The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been doc...The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been documented.This study aims to answer the following questions:Will the typical soums in the SRB become more overgrazed in the future?What optimal strategy should be implemented?Multisource data were integrated and utilized to model the pastoral system of typical soums using a system dynamics approach.Future scenarios under three SSP-RCPs were projected using the model.The conclusions are as follows:(1)From upstream to downstream,rational scenarios for pastoral system transferred from SSP1-RCP2.6 to SSP2-RCP4.5,which reflect improved productivity at the expense of ecosystem stability.(2)Compared with that during the historical period of 2000-2020,the projected carrying capacity of the soums decreases by 15.2%-37.3%,whereas the number of livestock continues to increase.Consequently,the stocking rate is expected to increase from 0.32-1.16 during 2000-2020 to 1.26-2.02 during 2021-2050,indicating that rangeland will become more overloaded.(3)A livestock reduction strategy based on future livestock stock and grassland carrying capacity scenarios was proposed to maintain a dynamic forage-livestock equilibrium.It is suggested that reducing livestock is a practical option for harmonizing grassland conservation with livestock husbandry development.展开更多
This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis...This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis,and Sen's slope estimation methods,historical climate trends(1980-2100)were analyzed,while land cover changes represented human impacts.Future projections were simulated using the MIROC model with Shared Socioeconomic Pathways(SSPs)and the Tank model.Results show that during the past 40 years,air temperature significantly increased(Z=3.93^(***)),while precipitation(Z=-1.54^(*))and river flow(Z=-1.73^(*))both declined.The Khyargas Lake water level dropped markedly(Z=-5.57***).Land cover analysis reveals expanded cropland and impervious areas due to human activity.Under the SSP1.26 scenario,which assumes minimal climate change,air temperature is projected to rise by 2.0℃,precipitation by 21.8 mm,and river discharge by 1.61 m^(3)/s between 2000 and 2100.These findings indicate that both global warming and intensified land use have substantially altered hydrological and climatic processes in the basin,highlighting the vulnerability of western Mongolia's water resources to combined climatic and anthropogenic influence.展开更多
The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide ...The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.展开更多
There is currently considerable interest in what degrowth compatible business practices may be and what they may look like.However,while the embeddedness of a degrowth business in the wider environment has been recogn...There is currently considerable interest in what degrowth compatible business practices may be and what they may look like.However,while the embeddedness of a degrowth business in the wider environment has been recognised,and this affects theorising of practices and principles,there remains a need to seriously consider the inter-connection between degrowth business and its surrounding environment as a physical and cultural space.To avoid merely hinting at geographical concepts such as space,place,and location,a better approach is establishing a dialogue between degrowth business and geography.To do this,I use the degrowth business framework and connect its elements with the concepts of space,place,and location.This analysis shows that each of the elements is intimately inter-related with geographical concepts and needs to be thought of,theorised,and implemented as such.I conclude that geographical concepts should not be merely implied when theorising degrowth business.Rather,looking at degrowth business through various lenses provided by geographies is indispensable for making degrowth reality in diverse locations.展开更多
Currently, the OGC GML （Geography Markup Language） specification has been the de facto standard for GIS data sharing and exchanging and spatial interoperation. Adopting nested association expression approach of XML ...Currently, the OGC GML （Geography Markup Language） specification has been the de facto standard for GIS data sharing and exchanging and spatial interoperation. Adopting nested association expression approach of XML data, GML data documents can store both spatial information and semantic relationship information of geographical elements. To improve the efficiency of path query on GML two type information, the paper describes a holistic index method for GML data, which we call EKR^＋ （optimized R＋-tree base on Extend Region Code and K-means extent partition of GML feature elements）. The experiment results show that the efficiency of semantic-spatial query can be improved greatly by utilizing EKR^＋.展开更多
Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful l...Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful land resource management plan is the evaluation of Land Use Land Cover(LULC).Over the past 20 years,our planet’s land cover resources have undergone substantial changes due to rapid development.The Land Use Land Cover(LULC)categories of the Patna Urban Agglomeration(PUA),including water bodies,agricultural land,barren land,built-up areas,and vegetation,were identified using Geographic Information System(GIS)techniques.Three multi-temporal images were analyzed and classified through supervised classification using the maximum likelihood method.By comparing three separately created LULC categorized maps from 1990 and 2024,temporal changes were analyzed.In order to update land cover or manage natural resources,it is vital to use change detection as a tool to identify changes in LULC over time in PUA,Patna between 1990,2010 and 2024.According to their respective Kappa coefficients,the accuracy rates for 1990,2010 and 2024 LULC are 91.66 and 94.93,respectively.An accuracy evaluation was conducted to determine the correctness of the classification system and to determine the efficacy of the LULC classification maps.One hundred reference test pixels were identified.There have been found significant changes in the LULC were built up area has increased doubled in last thirty-four years of timeline.展开更多
Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different educ...Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.展开更多
Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LM...Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.展开更多
Land use transformations in Sonipat District,Haryana,driven by urbanization,industrialization,and land acquisitions,have posed significant ecological and socio-economic challenges,particularly concerning food security...Land use transformations in Sonipat District,Haryana,driven by urbanization,industrialization,and land acquisitions,have posed significant ecological and socio-economic challenges,particularly concerning food security.This study investigates the interplay between these land use changes and their environmental implications at macro(district)and micro(village)levels,focusing on agricultural productivity and resource sustainability.The study employs a mixed-method approach,integrating secondary data from official datasets and primary data gathered through structured household surveys,focus group discussions,and visual analysis techniques.Data from 20 villages,selected based on predominant land use characteristics,were analysed using statistical and geospatial tools,including ArcGIS and STATA,to quantify food grain losses and evaluate environmental degradation.Findings of this study reveal a 19%reduction in agricultural land over two decades(2000-2024),correlating with increased residential and industrial areas.Groundwater resources face severe overexploitation,with pollution from industrial clusters further degrading water and soil quality.The study estimates a total food grain loss of 1.5 million kilograms across surveyed villages due to land acquisitions.A strong positive correlation(R^(2)=0.98)between land acquisition and food loss underscores the direct impact of urbanization on agricultural output.The research underscores the urgency of sustainable land management practices,including preserving agricultural lands,optimizing groundwater usage,and enhancing community involvement in planning.By addressing these challenges,the study advocates for balanced urban expansion and food security to ensure ecological and economic resilience in the region.展开更多
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research probl...Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.展开更多
Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environment...Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.展开更多
Vegetable toothbrushes are secondary forest products with health, medicinal, and pharmaceutical properties. They constitute an important resource permanently exploited by the populations of the Kpakpamè District....Vegetable toothbrushes are secondary forest products with health, medicinal, and pharmaceutical properties. They constitute an important resource permanently exploited by the populations of the Kpakpamè District. This research aims to identify the different plants used by the populations of Kpakpamè as toothbrushes and their therapeutic values. To reach this objective, documentary research, direct observation, and data collection from hundred and ninety-five (195) people randomly chosen but following well-defined criteria were carried out. The consensus value for plant parts noted CPP, is calculated to find the number of times a plant part is cited (Px) divided by the total number of times all parts are cited (Pt), and also to determine the most frequent collection sites, the consensus value for collection sites is calculated. In total, nineteen (19) species have been cited and grouped into nineteen (19) genera and eleven (11) families. Pseudocedrella kostchyi and Zanthoxylum zanthoxyloides are the most cited species with respective citation frequencies of 0.27 and 0.14. They come more from village lands with a Consensus value for collection sites (CCS) of 0.49 and are used to cure about twelve (12) diseases including dental caries (33.33%). These species are now almost threatened with extinction according to the IUCN. It is therefore important to develop safeguarding and sustainable conservation actions for these plant species. This work has made it possible to identify the different species used by the populations of the Kpakpamé district as toothbrushes despite the urbanization and modernization of this locality formerly known in the Zou department as the most endogenous region. Several studies have focused on the diversity of plants used for oral hygiene and even the phytochemical properties of the species identified without taking into account the phytodistrict, social and perceptions of local populations.展开更多
