Geographies

Fast fashion is a rapidly expanding sector characterized by high production volumes, low costs, and short product lifecycles. While recent efforts have focused on improving sustainability within supply chains, consumer behavior remains a critical yet underexplored driver of environmental impacts. This study presents a web-based calculator tool designed to estimate both the carbon and plastic footprints associated with individual fast fashion consumption, with a particular focus on shopping behaviors, garment disposal, and laundry habits. Adopting a geographical perspective, the analysis explicitly considers the spatial dynamics of consumption and logistics within the urban context of Milan (Italy), a dense metropolitan area representative of high fashion activity and mobility. By incorporating user-reported travel patterns, logistics routes, and localized emission factors, the tool links consumer habits to place-specific environmental impacts. By involving over 360 users, the tool not only quantifies emissions and plastic waste (including microfibers) but also serves an educational function, raising awareness about the hidden consequences of fashion-related choices. Results reveal high variability in environmental impacts depending on user profiles and behaviors, with online shopping, frequent use of private vehicles, and improper garment disposal contributing significantly to emissions and plastic pollution. Our findings highlight the importance of integrating consumer-focused educational tools into broader sustainability strategies. The tool’s dual function as both calculator and awareness-raising platform suggests its potential value for educational and policy initiatives aimed at promoting more sustainable fashion consumption patterns. Full article

Flood impacts are intensifying due to the increasing frequency and severity of factors such as severe weather events, climate change, and unplanned urbanization. This study focuses on Briar Creek in Charlotte, North Carolina, an area historically affected by flooding. Three machine learning algorithms —bagging (random forest), extreme gradient boosting (XGBoost), and logistic regression—were used to develop a flood susceptibility model that incorporates topographical, hydrological, and meteorological variables. Key predictors included slope, aspect, curvature, flow velocity, flow concentration, discharge, and 8 years of rainfall data. A flood inventory of 750 data points was compiled from historic flood records. The dataset was divided into training (70%) and testing (30%) subsets, and model performance was evaluated using accuracy metrics, confusion matrices, and classification reports. The results indicate that logistic regression outperformed both XGBoost and bagging in terms of predictive accuracy. According to the logistic regression model, the study area was classified into five flood risk zones: 5.55% as very high risk, 8.66% as high risk, 12.04% as moderate risk, 21.56% as low risk, and 52.20% as very low risk. The resulting flood susceptibility map constitutes a valuable tool for emergency preparedness and infrastructure planning in high-risk zones. Full article

This study investigates how land access, inheritance expectations, and socio-economic conditions influence migration intentions of rural youth in central Vietnam. Drawing on survey data from 200 young respondents and employing logistic regression analysis, the research reveals that youth with higher levels of education and income exhibit a greater propensity to migrate in pursuit of improved livelihoods. Male respondents were significantly more likely to migrate, reflecting gender norms and unequal access to opportunities. Crucially, secure land tenure—measured through formal land titles and perceived inheritance rights—was strongly associated with lower migration intentions. Conversely, tenure insecurity emerged as a significant push factor, undermining youth confidence in long-term rural investment and contributing to land use instability. This study argues that secure land access is not only vital for sustaining rural livelihoods but also foundational for youth and women’s engagement, socio-economic stability, and long-term community resilience. From this viewpoint, this study highlights the need for youth-inclusive land reforms, the promotion of rural entrepreneurship, and expanded access to vocational training as critical policy interventions. Full article

The Cau River Basin in northeastern Vietnam is an ecologically and economically important watershed, yet it has lacked comprehensive hydrological modelling to date. Characterised by highly complex topography, diverse land use/land cover, and limited hydrometeorological data, the basin presents challenges for water resource assessment and management. This study applies the SWAT hydrological model to simulate streamflow dynamics in the Cau River Basin over a 31-year period (1990–2020) using multiple-source geospatial data, including a 30 m digital elevation model, official soil and land use maps, and daily climate records from six meteorological stations. Model calibration (1997–2008) and validation (2009–2020) were conducted using the SWAT-CUP tool, achieving strong performance with a Nash–Sutcliffe Efficiency (NSE) of 0.95 and 0.90, and R² of 0.95 and 0.91, respectively. Sensitivity analysis identified four key parameters most influential on streamflow (curve number, saturated hydraulic conductivity, soil evaporation compensation factor, and available water capacity), supporting a more focused and effective calibration process. Model results revealed substantial spatio-temporal variability in runoff, with annual surface runoff ranging from 19.8 mm (2011) to 56.4 mm (2013), generally lower in upstream sub-watersheds (<30 mm) and higher in downstream areas (>60 mm). The simulations also showed a clear seasonal contrast between the wet and dry periods. These findings support evidence-based strategies for flood and drought mitigation, inform agricultural and land use planning, and offer a transferable modelling framework for similarly complex watersheds. Full article

