Search Results (111)

In arid regions with low precipitation, like most of the Cape Verde islands, irrigation is essential for maintaining agricultural production and food security. However, due to significant investment needs, it is critical to improve irrigation efficiency and reduce water losses. The aim of this study is to evaluate irrigated agriculture in Cape Verde and its relationship with water scarcity through the calculation of key indicators and the analysis of statistical and remote sensing data. Crop production data were collected from the Ministry of Agriculture and Environment, and climatic data from the National Institute of Meteorology and Geophysics of Cape Verde (INMG) and FAO’s WaPOR platform. The aridity index was calculated using the UNEP method based on data from INMG. The island of Sal showed the lowest aridity index value (0.07), while Cachaço (São Nicolau island) had the highest (0.41). Sugarcane is currently the dominant irrigated crop, covering over 3000 hectares, about 62% of irrigated land, despite its high water demands. The expansion of sugarcane threatens long-term water sustainability and food production. Promoting crops with higher water productivity and technical training are key actions to ensure the sustainability of irrigated agriculture in Cape Verde. Findings point to the urgent need to improve irrigation infrastructure, maintenance, and system design. Full article

This study investigates the salinization processes affecting the coastal aquifer within the Torre Guaceto State Nature Reserve, a Mediterranean coastal area characterized by a unique ecological value of a brackish wetland threatened by water-intensive agricultural activities. Groundwater salinization threatens biodiversity, agriculture, and water resource sustainability. This work integrates hydrogeological monitoring, geochemical and isotopic analyses, and geophysical surveys to understand salinity dynamics and identify key drivers, such as seawater intrusion, irrigation practices, and climate change. Data collected during monitoring campaigns from 2022 to 2024 reveal significant seasonal and spatial variations in groundwater salinity influenced by natural and human-induced factors. The results indicate that salt recycling from irrigation and marine spray deposition are important local contributors to groundwater salinity, in addition to seawater intrusion. These findings highlight the urgent need for integrated groundwater management approaches considering the combined effects of agricultural practices, irrigation water quality, and climate variability tailored to Mediterranean coastal ecosystems. Full article

The agricultural sector is one of the most significant sectors of the global economy, yet it is concurrently a highly energy-intensive industry. The issue of optimizing field operations in terms of energy consumption is therefore a key consideration for sustainable agriculture, and the solution to this issue leads to both environmental and financial benefits. The aim of this study was to estimate energy consumption during soil cultivation using geophysical scanning data and machine learning (ML) algorithms. This included determining the optimal set of independent variables and the most suitable ML method. Soil parameters such as electrical conductivity, magnetic susceptibility, and soil reflectance in infrared spectra were mapped using data from Geonics EM-38 and Veris 3100 scanners. These data, along with soil texture, served as inputs for predicting fuel consumption and field productivity. Three machine learning algorithms were tested: support vector machines (SVMs), multilayer perceptron (MLP), and radial basis function (RBF) neural networks. Among these, SVM achieved the best performance, showing a MAPE of 4% and a strong correlation (R = 0.97) between predicted and actual productivity values. For fuel consumption, the optimal method was MLP (MAPE = 4% and R = 0.63). The findings demonstrate the viability of geophysical scanning and machine learning for accurately predicting energy use in tillage operations. This approach supports more sustainable agriculture by enabling optimized fuel use and reducing environmental impact through data-driven field management. Further research is needed to obtain training data for different soil parameters and agrotechnical treatments in order to develop more universal models. Full article

