The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents t...The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents the integration of morphometric indices to quantitatively assess the spatial variation of tectonic activity along the AFZ.The AFZ is an active fault with both strike-slip and normal fault components and consists of two main branches,Mercimekdağı-Çamdere Fault(MÇF)and Tokat Fault(TF)segments.This study aims to assess the relative tectonic activity of the AFZ using various morphometric indices,based on a 10 m resolution DEM,with the aid of ArcGIS and MATLAB software.For this purpose,morphometric indices such as hypsometric integral(HI:0.35-0.65),mountain front sinuosity(Smf:1.3-1.44),valley floor width-height ratio(Vf:0.15-2.28),asymmetry factor(AF:23-77),drainage basin shape(Bs:1.13-6.10)and normalized steepness index(ksn:1-498)were applied to 53 drainage basins.When the Smf and mean Vf indices results were evaluated,it was calculated that the uplift ratio of the region was more than 0.5 mm/yr.The spatial distribution of the relative tectonic activity(Iat)of the area was revealed by combining the obtained morphometric indices analysis results.According to the Iat result,it was concluded that the MercimekdağıÇamdere Fault and Tokat Fault segments have high tectonic activity,but the Mercimekdağı-Çamdere Fault segment has higher tectonic activity.The results obtained were also confirmed by field observations.This research provides valuable information for the evaluation of tectonic activity in drainage systems controlled by splay faults.展开更多
Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy ch...Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy chimneys,castle koppies,pillars,weathered rock blocks,perched rocks,cavernous weathering features,grooves,and gnammas,formed on tuffs in semi-arid to semi-humid climatic conditions,as well as geoarchaeological remains belonging to various civilisations,primarily the Phrygians(including rock-cut tombs and settlements,fortresses,rock churches,façades,altars,and niches).This study aims at identifying these remarkable landforms that host cultural heritage and revealing the geoheritage value and geotourism potential of the region.The data obtained from the fieldwork were evaluated using the methodology proposed by Pereira and Pereira in 2010,and 26 geomorphosites were selected from 61 potential sites using this method.The analysis results revealed that although the region hosts numerous geomorphosites with high scientific,cultural,aesthetic,and ecological value,the overall levels of protection and touristic use of these landforms are generally low.Indeed,the area,which has the potential to be an important tourism region in the future,faces problems such as infrastructure deficiencies,transportation difficulties,lack of promotion,weaknesses in accommodation services,and destruction of geoheritage.These results highlight the importance of implementing sustainable geotourism strategies that are compatible with the region’s unique geoheritage.In this respect,this study is among the first to comprehensively inventory and assess the geomorphosites of Mountainous Phrygia,contributing to regional geoconservation and sustainable tourism development.展开更多
Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of ...Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of dolines.In this research,doline susceptibility map was prepared in Saldaran mountain by generalized linear model(GLM)using 14 affecting parameters extracted from satellite images,digital elevation model,and geology map.Only 8 parameters have been inputted to the model which had correlation with dolines.In this regards,306 dolines were identified by the photogrammetric Unmanned Aerial Vehicles(UAV)method in 600 hectares of Salderan lands and then,these data were divided into the training(70%)and testing(30%)data for modelling.The results of DSM modeling showed that classified probability of doline occurrences in the Saldaran mountain were as follow:16.5%of the area high to very high,72%in the class of low to very low,and 5%in the moderate class.Also,locally,in Saldaran mountain,the Pirghar aquifer has the highest potential for the doline development,followed by Bagh Rostam and Sarab aquifers.Also,the precipitation,digital elevation model,Topographic Position Index,drainage density,slope,TRASP(transformed the circular aspect to a radiation index),Snow-Covered Days and vegetation cover index are of highest importance in the DSM modeling,respectively.Accurate evaluation of the model using the Receiver Operating Characteristics(ROC)curve represents a very good accuracy(AUC=0.953)of the DSM model.展开更多
Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research ...Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.展开更多
This study examines the impact of urbanization on the Surface Urban Heat Island(SUHI)effect in the Bangkok Metropolitan Region(BMR)over a 36-year period,utilizing advanced machine learning techniques to assess changes...This study examines the impact of urbanization on the Surface Urban Heat Island(SUHI)effect in the Bangkok Metropolitan Region(BMR)over a 36-year period,utilizing advanced machine learning techniques to assess changes in land use and land cover(LULC).The research addresses three key questions:(1)How have changes in LULC influenced the dynamics of the urban heat island(UHI)effect in the BMR?(2)What roles do green and blue infrastructure play in mitigating urban heat?(3)How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning?The findings reveal a strong correlation between urban growth and increased land surface temperatures(LST),with parks and water bodies exhibiting lower LSTs,emphasizing the importance of green and blue infrastructure in mitigating urban heat.The SUHI effect,initially measured at 3℃ from 1988 to 1991,peaked at 4.8℃ between 2012 and 2019 before slightly declining to 4.1℃ in recent years due to urban greening initiatives.However,ongoing urban development continues to diminish green spaces and water bodies,underscoring the urgent need for sustainable urban planning.Economic factors,including the 1997 Asian Financial Crisis and land tax laws introduced in 2019,influenced land use patterns,further exacerbating the SUHI effect.The research highlights the necessity of integrated urban management and sustainable land use policies to enhance climate resilience in rapidly urbanizing regions like the BMR.展开更多
