Soil electrical resistivity is a fundamental parameter in various geotechnical, agricultural, environmental, and engineering applications, as it directly depends on the soil’s moisture content and physical properties. Understanding this relationship is crucial for improving the safety and efficiency of electrical installations. This study analyzes the relationship between soil electrical resistivity and gravimetric moisture content in three soil types, sandy, clayey, and silty, with the aim of comparing the performance of different predictive models under controlled laboratory conditions. Seven fitting models were evaluated, Logarithmic Spline, Radial Basis Function (RBF), Locally Estimated Scatterplot Smoothing (LOESS), Least Absolute Shrinkage and Selection Operator (LASSO), Ridge Regression (RIDGE), Power Law and a segmented equation, using metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and coefficient of determination $R^2$ . The Spline and RBF models showed excellent accuracy and near-zero errors in all soils, although their applicability is limited by the lack of an explicit formulation and by the fact that, as interpolation methods, they do not guarantee predictive capacity outside the experimental dataset. Therefore, their use should be restricted to controlled laboratory conditions, as field variability factors can significantly alter soil resistivity responses. Among the explicit models, the Segmented Equation obtained a MAPE of 6.14% (sandy), 15.1% (clayey), and 13.16% (silty), with $R^2$ values of 0.91, 0.93, and 0.89, respectively, demonstrating good performance and functionality. The Power Law model, although showing an $R^2$ close to 0.96, presented significant overestimations, especially in silty soils (MAPE > 187%). The LASSO model yielded inconsistent predictions with percentage errors exceeding 120% in silty soils. In conclusion, nonparametric models provide excellent accuracy, while the segmented equation stands out as the best explicit alternative for estimating resistivity with reasonable precision.

A grounding system (GS) is an indispensable component in an electrical system network, as it is responsible for conducting electrical discharges to the ground due to faults caused by lightning strikes or transient system failures. Globally, it is estimated that 40 lightning strikes occur per second on the planet, amounting to around 1.2 billion per year, resulting in daily losses of various electrical equipment and human fatalities ranging from 6,000 to 24,000. Additionally, soil resistivity, which impedes the flow of electricity from electrical discharges into the ground, leads to inadequate mitigation of electrical overload effects, resulting in poor GS performance. Consequently, the implementation of ground enhancement materials (GEMs) to reduce impedance to optimal levels becomes necessary. The objective of this review is to broadly examine the current status of GEMs reported in the literature for use in GS, focusing on their composition and their effectiveness in improving soil conductivity and dissipating electrical currents as well as to identify emerging trends and current challenges in the development and application of these materials, in order to provide information to guide future research in the design and implementation of efficient and safe GS.

Soil electrical resistivity is a fundamental property in various engineering applications, such as electrical, geotechnical or geophysical; its application can even be extended to those aspects related to agriculture. On the other hand, worldwide, there are soils with high resistivity. In the Middle East, for example, there are high resistivity values ​​that range between 10,000 Ωcm and 200,000 Ωcm (ohm per centimeter). In West Africa, desert soils reach up to 30,000 Ωm. Also, in some Asian countries, resistivity values ​​​​of up to 200,000 Ωm have been measured. Furthermore, various studies have shown that there is an inverse relationship between resistivity and soil humidity content. Thus, to counteract the negative effects due to the high resistivity of soils, Ground Enhancement Material (GEM) have been developed, composed mainly of materials with high hygroscopicity and low resistivity. The objective of this article was to investigate the relationship between electrical resistivity and humidity incorporation in the development of a GEM. Combinations of different chemical materials such as magnesium sulfate (MgSO₄), sodium sulfate (Na₂SO₄) and sodium carbonate (Na₂CO₃), combined with bentonite clay, were studied. The mixtures were evaluated through laboratory tests to determine their electrical resistivity by varying the humidity between 30% and 60% at different frequencies. The mixture containing 100% Na₂SO₄ was found to have the lowest resistivity, as varying the humidity content from 30 to 60% reduced the resistivity from 58 Ωcm to 23 Ωcm. The results obtained can provide researchers, engineers, and specialists with the potential for the developed GEM to be used in soils with varying humidity conditions in different systems, depending on the frequency at which electrical resistivity is measured.