Studies on plant diversity are usually based on the total number of species in a community.However,few studies have examined species richness(SR)of different plant life forms in a community along largescale environmen...Studies on plant diversity are usually based on the total number of species in a community.However,few studies have examined species richness(SR)of different plant life forms in a community along largescale environmental gradients.Particularly,the relative importance(RIV)of different plant life forms in a community and how they vary with environmental variables are still unclear.To fill these gaps,we determined plant diversity of ephemeral plants,annual herbs,perennial herbs,and woody plants from 187 sites across drylands in China.The SR patterns of herbaceous plants,especially perennial herbs,and their RIV in plant communities increased with increasing precipitation and soil nutrient content;however,the RIV of annual herbs was not altered along these gradients.The SR and RIV of ephemeral plants were affected mainly by precipitation seasonality.The SR of woody plants had a unimodal relationship with air temperature and exhibited the highest RIV and SR percentage in plant communities under the harshest environments.An obvious shift emerged in plant community composition,SR and their critical impact factors at 238.5 mm of mean annual precipitation(MAP).In mesic regions(>238.5 mm),herbs were the dominant species,and the SR displayed a relatively slow decreasing rate with increasing aridity,which was mediated mainly by MAP and soil nutrients.In arid regions(<238.5 mm),woody plants were the dominant species,and the SR displayed a relatively fast decreasing rate with increasing aridity,which was mediated mainly by climate variables,especially precipitation.Our findings highlight the importance of comparative life form studies in community structure and biodiversity,as their responses to gradients differed substantially on a large scale.展开更多
The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and...The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.展开更多
Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention ha...Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention has been paid to changes in the genesis locations of mesoscale eddies.Here,we provide evidence from three decades of satellite altimetry observations for the heterogeneity of the poleward shift of mesoscale activities,with the largest trend of~0.23°±0.05°(10 yr)^(-1) over the Atlantic sector and a moderate trend of~0.1°±0.03°(10 yr)^(-1) over the Indian sector,but no significant trend in the Pacific sector.The poleward shift of mesoscale eddies is associated with a southward shift of the local westerly winds while being constrained by the major topographies.As the poleward shift of westerly winds is projected to persist,the poleward oceanic heat flux from mesoscale eddies may influence future ice melt.展开更多
The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that...The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.展开更多
This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.W...This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO₂,nano-Fe₃O₄,and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.展开更多
Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flo...Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flood frequency analysis(FFA)and flood susceptibility mapping cannot be overstated.This study focuses on the Haora River basin in Tripura,a region prone to frequent flooding due to a combination of natural and anthropogenic factors.This study evaluates the suitability of the Log-Pearson Type Ⅲ(LP-Ⅲ)and Gumbel Extreme Value-1(EV-1)distributions for estimating peak discharges and delineates floodsusceptible zones in the Haora River basin,Tripura.Using 40 years of peak discharge data(1984-2023),the LP-Ⅲ distribution was identified as the most appropriate model based on goodness-of-fit tests.Flood susceptibility mapping,integrating 16 thematic layers through the Analytical Hierarchy Process,identified 8%,64%,and 26%of the area as high,moderate,and low susceptibility zones,respectively,with a model success rate of 0.81.The findings highlight the need for improved flood management strategies,such as enhancing river capacity and constructing flood spill channels.These insights are critical for designing targeted flood mitigation measures in the Haora basin and other flood-prone regions.展开更多
