understanding of lattice-resolved electrical conductivity data on graphite surfaces and suggest a novel approach to amplify small lateral forces using inhomogeneous probe tips.

Investigation of ion pairs in electrochemical hexacyanoferrate(II)– hexacyanoferrate(III) system in presence of supporting electrolyte

The study of ion pair formation involving redox couples and the cation or anion of supporting electrolytes in solutions is a fundamental question in the field of fluid mechanics and electrochemistry. In this research, density functional theory (DFT) calculations were performed to investigate the ion pair reactions of hexacyanoferrate(III) and hexacyanoferrate(II) with varying numbers of potassium ions from the supporting electrolyte KCl. The binding energy and Gibbs free energy for the ion pair reactions were evaluated. The DFT results revealed a non-monotonic behavior in the binding energy and Gibbs free energy for the ion pair reaction of hexacyanoferrate(III) with different numbers of K ions.Further exploration of the chemical structures of ion pair compounds of hexacyanoferrate(III) and hexacyanoferrate(II) with varying numbers of K ions was conducted using DFT methods. Notably, in the first step of the ion pair reaction with K ions, the iron-potassium chemical bond length in hexacyanoferrate(III) was observed to be smaller than in subsequent steps.The DFT results also provided insights into the capacity of hexacyanoferrate(III) and hexacyanoferrate(II) to accept potassium ions for forming ion pair structures, showing that the former has a lower acceptance capacity than the latter. Furthermore, DFT calculations of equilibrium constants confirmed experimental results based on reduction electrical conductivity data obtained from ion pair formation in the solution.

Comparison of Water and DTPA Extractants for Testing of Greenhouse Soilless Substrates

ABSTRACT The main purpose of this study was to improve the accuracy and reliability of nutrient analysis on soilless substrates by comparing two different saturated medium extract (SME) methods, using either water (SMEW) or DTPA (diethylenetriamine-pentaacetic acid, SMED) as extractants. A series of analyses were performed to compare ion levels quantified from either SMEW or SMED. Substrate pH, electrical conductivity (EC) and nutrient data were analyzed from a survey of substrate components (coconut coir, peat, bark, perlite, vermiculite), and blended greenhouse propagation substrates using the SMEW and SMED methods. In addition, a series of SMEW and SMED extracted samples were sent to three commercial soil testing laboratories for nutrient analysis. The objectives of these analyses were to (1) validate that published relationships between SMEW and SMED methods were consistent with correlation curves for pH, EC and nutrient levels across a wide range of soilless substrates, (2) compare statistical variability of results from SMEW and SMED methods and (3) compare variability in results between different laboratories. The results validated that previously published standards for interpreting SMEW extractions can be used for SMED method for macronutrients and EC due to an approximately 1:1 relationship for test results between extraction methods. Up to 2 orders of magnitude higher levels of micronutrients were extracted for iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu) using SMED compared with SMEW, with low correlation between extractants. Concentrations of ions from SMED extractions were less variable than SMEW for micronutrient analysis but were comparable for macronutrient analysis. Results from this study were combined with published research to provide suggested ranges using SMED for soilless substrates.

Leafiness-LiDAR index and NDVI for identification of temporal patterns in super-intensive almond orchards as response to different management strategies

The use of super-intensive orchards is a growing trend in fruit production. The present study aims to improve management of these cropping systems by focusing on how agronomic decisions impact orchard dynamics in the short to medium term and by providing a decision-support approach based on stable temporal patterns from previous seasons. A multitemporal study using remote sensing and LiDAR was conducted in a commercial almond orchard over four growing seasons (2019–2022) to determine the optimal timing of image acquisition for variable pre-harvest treatments. A model-based clustering (mclust) was applied to optimal Sentinel-2 NDVI maps and apparent soil electrical conductivity (ECa) data, interpolated to the pixel centroids of Sentinel-2 image grids, to delineate potential management zones (PMZs). The leafiness-LiDAR index (LLI), a leaf area index (LAI) estimator, was obtained as ground truth after summer pruning and before harvesting, showing a significant influence of fertigation and pruning on the LAI, with summer pruning particularly influencing orchard dynamics. The optimal time for NDVI mapping was found to be two months after summer pruning in productive years and two weeks after in unproductive years. The delineated PMZs were consistent across seasons and corresponded to significant LAI differences. This method could contribute to improving resource management and sustainability in super-intensive commercial orchards.