This study examines the role of maize in food security and economic stability,focusing on its response to climate change and strategies to enhance resilience.Using a qualitative descriptive research methodology,the st...This study examines the role of maize in food security and economic stability,focusing on its response to climate change and strategies to enhance resilience.Using a qualitative descriptive research methodology,the study analyzes the impact of climate change on global maize production and proposes innovative strategies for sustainability and food security.The agricultural environment is vulnerable to heavy metal toxicity,which is linked to the relationship between soil health and climate change.From 1850 to 2020,the Earth’s temperature increased by 1.1℃,with projections indicating continued warming.This trend has significant economic implications,particularly in developing countries where agriculture employs 69%of the population.Heat waves and droughts represent abiotic stresses faced by maize.Research suggests that high greenhouse gas emissions could lead to a 24%reduction in maize yield by 2030.The study highlights the need to focus on breeding and phenotyping technologies to develop heat-and drought-tolerant maize varieties that use water efficiently.Additionally,strategies such as genomic editing,transcriptome analysis,and maize quality mapping are crucial to addressing these challenges.Developing insect-resistant maize is another objective.This study emphasizes the necessity of ongoing research to improve agricultural productivity and ensure food security,especially in light of global population growth.It also advocates for new regulations to reduce greenhouse gas emissions,which contribute to global warming.展开更多
This study investigates the prediction of groundwater Storage in the Rabat-Sale-Kenitra region under climate change conditions using advanced machine learning models.A comprehensive dataset encompassing hydrological,m...This study investigates the prediction of groundwater Storage in the Rabat-Sale-Kenitra region under climate change conditions using advanced machine learning models.A comprehensive dataset encompassing hydrological,meteorological,and geological factors was meticulously curated and preprocessed for model training.Six regression models Decision Tree,Random Forest,LightGBM,CatBoost,Extreme Learning Machine(ELM),and Artificial Neural Network(ANN)were employed to predict groundwater Storage,with hyperparameters optimized via grid search.The performance of these models was rigorously evaluated using metrics such as Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),and the coefficient of determination(R^(2)).Results demonstrated that the LightGBM model outperformed the others,achieving an impressive testing RMSE of 3.07 and an R^(2)of 0.9997,indicating its robustness in handling large datasets.The Extreme Learning Machine and ANN showed considerable limitations,highlighting the importance of model selection.This research underscores the critical role of advanced machine learning techniques in enhancing groundwater resource management,providing valuable insights for policymakers in developing sustainable strategies to address groundwater challenges in the face of climate variability.展开更多
Mangrove ecosystems support biodiversity,protect coastal areas,and provide sustainable livelihoods.However,they face significant threats from deforestation and unsustainable land use practices.This study examines the ...Mangrove ecosystems support biodiversity,protect coastal areas,and provide sustainable livelihoods.However,they face significant threats from deforestation and unsustainable land use practices.This study examines the viability of the payments for ecosystem services(PES)programs in promoting sustainable mangrove tourism in Tongke-Tongke Village,Sinjai District,South SulawesiProvince,Indonesia.We collected data through household surveys,semi-structured stakeholder interviews,and tourist questionnaires to evaluate the economic value of mangrove tourism and tourists’willingness to pay(WTP)for conservation.Analytical methods included quantitative descriptive analysis,thematic analysis,travel cost analysis,and contingent valuationmethod.The results indicatedstrong community support,with 70.00% of respondents acknowledging sustainable mangrove tourism’s economic,environmental,and cultural benefits.Economic estimates revealedthat mangrove tourism generated 943.00 USD/(hm^(2)·a),while tourists’WTP for conservation rangedfrom 0.21 to 0.56 USD/(person×month),contributing approximately 11.39 USD/(hm^(2)·a).Despite challenges such as inadequate infrastructure,socioeconomic disparities,and land privatization,this study advocates for integrating the PES programs,enhancing governance frameworks,and fostering local community engagement to ensure equitable benefit distribution and maximize the potential of mangrove tourism.These strategies aim to bolster conservation efforts,improve local livelihoods,and strengthen the resilience of mangroveecosystems.展开更多
The author affiliation and the funding information in the Acknowledgement section of the online version of the original article was revised.One affiliation(the 8th affiliation)of the first author is added.The Acknowle...The author affiliation and the funding information in the Acknowledgement section of the online version of the original article was revised.One affiliation(the 8th affiliation)of the first author is added.The Acknowledgement section of the original article has been revised to:Acknowledgments:This research was funded by the National University of Mongolia under grant agreement P2023(grant number P2023-4578)and supported by the Chey Institute for Advanced Studies“International Scholarship Exchange Fellowship for the academic year of 2024-2025”,Republic of Korea,and the National University of Mongolia.We would like to acknowledge the National University of Mongolia and Soumik Das from the Center for the Study of Regional Development,Jawaharlal Nehru University,New Delhi-110067,for his valuable assistance in preparing the geological maps.展开更多