Natural resource management is essential to sustain human well-being and the environment.Water and soil are two of the most important natural resources that require careful management.The western part of India faces m...Natural resource management is essential to sustain human well-being and the environment.Water and soil are two of the most important natural resources that require careful management.The western part of India faces multiple challenges,including climatic variability,soil degradation,water scarcity,deforestation,etc.The basin’s sub-watersheds are delineated and prioritised using the Soil and Water Assessment Tool(SWAT)and Sub Watershed Prioritization Tool(SWPT),respectively,using morphometric and topo-hydrological characteristics,and the sub-watersheds are further ranked using Weighted Sum Analysis(WSA).The findings indicate that SWS19,SWS18,SWS1,SWS17,SWS16,and SWS15,which are drained by the rivers Chambal,Kali Sindh,Mashi,Parbati,Parwan,and Beradi,are highly vulnerable sub-watersheds.By integrating remote sensing,GIS techniques,and quantitative morphometric analysis,parameters such as drainage density,stream frequency,bifurcation ratio,and slope gradient were evaluated.The analysis revealed critical sub-watersheds characterized by steep slopes,high drainage density,and poor vegetation cover,indicating their susceptibility to erosion and runoff.The findings underscore the necessity for targeted soil conservation measures,such as contour bunding,afforestation,and water retention structures.This study highlights the utility of geospatial tools for sustainable watershed management and provides a replicable framework for prioritizing sub-watersheds in similar regions.展开更多
基金National Natural Science Foundation of China,No.32161143025,No.42371283,No.W2412155National Key R&D Program of China,No.2022YFE0119200。
文摘The Selenge River Basin(SRB)in Mongolia has faced ecosystem degradation because of climate change and overloading.The dynamics of the pastoral system and the extent of overload under future scenarios have not been documented.This study aims to answer the following questions:Will the typical soums in the SRB become more overgrazed in the future?What optimal strategy should be implemented?Multisource data were integrated and utilized to model the pastoral system of typical soums using a system dynamics approach.Future scenarios under three SSP-RCPs were projected using the model.The conclusions are as follows:(1)From upstream to downstream,rational scenarios for pastoral system transferred from SSP1-RCP2.6 to SSP2-RCP4.5,which reflect improved productivity at the expense of ecosystem stability.(2)Compared with that during the historical period of 2000-2020,the projected carrying capacity of the soums decreases by 15.2%-37.3%,whereas the number of livestock continues to increase.Consequently,the stocking rate is expected to increase from 0.32-1.16 during 2000-2020 to 1.26-2.02 during 2021-2050,indicating that rangeland will become more overloaded.(3)A livestock reduction strategy based on future livestock stock and grassland carrying capacity scenarios was proposed to maintain a dynamic forage-livestock equilibrium.It is suggested that reducing livestock is a practical option for harmonizing grassland conservation with livestock husbandry development.
基金The National University of Mongolia,No.P2024-4814The Mongolian Science and Technology Foundation,No.CHN-2022/274The‘Chey Institute for Advanced Studies’International Scholar Exchange Fellowship for the Academic Year of 2025-2026。
文摘This study investigates climate-and human-induced hydrological changes in the Zavkhan River-Khyargas Lake Basin,a highly sensitive arid and semi-arid region of Central Asia.Using Mann-Kendall,innovative trend analysis,and Sen's slope estimation methods,historical climate trends(1980-2100)were analyzed,while land cover changes represented human impacts.Future projections were simulated using the MIROC model with Shared Socioeconomic Pathways(SSPs)and the Tank model.Results show that during the past 40 years,air temperature significantly increased(Z=3.93^(***)),while precipitation(Z=-1.54^(*))and river flow(Z=-1.73^(*))both declined.The Khyargas Lake water level dropped markedly(Z=-5.57***).Land cover analysis reveals expanded cropland and impervious areas due to human activity.Under the SSP1.26 scenario,which assumes minimal climate change,air temperature is projected to rise by 2.0℃,precipitation by 21.8 mm,and river discharge by 1.61 m^(3)/s between 2000 and 2100.These findings indicate that both global warming and intensified land use have substantially altered hydrological and climatic processes in the basin,highlighting the vulnerability of western Mongolia's water resources to combined climatic and anthropogenic influence.
基金Under the auspices of the National Social Science Foundation of China(No.17ZDA055).
文摘The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.
文摘There is currently considerable interest in what degrowth compatible business practices may be and what they may look like.However,while the embeddedness of a degrowth business in the wider environment has been recognised,and this affects theorising of practices and principles,there remains a need to seriously consider the inter-connection between degrowth business and its surrounding environment as a physical and cultural space.To avoid merely hinting at geographical concepts such as space,place,and location,a better approach is establishing a dialogue between degrowth business and geography.To do this,I use the degrowth business framework and connect its elements with the concepts of space,place,and location.This analysis shows that each of the elements is intimately inter-related with geographical concepts and needs to be thought of,theorised,and implemented as such.I conclude that geographical concepts should not be merely implied when theorising degrowth business.Rather,looking at degrowth business through various lenses provided by geographies is indispensable for making degrowth reality in diverse locations.