Seasonal meteorological forcing controls runoff generation at multiple scales in a Mediterranean forested mountain catchment

Understanding hydrological processes during dry periods in Mediterranean mountain catchments is critical due to the increasing frequency of drought episodes. In this work, we aimed at characterizing the effect of the seasonal variability of meteorological forcing on the hydrological response of a small mountain forested catchment in the Mediterranean region. We analyzed the hydrological response and its timing based on hydrometric and electrical conductivity (EC) data for a year in the nested (0.31–2 km2) Re della Pietra catchment, in Central Italy. We used a soil moisture-based metric to distinguish between wet and dry periods and performed EC-based hydrograph separations during these two periods. The results revealed the important role of seasonality as a meteorological forcing affecting soil moisture, groundwater, streamflow response, and stream event water fractions. Wet and dry periods were distinctly characterized by different streamflow, soil moisture, and groundwater responses. Event water fractions in streamflow also highlight the relevance of the seasonality in the meteorological forcing on runoff generation. Particularly, at the rainfall-runoff event scale, the combination of antecedent soil moisture and precipitation depth controlled the non-linear response of streamflow, groundwater, and different event water fractions in the wet and dry periods.Stream stages and event water fractions also varied across nested spatial scales. Antecedent moisture conditions triggered a faster streamflow response due to higher connectivity along the hillslope in the wet period, with higher event water fractions in the upper sub-catchments (25 %) compared to the lower sub-catchments (15 %). Conversely, in the dry period, higher event water fractions were registered at the outlet (11 %) than at the headwaters (7 %). Time lags between peak flows observed across the nested catchment showed a complex pattern, suggesting the interaction of multiple factors controlling the timing of streamflow peaks in the study area. These findings contributed to improve our mechanistic insights into the elusive seasonal hydrological patterns observed in Mediterranean mountain forested catchments.

The impact of helium clusters on the electronic thermal transport properties of tungsten plasma-facing materials at finite temperatures

In this work, we investigated the impact of different concentrations of helium (He) impurities on the electronic thermal transport properties of tungsten plasma-facing materials (W-PFMs) at finite temperatures using the W-He tight-binding (TB) potential model. We found that the electronic transport performance decreases with increasing He atom concentration at different sites, where the greatest reduction in the electrical conductivity of the system is caused by the introduction of He atoms at neighboring tetrahedral sites. As the temperature increases, the electrical conductivity decreases, while the electronic thermal conductivity increases. Importantly, the higher the temperature is, the weaker the response of the electrical conductivity and electronic thermal conductivity to the He atom concentration. We suggest that this behavior is attributed to the diverse contributions of scattering mechanisms within various temperature ranges. Furthermore, as the temperature increases, the electron scattering mechanism gradually transitions from electron-impurity scattering to electron-electron scattering. Additionally, our calculated atomic resolved electrical conductivity data indicate that at lower temperatures, the electrical conductivity is predominantly contributed by W atoms around the He cluster.

Electrical Conductivity of Subsurface Ocean Analogue Solutions from Molecular Dynamics Simulations.

Investigating the habitability of ocean worlds is a priority of current and future NASA missions. The Europa Clipper mission will conduct approximately 50 flybys of Jupiter's moon Europa, returning a detailed portrait of its interior from the synthesis of data from its instrument suite. The magnetometer on board has the capability of decoupling Europa's induced magnetic field to high precision, and when these data are inverted, the electrical conductivity profile from the electrically conducting subsurface salty ocean may be constrained. To optimize the interpretation of magnetic induction data near ocean worlds and constrain salinity from electrical conductivity, accurate laboratory electrical conductivity data are needed under the conditions expected in their subsurface oceans. At the high-pressure, low-temperature (HPLT) conditions of icy worlds, comprehensive conductivity data sets are sparse or absent from either laboratory data or simulations. We conducted molecular dynamics simulations of candidate ocean compositions of aqueous NaCl under HPLT conditions at multiple concentrations. Our results predict electrical conductivity as a function of temperature, pressure, and composition, showing a decrease in conductivity as the pressure increases deeper into the interior of an icy moon. These data can guide laboratory experiments at conditions relevant to icy moons and can be used in tandem to forward-model the magnetic induction signals at ocean worlds and compare with future spacecraft data. We discuss implications for the Europa Clipper mission.