Bees are essential to human life and ecosystems,significantly contributing to medicine,economics,and environmental equilibrium.Bees serve an essential function as pollinators,facilitating the cultivation of various fr...Bees are essential to human life and ecosystems,significantly contributing to medicine,economics,and environmental equilibrium.Bees serve an essential function as pollinators,facilitating the cultivation of various fruits and vegetables.Bees contribute approximately 117 billion US dollars annually to the economy through their role in crop pollination.They have a direct impact on 35%of agricultural crops and 84%of cultivated plants.Bee products,including honey,propolis,and royal jelly,have been utilized in various traditional medicine practices across numerous countries.These substances have been utilized for their anti-inflammatory,antioxidant,and antibacterial properties.In addition to their economic,ecological,and medical significance,they serve as bioindicators for assessing the health of ecological systems by monitoring distribution and population dynamics.This offers important insights into the current situation,especially regarding the substantial impacts of climate change on the environment.This article seeks to synthesize data from various studies to examine the impact of climate change on bee populations and their habitats.This study illustrates the significant effects of future climate models for 2050 and 2070 on bee distribution,resulting in the decline of specific species populations.展开更多
Meeting China's burgeoning food demand while safeguarding the resources and environmental long-term development is a critical challenge for the sustainable food systems of this century.China's accelerated food...Meeting China's burgeoning food demand while safeguarding the resources and environmental long-term development is a critical challenge for the sustainable food systems of this century.China's accelerated food imports have far-reaching implications for global resource allocation and environmental development.Hence,detailed information regarding China's food trade resource-environmental impacts is imperative for the design of effective policies that promote environmental mitigation and resource conservation.This study estimated the spatial transfers of virtual water trade(VWT),virtual land trade(VLT),and virtual GHG emission trade(VGT)embodied in China's food trade.Findings indicate that the VWT,VLT,and VGT transfers embodied in China's food trade increased by 10.4%,9.8%,and 15.2%annually.It is more important to mention that virtual water import(VWI)and virtual land import(VLI)saved 119.5×10~9m^(3)of global water resources and 29.5 Mha of land resources,respectively,but virtual GHG emission import(VGI)increased global 13 Mt CO_(2)-eq GHG emissions.The divergent impacts of China's food import on global food sustainability stem from variations in virtual water content,yields and emission intensities.Moreover,significant differences in sustainability scores were found among the top 15 importing countries,indicating that China's food trade contributes to the deepening of global food system sustainability.This study highlights the need for a multifaceted approach that considers the various environmental impacts of food trade.China is therefore encouraged to fully integrate the benefits of resource and environmental conservation into its sustainable food trade strategy,restructuring the food system to ensure the long-term nourishment of its large population.展开更多
Accurate spatial prediction of soil organic carbon(SOC)and soil inorganic carbon(SIC)is vital for land management decisions.This study targets SOC/SIC mapping challenges at the watershed scale in central Iran by addre...Accurate spatial prediction of soil organic carbon(SOC)and soil inorganic carbon(SIC)is vital for land management decisions.This study targets SOC/SIC mapping challenges at the watershed scale in central Iran by addressing environmental heterogeneity through a random forest(RF)model combined with bootstrapping to assess prediction uncertainty.Thirty-eight environmental variables-categorized into climatic,soil physicochemical,topographic,geomorphic,and remote sensing(RS)-based factors-were considered.Variable importance analysis(via)and partial dependence plots(PDP)identified land use,RS indices,and topography as key predictors of SOC.For SIC,soil reflectance(Bands 5 and 7,ETM+),topography,and geomorphic units were most influential.Climatic factors showed minimal impact in the studied semi-arid watershed.The RF model achieved moderate prediction accuracy(SOC:R^(2)=0.43±0.13,nRMSE=0.28;SIC:R^(2)=0.47±0.11,nRMSE=0.37).Via and PDP analyses enhanced model interpretability by clarifying environmental influences on SOC/SIC spatial distribution.展开更多
Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a...Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a.s.l.).The objectives of this study were to assess how climate influenced the formation of periglacial landforms in Mount Ilgar,identify the morphological characteristics of each patterned ground by periglacial landforms,and investigate the pedological processes,physicochemical,biological,and mineralogical characteristics of the soils that developed on each of them.Non-sorted steps,mud circles,and stony earth circles are examples of periglacial landforms found on the slopes of the hills?küzkoku(2804 m a.s.l.)and Misikan(2674 m a.s.l.)to the north of Mount Ilgar.In terms of soil physical characteristics,the average aggregate stability and clay content of soils created on non-sorted steps are 43.52%and 8.9%,respectively;these values,however,rise dramatically in soils formed on mud circles and stony earth circles.Chemically,the soils generated on the mud and stony earth circles have lower pH values than the soils formed on the non-sorted steps,but they have higher levels of organic matter.The microbial biomass carbon and basal respiration values of the soils generated on mud circles and stony earth circles are high due to the low pH values and high organic matter contents of these soils,which also have an impact on biological activity.The rate at which soils weather is also influenced by variations in their physical,chemical,and biological characteristics.It is found that the quartz mineral is more prevalent in the soils developed on mud circles landforms,despite the fact that the distribution of the basic clay minerals in the soils is essentially the same.Additionally,smectite clay minerals with a 2:1 layer are present,according to clay mineral analysis,especially in soils that are produced from mud circle formations.One may argue that the influence of local microtopographic landforms on soil formations were the primary cause of the differences in soils on periglacial landforms developed on identical geological material and at similar elevations.展开更多
This study investigates the spatial and temporal dynamics of key air pollutants-nitrogen dioxide(NO_(2)),carbon monoxide(CO),methane(CH_(4)),formaldehyde(HCHO),and the ultraviolet aerosol index(UVAI)-over the period 2...This study investigates the spatial and temporal dynamics of key air pollutants-nitrogen dioxide(NO_(2)),carbon monoxide(CO),methane(CH_(4)),formaldehyde(HCHO),and the ultraviolet aerosol index(UVAI)-over the period 2019-2024.Utilizing high-resolution remote sensing data from the Sentinel-5 Precursor satellite and its TROPOspheric Monitoring Instrument(TROPOMI)processed via Google Earth Engine(GEE),pollutant concentrations were analyzed,with spatial visualizations produced using ArcGIS Pro.The results reveal that urban and industrial hotspots-notably in Damascus,Aleppo,Homs,and Hama-exhibit elevated NO_(2) and CO levels,strongly correlated with population density,traffic,and industrial emissions.Temporal trends indicate significant pollutant fluctuations linked to external factors such as economic activities and regulatory measures.Methane concentrations have shown a steady increase,driven by intensified oil refining,biomass burning,and agricultural practices.Formaldehyde levels initially declined-due to reduced industrial activity-before experiencing a moderate rebound,though remaining below 2019 levels overall.The UV aerosol index demonstrated marked variability,predominantly influenced by winddriven dust transport,desert dust storms,and localized anthropogenic emissions.These findings underscore the intricate interplay between economic dynamics and environmental processes,highlighting the critical need for robust air quality management strategies.展开更多
Electricity theft significantly impacts the reliability and sustainability of electricity services,particularly in developing regions.However,the socio-economic,infrastructural,and institutional drivers of theft remai...Electricity theft significantly impacts the reliability and sustainability of electricity services,particularly in developing regions.However,the socio-economic,infrastructural,and institutional drivers of theft remain inadequately explored.Here we examine electricity theft in Lubumbashi,Democratic Republic of Congo,focusing on its patterns,causes,and impacts on service quality.Theft rates exceeded 75%in peripheral municipalities like Katuba and Kampemba,driven by poverty,weak law enforcement,and poor infrastructure dominated by above-ground networks.In contrast,central areas like Kamalondo and Lubumbashi reported lower theft rates due to better urban planning and underground systems.We found that electricity theft directly correlates with frequent voltage fluctuations,prolonged outages,and grid overloads.Socio-economic factors,including high connection fees and poverty,emerged as primary drivers,while institutional weaknesses such as corruption and ineffective enforcement perpetuate theft.Addressing theft requires a holistic approach integrating infrastructure modernization,socio-economic reforms,and institutional strengthening.Transitioning to underground networks,providing affordable electricity access,and adopting advanced metering systems are crucial.Overall,this study highlights the systemic nature of electricity theft and provides actionable insights for improving electricity service delivery and equity in urban settings.展开更多
Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides...Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics(ROC) curve, spatially agreed area approach and seed cell area index(SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.展开更多
The International Association of Hydrological Sciences （IAHS） recognized the lack of hydro- logical data as a world-wide problem in 2002 and adopted the Prediction of Ungauged Basins （PUB） as a decadal research ag...The International Association of Hydrological Sciences （IAHS） recognized the lack of hydro- logical data as a world-wide problem in 2002 and adopted the Prediction of Ungauged Basins （PUB） as a decadal research agenda during the period of 2003 to 2012. One of the objectives is to further develop methodologies for prediction in ungauged basins and to reduce uncertainties in model prediction. Estimation of stream flows is required for flood control, water quality control, valley habitat assessment and water budget of a country. However, the majority of water catchments, streams and valleys are ungauged in most developing countries. The main objective of this paper is to introduce the IHACRES （Identification of Hy- drographs and Components from Rainfall, Evaporation and Stream） model into African hydrological plan- ning as a methodology for water resources