Climate change represents one of the main challenges of this century. The hazards generated by this process are various and involve territorial assets all over the globe. Hydrogeological risk represents one of these aspects, and the violence of rain precipitations has led experts to focus their interest on the study of geotechnical assets in relation to these dangerous weather events. At the same time, geospatial representation in 3D WebGIS based on open-source solutions led specialists to employ this kind of technology to remotely analyze and monitor territorial events considering different sources of information. This study considers the construction of a 3D WebGIS framework for the real-time management of geospatial information developed with open-source technologies applied to the dynamic mapping of precipitation in the metropolitan area of Palermo (Italy) based on real-time weather station acquisitions. The structure considered is a WebGIS platform developed with Cesium.js JavaScript libraries, the Postgres database, Geoserver and Mapserver geospatial servers, and the Anaconda Python platform for activating real-time data connections using Python scripts. This framework represents a basic geospatial digital twin structure useful to municipalities, civil protection services, and firefighters for land management and for activating any preventive operations to ensure territorial safety. Furthermore, the open-source nature of the platform favors the free diffusion of this solution, avoiding expensive applications based on property software. The components of the framework are available and shared using GitHub. Full article

An indicator-based approach was implemented to assess the contributions of soils in supplying ecosystem services, providing a scalable tool for modeling the spatial heterogeneity of soil functions at regional and local scales. The method consisted of (i) the definition of soil-based ecosystem services (SESs), using available point data and thematic maps; (ii) the definition of appropriate SES indicators; (iii) the assessment and mapping of potential SESs provision for the Emilia-Romagna region (22.510 km²) in NE Italy. Depending on data availability and on the role played by terrain features and soil geography and its complexity, maps of basic soil characteristics (textural fractions, organic C content, and pH) covering the entire regional territory were produced at a 1 ha resolution using digital soil mapping techniques and geostatistical simulations to explicitly consider spatial variability. Soil physical properties such as bulk density, porosity, and hydraulic conductivity at saturation were derived using pedotransfer functions calibrated using local data and integrated with supplementary information such as land capability and remote sensing indices to derive the inputs for SES assessment. Eight SESs were mapped at 1:50,000 reference scale: buffering capacity, carbon sequestration, erosion control, food provision, biomass provision, water regulation, water storage, and habitat for soil biodiversity. The results are discussed and compared for the different pedolandscapes, identifying clear spatial patterns of soil functions and potential SES supply. Full article

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

The prevailing environmental conditions before and during the 28 Large Forest Fires (LFFs) that have occurred in the Canary Islands since 1983 are analyzed. These conditions are often associated with episodes characterized by the advection of continental tropical air masses originating from the Sahara, which frequently result in intense heatwaves. During the onset of the LFFs, the base of the subsidence thermal inversion layer—separating a lower layer of cool, moist air from an upper layer of warm, dry air—is typically located at an altitude of around 350 m above sea level, approximately 600 m below the usual average. Understanding these Saharan air advection events is crucial, as they significantly alter the vertical thermal structure of the atmosphere and create highly conducive conditions for wildfire ignition and spread in the forested mid- and high-altitude zones of the archipelago. Analysis of meteorological records from various weather stations reveals that the average maximum temperature on the first day of fire ignition is 30.3 °C, with mean temperatures of 27.4 °C during the preceding week and 28.9 °C throughout the fire activity period. Relative humidity on the ignition days averages 24.3%, remaining at around 30% during the active phase of the fires. No significant correlation has been found between dry or wet years and the occurrence of LFFs, which have been recorded across years with widely varying precipitation levels. Full article