Grounding Systems (GS) play a critical role in electrical safety, lightning protection, and the reliable operation of power and renewable energy infrastructures, particularly in high-resistivity soils. In this context, Ground Enhancement Materials (GEM) are widely used to reduce soil resistivity and improve grounding performance. This systematic review analyzes and synthesizes recent advances (2018–2025) in GEM applied to GS, with emphasis on their electrical performance, durability, and environmental sustainability. The review covers conventional GEM, industrial waste-derived materials, and hybrid formulations, evaluating their effectiveness under different soil types and moisture conditions. Comparative analysis of the literature indicates that GEM derived from industrial byproducts and hybrid composites often exhibit superior long-term resistivity reduction due to enhanced moisture retention and material-soil interactions, especially in clay-rich and heterogeneous soils. Sustainability considerations such as environmental impact, material availability, and long-term stability are increasingly influencing GEM selection and design. Overall, this review provides a structured framework for understanding the factors governing GEM performance while highlighting current trends, challenges, and future research directions in the development of sustainable grounding solutions.

Soil electrical resistivity (SER) is widely used as an indirect indicator of soil physical, chemical, and hydrological properties and plays an important role in applications such as grounding system design, geotechnical site characterization, agricultural soil monitoring, and environmental contamination assessment. However, SER is strongly influenced by environmental variables including soil moisture content, temperature, salinity, and soil texture, which makes accurate prediction challenging under heterogeneous field conditions. A systematic review was conducted following the PRISMA 2020 protocol using the Scopus database to identify peer-reviewed studies published between 2018 and 2026 related to predictive models of soil electrical resistivity based on environmental parameters. After applying defined inclusion and exclusion criteria, a set of relevant studies was selected for qualitative and comparative analysis. The reviewed studies consistently identify soil moisture content as the most frequently reported influential factor affecting SER, followed by temperature, salinity, and soil texture. This observation reflects the predominant focus of the analyzed literature within the selected time frame rather than a definitive representation of all controlling physical processes. Similarly, the reviewed literature suggests that empirical and statistical models remain valuable due to their simplicity and interpretability, whereas machine learning approaches such as artificial neural networks, support vector regression, and ensemble methods are often reported to achieve higher predictive accuracy in complex soil environments. The predictive SER modeling represents a rapidly evolving research field, and future work should focus on hybrid physics-informed machine learning models, the development of standardized datasets, and the integration of predictive algorithms with emerging sensing technologies and IoT-based monitoring systems.

The construction sector is responsible for significant global energy consumption and CO₂ emissions, largely driven by carbon-intensive materials such as ordinary Portland cement and steel. In response to increasing decarbonization and circular economy demands, several strategically relevant categories of sustainable construction materials have been developed, particularly natural and bio-based systems, recycled and waste-derived materials, low-carbon cementitious binders, and emerging multifunctional composites. However, research remains fragmented across material classes and performance metrics. This systematic review evaluates advances published between 2018 and 2026 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 methodology. Peer-reviewed studies were systematically identified and analyzed to compare mechanical performance, durability, embodied carbon reduction, and life-cycle environmental impacts across these selected material pathways. The results indicate substantial decarbonization potential. Low-carbon cementitious materials report CO₂ reductions of approximately 10–75% relative to conventional systems, while engineered timber and bamboo demonstrate 28–70% lower carbon footprints due to reduced embodied energy and biogenic carbon storage. Recycled aggregates and industrial by-products enhance circularity but remain sensitive to transport distance and processing intensity. Trade-offs between mechanical capacity and environmental performance are evident in lightweight and bio-based systems. Overall, sustainability gains are maximized through integrated hybrid construction strategies rather than isolated material substitution. This review provides a comparative evidence-based synthesis and identifies key research gaps and implementation challenges for accelerating low-carbon construction.