assessment, which in turn can be used to resolve water conflicts between communities and countries and to study the climate change issues. This is because the IHACRES model is applied for the estimation of flows in ungauged catchments whose physical catchments descriptors （PCDs） can be determined by driving variables （i.e. rainfall and temperature）; and also in gauged streams but whose gauging stations are no longer operational but historical data are available for model calibration. The model provides a valuable insight into the hydrologic behaviour of the upper water sources for valleys as well as provides a useful methodology for water resources assessment in situations of scarce financial resources in developing countries. In addition, it requires relatively few parameters in its calibration and has been successful applied in previous regionalization studies. It will also make possible the equitable distri- bution of water resources in international basins and rivers＇ catchments. This paper does not apply the model anywhere, but recommends it as a methodology for water resources assessment in order to cure water conflicts on the African continent.展开更多
文摘The Almus Fault Zone(AFZ)is one of the major splay faults of the North Anatolian Fault Zone(NAFZ)and is important for understanding its tectonic features and assessing regional seismic hazards.This research presents the integration of morphometric indices to quantitatively assess the spatial variation of tectonic activity along the AFZ.The AFZ is an active fault with both strike-slip and normal fault components and consists of two main branches,Mercimekdağı-Çamdere Fault(MÇF)and Tokat Fault(TF)segments.This study aims to assess the relative tectonic activity of the AFZ using various morphometric indices,based on a 10 m resolution DEM,with the aid of ArcGIS and MATLAB software.For this purpose,morphometric indices such as hypsometric integral(HI:0.35-0.65),mountain front sinuosity(Smf:1.3-1.44),valley floor width-height ratio(Vf:0.15-2.28),asymmetry factor(AF:23-77),drainage basin shape(Bs:1.13-6.10)and normalized steepness index(ksn:1-498)were applied to 53 drainage basins.When the Smf and mean Vf indices results were evaluated,it was calculated that the uplift ratio of the region was more than 0.5 mm/yr.The spatial distribution of the relative tectonic activity(Iat)of the area was revealed by combining the obtained morphometric indices analysis results.According to the Iat result,it was concluded that the MercimekdağıÇamdere Fault and Tokat Fault segments have high tectonic activity,but the Mercimekdağı-Çamdere Fault segment has higher tectonic activity.The results obtained were also confirmed by field observations.This research provides valuable information for the evaluation of tectonic activity in drainage systems controlled by splay faults.
文摘Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy chimneys,castle koppies,pillars,weathered rock blocks,perched rocks,cavernous weathering features,grooves,and gnammas,formed on tuffs in semi-arid to semi-humid climatic conditions,as well as geoarchaeological remains belonging to various civilisations,primarily the Phrygians(including rock-cut tombs and settlements,fortresses,rock churches,façades,altars,and niches).This study aims at identifying these remarkable landforms that host cultural heritage and revealing the geoheritage value and geotourism potential of the region.The data obtained from the fieldwork were evaluated using the methodology proposed by Pereira and Pereira in 2010,and 26 geomorphosites were selected from 61 potential sites using this method.The analysis results revealed that although the region hosts numerous geomorphosites with high scientific,cultural,aesthetic,and ecological value,the overall levels of protection and touristic use of these landforms are generally low.Indeed,the area,which has the potential to be an important tourism region in the future,faces problems such as infrastructure deficiencies,transportation difficulties,lack of promotion,weaknesses in accommodation services,and destruction of geoheritage.These results highlight the importance of implementing sustainable geotourism strategies that are compatible with the region’s unique geoheritage.In this respect,this study is among the first to comprehensively inventory and assess the geomorphosites of Mountainous Phrygia,contributing to regional geoconservation and sustainable tourism development.
文摘Doline susceptibility mapping(DSM)in karst aquifer is important in terms of estimating the vulnerability of the aquifer to pollutants,estimating the infiltration rate,and infrastructures exposed to the development of dolines.In this research,doline susceptibility map was prepared in Saldaran mountain by generalized linear model(GLM)using 14 affecting parameters extracted from satellite images,digital elevation model,and geology map.Only 8 parameters have been inputted to the model which had correlation with dolines.In this regards,306 dolines were identified by the photogrammetric Unmanned Aerial Vehicles(UAV)method in 600 hectares of Salderan lands and then,these data were divided into the training(70%)and testing(30%)data for modelling.The results of DSM modeling showed that classified probability of doline occurrences in the Saldaran mountain were as follow:16.5%of the area high to very high,72%in the class of low to very low,and 5%in the moderate class.Also,locally,in Saldaran mountain,the Pirghar aquifer has the highest potential for the doline development,followed by Bagh Rostam and Sarab aquifers.Also,the precipitation,digital elevation model,Topographic Position Index,drainage density,slope,TRASP(transformed the circular aspect to a radiation index),Snow-Covered Days and vegetation cover index are of highest importance in the DSM modeling,respectively.Accurate evaluation of the model using the Receiver Operating Characteristics(ROC)curve represents a very good accuracy(AUC=0.953)of the DSM model.
文摘Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.