Sustainable Development Reserves are organized units in the Amazon that are essential for the proper use and sustainable management of the region’s natural resources and for the livelihoods and economy of the local communities. This study aims to provide a climatic characterization of the Madeira River Sustainable Development Reserve (MSDR), offering scientific support to efforts to assess the feasibility of implementing adaptation measures to increase the resilience of isolated Amazon communities in the face of extreme climate events. Significant statistical analyses based on time series of observational and reanalysis climate data were employed to obtain a detailed diagnosis of local climate variability. The results show that monthly mean two-meter temperatures vary from 26.5 °C in February, the coolest month, to 28 °C in August, the warmest month. Monthly precipitation averages approximately 250 mm during the rainy season, from December until May. July and August are the driest months, August and September are the warmest months, and September and October are the months with the lowest river level. Cold spells were identified in July, and warm spells were identified between July and September, making this period critical for public health. Heavy precipitation events detected by the R80, Rx1day, and Rx5days indices show an increasing trend in frequency and intensity in recent years. The analyses indicated that the MSDR has no potential for wind-energy generation; however, photovoltaic energy production is viable throughout the year. Regarding the two major commercial crops and their resilience to thermal stress, the region presents suitable conditions for açaí palm cultivation, but Brazil nut production may be adversely affected by extreme drought and heat events. The results of this study may support research on adaptation strategies that includethe preservation of local traditions and natural resources to ensure sustainable development. Full article

This study was conducted in the northeast of the Tadla plain, within the Beni Mellal-Khenifra region of Morocco. The primary objective is to elucidate the geometric and hydrogeological characteristics of this aquifer by analyzing and interpreting data from deep boreholes as well as gravimetric and electrical measurements using GIS analysis. First, the regional gradient was established. Then, the initial data were extracted. Subsequently, based on the extracted data, a gravity map was created. The investigation of the Bouguer anomaly’s gravity map exposes the presence of a regional gradient, with values varying from −100 mGal in the South to −30 mGal in the North of the area. These Bouguer anomalies often correlate with exposed basement rock areas and variations in the thickness of sedimentary layers across the study area. The analysis of existing electrical survey and deep drilling data confirms the results of the gravimetry survey after applying different techniques such as horizontal gradient and upward extension on the gravimetric map. The findings enabled us to create a structural map highlighting the fault systems responsible for shaping the study area’s structure. The elaborated structural map serves as an indispensable geotectonic reference, facilitating the delineation of subsurface heterogeneities and providing a robust foundation for further hydrogeological assessments in the Tadla Plain. Full article

The Quaternary saw numerous reorganizations of the hydrographic network, greatly modifying the hydrological network of these rivers. Eastern France is well known for many stream captures, described as early as the late 19th century. The oldest of these have been dated to the Middle Pleistocene. It is interesting to note, however, that these sites, located in the heart of vast limestone plateaus, have systematically become peatland zones, and understanding their functioning is fundamental to wetland restoration and renaturation programs. In addition to serving as biodiversity reservoirs, these peatlands also represent substantial carbon storage potential in the context of global climate change. Using two examples—the Marais de Saint-Gond and the Bar peatland—we propose to provide the key to understanding the origin of their sedimentary filling and the consequences of their current hydrogeological functioning. Full article

The Chacopampean Plain is a major physiographic unit in Argentina, bounded by the Colorado River to the south, the Sierras Pampeanas and Subandinas to the west, and the Paraná River, Río de la Plata Estuary, and the Argentine Sea to the east. Its subsurface preserves sediments from the Miocene marine transgression, while the surface hosts some of the country’s most productive soils. Two main geomorphological domains are recognized: fluvial systems dominated by alluvial megafans in the north, and aeolian systems characterized by loess accumulation and wind erosion in the south. The southern sector exhibits diverse landforms such as deflation basins, ridges, dune corridors, lunettes, and mantiform loess deposits. Despite their regional extent, the origin and chronology of many aeolian features remain poorly constrained, as previous studies have primarily focused on depositional units rather than wind-sculpted erosional features. This study integrates remote sensing data, field observations, and a synthesis of published chronometric and sedimentological information to characterize these aeolian landforms and elucidate their genesis. Our findings confirm wind as the dominant morphogenetic agent during Late Quaternary glacial stadials. These aeolian morphologies significantly influence the region’s hydrology, as many permanent and ephemeral water bodies occupy deflation basins or intermediate low-lying sectors prone to flooding under modern climatic conditions, which are considerably wetter than during their original formation. Full article