Urban streams undergo significant ecological alterations due to urbanization, including hydrological changes, water contamination, and biodiversity loss. This research employs a combination of satellite and drone imagery alongside traditional chemical and geophysical methods, facilitating a multi-dimensional assessment of Almyros and Gazanos urban stream health in Heraklion (Crete, Greece). The satellite imagery, obtained from the Copernicus program, allows for monitoring land use and impervious surface density around the streams, while drone surveys capture high-resolution images and calculate various water quality indices. In addition, chemical analyses of water samples for pollutants, as well as geophysical measurements using spectral induced polarization (SIP) and electromagnetic scanning (GEM-2), provide insight into the integrity of aquatic and riparian ecosystems. The study reflects on the different types of anthropogenic pressure faced by these two ecosystems. Almyros stream exhibits signs of eutrophication, characterized by elevated levels of chlorophyll and the presence of algal blooms, possibly due to runoff from adjacent agricultural activities. Conversely, the Gazanos stream shows signs of pollution mostly related to urbanization. The findings emphasize that both streams are under increasing anthropogenic pressure, thus highlighting the importance of employing comprehensive methods for effective stream management and policy implementation. This study ultimately advocates for ongoing monitoring initiatives that embrace technological advancements to safeguard urban water ecosystems. Full article

This study introduces a geospatial comprehensive methodological system aimed at evaluating the suitability and need for agricultural digital solutions (ADSs) across Europe. This system integrates a diverse range of factors, including geophysical characteristics, climate patterns, and socioeconomic conditions, evaluated at regional- and farm-specific levels. By leveraging open-source Earth observations and socioeconomic data, we develop multiple performance, environmental, and socioeconomic similarity indexes that compare regions based on shared characteristics, such as soil quality, climate, and socioeconomic factors. Using advanced statistical and multi-criteria analysis tools, these indexes are tailored to different stages of agricultural production, enabling region-specific assessments that identify and prioritize the needs for digital solutions across Europe. The results indicate that the developed indexes effectively categorize regions based on comparable characteristics, facilitating the targeted recommendation of ADSs. Additionally, a connectivity performance index is created to assess the local deployment model of agricultural digital solutions (cloud, edge, or mixed), ensuring that the recommendations for technological implementation are feasible and effective given the local connectivity conditions. Full article

Sustainable planning in New Sohag City, Egypt, can be significantly enhanced by employing integrated geophysical techniques. The current research presents the applicability of multiple integrated geophysical methods to prepare the optimal land use plans for the sustainable development of the new urban extension of Sohag Governorate, Upper Egypt, to tackle residential density and overcrowding in the governorate. The utilized geophysical techniques were electrical resistivity tomography (ERT), seismic refraction (SR), and ground penetrating radar (GPR). All these applied geophysical techniques concluded the near-surface stratigraphic sequence, which can be summarized by a generic subsurface model: variable wadi-fill deposits due to the variation in the flooding nature of the Nile River over the past millions of years, with an average thickness of 4.1 m; wet sand with intercalations of silt and clay, with an average thickness of 9.2 m. The model ends with highly saturated sand and gravel deposits, representing the groundwater aquifer throughout the studied area. The integration of the geophysical techniques, as well as the geological investigation, proved a clear efficacy for preparing the optimal land-use plan of the studied site, in the form of the proposed extensions of the agricultural activities, green and open areas, old quarrying areas, construction areas, and the groundwater potential throughout the studied area to conserve natural resources and ensure sustainable land use. Full article

Soil degradation is a critical challenge to global agricultural sustainability, driven by intensive land use, unsustainable farming practices, and climate change. Conventional soil monitoring techniques often rely on invasive sampling methods, which can be labor-intensive, disruptive, and limited in spatial coverage. In contrast, non-invasive geophysical techniques, particularly ground-penetrating radar, have gained attention as tools for assessing soil properties. However, an assessment of ground-penetrating radar’s applications in agricultural soil research—particularly for detecting soil structural changes related to degradation—remains undetermined. To address this issue, a systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. A search was conducted across Scopus and Web of Science databases, as well as relevant review articles and study reference lists, up to 31 December 2024. This process resulted in 86 potentially relevant studies, of which 24 met the eligibility criteria and were included in the final review. The analysis revealed that the ground-penetrating radar allows the detection of structural changes associated with tillage practices and heavy machinery traffic in agricultural lands, namely topsoil disintegration and soil compaction, both of which are important indicators of soil degradation. These variations are reflected in changes in electrical permittivity and reflectivity, particularly above the tillage horizon. These shifts are associated with lower soil water content, increased soil homogeneity, and heightened wave reflectivity at the upper boundary of compacted soil. The latter is linked to density contrasts and waterlogging above this layer. Additionally, ground-penetrating radar has demonstrated its potential in mapping alterations in electrical permittivity related to preferential water flow pathways, detecting shifts in soil organic carbon distribution, identifying disruptions in root systems due to tillage, and assessing soil conditions potentially affected by excessive fertilization in iron oxide-rich soils. Future research should focus on refining methodologies to improve the ground-penetrating radar’s ability to quantify soil degradation processes with greater accuracy. In particular, there is a need for standardized experimental protocols to evaluate the effects of monocultures on soil fertility, assess the impact of excessive fertilization effects on soil acidity, and integrate ground-penetrating radar with complementary geophysical and remote sensing techniques for a holistic approach to soil health monitoring. Full article