文摘This study examines the impact of urbanization on the Surface Urban Heat Island(SUHI)effect in the Bangkok Metropolitan Region(BMR)over a 36-year period,utilizing advanced machine learning techniques to assess changes in land use and land cover(LULC).The research addresses three key questions:(1)How have changes in LULC influenced the dynamics of the urban heat island(UHI)effect in the BMR?(2)What roles do green and blue infrastructure play in mitigating urban heat?(3)How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning?The findings reveal a strong correlation between urban growth and increased land surface temperatures(LST),with parks and water bodies exhibiting lower LSTs,emphasizing the importance of green and blue infrastructure in mitigating urban heat.The SUHI effect,initially measured at 3℃ from 1988 to 1991,peaked at 4.8℃ between 2012 and 2019 before slightly declining to 4.1℃ in recent years due to urban greening initiatives.However,ongoing urban development continues to diminish green spaces and water bodies,underscoring the urgent need for sustainable urban planning.Economic factors,including the 1997 Asian Financial Crisis and land tax laws introduced in 2019,influenced land use patterns,further exacerbating the SUHI effect.The research highlights the necessity of integrated urban management and sustainable land use policies to enhance climate resilience in rapidly urbanizing regions like the BMR.
文摘This study examines the role of maize in food security and economic stability,focusing on its response to climate change and strategies to enhance resilience.Using a qualitative descriptive research methodology,the study analyzes the impact of climate change on global maize production and proposes innovative strategies for sustainability and food security.The agricultural environment is vulnerable to heavy metal toxicity,which is linked to the relationship between soil health and climate change.From 1850 to 2020,the Earth’s temperature increased by 1.1℃,with projections indicating continued warming.This trend has significant economic implications,particularly in developing countries where agriculture employs 69%of the population.Heat waves and droughts represent abiotic stresses faced by maize.Research suggests that high greenhouse gas emissions could lead to a 24%reduction in maize yield by 2030.The study highlights the need to focus on breeding and phenotyping technologies to develop heat-and drought-tolerant maize varieties that use water efficiently.Additionally,strategies such as genomic editing,transcriptome analysis,and maize quality mapping are crucial to addressing these challenges.Developing insect-resistant maize is another objective.This study emphasizes the necessity of ongoing research to improve agricultural productivity and ensure food security,especially in light of global population growth.It also advocates for new regulations to reduce greenhouse gas emissions,which contribute to global warming.
文摘This study investigates the prediction of groundwater Storage in the Rabat-Sale-Kenitra region under climate change conditions using advanced machine learning models.A comprehensive dataset encompassing hydrological,meteorological,and geological factors was meticulously curated and preprocessed for model training.Six regression models Decision Tree,Random Forest,LightGBM,CatBoost,Extreme Learning Machine(ELM),and Artificial Neural Network(ANN)were employed to predict groundwater Storage,with hyperparameters optimized via grid search.The performance of these models was rigorously evaluated using metrics such as Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),and the coefficient of determination(R^(2)).Results demonstrated that the LightGBM model outperformed the others,achieving an impressive testing RMSE of 3.07 and an R^(2)of 0.9997,indicating its robustness in handling large datasets.The Extreme Learning Machine and ANN showed considerable limitations,highlighting the importance of model selection.This research underscores the critical role of advanced machine learning techniques in enhancing groundwater resource management,providing valuable insights for policymakers in developing sustainable strategies to address groundwater challenges in the face of climate variability.
基金the State University of Makassar for their financial backing of this study(SP DIPA-023.17.2.677523/2021 Revision 01).
文摘Mangrove ecosystems support biodiversity,protect coastal areas,and provide sustainable livelihoods.However,they face significant threats from deforestation and unsustainable land use practices.This study examines the viability of the payments for ecosystem services(PES)programs in promoting sustainable mangrove tourism in Tongke-Tongke Village,Sinjai District,South SulawesiProvince,Indonesia.We collected data through household surveys,semi-structured stakeholder interviews,and tourist questionnaires to evaluate the economic value of mangrove tourism and tourists’willingness to pay(WTP)for conservation.Analytical methods included quantitative descriptive analysis,thematic analysis,travel cost analysis,and contingent valuationmethod.The results indicatedstrong community support,with 70.00% of respondents acknowledging sustainable mangrove tourism’s economic,environmental,and cultural benefits.Economic estimates revealedthat mangrove tourism generated 943.00 USD/(hm^(2)·a),while tourists’WTP for conservation rangedfrom 0.21 to 0.56 USD/(person×month),contributing approximately 11.39 USD/(hm^(2)·a).Despite challenges such as inadequate infrastructure,socioeconomic disparities,and land privatization,this study advocates for integrating the PES programs,enhancing governance frameworks,and fostering local community engagement to ensure equitable benefit distribution and maximize the potential of mangrove tourism.These strategies aim to bolster conservation efforts,improve local livelihoods,and strengthen the resilience of mangroveecosystems.
文摘The author affiliation and the funding information in the Acknowledgement section of the online version of the original article was revised.One affiliation(the 8th affiliation)of the first author is added.The Acknowledgement section of the original article has been revised to:Acknowledgments:This research was funded by the National University of Mongolia under grant agreement P2023(grant number P2023-4578)and supported by the Chey Institute for Advanced Studies“International Scholarship Exchange Fellowship for the academic year of 2024-2025”,Republic of Korea,and the National University of Mongolia.We would like to acknowledge the National University of Mongolia and Soumik Das from the Center for the Study of Regional Development,Jawaharlal Nehru University,New Delhi-110067,for his valuable assistance in preparing the geological maps.
