Search Results (5,944)

Throughout history, humans have modified the environment, transforming natural biomes into agricultural areas. In the 1990s, economic policies accelerated the expansion of agricultural frontiers in Brazil, including the Triângulo Mineiro and Alto Paranaíba regions. This study analyzes rainfall variability from 1990 to 2021 and its relationship with land use. For this purpose, satellite data from MapBiomas, ERA5, and NASA POWER were processed using Google Earth Engine and QGIS. Statistical methods included the Spearman correlation and the Mann–Kendall trend test. The results revealed that average annual precipitation decreased from 1663.35 mm in 1991 to 1128.94 mm in 2022—a 32.14% reduction. Simultaneously, agricultural and urban areas increased by 365% and 237.59%, respectively. Spearman analysis showed negative correlations between precipitation and agriculture (ρ = −0.51) and urbanization (ρ = −0.51), and positive correlations with pasture (ρ = +0.52) and water bodies (ρ = +0.46). These trends suggest that land use intensification significantly affects regional rainfall patterns. Unlike studies focusing mainly on Amazon deforestation, this research emphasizes the Cerrado biome’s climatic vulnerability. The use of long-term, high-resolution remote sensing data allows a robust analysis of land use impacts. By highlighting a clear link between land transformation and precipitation decline, this study offers insights for policymaking aimed at balancing agricultural development and water resource preservation. This research underscores the importance of sustainable land management practices, such as agroecology, reforestation, and ecological corridors, for regional climate resilience. Full article

This paper investigates the optimization of an irrigation system distributed over an agricultural area discretized into unit cells, using evolutionary algorithms for the control of water irrigation points (taps). The model simulates the distribution of water through strategically placed irrigation points, considering the individual requirements of each cell. The main objective is to minimize the difference between the amount of water needed and delivered, while reducing the total consumption. The dynamics of fitness over generations are analyzed, as well as the average behavior of deficit, surplus, and relative humidity. The results highlight a relatively uniform distribution of delivered water and a stable convergence of the fitness function, demonstrating the efficiency of the proposed method in managing water resources in a sustainable way. In this matter, compared to the full-activation scenario, the presented model reduced total water use by more than 50%, achieving zero deficit, minimal surplus, and a 46% improvement in overall fitness. Although the approach demonstrates promising results in simulated scenarios, it does not currently incorporate real-time sensor data or field validation, which are planned for future development. The study provides a solid basis for the development of smart irrigation systems, adaptable to the variability of soil and climatic conditions. Full article

The Internet of Things (IoT) has become an integral part of today’s smart and digitally connected world. IoT devices and technologies now connect almost every aspect of daily life, generating, storing, and analysing vast amounts of data. One important use of IoT is in utility management, where essential services such as water are supplied through IoT-enabled infrastructure to ensure fair, efficient, and sustainable delivery. The large volumes of data produced by water distribution networks must be safeguarded against manipulation, theft, and other malicious activities. Incidents such as the Queensland user data breach (2020–21), the Oldsmar water treatment plant attack (2021), and the Texas water system overflow (2024) show that attacks on water treatment plants, distribution networks, and supply infrastructure are common in Australia and worldwide, often due to inadequate security measures and limited technical resources. Lightweight cryptographic algorithms are particularly valuable in this context, as they are well-suited for resource-constrained hardware commonly used in IoT systems. This study focuses on the in-house developed ChaosFortress lightweight cryptographic algorithm, comparing its performance with other widely used lightweight cryptographic algorithms. The evaluation and comparative testing used an Arduino and a LoRa-based transmitter/receiver pair, along with the NIST Statistical Test Suite (STS). These tests assessed the performance of ChaosFortress against popular lightweight cryptographic algorithms, including ACORN, Ascon, ChaChaPoly, Speck, tinyAES, and tinyECC. ChaosFortress was equal in performance to the other algorithms in overall memory management but outperformed five of the six in execution speed. ChaosFortress achieved the quickest transmission time and topped the NIST STS results, highlighting its strong suitability for IoT applications. Full article