Retrieving soil moisture (SM) and land surface temperature (LST) provides crucial environmental data for smart agriculture, enabling precise irrigation, crop health monitoring, and yield optimization. The rapid advancement of Artificial intelligence (AI) hardware offers new opportunities to overcome the limitations of traditional geophysical parameter retrieval methods. We propose a nested large–small model method that uses AI techniques for the joint iterative retrieval of passive microwave SM and LST. This method retains the strengths of traditional physical and statistical methods while incorporating spatiotemporal factors influencing surface emissivity for multi-hierarchical classification. The method preserves the physical significance and interpretability of traditional methods while significantly improving the accuracy of passive microwave SM and LST retrieval. With the use of the terrestrial area of China as a case, multi-hierarchical classification was applied to verify the feasibility of the method. Experimental data show a significant improvement in retrieval accuracy after hierarchical classification. In ground-based validation, the ascending and descending orbit SM retrieval models 5 achieved MAEs of 0.026 m³/m³ and 0.030 m³/m³, respectively, improving by 0.015 m³/m³ and 0.012 m³/m³ over the large model, and 0.032 m³/m³ and 0.028 m³/m³ over AMSR2 SM products. The ascending and descending orbit LST retrieval models 5 achieved MAEs of 1.67 K and 1.72 K, respectively, with improvements of 0.67 K and 0.49 K over the large model, and 0.57 K and 0.56 K over the MODIS LST products. The retrieval model can theoretically be enhanced to the pixel level, potentially maximizing retrieval accuracy, which provides a theoretical and technical basis for the parameter retrieval of AI passive microwave large models. Full article

The number of studies on submarine groundwater discharge (SGD) and the evidence of its significance in biogeochemical cycling and potential impacts on the chemical and ecological status of coastal waters is increasing globally. Here, we briefly present SGD studies from the Baltic Sea identified along the coastlines of Denmark, Finland, Germany, Poland, Sweden and Russia in the southwestern, southern and north–northeastern parts of the Baltic Sea. We introduce a digital SGD map viewer and information platform enabling easy overview and access to information on identified SGD sites in the coastal areas of the Baltic Sea. SGDs potentially transport critical pollutants from urban and agricultural areas on land to the marine environment. The pollutants include nutrients, dissolved organic and inorganic carbon, metals, pharmaceuticals, and other emerging contaminants, potentially harming marine ecosystems and biodiversity and possibly contributing to the poor chemical or ecological status of coastal waters, affecting human and environmental health. We focus on case studies from Finland, Germany, Poland and Denmark that include the results and interpretations from the applied geochemical, geophysical and geological methods, as well as bionic autonomous underwater vehicles (AUVs) for locating, investigating, modelling and visualizing SGD sites in 2D and 3D. The potential Pan-European or even global SGD information platform established within the European Geological Data Infrastructure (EGDI) enables the easy combination and comparison of map layers such as seabed sediment types and coastal habitats. The EGDI map viewer provides easy access to information from SGD studies and may serve as an entry point to relevant information on SGDs, including contents of pollutants, for the scientific community and policy-makers. The information potentially includes the results of model simulations, data from near real-time sensors at permanently installed monitoring stations and surveys in time and space conducted by AUVs. The presented digital SGD information platform is particularly pertinent to the UN Sustainable Development Goal (SDG) No. 14, which focuses on the conservation and sustainable use of oceans and marine resources. Full article