This study explores the water harvesting systems of mgouds in southern Tunisia and boqueras in southeastern Spain to understand their adaptation to semi-arid conditions and geomorphic contexts. These systems use ephemeral water through medieval-origin infrastructures to increase the water supply to rainfed crops. The hypothesis is that the diversity of these systems stems from environmental rather than cultural factors. By employing a qualitative–analytical approach, this study compares concentrated runoff diversion systems to investigate the use of boqueras/mgouds in terraces and glacis in the arid and semi-arid areas of Tunisia and the southeastern Iberian Peninsula. The research involved performing detailed geomorphological and climatological analyses and comparing structural complexities and water management strategies across different regions. The results indicate significant variability in system size and complexity. Tunisian mgouds are typically simpler and more individualised, while Spanish boqueras are larger and more complex due to more frequent and intense torrential rainfall. No common patterns were identified between the two regions. This study reveals that both types of systems reflect sophisticated adaptations to manage water scarcity and mitigate the impacts of intense rainfall, with geomorphic and climatic factors playing a decisive role. The primary conclusion is that the design and functionality of these water systems are predominantly influenced by environmental conditions rather than cultural factors. This research provides insights for developing sustainable water management strategies in other semi-arid regions. Full article

Indonesia faces significant challenges in meeting food security targets due to rapid agricultural land loss, with approximately 1.22 million hectares of rice fields converted between 1990 and 2022. Therefore, this study developed a prediction model for the loss of rice fields by 2030, incorporating land productivity attributes, specifically rice cropping intensity/RCI, using geospatial technology—a novel method with a resolution of approximately 10 m for quantifying ecosystem service (ES) impacts. Land use/land cover data from Landsat images (2013, 2020, 2024) were classified using the Random Forest algorithm on Google Earth Engine. The prediction model was developed using a Multi-Layer Perceptron Neural Network and Markov Cellular Automata (MLP-NN Markov-CA) algorithms. Additionally, time series Sentinel-1A satellite imagery was processed using K-means and a hierarchical clustering analysis to map rice fields and their RCI. The validation process confirmed high model robustness, with an MLP-NN Markov-CA accuracy and Kappa coefficient of 83.90% and 0.91, respectively. The present study, which was conducted in Indramayu Regency (West Java), predicted that 1602.73 hectares of paddy fields would be lost within 2020–2030, specifically 980.54 hectares (61.18%) and 622.19 hectares (38.82%) with 2 RCI and 1 RCI, respectively. This land conversion directly threatens ES, resulting in a projected loss of 83,697.95 tons of rice production, which indicates a critical degradation of service provisioning. The findings provide actionable insights for land use planning to reduce agricultural land conversion while outlining the urgency of safeguarding ES values. The adopted method is applicable to regions with similar characteristics. Full article

Wildfires play a pivotal role in shaping and regulating the structural characteristics of forest ecosystems. This study examined post-fire vegetation dynamics following the 2020 Bighorn Fire in the Santa Catalina Mountains, Arizona, USA, by integrating pre- and post-fire airborne LiDAR data with Landsat-derived burn severity indices from 2019 to 2024. We analyzed structural and functional vegetation traits across 12,500 hectares to assess the changes pre- to post-fire, and to evaluate how these changes were influenced by the burn severity. We applied a correlation analysis to explore the relationships among the structural variables across different vegetation cover types. Non-parametric LOESS regression revealed that the dNBR was more strongly associated with changes in the tree density than with vertical structural attributes. The functional recovery, indicated by the NDVI, generally outpaced the structural recovery captured by the NBR. Densely forested areas experienced greater declines in vegetation volumes and slower regeneration, whereas herbaceous and sparsely vegetated areas showed a more rapid, but compositionally distinct, recovery. The divergence between the NDVI and NBR trajectories underscores the importance of integrating structural and functional indicators to comprehensively assess the post-fire ecosystem resilience and inform targeted restoration efforts. Full article

Erosion represents a significant global threat to coastal zones, especially beaches, which are among the most valuable coastal landforms. This study evaluates the vulnerability to coastal erosion along the Brazilian Amazon coast, focusing on eight recreational beaches. The research is based on an assessment of geological, physical, ecological, and anthropogenic indicators. Some of these indicators were proposed in this study to enhance the evaluation of vulnerability in Amazonian beaches. The analysis reveals that most of the beaches studied are highly vulnerable to erosion due to a combination of natural factors and human activities. The barrier–beach ridge, composed of unconsolidated sediments, exhibits the highest vulnerability, while low cliffs present a moderate level of risk. The study highlights that semi-urban beaches with significant infrastructure development are particularly susceptible to erosion, a problem exacerbated by unplanned land use. Conversely, rural beaches, especially those located in protected areas, show lower vulnerability due to reduced human impact and better conservation of natural ecosystems. Furthermore, the study underscores the effects of extreme climatic events, such as prolonged rainfall and high-energy waves, which can intensify erosion risks. The findings suggest that anthropogenic changes, combined with extreme climate events, significantly influence the dynamics of coastal erosion. This research emphasizes the importance of targeted management strategies that address both natural and human-induced vulnerabilities, aiming to enhance coastal resilience and sustainability for Amazonian beaches. Full article