Hibiscus sabdariffa (H. sabdariffa) is a high-value economic and functional crop, limited by agroclimatic conditions and low technological adoption. This systematic review examines the current state of artificial intelligence applications in agricultural management, analyzing 2111 records, selecting 82, and synthesizing 22 studies that meet the inclusion criteria. This review adopts a holistic framework aligned with three priority areas in agriculture—resource and climate management, crop productivity and quality, and sustainability—to explore how AI addresses key challenges in the cultivation and post-harvest processing of Hibiscus sabdariffa. The results show a predominance of classical machine learning techniques, with limited implementation of deep learning models. The most common applications include image classification, yield prediction, and analysis of bioactive compounds. However, limitations remain in the availability of open data, reproducible code, and standardized metrics. The narrative synthesis identified clear opportunities to integrate emerging technologies, such as deep neural networks and the Internet of Things (IoT), particularly in water management and stress monitoring. The review concludes that strengthening interdisciplinary research and promoting data openness is key to achieving a more resilient, sustainable, and technologically advanced crop. Full article

This study addresses the effects of climate variability and land-use change on groundwater recharge in Major Groundwater Reservoir 406 (MGR 406) in southeastern Poland, a key strategic water resource. It focuses on how regional shifts in precipitation patterns and spatial development influence the volume and distribution of renewable groundwater resources. The analysis integrates meteorological data (1951–2024), groundwater modeling outputs, groundwater-use data, and land cover changes from CORINE datasets (1990–2018). A spatial assessment of hydrogeological conditions was performed using the Groundwater Resources Assessment Index (GRAI), combining drought frequency, recharge conditions, land-use classes, and groundwater extraction levels. Results indicate a long-term increase in annual precipitation alongside more frequent but shorter drought episodes. Urban expansion and land sealing were found to reduce infiltration efficiency, particularly in and around the city of Lublin, where the highest extraction rates were recorded. The assessment identified several zones of high threat to groundwater resources, which have no sufficient legal protection. These findings highlight the need to integrate groundwater management into local spatial planning and land management strategies. The study concludes that balancing water use and recharge potential under evolving climate and land-use pressures are essential to ensuring the sustainability of groundwater resources in MGR 406. Full article

Groundwater is essential for irrigated agriculture, yet its use remains unsustainable in many regions worldwide. In countries like Pakistan, the situation is particularly pressing. The irrigated agriculture of Pakistan heavily relies on groundwater resources owing to limited canal-water availability. The groundwater quality in the region ranges from good to poor, with the lower-quality water adversely affecting soil structure and plant health, leading to reduced agricultural productivity. The delineation of quality zones with respect to irrigation parameters is thus crucial for optimizing its sustainable use and management. Therefore, this research study was carried out in the Lower Chenab Canal (LCC) irrigation system to assess the spatial distribution of groundwater quality. The geostatistical analysis was conducted using Gamma Design Software (GS+) and the Kriging interpolation method was applied within a Geographic Information System (GIS) framework to generate groundwater-quality maps. Semivariogram models were evaluated for major irrigation parameters such as electrical conductivity (EC), residual sodium carbonate (RSC), and sodium adsorption ratio (SAR) to identify the best fit for various Ordinary Kriging models. The spherical semivariogram model was the best fit for EC, while the exponential model best suited SAR and RSC. Overlay analysis was performed to produce combined water-quality maps. During the pre-monsoon season, 17.83% of the LCC area demonstrated good irrigation quality, while 42.84% showed marginal quality, and 39.33% was deemed unsuitable for irrigation. In the post-monsoon season, 17.30% of the area had good irrigation quality, 44.53% exhibited marginal quality, and 38.17% was unsuitable for irrigation. The study revealed that Electrical Conductivity (EC) was the primary factor affecting water quality, contributing to 71% of marginal and unsuitable conditions. In comparison, the Sodium Adsorption Ratio (SAR) accounted for 38% and Residual Sodium Carbonate (RSC) contributed 45%. Therefore, it is recommended that groundwater in unsuitable zones be subjected to artificial recharge methods and salt-tolerated crops to enhance its suitability for agricultural applications. Full article

