Earth

Aquifer Storage and Recovery (ASR) can involve injecting available surface water into an unconfined aquifer and then extracting it to provide secondary water for irrigation. This study demonstrates a method for evaluating the appropriateness of steady injection versus unsteady injection for an assumed situation. In design, it can be important to affect the transient: the proportion of the injected water that would be subsequently extracted (versus that remaining in the aquifer) and the proportion within the extracted water that would be an injectate (versus ambient groundwater). These proportions can be predicted from the predicted value of an ASR well’s Recovery Effectiveness (REN)—the time-varying proportion of injectate that is extracted subsequently from the same fully penetrating well. Applying the demonstrated procedure with appropriately detailed data and simulation models can predict the REN values resulting from steady versus unsteady injection, followed by steady extraction. For convenience in displaying and computing REN, the injectate was assumed to have a 100 ppm conservative solute concentration. For this demonstration, a homogenous isotropic unconfined one-layer aquifer was assumed. The scenarios involved steady or unsteady injection for 61 days via a fully penetrating ASR well. Then, 91 days of steady pumping led to the extraction of a total volume equal to that injected. For the assumed hydrogeologic data—31 years of Salt Lake City, Utah, rainfall data and estimated captured runoff—the results show that steady injection is more likely to cause a predictable REN but might not cause a higher REN than daily varying injection of the same total volume. Assuming different runoff or hydrogeologic flows would lead to different REN values. Steady injection causes a predictable groundwater mound and can assure a sufficient vadose zone thickness for overlying plants. Augmentation and storage of captured rainwater can help to provide a steady injection rate. For a situation that requires REN management, appropriate simulations can help water managers design ASR systems that will achieve REN goals and increase sustainable groundwater availability. Full article

Species distribution modeling (SDM) is a vital tool for ecological and biogeographical research, allowing precise predictions of species distributions based on environmental variables. This study reviews the evolution of SDM techniques from 1985 to 2023, focusing on model development and applications in conservation, climate change adaptation, and invasive species management. We employed a mixed review with bibliometric and systematic element approaches using the Scopus database, analyzing 982 documents from 275 sources. The MaxEnt model emerged as the most frequently used technique, applied in 85% of the studies due to its adaptability and accuracy. Our findings highlight the increasing trend in international collaboration, particularly between China, the United Kingdom, and Brazil. The study reveals a significant annual growth rate of 11.99%, driven by technological advancements and the urgency to address biodiversity loss. Our analysis also shows that while MaxEnt remains dominant, deep learning and other advanced computational techniques are gaining traction, reflecting a shift toward integrating AI in ecological modeling. The results emphasize the importance of global cooperation and the continued evolution of SDM methodologies, projecting further integration of real-time data sources like UAVs and satellite imagery to enhance model precision and applicability in future conservation efforts. Full article

The increasing demand for large-scale, high-frequency environmental monitoring has driven the adoption of satellite-based technologies for effective forest management, especially in the context of climate change. This study explores the potential of SAR for estimating the mass of harvesting residues, a significant component of forest ecosystems that impacts nutrient cycling, fire risk, and bioenergy production. The research hypothesizes that while the spatial distribution of residues remains stable, changes in moisture content—reflected in variations in the dielectric properties of the woody material—can be detected by SAR techniques. Two models, the generalized linear model (GLM) and random forest (RF) model, were used to predict the mass of residues using interferometric variables (phase, amplitude, and coherence) as well as the backscatter signal from several acquisition pairs. The models provided encouraging results (R² of 0.48 for GLM and 0.13 for RF), with an acceptable bias and RMSE. It was concluded that it is possible to derive useful indications about the mass of harvesting residues from SAR data and the findings could lead to the improved monitoring and management of forest residues, contributing to sustainable forestry practices and the enhanced utilization of bioenergy resources. Full article