The magnetic field penetration depth poses challenges in communications, geophysical exploration, biomedical therapies, and superconducting device design. The objective of this systematic review was to identify, analyze, and understand the depth of magnetic field penetration in conductors, semiconductors, superconductors, insulators and natural materials, modelling applications in medicine, engineering, and basic sciences. An exhaustive search was carried out in databases such as Scopus, IEEE Xplore, ScienceDirect, and IOPSCIENCE using keywords such as depth and penetration and magnetic and field and materials. PRISMA was used as a method to define inclusion and exclusion criteria, ensuring quality, transparency, and methodological rigor, followed by a detailed statistical analysis. The results showed that the penetration depth varies according to the material, frequency, and application conditions. In human tissues, infrastructure, and agricultural applications, the penetration range is between 0.01 and 0.2 m, with the possibility of a range greater than one meter in specific applications. The higher the frequency, the lower the penetration depth is confirmed. In conclusion, the penetration of the magnetic field depends on material properties such as conductivity and magnetic permeability, frequency, and temperature. The developed models offer relevant information for future research and technological applications. Full article

Nowadays, there is a particular need to estimate soil water content accurately over space and time scales in various applications. For example, precision agriculture, as well as the fields of geology, ecology, and hydrology, necessitate rapid, onsite water content measurements. The time domain reflectometry (TDR) technique is a geophysical method that allows, in a time-varying electric field, the determination of dielectric permittivity and electrical conductivity for a wide class of porous materials. Measuring the volumetric water content in soils is the most frequent application of TDR in soil science and soil hydrology. TDR has grown in popularity over the last 40 years because it is a practical and non-destructive technique that provides laboratory and field-scale measurements. However, a significant limitation of this technique is the relatively high cost of TDR devices, despite the availability of a range of commercial systems with varying prices. This paper aimed to design and implement a low-cost, compact TDR device tailored for classical hydrological applications. A series of laboratory experiments were carried out on soils of different textures to calibrate and validate the proposed measuring system. The results show that the device can be used to obtain predictions for monitoring soil water status with acceptable accuracy (R² = 0.95). Full article

Investigating the sonosphere can serve as a valuable proxy for understanding various ecosystem processes. Consequently, an ecoacoustic perspective broadens our capacity to understand how airborne sounds interact along an ecotone at the soil surface with the subterranean sounds generated within a pedon. We explored techniques that could detect, quantify, and analyze the sonic dimensions of a sonosphere in the form of sounds within a unit of soil (sonopedon), sounds from a landscape unit (sonotope), and the sonic ecotone (sonotone) where these phenomena converge. We recorded sounds for 24 h over 20 days in September 2024 at 40 sites distributed evenly across a small rural parcel of agricultural land in Northern Italy. We utilized a sound recording device fabricated with a sonic probe that simultaneously operated inside the soil and the grounds’ surface, which successfully captured sounds attributable both to the soilscape and to the landscape. We calculated the Sonic Heterogeneity Indices, SHI_tf and SHI_ft, and analyzed the Spectral and Temporal Sonic Signatures along with Spectral Sonic Variability, Effective Number of Frequency Bins, and Sonic Dissimilarity. Each calculation contributed to a detailed description of how the sonosphere is characterized across the frequency spectrum, temporal dynamics, and sound sources. The sonosphere in our study area, primarily characterized by the low-frequency spectra, possessed a mix of biological, geophysical, and anthropogenic sounds displaying distinct temporal patterns (sonophases) that coincided with astronomic divisions of the day (daytime, twilights, and nighttime). Full article