This study provides a comprehensive assessment of water infrastructure, consumption management, and educational practices across all public pre-university educational institutions in Cluj County, Romania. The research addresses the increasingly urgent imperative of sustainable water resource management within educational settings, in alignment with both European and global priorities. This analysis is based on a comprehensive data set collected in June 2025 from all 392 public pre-university educational institutions in Cluj County, encompassing both urban and rural areas, all educational levels, and all types of institutions. Data was gathered using a standardized questionnaire, which was validated with the official support of the Cluj County School Inspectorate. The quantitative analysis highlights significant urban–rural disparities: 95.566% of urban institutions are equipped with modern meters and connected to public water networks, compared to only 68.254% in rural areas. Water consumption monitoring relies predominantly on invoice data (69.388%), while the adoption of advanced monitoring technologies remains limited. Reported water losses are minimal (1.531%), and only 0.765% of educational institutions have indicated non-compliance issues related to water quality in the past three years. Educational measures and water-saving awareness campaigns are present in 65.562% of institutions, yet only about one-third (32.908%) have implemented dedicated projects or partnerships. The financial analysis reveals that 90.487% of annual water and sewerage costs are borne by urban institutions. The study highlights both the progress achieved and the persistent challenges, particularly in rural infrastructure and the expansion of educational interventions. The results provide a robust empirical basis for informing regional and national policies, supporting targeted investments, integrated educational programs, and continuous monitoring to ensure sustainable water resource management in the Romanian educational system. Full article

Intensified by climate change and anthropogenic activities, flood disasters necessitate rapid and accurate mapping for effective disaster management. This study develops an integrated framework leveraging synthetic aperture radar (SAR) and cloud computing to enhance flood monitoring, with a focus on a 2024 extreme rainfall event in Liaoning Province, China. Utilizing the Google Earth Engine (GEE) platform, we combine three complementary techniques: (1) Otsu automatic thresholding, for efficient extraction of surface water extent from Sentinel-1 GRD time series (154 scenes, January–October 2024), achieving processing times under 2 min with >85% open-water accuracy; (2) random forest (RF) classification, integrating multi-source features (SAR backscatter, terrain parameters from 30 m SRTM DEM, NDVI phenology) to distinguish permanent water bodies, flooded farmland, and urban areas, attaining an overall accuracy of 92.7%; and (3) Fuzzy C-Means (FCM) clustering, incorporating backscatter ratio and topographic constraints to resolve transitional “mixed-pixel” ambiguities in flood boundaries. The RF-FCM synergy effectively mapped submerged agricultural land and urban spill zones, while the Otsu-derived flood frequency highlighted high-risk corridors (recurrence > 10%) along the riverine zones and reservoir. This multi-algorithm approach provides a scalable, high-resolution (10 m) solution for near-real-time flood assessment, supporting emergency response and sustainable water resource management in affected basins. Full article

This study addresses the use of porcelain polishing waste as a pyro-expansive agent in clay-based formulations for the production of lightweight aggregates, aiming to reduce the consumption of natural resources and mitigate environmental impacts. In line with circular economy principles and sustainable construction goals, this study investigates the potential use of porcelain polishing waste as a pyro-expansive agent in clay-based formulations for producing sustainable lightweight aggregates. Using the Taguchi method and ANOVA, the effects of key processing parameters were evaluated. The results demonstrated a broad range of volumetric changes, from shrinkage of 40.84% to expansion of 91.69%, depending on the formulation and processing conditions. The aggregates exhibited specific mass values ranging from 0.99 g/cm³ to 2.36 g/cm³, water absorption up to 3.29%, and mechanical strength from 4.57 MPa to 39.87 MPa. Notably, nine of the sixteen experimental conditions met the technical standards for classification as LWA, indicating suitability for applications in high-strength, structural, and non-structural lightweight concretes, as well as lightweight mortars. The performance of these materials was directly linked to the chemical and mineralogical characteristics of the precursors and the proportion of pyro-expansive waste used. Overall, the findings suggest that 50% of the produced aggregates are viable for high-performance concrete applications, offering an environmentally responsible alternative to virgin raw materials and contributing to sustainable waste valorization in the ceramic and construction industries. Full article