文摘Currently, the OGC GML （Geography Markup Language） specification has been the de facto standard for GIS data sharing and exchanging and spatial interoperation. Adopting nested association expression approach of XML data, GML data documents can store both spatial information and semantic relationship information of geographical elements. To improve the efficiency of path query on GML two type information, the paper describes a holistic index method for GML data, which we call EKR^＋ （optimized R＋-tree base on Extend Region Code and K-means extent partition of GML feature elements）. The experiment results show that the efficiency of semantic-spatial query can be improved greatly by utilizing EKR^＋.
文摘Patna is among the cities high populated at risk of ecological and environmental deterioration due to a variety of human activities,such as poor land cover management.One of the most crucial elements of a successful land resource management plan is the evaluation of Land Use Land Cover(LULC).Over the past 20 years,our planet’s land cover resources have undergone substantial changes due to rapid development.The Land Use Land Cover(LULC)categories of the Patna Urban Agglomeration(PUA),including water bodies,agricultural land,barren land,built-up areas,and vegetation,were identified using Geographic Information System(GIS)techniques.Three multi-temporal images were analyzed and classified through supervised classification using the maximum likelihood method.By comparing three separately created LULC categorized maps from 1990 and 2024,temporal changes were analyzed.In order to update land cover or manage natural resources,it is vital to use change detection as a tool to identify changes in LULC over time in PUA,Patna between 1990,2010 and 2024.According to their respective Kappa coefficients,the accuracy rates for 1990,2010 and 2024 LULC are 91.66 and 94.93,respectively.An accuracy evaluation was conducted to determine the correctness of the classification system and to determine the efficacy of the LULC classification maps.One hundred reference test pixels were identified.There have been found significant changes in the LULC were built up area has increased doubled in last thirty-four years of timeline.
基金Under the auspices of Natural Science Basic Research Plan in Shaanxi Province of China(No.2024JC-YBMS-196)。
文摘Increased exposure to campus green spaces can make a positive contribution to the healthy development of students.However,understanding of the current supply of campus green space(CGS)and its drivers at different education stages is still limited.A new framework was established to evaluate the spatial heterogeneity and its influencing factors across all education stages(kindergarten,primary school,middle school,college)in 1100 schools at the urban scale of Xi’an,China.The research results show that:1)CGS is lower in the Baqiao district and higher in the Yanta and Xincheng districts of Xi’an City.‘Green wealthy schools are mainly concentrated in the Weiyang,Chang’an and Yanta districts.2)CGS of these schools in descending order is college(31.40%)>kindergarten(18.32%)>middle school(13.56%)>primary school(10.70%).3)Colleges have the most recreation sites(n(number)=2),the best education levels(11.93 yr),and the lowest housing prices(1.18×10^(4) yuan(RMB)/m^(2));middle schools have the highest public expenditures(3.97×10^(9) yuan/yr);primary schools have the highest CGS accessibility(travel time gap(TTG)=31.33).4)Multiscale Geographically Weighted Regression model and Spearman’s test prove that recreation sites have a significant positive impact on college green spaces(0.28–0.35),and education level has a significant positive impact on kindergarten green spaces(0.16–0.24).This research framework provides important insights for the assessment of school greening initiatives aimed at fostering healthier learning environments for future generations.
基金National Natural Science Foundation of China,No.42161006Yunnan Fundamental Research Projects No.202201AT070094,No.202301BF070001-004+1 种基金Special Project for High-level Talents of Yunnan Province for Young Top Talents,No.C6213001159European Research Council(ERC)Starting-Grant STORIES,No.101040939。
文摘Due to water conflicts and allocation in the Lancang-Mekong River Basin(LMRB),the spatio-temporal differentiation of total water resources and the natural-human influence need to be clarified.This work investigated LMRB's terrestrial water storage anomaly(TWSA)and its spatio-temporal dynamics during 2002–2020.Considering the effects of natural factors and human activities,the respective contributions of climate variability and human activities to terrestrial water storage change(TWSC)were separated.Results showed that:(1)LMRB's TWSA decreased by 0.3158 cm/a.(2)TWSA showed a gradual increase in distribution from southwest of MRB to middle LMRB and from northeast of LRB to middle LMRB.TWSA positively changed in Myanmar while slightly changed in Laos and China.It negatively changed in Vietnam,Thailand and Cambodia.(3)TWSA components decreased in a descending order of soil moisture,groundwater and precipitation.(4)Natural factors had a substantial and spatial differentiated influence on TWSA over the LMRB.(5)Climate variability contributed 79%of TWSC in the LMRB while human activities contributed 21%with an increasing impact after 2008.The TWSC of upstream basin countries was found to be controlled by climate variability while Vietnam and Cambodia's TWSC has been controlled by human activities since 2012.