文摘Bees are essential to human life and ecosystems,significantly contributing to medicine,economics,and environmental equilibrium.Bees serve an essential function as pollinators,facilitating the cultivation of various fruits and vegetables.Bees contribute approximately 117 billion US dollars annually to the economy through their role in crop pollination.They have a direct impact on 35%of agricultural crops and 84%of cultivated plants.Bee products,including honey,propolis,and royal jelly,have been utilized in various traditional medicine practices across numerous countries.These substances have been utilized for their anti-inflammatory,antioxidant,and antibacterial properties.In addition to their economic,ecological,and medical significance,they serve as bioindicators for assessing the health of ecological systems by monitoring distribution and population dynamics.This offers important insights into the current situation,especially regarding the substantial impacts of climate change on the environment.This article seeks to synthesize data from various studies to examine the impact of climate change on bee populations and their habitats.This study illustrates the significant effects of future climate models for 2050 and 2070 on bee distribution,resulting in the decline of specific species populations.
基金supported by the National Natural Science Foundation of China(Grant No.42301235)Gansu Province Key Research and Development Program Project(Grant No.22YF7FA124)+1 种基金Lanzhou Youth Science and Technology Talent Innovation Program(Grant No.2023-QN-54)Northwest Normal University Young Teachers’Research Ability Enhancement Program Backbone Project(Grant No.NWNU-LKQN2023-11)。
文摘Meeting China's burgeoning food demand while safeguarding the resources and environmental long-term development is a critical challenge for the sustainable food systems of this century.China's accelerated food imports have far-reaching implications for global resource allocation and environmental development.Hence,detailed information regarding China's food trade resource-environmental impacts is imperative for the design of effective policies that promote environmental mitigation and resource conservation.This study estimated the spatial transfers of virtual water trade(VWT),virtual land trade(VLT),and virtual GHG emission trade(VGT)embodied in China's food trade.Findings indicate that the VWT,VLT,and VGT transfers embodied in China's food trade increased by 10.4%,9.8%,and 15.2%annually.It is more important to mention that virtual water import(VWI)and virtual land import(VLI)saved 119.5×10~9m^(3)of global water resources and 29.5 Mha of land resources,respectively,but virtual GHG emission import(VGI)increased global 13 Mt CO_(2)-eq GHG emissions.The divergent impacts of China's food import on global food sustainability stem from variations in virtual water content,yields and emission intensities.Moreover,significant differences in sustainability scores were found among the top 15 importing countries,indicating that China's food trade contributes to the deepening of global food system sustainability.This study highlights the need for a multifaceted approach that considers the various environmental impacts of food trade.China is therefore encouraged to fully integrate the benefits of resource and environmental conservation into its sustainable food trade strategy,restructuring the food system to ensure the long-term nourishment of its large population.
基金The Iranian National Science Foundation(INSF)provided financial support for this research under Project Number 4004169the authors would like to thank Isfahan University of Technology and the University of Isfahan for their valuable contributions.
文摘Accurate spatial prediction of soil organic carbon(SOC)and soil inorganic carbon(SIC)is vital for land management decisions.This study targets SOC/SIC mapping challenges at the watershed scale in central Iran by addressing environmental heterogeneity through a random forest(RF)model combined with bootstrapping to assess prediction uncertainty.Thirty-eight environmental variables-categorized into climatic,soil physicochemical,topographic,geomorphic,and remote sensing(RS)-based factors-were considered.Variable importance analysis(via)and partial dependence plots(PDP)identified land use,RS indices,and topography as key predictors of SOC.For SIC,soil reflectance(Bands 5 and 7,ETM+),topography,and geomorphic units were most influential.Climatic factors showed minimal impact in the studied semi-arid watershed.The RF model achieved moderate prediction accuracy(SOC:R^(2)=0.43±0.13,nRMSE=0.28;SIC:R^(2)=0.47±0.11,nRMSE=0.37).Via and PDP analyses enhanced model interpretability by clarifying environmental influences on SOC/SIC spatial distribution.
基金supported by Ardahan University,Scientific Research Projects Office(Project No:2020-001)。
文摘Soil development may be impacted by periglacial processes that take place in regions where freezing and thawing episodes predominate.Mount Ilgar(2918 m a.s.l.)is a volcanic mass located on the Lesser Caucasus(4090 m a.s.l.).The objectives of this study were to assess how climate influenced the formation of periglacial landforms in Mount Ilgar,identify the morphological characteristics of each patterned ground by periglacial landforms,and investigate the pedological processes,physicochemical,biological,and mineralogical characteristics of the soils that developed on each of them.Non-sorted steps,mud circles,and stony earth circles are examples of periglacial landforms found on the slopes of the hills?küzkoku(2804 m a.s.l.)and Misikan(2674 m a.s.l.)to the north of Mount Ilgar.In terms of soil physical characteristics,the average aggregate stability and clay content of soils created on non-sorted steps are 43.52%and 8.9%,respectively;these values,however,rise dramatically in soils formed on mud circles and stony earth circles.Chemically,the soils generated on the mud and stony earth circles have lower pH values than the soils formed on the non-sorted steps,but they have higher levels of organic matter.The microbial biomass carbon and basal respiration values of the soils generated on mud circles and stony earth circles are high due to the low pH values and high organic matter contents of these soils,which also have an impact on biological activity.The rate at which soils weather is also influenced by variations in their physical,chemical,and biological characteristics.It is found that the quartz mineral is more prevalent in the soils developed on mud circles landforms,despite the fact that the distribution of the basic clay minerals in the soils is essentially the same.Additionally,smectite clay minerals with a 2:1 layer are present,according to clay mineral analysis,especially in soils that are produced from mud circle formations.One may argue that the influence of local microtopographic landforms on soil formations were the primary cause of the differences in soils on periglacial landforms developed on identical geological material and at similar elevations.