The Lobo reservoir, designed to supply water to the Daloa city population (central west of Côte d’Ivoire), is facing the phenomenon of eutrophication due to the agricultural plots located upstream of the reservoir inputs. Studies have highlighted the reservoir pollution and sedimentation problems. This study was initiated to test the effectiveness of a transfer model in the fight against the eutrophication problem. The objective of this study was to determine the optimal width of a vegetative filter strip on the banks of the Lobo reservoir, where the water intake installations of the drunk water company SODECI are located, using the VFSMOD model. The methodological approach is structured into four (4) main stages: 1—Evaluation of runoff from the source of pollution (contributing surface) during a rainy episode; 2—Calculation of the incoming runoff volume and the sediment load; 3—Simulation of runoff reduction and incoming sediments within the grassy filter strip; and 4—Determination of the optimal width of the grassy strip. The results obtained showed a contributing source area of 13.5 ha and 2% as the average slope. A runoff volume of 4680 m³ coming from the source of pollution is reduced by 1119 m³ (24%) through a grassy strip that is 3 m wide. The sediment load goes from 132 kg to 33 kg, a reduction of 75% in the quantity of sediment entering. The scenarios tested showed that a grassy strip width equal to 3 m should allow for a reduction of 75% of upstream sediments. This grassy strip width of 3 m should be considered for implementing a vegetative filter strip around the Lobo reservoir. Full article

The Irawan Watershed in Puerto Princesa, Philippines, is an important resource that supports domestic, agricultural, and industrial water needs. This study applies the Water Evaluation and Planning (WEAP) model to project the impacts of climate change on future surface water availability, integrating the findings into an Integrated Water Resource Management (IWRM) framework. Using bias-corrected General Circulation Models (GCMs) under four shared socioeconomic pathways (SSPs), this study examines scenarios from low to high emissions (SSP126, SSP245, SSP370, and SSP585) for the assessment of potential variations in water supply. The results indicate a significant vulnerability to water availability, especially under SSP370 and SSP585, where climate warming is pronounced, leading to significant reductions in streamflow. Conversely, SSP126 suggests relatively stable conditions with less pronounced hydrological changes. The study also explores the socioeconomic drivers that affect water demand, including population growth and land use changes that influence agricultural water needs. The findings underscore the urgency of using adaptive management strategies to conserve water resources in the face of these anticipated challenges. Key recommendations include optimizing water use efficiency in all sectors, establishing protective zones around natural ecosystems, implementing climate-resilient infrastructure, and promoting community engagement in water management. These measures are critical for enhancing water security and promoting sustainable development within the watershed, contributing to the broader goals of Sustainable Development Goal (SDG) 6. This study offers decision-makers and resource managers an evidence-based framework for integrating hydrological modeling into IWRM, providing valuable insights to navigate the complexities of climate change and ensure the long- term sustainability of water resources in the Philippines. Full article

Urban water systems are increasingly vulnerable to climate change. Traditional planning, often based on past conditions, fails to address these new challenges. We suggest policy options for integrating climate scenarios into urban water planning, which will enhance the resilience of drinking water, wastewater, and stormwater systems. The policy options are (1) requiring climate scenario analysis in planning processes, (2) developing climate-resilient infrastructure standards, (3) promoting low-impact development and nature-based solutions, (4) creating regional planning bodies, (5) educating professionals for climate-responsive planning, and (6) securing funding for climate adaptation. We discuss our experience in the state of Utah, USA, and summarize case studies in Copenhagen, New York, and Melbourne. The policy options align with Sustainable Development Goals and offer a roadmap for building adaptable, sustainable urban water systems. Full article