文摘Land use transformations in Sonipat District,Haryana,driven by urbanization,industrialization,and land acquisitions,have posed significant ecological and socio-economic challenges,particularly concerning food security.This study investigates the interplay between these land use changes and their environmental implications at macro(district)and micro(village)levels,focusing on agricultural productivity and resource sustainability.The study employs a mixed-method approach,integrating secondary data from official datasets and primary data gathered through structured household surveys,focus group discussions,and visual analysis techniques.Data from 20 villages,selected based on predominant land use characteristics,were analysed using statistical and geospatial tools,including ArcGIS and STATA,to quantify food grain losses and evaluate environmental degradation.Findings of this study reveal a 19%reduction in agricultural land over two decades(2000-2024),correlating with increased residential and industrial areas.Groundwater resources face severe overexploitation,with pollution from industrial clusters further degrading water and soil quality.The study estimates a total food grain loss of 1.5 million kilograms across surveyed villages due to land acquisitions.A strong positive correlation(R^(2)=0.98)between land acquisition and food loss underscores the direct impact of urbanization on agricultural output.The research underscores the urgency of sustainable land management practices,including preserving agricultural lands,optimizing groundwater usage,and enhancing community involvement in planning.By addressing these challenges,the study advocates for balanced urban expansion and food security to ensure ecological and economic resilience in the region.
基金supported by the Key Research and Development Program in Shaanxi Province,China(No.2022ZDLSF07-05)the Fundamental Research Funds for the Central Universities,CHD(No.300102352901)。
文摘Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide.Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem.Previous studies relied on statistical regression models that failed to capture the complex nonlinear relationships between carbon emissions and characteristic variables.In this study,we propose a machine learning algorithm for carbon emissions,a Bayesian optimized XGboost regression model,using multi-year energy carbon emission data and nighttime lights(NTL)remote sensing data from Shaanxi Province,China.Our results demonstrate that the XGboost algorithm outperforms linear regression and four other machine learning models,with an R^(2)of 0.906 and RMSE of 5.687.We observe an annual increase in carbon emissions,with high-emission counties primarily concentrated in northern and central Shaanxi Province,displaying a shift from discrete,sporadic points to contiguous,extended spatial distribution.Spatial autocorrelation clustering reveals predominantly high-high and low-low clustering patterns,with economically developed counties showing high-emission clustering and economically relatively backward counties displaying low-emission clustering.Our findings show that the use of NTL data and the XGboost algorithm can estimate and predict carbon emissionsmore accurately and provide a complementary reference for satellite remote sensing image data to serve carbon emission monitoring and assessment.This research provides an important theoretical basis for formulating practical carbon emission reduction policies and contributes to the development of techniques for accurate carbon emission estimation using remote sensing data.