Influence of the oxidative phosphorylation uncoupler m-chlorophenol on activated sludge production, nutrients removal efficiency and bacterial community structure of a membrane reactor system

In this work, the effects of the metabolic uncoupler meta-chlorophenol (m-CP) on excess sludge production and performance of an MBR system, as well as on activated sludge communities, were investigated. MLVSS were significantly reduced from 8410 mg/L to 5175 mg/L during the first week of the addition of 125 mg/L m-CP, while, thereafter, biosolids were restored to the level prior to uncoupler’s addition. Adding m-CP resulted in more severe effects on nitrifiers rather than organoheterotrophs. Both alkalinity, dissolved oxygen (DO), electrical conductivity (EC) and pH data evidenced the adverse effect of m-CP on the nitrification process. PO43--P concentration drastically raised immediately after m-CP addition from 2.48 ± 0.35 mg/L to 11.84 mg/L, possibly due to the uncoupling of P-release and the hydrolysis of phosphorus reserves. Diversity was highly affected by the addition of m-CP, resulting in the significant decrease of Chao1, Shannon and Fisher indices. By establishing stable operating conditions after m-CP addition, Pseudomonas, Arcanobacterium, Trichococcus, Kocuria and Actinobaculum raised from almost undetectable levels (0.12 % of the total relative abundance) to 35.9 %, 17.8 %, 15.1 %, 11.5 % and 5.7 %, respectively, indicating a massive shift in bacterial community structure, while no nitrifying taxa were detected after m-CP addition.

Assessment of soil salinity using explainable machine learning methods and Landsat 8 images

The aim of this study is to comparatively analyze the performance of machine learning (ML) algorithms for modeling soil salinity using field-based electrical conductivity (EC) data and Landsat-8 OLI satellite images with derived environmental covariates. We also aim to interpret and explain the ML models with and without over-sampling methods using Shapley (SHAP) values, an explainable ML approach that has not yet been utilized for soil salinity estimation tasks as an ML problem. We investigate two case study areas from western and southeastern Lake Urmia Playas (LUP) in the Northwest of Iran. Our study uses 26 environmental covariates, two ML models, namely extreme gradient boosting (XGBoost) and random forest (RF), and two over-sampling methods: synthetic minority over-sampling technique (SMOTE) and random over-sampling (ROS). Results indicate that XGBoost performs better compared to RF in terms of both R2 and RMSE. Additionally, the visual interpretation of soil salinity maps demonstrated the superiority of XGBoost. SMOTE produced superior results than ROS and no over-sampling test cases. Finally, SHAP analysis illustrated that vegetation indices made a greater contribution to the soil salinity prediction in the West LUP, while visible bands contributed more in the Southeast LUP Region.

Technical note: Two-component electrical-conductivity-based hydrograph separation employing an exponential mixing model (EXPECT) provides reliable high-temporal-resolution young water fraction estimates in three small Swiss catchments