Maintaining the operability of a hydroelectric power station at a scale originally designed is being compromised by continuous reservoir sedimentation. The underlying factors include a complex mix of landscape alterations owing to natural and anthropogenic activities around dam areas, such as gully erosion, landslides, floods triggered by heavy rainfall, climate change, and construction activities. The hydropower projects in the low-to-mid mountain regions of Nepal are witnessing a combination of these phenomena, affecting their optimal performance in meeting long-term sustainable power supply targets. This paper presents a combination of geo-spatial analysis and field evaluations to identify the trends from Kulekhani-I, one of the oldest storage-type hydropower projects in Nepal, using long-term time series remote sensing satellite imagery from 1988 to 2020. Our analysis shows an expansion of the surface water content area over time, attributed mainly to high sedimentation deposition owing to multiple factors. This study has identified an urgent need for addressing the following two key contributory factors through an effective control mechanism to avoid rapid sedimentation in the reservoirs: natural—landslides and floods leading to mainly silt deposition during heavy rainfalls; and anthropogenic—road construction materials dumped directly in the reservoir. Effective implementation of a remote sensing monitoring scheme can safeguard future damages to dam environments of more recently built storage-type hydropower projects. Full article

South America has experienced significant changes in climate patterns over recent decades, particularly in terms of precipitation and temperature extremes. This study analyzes trends in climate extremes from 1979 to 2020 across South America, focusing on their relationships with sea surface temperature (SST) anomalies in the Pacific and Atlantic Oceans. The analysis uses precipitation and temperature indices, such as the number of heavy rainfall days (R10mm, R20mm, R30mm), total annual precipitation (PRCPTOT), hottest day (TXx), and heatwave duration (WSDI), to assess changes over time. The results show a widespread decline in total annual precipitation across the continent, although some regions, particularly in the northeast and southeast, experienced an increase in the intensity and frequency of extreme precipitation events. Extreme temperatures have also risen consistently across South America, with an increase in both the frequency and duration of heat extremes, indicating an ongoing warming trend. The study also highlights the significant role of SST anomalies in both the Pacific and Atlantic Oceans in driving these climate extremes. Strong correlations were found between Pacific SST anomalies (Niño 3.4 region) and extreme precipitation events in the northern and southern regions of South America. Similarly, Atlantic SST anomalies, especially in the Northern Atlantic (TNA), exhibited notable impacts on temperature extremes, particularly heatwaves. These findings underscore the complex interactions between SST anomalies and climate variability in South America, providing crucial insights into the dynamics of climate extremes in the region. Understanding these relationships is essential for developing effective adaptation and mitigation strategies in response to the increasing frequency and intensity of climate extremes. Full article

The living lab (LL) concept has a significant potential to drive sustainable development, particularly in the bioeconomy sector, by assisting communities in improving their quality of life whilst also considering the environmental impact. In this context, the main research question was the following: is there any specific mechanism through which living labs operate under the sustainable development concept? We reviewed 120 papers addressing this topic and performed a bibliometric analysis on the linkage between sustainability and living labs by applying the methodology of a systematic review. We concluded that living labs can drive innovation and experimentation in sustainability, which can be transposed into tangible solutions to economic, environmental, and social problems. The role of living labs in the transition to a bioeconomy is discussed and further research directions are presented. Full article

Landslides and their resulting impacts on property and human life have become an ongoing challenge in the hilly regions of Bangladesh. This study aims to systematically review diverse landslide studies in Bangladesh, particularly focusing on landslide disaster management (LDM) from 2008 to 2023, encompassing the pre-disaster, syn-disaster, and post-disaster phases. Several key attributes of landslide studies were considered, including general trends, data types, study scales, contributing factors, methodologies, results, and validation approaches, to investigate challenges and subsequently identify research gaps. This study evaluated 51 research articles on LDM using a systematic literature review (SLR) technique that adhered to the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) framework. Our finding revealed that articles on LDM were dominated by the pre-disaster (76%) and the syn-disaster phases (12%), with the post-disaster phase (12%) receiving equal attention. The SLR revealed a growing number of studies since 2020 that used data-driven methods and secondary spatial data, often focused on medium-scale analyses (district level) that, however, often lacked field-based validation. From the factors examined in various landslide studies, topographical and hydrological factors were found to be the most significant attributes in assessment. This study identified key challenges, such as insufficient landslide inventories including poor site accessibility and a lack of high-resolution geological, soil, and rainfall data. It also highlighted critical research gaps, including the need for advanced technologies in susceptibility mapping for national hazard atlas, the investigation of underexplored causative factors, effective early warning systems, detailed post-event characterization, health impact assessment, risk-sensitive land use planning, and interactive web portals for landslide prone areas. This study would thus aid researchers in understanding the depth of existing knowledge and provide insights into how landslides fit into broader disaster management frameworks, facilitating interdisciplinary approaches. Full article