基金National Natural Science Foundation of China,No.42207078CUG Scholar-Scientific Research Funds at China University of Geosciences(Wuhan),No.2022166+1 种基金China Scholarship Council,No.202306410026Opening Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research,No.IWHR-SKL-KF202217。
文摘Wetlands play a critical role in the global environment.The Middle Yangtze River Basin(MYRB),known for its abundant wetland resources,has experienced notable changes resulting from the complex interplay of environmental factors.Therefore,we investigated the spatiotemporal characteristics of wetland ecological quality in the MYRB from 2001 to 2020.Utilizing the random forest(RF)regression algorithm and patch-generated land-use simulation(PLUS)model,we forecasted variations in wetland habitat quality and their determinants under the Shared Socioeconomic Pathway-Representative Concentration Pathway(SSPRCP)framework from 2035 to 2095.The main findings are as follows:(1)The RF algorithm was optimal for land-use and land-cover(LULC)classification in the MYRB from 2001 to 2020,when notable changes were observed in water bodies and buildings.However,the forested area exhibited an increase and decrease of 3.9%and 1.2%under the SSP1-2.6 and SSP5-8.5 scenarios,respectively,whereas farmland exhibited a diminishing trend.(2)Wetlands were primarily concentrated in the central and eastern MYRB,with counties in the southwest exhibiting superior ecological-environmental quality from 2001 to 2020.Notably,wetland coverage revealed significantly high level,significant changes,frequent but relatively minor changes under the SSP1-2.6,SSP2-4.5,and SSP 5-8.5 scenarios,respectively.(3)Regions with lower habitat quality were primarily concentrated in urbanized areas characterized by frequent human activities,indicating a clear degradation in habitat quality across different scenarios.In conclusion,we established a foundational framework for future investigations into the eco-hydrological processes and ecosystem quality of watersheds.
文摘Vegetable toothbrushes are secondary forest products with health, medicinal, and pharmaceutical properties. They constitute an important resource permanently exploited by the populations of the Kpakpamè District. This research aims to identify the different plants used by the populations of Kpakpamè as toothbrushes and their therapeutic values. To reach this objective, documentary research, direct observation, and data collection from hundred and ninety-five (195) people randomly chosen but following well-defined criteria were carried out. The consensus value for plant parts noted CPP, is calculated to find the number of times a plant part is cited (Px) divided by the total number of times all parts are cited (Pt), and also to determine the most frequent collection sites, the consensus value for collection sites is calculated. In total, nineteen (19) species have been cited and grouped into nineteen (19) genera and eleven (11) families. Pseudocedrella kostchyi and Zanthoxylum zanthoxyloides are the most cited species with respective citation frequencies of 0.27 and 0.14. They come more from village lands with a Consensus value for collection sites (CCS) of 0.49 and are used to cure about twelve (12) diseases including dental caries (33.33%). These species are now almost threatened with extinction according to the IUCN. It is therefore important to develop safeguarding and sustainable conservation actions for these plant species. This work has made it possible to identify the different species used by the populations of the Kpakpamé district as toothbrushes despite the urbanization and modernization of this locality formerly known in the Zou department as the most endogenous region. Several studies have focused on the diversity of plants used for oral hygiene and even the phytochemical properties of the species identified without taking into account the phytodistrict, social and perceptions of local populations.
基金supported by the National Key Research and Development Program of China(2023YFF0805602)National Natural Science Foundation of China(32225032,32001192,32271597)+1 种基金the Innovation Base Project of Gansu Province(2021YFF0703904)the Science and Technology Program of Gansu Province(24JRRA515,22JR5RA525,23JRRA1157).
文摘Studies on plant diversity are usually based on the total number of species in a community.However,few studies have examined species richness(SR)of different plant life forms in a community along largescale environmental gradients.Particularly,the relative importance(RIV)of different plant life forms in a community and how they vary with environmental variables are still unclear.To fill these gaps,we determined plant diversity of ephemeral plants,annual herbs,perennial herbs,and woody plants from 187 sites across drylands in China.The SR patterns of herbaceous plants,especially perennial herbs,and their RIV in plant communities increased with increasing precipitation and soil nutrient content;however,the RIV of annual herbs was not altered along these gradients.The SR and RIV of ephemeral plants were affected mainly by precipitation seasonality.The SR of woody plants had a unimodal relationship with air temperature and exhibited the highest RIV and SR percentage in plant communities under the harshest environments.An obvious shift emerged in plant community composition,SR and their critical impact factors at 238.5 mm of mean annual precipitation(MAP).In mesic regions(>238.5 mm),herbs were the dominant species,and the SR displayed a relatively slow decreasing rate with increasing aridity,which was mediated mainly by MAP and soil nutrients.In arid regions(<238.5 mm),woody plants were the dominant species,and the SR displayed a relatively fast decreasing rate with increasing aridity,which was mediated mainly by climate variables,especially precipitation.Our findings highlight the importance of comparative life form studies in community structure and biodiversity,as their responses to gradients differed substantially on a large scale.