Abstract. The young water fraction represents the portion of water molecules in a stream that have entered the catchment relatively recently, typically within 2–3 months. It can be reliably estimated in spatially heterogeneous and nonstationary catchments from the amplitude ratio of seasonal isotope (δ18O or δ2H) cycles of stream water and precipitation, respectively. Past studies have found that young water fractions increase with discharge (Q), thus reflecting the higher direct runoff under wetter catchment conditions. The rate of increase in the young water fraction with increasing Q, defined as the discharge sensitivity of the young water fraction (Sd*), can be useful for describing and comparing catchments' hydrological behaviour. However, the existing method for estimating Sd*, which only uses biweekly isotope data, can return highly uncertain and unreliable Sd* when stream water isotope data are sparse and do not capture the entire flow regime. Indeed, the information provided by isotope data depends on when the respective sample was taken. Accordingly, the low sampling frequency results in information gaps that could potentially be filled by using additional tracers sampled at a higher temporal resolution. By utilizing high-temporal-resolution and cost-effective electrical conductivity (EC) measurements, along with information obtainable from seasonal isotope cycles in stream water and precipitation, we develop a new method that can estimate the young water fraction at the same resolution as EC and Q measurements. These high-resolution estimates allow for improvements in the estimates of the Sd*. Our so-called EXPECT (Electrical-Conductivity-based hydrograph separaTion employing an EXPonential mixing model) method is built upon the following three key assumptions: We construct a mixing relationship consisting of an exponential decay of stream water EC with increasing young water fraction. This has been obtained based on the relationship between flow-specific young water fractions and EC. We assume that the two-component EC-based hydrograph separation technique, using the above-mentioned exponential mixing model, can be used for a time-source partitioning of stream water into young (transit times &lt; 2–3 months) and old (transit times &gt; 2–3 months) water. We assume that the EC value of the young water endmember (ECyw) is lower than that of the old water endmember (ECow). Selecting reliable values from measurements of ECyw and ECow to perform this unconventional EC-based hydrograph separation is challenging, but the combination of information derived from the two tracers allows for the estimation of endmembers' values. The two endmembers have been calibrated by constraining the unweighted and flow-weighted average young water fractions obtained with the EC-based hydrograph separation to be equal to the corresponding quantities derived from the seasonal isotope cycles. We test the EXPECT method in three small experimental catchments in the Swiss Alptal Valley using two different temporal resolutions of Q and EC data: sampling resolution (i.e. we only consider Q and EC measurements during dates of isotope sampling) and daily resolution. The EXPECT method has provided reliable young water fraction estimates at both temporal resolutions, from which a more accurate discharge sensitivity of the young water fraction (SdEXP) could be determined compared with the existing approach. Also, the method provided new information on ECyw and ECow, yielding calibrated values that fall outside the range of measured EC values. This suggests that stream water is always a mixture of young and old water, even under very high or very low wetness conditions. The calibrated endmembers revealed a good agreement with both endmembers obtained from an independent method and EC measurements from groundwater wells. For proper use of the EXPECT method, we have highlighted the limitations of EC as a tracer, identified certain catchment characteristics that may constrain the reliability of the current method and provided recommendations about its adaptation for future applications in catchments other than those investigated in this study.

Mapping saltwater intrusion via Electromagnetic Induction (EMI) for planning a Managed Aquifer Recharge (MAR) facility in Maltese Island

In coastal areas, saltwater intrusion causes a depletion of the resource by reducing potable and irrigation freshwater supplies and causing severe deterioration of groundwater quality. This trend is observed in Pwales Valley, in the North part of Malta where the management of water resources plays a crucial role for the environmental sustainability of the area, given the importance of intensive agricultural activity along this valley. In order to tackle such phenomenon, actions or adaptation measures against climate change are strongly required. For example, Managed Aquifer Recharge (MAR) is an increasingly important water management strategy to maintain, enhance and secure stressed groundwater systems and to protect and improve water quality. To accurately plan a Managed Aquifer Recharge scheme, it is crucial to define a hydrogeological model of the studied area, with the use of traditional hydrogeological measurements and innovative unconventional techniques. In recent years, Electromagnetic Induction measurements, based on induction of em fields, have been increasingly used for investigating the saltwater intrusion dynamics due to their high sensitivity to the salinity. In the study area of Pwales Valley, a Managed Aquifer Recharge scheme is being planned and, for this aim, a hydrogeological model has been developed through an Electromagnetic Induction survey. More than 20,000 apparent electrical conductivity (ECa) data were collected to generate a quasi 3D high-resolution model of electrical conductivity of the Pwales Valley. The results highlighted the spatial extension of the tongue-shape salt water intrusion from east to west along the valley, as well as some geological-hydrogeological peculiarities such as the thickness of the salt wedge and the irregular top surface of the bottom impermeable layer, otherwise undetectable with other direct techniques at the field scale resolution. The approach was confirmed to be a useful tool for an effective hydrogeological characterisation, essential for planning adaptation measures to a changing climate, such as the implementation of a Managed Aquifer Recharge scheme.