Mozambique is confronted with numerous risks related to food security and natural disasters. The study conducted a literature review on natural hazards and food security. This can help to identify gaps and further areas of research. A bibliometric analysis was conducted using standardized text search terms, and the VOSviewer tool was used to analyze over 7000 scientific articles and cluster over 60,000 keyword co-occurrences. The results show that research on natural hazards for food security needs to be integrated. The priority topic of disasters focuses on specific hazards such as climate change, floods, and hurricanes, which are also linked to demographic and other social variables. More studies on food security, such as droughts, sustainable development, and other human and social conditions, are being conducted. Resilience as an emerging research paradigm needs to be addressed in comparison. One result is an analytical framework on impacts on food security in the context of disaster risk, based on the empirical findings of the literature review. It shows how everyday risks such as disease or food security can be conceptually better linked to natural hazards and resilience. It shows that further research is needed on the interlinkages of multiple risks, of which Mozambique is an outstanding example. The methodology presented is also applied to provide a framework for linking multiple risks to food security and natural hazards. The innovative dimension of the research is that this inquiry constitutes one of the pioneering attempts to conduct a bibliometric analysis of the linkages between natural hazards, food security, and resilience in Mozambique. Another noteworthy contribution is introducing a novel analytical framework that integrates food security and disaster risks. Full article

Artisanal and small-scale gold mining (ASCGM) provides a livelihood for many communities worldwide, but it has profound environmental impacts, especially on the quality of nearby water resources. This study assessed the impacts of ASCGM on the physicochemical quality of water and sediments from Kitengure stream, Buhweju Plateau, Western Uganda. Surface water (n = 94) and superficial sediments (n = 36) were sampled between October 2021 and January 2022 from three different sections of Kitengure stream (upstream, midstream around the ASCGM area, and downstream). The samples were analyzed for various physicochemical parameters and selected potentially toxic elements (PTXEs), namely: zinc (Zn), cadmium (Cd), lead (Pb), copper (Cu), and arsenic (As). A health risk assessment was performed using the hazard index and incremental life cancer risk methods. Pearson’s bivariate correlation, geoaccumulation, and pollution indices were used to establish the sources and potential risks that PTXEs in sediments could pose to aquatic organisms. The results indicated that water in Kitengure stream draining the ASCGM site was highly colored (1230.00 ± 134.09 Pt-co units; range = 924.00–1576.00 Pt-co units) and turbid (194.75 ± 23.51 NTU; range = 148–257 NTU). Among the five analyzed PTXEs, only Cd (0.082 ± 0.200–0.092 ± 0.001 mg/L) and Cu (0.022 ± 0.004–0.058 ± 0.005 mg/L) were detected in water, and Cd was above the permissible limit of 0.003 mg/L for potable water. Upon calculating the water quality index (WQI), the water samples were categorized as very poor for upstream samples (WQI = 227) and unfit for use (WQI = 965 and 432) for midstream and downstream samples, respectively. In sediments, the mean concentration ranges of Zn, Cd, Pb, Cu, and As were 0.991 ± 0.038–1.161 ± 0.051, 0.121 ± 0.014–0.145 ± 0.025, 0.260 ± 0.027–0.770 ± 0.037, 0.107 ± 0.017–0.422 ± 0.056, and 0.022 ± 0.002–0.073 ± 0.003 mg/kg, respectively, and they were all below their average shale, toxicity reference, and consensus-based sediment quality guidelines. Geoaccumulation indices suggested that there was no enrichment of the elements in the sedimentary phase and the associated ecological risks were low. However, there were potential non-carcinogenic health risks that maybe experienced by children who drink water from Kitengure stream. No discernable health risks were likely due to dermal contact with water and sediments during dredging or panning activities. It is recommended that further studies should determine the total mercury content of water, sediments, and crops grown along the stream as well as the associated ecological and human health risks. Full article