Along the southern North Sea coast from the Netherlands to Denmark, human cultivation efforts have created a unique cultural landscape. Since the Middle Ages, these interactions between humans and natural forces have induced major coastal changes. In North Frisia (Germany), storm floods in 1362 AD and 1634 AD turned wide areas of embanked cultural land into tidal flats. Systematic geoarchaeological investigations between Nordstrand and Hallig Südfall comprise coring, trenching, sedimentary, geochemical and microfaunal palaeoenvironmental parameter analyses and radiocarbon dating. Together with geophysical prospection results and archaeological surveys, they give insights into the landscape’s development and causes for land losses. Results reveal that fens and bogs dominated from c. 800 BC to 1000 AD but are mostly missing in the stratigraphy. Instead, we found 12th to 14th cent. AD settlement remains directly on top of a pre-800 BC fossil marsh. This hiatus of c. 2000 years combined with local ‘Hufen’ settlements implies an extensive removal of peat during cultivation eventually resulting in the use of underlying marshland for agricultural purposes. Fifteenth cent. AD tidal flat deposits on top of the cultivated marsh prove that human impact lowered the ground surface below the mean high water of that time, clearly increasing the coastal vulnerability. We consider these intensive human–environment interactions as a decisive trigger for the massive loss of land and establishment of the tidal flats in North Frisia that are currently part of the UNESCO World Heritage “Wadden Sea”. Full article

Recently, there has been increasing interest in organic carbon (OC) certification of soil as an incentive for farmers to adopt sustainable agricultural practices. In this context, this pilot project combines geochemical and geophysical methods to map the distribution of OC contents in agricultural fields, allowing us to detect variations in time and space. Here we demonstrated a relationship between soil OC contents estimated in the laboratory and the apparent electrical conductivity (ECa) measured in the field. Specifically, geochemical elemental analyses were used to evaluate the OC content and relative isotopic signature in collected soil samples from a hazelnut orchard in the Emilia–Romagna region of Northeastern Italy, while the geophysical Electromagnetic Induction (EMI) method enabled the in situ mapping of the ECa distribution in the same soil field. According to the results, geochemical and geophysical data were found to be reciprocally related, as both the organic matter and soil moisture were mainly incorporated into the fine sediments (i.e., clay) of the soil. Therefore, such a relation was used to create a map of the OC content distribution in the investigated field, which could be used to monitor the soil C sequestration on small-scale farmland and eventually develop precision agricultural services. In the future, this method could be used by farmers and regional and/or national policymakers to periodically certify the farm’s soil conditions and verify the effectiveness of carbon sequestration. These measures would enable farmers to pursue Common Agricultural Policy (CAP) incentives for the reduction of CO₂ emissions. Full article

The fraction of absorbed photosynthetically active radiation (FAPAR) is one of the bio-geophysical Essential Climate Variables assessed through remote sensing observations and distributed globally by space and environmental agencies. Any reliable remote sensing product should be benchmarked against a reference, which is normally determined by means of ground-based measurements. They should generally be aggregated spatially to be compared with remote sensing products at different resolutions. In this work, the effectiveness of various in situ sampling methods proposed to assess FAPAR from flux measurements was evaluated using a three-dimensional radiative transfer framework over eight virtual vegetated landscapes, including dense forests (leaf-on and leaf-off models), open canopies, sparse vegetation, and agricultural fields with a nominal extension of 1 hectare. The reference FAPAR value was determined by summing the absorbed PAR-equivalent photons by either all canopy components, both branches and leaves, or by only the leaves. The incoming and upwelling PAR fluxes were simulated in different illumination conditions and at a high spatial resolution (50 cm). They served to replicate in situ virtual FAPAR measurements, which were carried out using either stationary sensor networks or transects. The focus was on examining the inherent advantages and drawbacks of in situ measurement protocols against GCOS requirements. Consequently, the proficiency of each sampling technique in reflecting the distribution of incident and reflected PAR fluxes—essential for calculating FAPAR—was assessed. This study aims to support activities related to the validation of remote sensing FAPAR products by assessing the potential uncertainty associated with in situ determination of the reference values. Among the sampling schemes considered in our work, the cross shaped sampling schemes showed a particular efficiency in properly representing the pixel scale FAPAR over most of the scenario considered. Full article