基金Under the auspices of National Natural Science Foundation of China(No.42201374,42071359)。
文摘The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology differ.Although previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains limited.In this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal forest.The estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario datasets.The sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime temperature.The LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN model.By incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is achieved.Furthermore,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study area.The simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate scenarios.This study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.
基金supported by the National Natural Science Foundation of China(Grant Nos.42230405,42006029)Science and Technology Plan of Liaoning Province(2024JH2/102400061)+1 种基金Dalian Science and Technology Innovation Fund(2024JJ11PT007)Dalian Science and Technology Pro-gram for Innovation Talents of Dalian(2022RJ06).
文摘Mesoscale eddies play a central role in the poleward oceanic heat flux in the Southern Ocean.Previous studies have documented changes in the location of temperature fronts in the Southern Ocean,but little attention has been paid to changes in the genesis locations of mesoscale eddies.Here,we provide evidence from three decades of satellite altimetry observations for the heterogeneity of the poleward shift of mesoscale activities,with the largest trend of~0.23°±0.05°(10 yr)^(-1) over the Atlantic sector and a moderate trend of~0.1°±0.03°(10 yr)^(-1) over the Indian sector,but no significant trend in the Pacific sector.The poleward shift of mesoscale eddies is associated with a southward shift of the local westerly winds while being constrained by the major topographies.As the poleward shift of westerly winds is projected to persist,the poleward oceanic heat flux from mesoscale eddies may influence future ice melt.
文摘The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.
文摘This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO₂,nano-Fe₃O₄,and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.
文摘Flooding remains one of the most destructive natural disasters,posing significant risks to both human lives and infrastructure.In India,where a large area is susceptible to flood hazards,the importance of accurate flood frequency analysis(FFA)and flood susceptibility mapping cannot be overstated.This study focuses on the Haora River basin in Tripura,a region prone to frequent flooding due to a combination of natural and anthropogenic factors.This study evaluates the suitability of the Log-Pearson Type Ⅲ(LP-Ⅲ)and Gumbel Extreme Value-1(EV-1)distributions for estimating peak discharges and delineates floodsusceptible zones in the Haora River basin,Tripura.Using 40 years of peak discharge data(1984-2023),the LP-Ⅲ distribution was identified as the most appropriate model based on goodness-of-fit tests.Flood susceptibility mapping,integrating 16 thematic layers through the Analytical Hierarchy Process,identified 8%,64%,and 26%of the area as high,moderate,and low susceptibility zones,respectively,with a model success rate of 0.81.The findings highlight the need for improved flood management strategies,such as enhancing river capacity and constructing flood spill channels.These insights are critical for designing targeted flood mitigation measures in the Haora basin and other flood-prone regions.
文摘Natural resource management is essential to sustain human well-being and the environment.Water and soil are two of the most important natural resources that require careful management.The western part of India faces multiple challenges,including climatic variability,soil degradation,water scarcity,deforestation,etc.The basin’s sub-watersheds are delineated and prioritised using the Soil and Water Assessment Tool(SWAT)and Sub Watershed Prioritization Tool(SWPT),respectively,using morphometric and topo-hydrological characteristics,and the sub-watersheds are further ranked using Weighted Sum Analysis(WSA).The findings indicate that SWS19,SWS18,SWS1,SWS17,SWS16,and SWS15,which are drained by the rivers Chambal,Kali Sindh,Mashi,Parbati,Parwan,and Beradi,are highly vulnerable sub-watersheds.By integrating remote sensing,GIS techniques,and quantitative morphometric analysis,parameters such as drainage density,stream frequency,bifurcation ratio,and slope gradient were evaluated.The analysis revealed critical sub-watersheds characterized by steep slopes,high drainage density,and poor vegetation cover,indicating their susceptibility to erosion and runoff.The findings underscore the necessity for targeted soil conservation measures,such as contour bunding,afforestation,and water retention structures.This study highlights the utility of geospatial tools for sustainable watershed management and provides a replicable framework for prioritizing sub-watersheds in similar regions.