This systematic review evaluates the health impacts of climate-induced extreme weather events and the effectiveness of various adaptation strategies. Seventeen studies were analyzed, focusing on adaptation measures such as agricultural adjustments, renewable energy, ecosystem restoration, infrastructure redesign, and public health interventions. Significant health impacts were identified, including increased morbidity and mortality due to heatwaves, floods, and vector-borne diseases. The success of adaptation strategies was found to be highly dependent on local context, implementation capacity, and sustainability. This review underscores gaps in data quality, the generalizability of findings, and the integration of adaptation measures into public health policies. An urgent need exists for interdisciplinary approaches and community engagement to ensure sustainable, equitable health outcomes in the face of climate change. Future research should focus on these areas to strengthen public health resilience. Full article

Conflicts between wildlife and humans are a major ecological issue. During migration, wildlife, especially wildebeest, often encounter significant environmental pressures from human activities. However, relatively few studies have been conducted to provide a concise, quantitative description of wildebeest migration in the Maasai Mara National Reserve (MMNR). In this study, we identified changes in the location of the wildebeest population over time in the Maasai Mara National Reserve. We then used a K-means algorithm (R² = 0.926) to fit coordinates representing the changes in the location of the wildebeests to enable a quantitative representation of their migration routes. Subsequently, we developed an environmental stress model to assess the changes in environmental stresses faced by wildebeests along their migration routes. We proposed a model of “migratory ecological corridors and customized buffer zones” and determined the response coefficient T_res. We used the response coefficients T_res = 0.06, 0.09, and 0.12 as the critical values to categorize the areas along the routes into weak, medium, and strong response regions. Then, we set the width of the buffer zones on both sides of the routes as 5 km, 7 km, and 9 km, respectively, and evaluated the buffer effect. This type of model achieved a good effect of reducing the environmental pressure by 54.06%. The “Migratory Ecological Corridor and Customized Buffer Zone” model demonstrated a high degree of economic feasibility while showing good practicality in mitigating the environmental conflicts between humans and migratory wildlife. The variability in the environmental pressures across the region indicates that the Nairobi and Nakuru districts may be undergoing a particular stage of urbanization that unleashes potential threats to the migration of wildebeests. Further research is essential to assess the feasibility of larger buffer zones. Full article

Being located in the middle of Southern Europe, and thus likely representing a particularly dynamic member of Mediterranean Europe, Italy has experienced a sudden increase in early desertification risk because of multiple factors of change. Long-term research initiatives have provided relatively well-known examples of the continuous assessment of the desertification risk carried out via multiple exercises from different academic and practitioner stakeholders, frequently using the Environmentally Sensitive Area Index (ESAI). This composite index based on a large number of elementary variables and individual indicators—spanning from the climate to soil quality and from vegetation cover to land-use intensity—facilitated the comprehensive, long-term monitoring of the early desertification risk at disaggregated spatial scales, being of some relevance for policy implementation. The present study summarizes the main evidence of environmental monitoring in Italy by analyzing a relatively long time series of ESAI scores using administrative boundaries for a better representation of the biophysical and socioeconomic trends of interest for early desertification monitoring. The descriptive analysis of the ESAI scores offers a refined representation of economic spaces in the country during past (1960–2010 on a decadal basis), present (2020), and future (2030, exploring four different scenarios, S1–S4) times. Taken as a proxy of the early desertification risk in advanced economies, the ESAI scores increased over time as a result of worse climate regimes (namely, drier and warmer conditions), landscape change, and rising human pressure that exacerbated related processes, such as soil erosion, salinization, compaction, sealing, water scarcity, wildfires, and overgrazing. Full article

