A salinity gradient solar pond (SGSP) is a large and deep artificial basin of layered brine, that collects and stores simultaneous solar energy for use in various applications. Experimental and theoretical studies have been launched to understand the thermal behavior of SGSPs, under different operating conditions. This article then traces the history of SGSPs, from their natural discovery to their current artificial applications and the progress of studies and research, according to their chronological sequence, in terms of determining their physical and dynamic aspects, their operation, management, and maintenance. It has extensively covered the theoretical and experimental studies, as well as the direct and laboratory applications of this technology, especially the most famous and influential in this field, classified according to the aspect covered by the study, with a comparison between the different results obtained. In addition, it highlighted the latest methods to improve the performance of an SGSP and facilitate its operation, such as the use of a magnetic field and the adoption of remote data acquisition, with the aim of expanding research and enhancing the benefit of this technology.

In this paper, an improved mathematical model for flashover behavior of polluted insulators is proposed based on experimental tests. In order to determine the flashover model of polluted insulators, the relationship between conductivity and salinity of solution pollution layer of the insulator is measured. Then, the leakage of current amplitude of four common insulators versus axial, thermal conductivity and arc constants temperature was determined. The experimental tests show that top leakage distance (TLd) to bottom leakage distance (BLd) ratio of insulators has a significant effect on critical voltage and current. Therefore, critical voltage and current were modeled by TLd to BLd ratio Index (M). Also, salinity of solution pollution layer of the insulators has been applied to this model by resistance pollution parameter. On the other hand, arc constants of each insulator in new model have been identified based on experimental results. Finally, a mathematical model is intended for critical voltage against salinity of solution pollution layer of different insulators. This model depends on insulator profile. There is a good agreement between the experimental tests of pollution insulators obtained in the laboratory and values calculated from the mathematical models developed in the present study.

Soil salinization is a difficult challenge for agricultural productivity and environmental sustainability, particularly in arid and semi-arid coastal regions. This study investigates the spatial variability of soil electrical conductivity (EC) and its relationship with key cations and anions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, CO₃²⁻, HCO₃⁻, SO₄²⁻) along the southeastern coast of the Caspian Sea in Iran. Using a combination of field-based soil sampling, laboratory analyses, and Landsat 8 spectral data, linear Multiple Linear Regression and Partial Least Squares Regression (MLR, PLSR) and nonlinear Artifician Neural Network and Support Vector Machine (ANN, SVM) modeling approaches were employed to estimate and map soil EC. Results identified Na⁺ and Cl⁻ as the primary contributors to salinity (r = 0.78 and r = 0.88, respectively), with NaCl salts dominating the region’s soil salinity dynamics. Secondary contributions from Potassium Chloride KCl and Magnesium Chloride MgCl₂ were also observed. Coastal landforms such as lagoon relicts and coastal plains exhibited the highest salinity levels, attributed to geomorphic processes and anthropogenic activities. Among the predictive models, the SVM algorithm outperformed others, achieving higher R² values and lower RMSE (RMSE_Test = 27.35 and RMSE_Train = 24.62, respectively), underscoring its effectiveness in capturing complex soil-environment interactions. This study highlights the utility of digital soil mapping (DSM) for assessing soil salinity and provides actionable insights for sustainable land management, particularly in mitigating salinity and enhancing agricultural practices in vulnerable coastal systems.

The biomass of three dominant mangrove species (Sonneratia apetala, Avicennia alba and Excoecaria agallocha) in the Indian Sundarbans, the designated World Heritage Site was evaluated to understand whether the biomass vary with spatial locations (western region vs. central region) and with seasons (pre-monsoon, monsoon and post-monsoon). The reasons for selecting these two regions and seasons are the contrasting variation in salinity. Among the three studied species, Sonneratia apetala showed the maximum biomass followed by Avicennia alba and Excoecaria agallocha. We also observed that the biomass varied significantly with spatial locations (p<0.05), but not with seasons. The variation may be attributed to different environmental conditions to which these forest patches are exposed to.

Soil salinity is a major abiotic stress that drastically hinders plant growth and development, resulting in lower crop yields and productivity. As one of the most consumed vegetables worldwide, tomato (Solanum lycropersicum L.) plays a key role in the human diet. The current study aimed to explore the differential tolerance level of two tomato varieties (Rio Grande and Agata) to salt stress. To this end, various growth, physiological and biochemical attributes were assessed after two weeks of 100 mM NaCl treatment. Obtained findings indicated that, although the effects of salt stress included noticeable reductions in shoots’ and roots’ dry weights and relative growth rate as well as total leaf area, for the both cultivars, Rio Grande performed better compared to Agata variety. Furthermore, despite the exposure to salt stress, Rio Grande was able to maintain an adequate tissue hydration and a high leaf mass per area (LMA) through the accumulation of proline. However, relative water content, LMA and proline content were noticeably decreased for Agata cultivar. Likewise, total leaf chlorophyll, soluble proteins and total carbohydrates were significantly decreased; whereas, malondialdehyde was significantly accumulated in response to salt stress for the both cultivars. Moreover, such negative effects were remarkably more pronounced for Agata relative to Rio Grande cultivar. Overall, the current study provided evidence that, at the early growth stage, Rio Grande is more tolerant to salt stress than Agata variety. Therefore, Rio Grande variety may constitute a good candidate for inclusion in tomato breeding programs for salt-tolerance and is highly recommended for tomato growers, particularly in salt-affected fields.

To investigate the possible role of arbuscular mycrrhizal fungi (AMF) in alleviating the negative effects of salinity on Stevia rebaudiana (Bert.), the regenerated plantlets in tissue culture was transferred to pots in greenhouse and inoculated with Glomus intraradices. Salinity caused a significant decrease in chlorophyll content, photosynthesis efficiency and enhanced the electrolyte leakage. The use of AMF in salt –affected plants resulted in improved all above mentioned characteristics. Hydrogen peroxide and malondialdehyde (MDA) contents increased in salt stressed plants while a reduction was observed due to AMF inoculation. CAT activity showed a significant increase up to 2 g/l and then followed by decline at 5 g/l NaCl in both AMF and non-AMF treated stevia, however, AMF inoculated plants maintained lower CAT activity at all salinity levels (2 and 5 g/l). Enhanced POX activities in salt- treated stevia plants were decreased by inoculation of plants with AMF. The addition of NaCl to stevia plants also resulted in an enhanced activity of SOD whilst, AMF plants maintained higher SOD activity at all salinity levels than those of non-AMF inoculated plants. AMF inoculation was capable of alleviating the damage caused by salinity on stevia plants by reducing oxidative stress and improving photosynthesis efficiency.