Most water systems that support ecosystems and feed humans are depleted or stressed. Aquifer characteristics, topography, subsurface activities, climate, and geochemical processes regulate groundwater availability, a reliable source of fresh water. Globally, agriculture, industries, and the domestic sector are the three major sectors that consume vast quantities of freshwater resources. Further anthropogenic activities, such as soil leaching, acid rain, fertilizer, pesticides, mining, and other industrial activities, resulted in the release of organic and inorganic pollutants that affected global water resources. In India, groundwater is used in huge quantities, resulting in groundwater depletion of 1 to 2 m a year. Low-income countries face many issues related to water pollution, and the availability of safe water is minimal. In 2019, deaths due to unsafe sanitation accounted for 2.2% of the total global deaths, amounting to 1.2 million people’s deaths. India recorded 6.6% of deaths due to unsafe sanitation in 2019. India and China accounted for around 90.41% and 60.4% of the groundwater utilization for agricultural purposes, respectively. In 2020, China and India utilized vast quantities of nutrients (nitrate and phosphate) for crop growth to enhance crop yield, resulting in the highest nitrate and phosphate concentrations in groundwater. Remediating contaminants from different sources requires knowledge of their concentration, behavior, cycling, and degradation pathways. According to safety guidelines, limiting and optimizing crop organic and inorganic fertilizer, pesticide waste disposal, and empty container disposal can reduce groundwater contamination. The present study summarized groundwater utilization in various sectors, potential sources of groundwater contamination impacts on human health and the environment, preventive measures, and mitigation methods to overcome groundwater pollution.

This paper introduces a new algorithm called Manifold Reconstruction Unitary ESPRIT (MR-UESPRIT) for accurately estimating the direction-of-arrival (DOA). The algorithm combines manifold reconstruction and unitary ESPRIT to overcome the limitations of traditional DOA estimation methods. In this approach, two smaller overlapping subarraysare used to derive a rotational invariance equation, which helps recover the array manifold matrix. As a result, the DOA estimation problem is divided into K˗ individual single-source DOA estimation problems. Each DOA is estimated by minimizing a nonlinear least squares fitting criterion using a computationally efficient Newton's method. Computer simulations are presented to demonstrate the effectiveness of the MR-UESPRIT method compared to standard DOA estimation methods.

Target recognition and localization in communication systems present significant challenges. Often, computationally expensive algorithms that utilize the entire sensor array are necessary. In this letter, we propose a novel methodology that leverages spectral factorization to address these challenges. By employing the Nystrom method on a randomly selected subset of array sensor outputs, we construct an advanced fast-modified root-MUSIC algorithm. This approach enables the efficient detection and localization of multiple narrowband far-field sources with enhanced resolution and reduced computational complexity. Through extensive computer simulations, we demonstrate that our proposed method achieves estimation performance comparable to traditional root-MUSIC techniques while utilizing only one-fourth of the sensor array outputs. By integrating spectral factorization and the Nystrom method, our methodology effectively mitigates computational overhead, providing researchers with a compelling solution for precise target detection and localization in communication systems.