Landslides are widespread and global geological disasters, affecting millions of people and causing numerous deaths each year. Despite technological advances, it is still difficult to accurately prevent landslides. Due to its geography and climatic conditions, Ecuador has been significantly affected by landslides, and the city of Penipe remains one of the most affected. For this reason, a low-cost SDRadar system was designed to detect translational landslide risk levels by measuring the electrical permittivity of Andepts subtype soils. Controlled laboratory tests were performed with soil samples to relate permittivity values to landslide risk levels, and subsequently field tests were carried out in Penipe to determine the efficiency of the methodology. The results showed that moderate humidity is important for soil compaction, regardless of the degree of sloping. However, with permittivity values lower than 1.5 or higher than 20, the risk of landslides is very high on slopes greater than 45°. These results were compared with records of the serious landslides that occurred in June 2024 in Ecuador, in which rainfall intensity values similar to those obtained in this study were recorded, suggesting that this system can prevent future disasters. Full article

Agroforestry systems are recognized as sustainable land use practices that foster environmental health and promote adaptive responses to global change. By harnessing the synergies between trees and agricultural activities, agroforestry systems provide multiple benefits, including soil conservation, biodiversity enhancement, and carbon sequestration. Windbreaks form integral elements of Hungarian agricultural landscapes, and the enhanced agroforestry subsidy framework might have a favorable impact on their expansion, underscoring the importance of evaluating their potential for carbon sequestration. In the present study, we assess the implications of doubling the extent of windbreak plantations in Hungary by planting an additional 14,256 hectares of windbreaks. We evaluate the total carbon sequestration and the annual climate change mitigation potential of the new plantations up to 2050. For the modeling, we use the recently developed Windbreak module of the Forest Industry Carbon Model, which is a yield table-based model specific to Hungary and allows for the estimation of living biomass, dead organic matter, and soil carbon balance. We project that new windbreak plantations will sequester 913 kt C by 2050, representing an average annual climate change mitigation potential of 144 kt CO₂ eq. Our findings reveal that doubling the extent of windbreak plantations could achieve an extra 5% carbon sequestration in forested areas as compared to business-as-usual (BAU) conditions. We conclude that new windbreak plantations on agricultural field boundaries have substantial climate change mitigation potential, underscoring agroforestry’s contribution to agricultural resilience and achieving Hungary’s climate goals set for the land-use (LULUCF) sector. Full article

Arctic coastlines are the most vulnerable regions of the Earth, and local communities in those areas are being affected by rising sea levels and temperature. Therefore, Earth Observation combined with up-to-date geoinformation tools offers a dependable, cost-effective, and time-efficient approach to understanding the socioeconomic impact of climate changes in Arctic coastal areas. A promising approach is the Coastal Vulnerability Index (CVI), which takes into account different factors such as geomorphology, sea factors, and shoreline retreat or advance, to estimate the grade of vulnerability of a coastal area. Notwithstanding its potential, its application in the Arctic is still challenging. This study targets to estimate CVI to value the vulnerability of the coastal areas of Norway located in the Arctic. For the application of CVI and specifically for geomorphological and sea factors, data were acquired from international and national institutes. After the collection of all the necessary parameters for CVI was completed, all datasets were imported into a GIS software program (ArcGIS Pro) where the vulnerability classes of CVI were estimated. The results show that most of the coast of Northern Norway is characterized by a low to high degree of vulnerability, while in the island of Tromsø the vulnerability is mainly high and very high. Full article