Investigation on NTC/PTC effects of cement-based self-heating composites with varied conductive filler contents

The present study systematically investigated the influence of varied conductive filler contents on the negative/positive temperature coefficient (NTC/PTC) effects in cement-based self-heating composites. Different composite formulations containing varying proportions of carbon nanotubes (CNT) and carbon fiber (CF) were prepared and subjected to self-heating tests at different input voltages. Analysis of temperature and electrical conductivity data obtained during the tests elucidated the NTC/PTC effects. Additionally, diverse analytical techniques were employed to characterize the physicochemical properties of the samples. Results indicated a correlation between NTC and PTC effects and thermal expansion as well as variations in electrical resistivity with increasing temperature. Moreover, a specific temperature and electrical resistivity range is identified where the NTC effect transitions to the PTC effect, a transition range influenced by the conductive filler content. Enhanced heat-generation accelerated the PTC effect by inducing structural alterations in the sample's physicochemical composition.

The Threat of Saltwater Intrusion on Rice Farming in Katingan I Lowland Irrigation Area, Central Kalimantan

The Katingan I Lowlands Irrigation Area (LIA) is one of tidal lowlands irrigation area in Central Kalimantan, Indonesia. Because the Katingan I LIA utilizes water from the estuary, the occurence of saltwater intrusion is likely to occur. Assessing water salinity due to saltwater intrusion provides essential information for farmers to manage water appropriately. In addition, this information can also be used by the government to develop policies and management strategies for Katingan I LIA. Saltwater intrusion that occurs when sea water flows into irrigation canals and agricultural land can lead to increased salinity. High salinity levels can affect agricultural productivity, especially in rice crops. Therefore, a thorough salinity study is needed to support the development of rice farming. This study aims to evaluate salinity levels due to saltwater intrusion and understand the factors affecting them. The study measured tidal (water level elevation), electrical conductivity (EC), and salinity data of the Katingan River and several locations in the primary and secondary channels. Data collection methods included continuous and instantaneous measurements using portable data logger installations and handheld devices. The existing water salinity conditions at Katingan I LIA obtained the maximum water salinity value from the three locations of 14,536 ppm and the lowest water salinity value of 3.02 ppm. The maximum water salinity value that enters the primary canal is 5,547 ppm, higher than the thershold salinity value for rice farming (5,120 ppm). Therefore, anticipatory measuers must be conducted to reduce salinity intrusion, such as optitmizing water channels, making water gates, and managing the water use efficiently. It is also recommended that measurements be carried out during the dry season to see the comparison of results and the magnitude of the maximum water salinity value that occurs because salinity problems occur more during the dry season

Hydrological dynamics of snowmelt induced streamflow in a high mountain catchment of the Pyrenees under contrasting snow accumulation and duration years

AbstractSnowmelt drives a large portion of streamflow in many mountain areas of the world. However, the water paths from snowmelt to the arrival of the water in the streams are still largely unknown. This work analyzes for first time the influence of snowmelt on spring streamflow with different snow accumulation and duration, in an alpine catchment of the central Spanish Pyrenees. This study presents the water balance of the main melting months (May and June). Piezometric values, water temperature, electrical conductivity and isotope data (δ18O) allow a better understanding of the hydrological functioning of the basin during these months. Results of the water balance calculations showed that snow represented on average 73% of the water available for streamflow in May and June while precipitation during these months accounted for only 27%. However, rainfall during the melting period was important to determine the shape of the spring hydrographs. On average, 78% of the sum of both the snow water equivalent (SWE) accumulated at the beginning of May and the precipitation in May and June converted into runoff during the May–June melting period. The average evaporation‐sublimation during the 2 months corresponded to 8.4% of the accumulated SWE and rainfall, so that only a small part of the water input was ultimately available for soil and groundwater storage. When snow cover disappeared from the catchment, soil water storage and streamflow showed a sharp decline. Consequently, streamflow electrical conductivity, temperature and δ18O showed a marked tipping point towards higher values. The fast hydrological response of the catchment to snow and meteorological fluctuations, as well as the marked diel fluctuations of streamflow δ18O during the melting period, strongly suggests short meltwater transit times. As a consequence of this hydrological behaviour, independently of the amount of snow accumulated and of melting date, summer streamflow remained always low, with only small runoff peaks driven by rainfall events.