Climate change, with its altered precipitation and extreme temperatures, significantly threatens global viticulture by affecting grapevine growth, yield, and fruit quality. Understanding the molecular underpinnings of grapevine resilience is crucial for developing adaptive strategies. Our aim is to explore the application of multi-omics approaches (integrating genomics, transcriptomics, proteomics, metabolomics, and epigenetics) to investigate grapevine stress responses. Advances in these omics technologies have been pivotal in identifying key stress-response genes, metabolic pathways, and regulatory networks, particularly those contributing to grapevine tolerance to water deficiency, (such as drought and decreased precipitation), extreme temperatures, UV radiation, and salinity. Furthermore, the rich genetic reservoir within grapevines serves as a vital resource for enhancing stress tolerance. While adaptive strategies such as rootstock selection and precision irrigation are important, future research must prioritize integrated multi-omics studies, including those on regional climate adaptation and long-term breeding programs. Such efforts are essential to exploit genetic diversity and ensure the sustainability of viticulture in the evolving climate. In summary, this review demonstrates how utilizing the inherent genetic variability of grapevines and employing multi-omics approaches are critical for understanding and enhancing their resilience to the challenges posed by climate change. Full article

Bambara groundnut (Vigna subterranea), a vital yet underutilized African legume, significantly boosts food security due to its nutritional value and adaptability to harsh climates and soils. However, its processing yields substantial waste like husks, shells, and haulms, which are often carelessly discarded, causing environmental damage. This paper highlights the urgent need to valorize these waste streams to unlock sustainable growth and economic development. Given their lignocellulosic composition, Bambara groundnut residues are ideal for generating biogas and bioethanol. Beyond energy, these wastes can be transformed into various bio-based products, including adsorbents for heavy metal removal, activated carbon for water purification, and bioplastics. Their inherent nutritional content also allows for the extraction of valuable components like dietary fiber, protein concentrates, and phenolic compounds for food products or animal feed. The nutrient-rich organic matter can also be composted into fertilizer, improving soil fertility. These valorization strategies offer multiple benefits, such as reduced waste, less environmental contamination, and lower greenhouse gas emissions, alongside new revenue streams for agricultural producers. This integrated approach aligns perfectly with circular economy principles, promoting resource efficiency and maximizing agricultural utility. Despite challenges like anti-nutritional factors and processing costs, strategic investments in technology, infrastructure, and supportive policies can unlock Bambara groundnut’s potential for sustainable innovation, job creation, and enhanced food system resilience across Africa and globally. Ultimately, valorizing Bambara groundnut waste presents a transformative opportunity for sustainable growth and improved food systems, particularly within African agriculture. Full article

This paper presents a preliminary feasibility study for integrating hydro-pneumatic energy storage (HPES) with off-grid offshore wind turbines and green hydrogen production facilities—a concept termed HydroGenEration (HGE). This study compares the performance of this innovative concept system with an off-grid direct wind-to-hydrogen plant concept without energy storage, both under central Mediterranean wind conditions. Numerical simulations were conducted at high temporal resolution, capturing 10-min fluctuations of open field measured wind speeds at an equivalent offshore wind turbine (WT) hub height over a full 1-year, seasonal cycle. Key findings demonstrate that the HPES system of choice, namely the Floating Liquid Piston Accumulator with Sea Water under Compression (FLASC) system, significantly reduces Proton Exchange Membrane (PEM) electrolyser (PEMEL) On/Off cycling (with a 66% reduction in On/Off events), while maintaining hydrogen production levels, despite the integration of the energy storage system, which has a projected round-trip efficiency of 75%. The FLASC-integrated HGE solution also marginally reduces renewable energy curtailment by approximately 0.3% during the 12-month timeframe. Economic analysis reveals that while the FLASC HPES system does introduce an additional capital cost into the energy chain, it still yields substantial operational savings exceeding EUR 3 million annually through extended PEM electrolyser lifetime and improved operational efficiency. The Levelized Cost of Hydrogen (LCOH) for the FLASC-integrated HGE system, which is estimated to be EUR 18.83/kg, proves more economical than a direct wind-to-hydrogen approach with a levelized cost of EUR 21.09/kg of H₂ produced. This result was achieved through more efficient utilisation of wind energy interfaced with energy storage as it mitigated the natural intermittency of the wind and increased the lifecycle of the equipment, especially that of the PEM electrolysers. Three scenario models were created to project future costs. As electrolyser technologies advance, cost reductions would be expected, and this was one of the scenarios envisaged for the future. These scenarios reinforce the technical and economic viability of the HGE concept for offshore green hydrogen production, particularly in the Mediterranean, and in regions having similar moderate wind resources and deeper seas for offshore hybrid sustainable energy systems. Full article