基金funded in part by the Brazilian Federal Agency for the Support and Evaluation of Graduate Education(CAPES)-Finance Code 001,and by the National Council for Scientific and Technological Development(CNPq),Brazil(Grant Nos.313358/2021-4 and 443905/2023-1).
文摘This study investigates the spatial and temporal dynamics of key air pollutants-nitrogen dioxide(NO_(2)),carbon monoxide(CO),methane(CH_(4)),formaldehyde(HCHO),and the ultraviolet aerosol index(UVAI)-over the period 2019-2024.Utilizing high-resolution remote sensing data from the Sentinel-5 Precursor satellite and its TROPOspheric Monitoring Instrument(TROPOMI)processed via Google Earth Engine(GEE),pollutant concentrations were analyzed,with spatial visualizations produced using ArcGIS Pro.The results reveal that urban and industrial hotspots-notably in Damascus,Aleppo,Homs,and Hama-exhibit elevated NO_(2) and CO levels,strongly correlated with population density,traffic,and industrial emissions.Temporal trends indicate significant pollutant fluctuations linked to external factors such as economic activities and regulatory measures.Methane concentrations have shown a steady increase,driven by intensified oil refining,biomass burning,and agricultural practices.Formaldehyde levels initially declined-due to reduced industrial activity-before experiencing a moderate rebound,though remaining below 2019 levels overall.The UV aerosol index demonstrated marked variability,predominantly influenced by winddriven dust transport,desert dust storms,and localized anthropogenic emissions.These findings underscore the intricate interplay between economic dynamics and environmental processes,highlighting the critical need for robust air quality management strategies.
文摘Electricity theft significantly impacts the reliability and sustainability of electricity services,particularly in developing regions.However,the socio-economic,infrastructural,and institutional drivers of theft remain inadequately explored.Here we examine electricity theft in Lubumbashi,Democratic Republic of Congo,focusing on its patterns,causes,and impacts on service quality.Theft rates exceeded 75%in peripheral municipalities like Katuba and Kampemba,driven by poverty,weak law enforcement,and poor infrastructure dominated by above-ground networks.In contrast,central areas like Kamalondo and Lubumbashi reported lower theft rates due to better urban planning and underground systems.We found that electricity theft directly correlates with frequent voltage fluctuations,prolonged outages,and grid overloads.Socio-economic factors,including high connection fees and poverty,emerged as primary drivers,while institutional weaknesses such as corruption and ineffective enforcement perpetuate theft.Addressing theft requires a holistic approach integrating infrastructure modernization,socio-economic reforms,and institutional strengthening.Transitioning to underground networks,providing affordable electricity access,and adopting advanced metering systems are crucial.Overall,this study highlights the systemic nature of electricity theft and provides actionable insights for improving electricity service delivery and equity in urban settings.
文摘Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics(ROC) curve, spatially agreed area approach and seed cell area index(SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.
文摘The International Association of Hydrological Sciences （IAHS） recognized the lack of hydro- logical data as a world-wide problem in 2002 and adopted the Prediction of Ungauged Basins （PUB） as a decadal research agenda during the period of 2003 to 2012. One of the objectives is to further develop methodologies for prediction in ungauged basins and to reduce uncertainties in model prediction. Estimation of stream flows is required for flood control, water quality control, valley habitat assessment and water budget of a country. However, the majority of water catchments, streams and valleys are ungauged in most developing countries. The main objective of this paper is to introduce the IHACRES （Identification of Hy- drographs and Components from Rainfall, Evaporation and Stream） model into African hydrological plan- ning as a methodology for water resources assessment, which in turn can be used to resolve water conflicts between communities and countries and to study the climate change issues. This is because the IHACRES model is applied for the estimation of flows in ungauged catchments whose physical catchments descriptors （PCDs） can be determined by driving variables （i.e. rainfall and temperature）; and also in gauged streams but whose gauging stations are no longer operational but historical data are available for model calibration. The model provides a valuable insight into the hydrologic behaviour of the upper water sources for valleys as well as provides a useful methodology for water resources assessment in situations of scarce financial resources in developing countries. In addition, it requires relatively few parameters in its calibration and has been successful applied in previous regionalization studies. It will also make possible the equitable distri- bution of water resources in international basins and rivers＇ catchments. This paper does not apply the model anywhere, but recommends it as a methodology for water resources assessment in order to cure water conflicts on the African continent.