Assessing shallow slope stability using electrical conductivity data and soil hydraulic characteristics

In-situ slope monitoring techniques can be used to observe hydrological and mechanical processes in soil, identify the development of unstable slope areas, and provide information for slope stability models. In recent years, the combination of hydrogeological surveys and geophysical monitoring methods has enabled us to obtain the geotechnical and hydrological propertied associated with landslides. However, the highly heterogeneous subsurface settings make it challenging to correlate geophysical monitoring data with soil engineering properties. In this study, we investigated the relationship between soil water content and electrical conductivity, and then associated it with the soil water characteristic curve and suction stress characteristic curve obtained by laboratory tests to derive the soil water potential–electrical conductivity curve and suction stress–electrical conductivity curve. Then, we extended the shear strength model for unsaturated soils to correlate the shear strength model with the matric suction and electrical conductivity. To verify the model rationality, we adopted the finite element analysis model HYDRUS-2D and Slope Cube Module to solve the variably saturated flow and stress problems and used the obtained local safety factor to evaluate the slope stability. The shear strength model developed in this study was applied to estimate the changes in shear strength at the study site, and the results were compared with in-situ displacement observations. We found that the shear strength model can indicate shallow slope failures caused by increased soil water content. The slope stability analysis revealed that the variation trend of the local safety factor is consistent with that of the shear strength, indicating that the shear strength model established in this study with electrical conductivity as a variable can reasonably evaluate slope stability, and is also suitable for analysis related to the hydraulic properties of unsaturated soils.

Structural, optical, and impedance spectroscopy of the pseudobrookite Pb0·5Ba0·5Fe2O5 synthesized by sol–gel route

Pseudobrookite of general formula Pb0·5Ba0·5Fe2O5 was synthesized by the sol–gel route. X-ray diffraction confirms the orthorhombic Pnma space group of our sample. UV–Vis absorption spectroscopy was used to characterize this material's optical properties. We used the Tauc model and absorption measurements to estimate the direct optical band gap at 3.53 eV. We also calculate the Urbach energy, the optical extinction coefficient, and the refractive index. In addition, the skin depth, optical conductivity, and Cauchy parameters were investigated in relation to the incident photon's wavelength. Electrical conductivity data flow the Jonscher's power law and show that PBFO has two different conducts; Semiconductor behavior in the temperatures region [400 K–520 K]. Then, a metallic trend was detected beyond TS-M = 520 K. The correlated barrier hopping (CBH) model is the appropriate model to describe the conduction process in low temperature range. On the other hand, the conduction is ensured by the non-overlapping small polaron tunneling (NSPT) at high temperature zone. The scaling study shows that the conductivity spectra deviate from Summerfield and Ghosh scaling. The random barrier model (RBM) is employed to correct the Summerfield approach and we note that the conductivity isotherms are combined into a single master curve. The estimated activation energies values from dc-conductivity, hopping frequency and relaxation time are very close. The behavior of dielectric parameters was examined using the Maxwell-Wagner theory of interfacial polarization. The dielectric-relaxation phenomenon is shown by the behaviors of imaginary parts of impedance (Z″) and modulus (M″). The ideal electrical equivalent circuit for simulating the Nyquist curves (i.e. Z′′(Z′)) for our pseudobrookite is (Rg + Rgb//CPEgb). Finally, the entropy (ΔS), and enthalpy (ΔH) were established as thermodynamic parameters.