The vulnerability framework developed by the Intergovernmental Panel on Climate Change (IPCC) defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. Building off this framework, the Connecticut Institute for Resilience and Climate Adaptation (CIRCA) developed a Climate Change Vulnerability Index (CCVI) for the state of Connecticut, designed to integrate flood and extreme heat-related climate exposure with impacted socioeconomic, infrastructure, and ecological variables into a single comprehensive index that can guide resilience planning and prioritization at multiple levels. The index serves as a central component of the Resilient Connecticut project, a statewide initiative to advance climate adaptation and resilience planning through data-driven tools, community engagement, and strategies to address flood and heat risks across vulnerable communities. In this article, we detail the development of the CCVI, including earlier iterations, methodology, stakeholder engagement activities, and lessons learned that can impact resiliency planning in Connecticut. Preliminary statistical analyses, notable regional trends, data limitations, and future areas for research advancement are also discussed. The CCVI framework detailed here can be used in the process of identifying priority areas for intervention and supporting the selection and design of targeted resilience projects, and can also be adapted for other states. Full article

In this study, we selected a series of pothole wetlands to investigate their nucleation, evolution, and recent anthropogenic degradation in the Alcores Depression (AD), southern Iberian Peninsula, where over 100 closed watersheds containing shallow, ephemeral water bodies up to 2 hm² have been identified. We surveyed the regional geological framework, utilized digital elevation models (DEMs), orthophotos, and aerial images since 1956. Moreover, we analyzed precipitation and temperature data in Seville from 1900 to 2024, collected hydrometeorological data since 1990 and modelled the water level evolution from 2002 to 2025 in a representative pothole in the area. Our observations indicate a flooded surface reduction by more than 90% from the 1950s to 2025. Climatic data reveal an increase in annual mean temperatures since 1960 and a sharp decline in annual precipitation since 2000. The AD’s inception due to tectonic isolation during the Quaternary favoured the formation of pothole wetlands in the floodplain. The reduction in the hydroperiod and wetland degradation was primarily due to agricultural expansion since 1950, which followed an increase in groundwater extraction and altered the original topography. Recently, decreased precipitation has exponentially accelerated the degradation and even the complete disappearance of many potholes. This study underscores the fragility of small wetlands in the Mediterranean basin and the critical role of human management in their preservation. Restoring these ecosystems could be a highly effective nature-based solution, especially in semi-arid climates like southern Spain. These prairie potholes are crucial for enhancing groundwater recharge, which is vital for maintaining water availability in regions with limited precipitation. By facilitating rainwater infiltration into the aquifer, recharge potholes increase groundwater levels. Additionally, they capture and store run-off during heavy rainfall, reducing the risk of flooding and soil erosion. Beyond their hydrological functions, these wetlands provide habitats that support biodiversity and promote ecological resilience, reinforcing the need for their protection and recovery. Full article

Pastoral activities are an essential part of the cultural and ecological landscape of Central Italy. This traditional practice supports local economies, maintains biodiversity, and contributes to the sustainable use of natural resources. Understanding livestock behavior in response to environmental variability is essential for improving grazing management and animal welfare and ensuring the sustainability of these systems. This study evaluated the movement patterns of sheep grazing on pastures with differing vegetation indices in the Sibillini Mountains. Twenty lactating ewes foraging on two different pastures were monitored from June to October 2023 using GPS collars and accelerometers. GPS tracks were segmented using the Expectation Maximization Binary Clustering (EmBC) method to characterize movement behaviors, such as foraging, traveling, and resting. The NDVI was used to characterize vegetation dynamics, showing notable differences between the two pastures and across the grazing season. Additive mixed models were used to analyze data, accounting for individual variability and temporal autocorrelation in the sample. The results suggest that variations in the NDVI influence grazing behavior, with sheep in areas of lower vegetation density exhibiting increased movement during foraging. These findings provide valuable insights for optimizing grazing practices and promoting sustainable land use. Full article