Agricultural activities are widely recognized as major sources of water pollution, primarily due to the introduction of heavy metals (HMs) through fertilizers, pesticides, manures, sewage sludge, and irrigation water. Owing to their persistence and non-biodegradability, these metals pose substantial risks to ecosystems and public health. While certain HMs such as cobalt, copper, and zinc are essential micronutrients for crops at low concentrations, others—like arsenic, cadmium, lead, and mercury—enter agricultural systems as contaminants and serve no biological function in plants. This paper explores the complex issue of HM contamination in water resulting from agricultural practices. It reviews the primary sources and pathways through which HMs enter aquatic systems, discusses their ecological and health impacts, and examines analytical methods used for HM detection and monitoring. In response to this challenge, several mitigation strategies are highlighted, including the optimized use of agrochemicals, adoption of sustainable farming practices, and implementation of phytoremediation and bioremediation techniques. Additionally, the importance of community education and regulatory enforcement is emphasized as part of an integrated approach to pollution control. Ultimately, this paper underscores the need for balanced solutions that safeguard water resources while maintaining agricultural productivity. Full article

The complex trade-offs and synergies among ecosystem services (ESs) in arid regions influence the stability and sustainable development of regional ecosystems. As a representative oasis–desert transition zone, the Kashgar region requires quantifying the key drivers and thresholds influencing ecosystem services, which is crucial for regional management. This study examines the spatio-temporal changes and interactions of five types of ES (grain production, water yield, soil retention, carbon storage, and habitat quality) and employs Restricted Cubic Splines to quantify the nonlinear changes and threshold effects of natural and social drivers. The results indicate the following: (1) During the period from 2000 to 2020, supply services (grain production) and regulatory services (water yield and soil retention) showed growth, while support services (carbon storage and habitat quality) declined slightly; (2) the synergistic effects of ecological services improved across the entire region, but trade-off effects emerged in certain local areas; and (3) the NDVI is the core natural factor driving the spatio-temporal differentiation of ESs. In 2020, when the NDVI exceeded 0.35, it had an adverse impact on habitat quality and carbon storage. Among social factors, water yield and habitat quality exhibit the highest threshold points with land use development intensity. An increase in land development intensity significantly impacts the trade-off and synergistic relationships among ESs, leading to local imbalances in ES resource supply and demand. These findings enhance our understanding of the nonlinear characteristics and potential mechanisms of ecosystems in arid regions, providing a scientific basis for ecosystem management in these areas. Full article

Understanding the mechanisms and speed of paleo-aridification in the Qaidam Block—driven by tectonic uplift and shifts in atmospheric circulation—provides critical long-term context for assessing modern climate variability and anthropogenic impacts on water resources and desertification. This knowledge is essential for informing sustainable development strategies. We reconstruct the post-Triassic–Jurassic extinction tectonic-climatic evolution of the Qaidam Block on the northern Qinghai-Tibet Plateau margin through an integrated analysis of sedimentary facies, palynological assemblages, and Chemical Index of Alteration values from Late Triassic to Jurassic strata. The Indo-Eurasian convergence drove the uplift of the East Kunlun Orogen and strike-slip movement along the Altyn Tagh Fault, establishing a basin-range system. During the initial Late Triassic to Early Jurassic period, warm-humid conditions supported gymnosperm/fern-dominated ecosystems and facilitated coal formation. A Middle Jurassic shift from extensional to compressional tectonics coincided with a climatic transition from warm-humid, through cold-arid, to hot-arid states. This aridification, evidenced by a Bathonian-stage surge in drought-tolerant Classopollis pollen and a sharp decline in Chemical Index of Alteration values, intensified in the Late Jurassic due to the Yanshanian orogeny and distal subduction effects. Resultant thrust-strike-slip faulting and southeastward depocenter migration, under persistent aridity and intensified atmospheric circulation, drove widespread development of aeolian dune systems (e.g., Hongshuigou Formation) and arid fluvial-lacustrine environments. The tectonic-climate-ecosystem framework reveals how Jurassic tectonic processes amplified feedback to accelerate aridification. This mechanism provides a critical geological analog for addressing the current sustainability challenges facing the Qaidam Basin. Full article