This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).Vietnam.Highperformance liquid chromatography(HPLC)w...This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).Vietnam.Highperformance liquid chromatography(HPLC)was employed to measure MC concentrations in various target samples.Results indicate that Microcystis spp.dominates as the primary MC producer in the DTR.The average concentrations of analyzed MCs in surface water ranged from 1.10 to 5.54μg/L,temporally and spatially.In sediment,average concentrations varied from 0.15 to 1.13μg/g wet weight(WW)temporally and from 0.41 to 0.72μg/g WW spatially.MCs were detected in different organs of fish species(Oreochromis sp.and Labiobarbus sp.)and in the entire soft tissues of bivalve(Corbicula sp.)and gastropod(Assiminea sp.).The highest observed MC concentration in July was 0.83±0.22μg/g WW in the intestines of fish Oreochromis sp.The presence of MCs in grass shrimp Palaemonetes sp.was observed solely in June,reaching a concentration of 0.28±0.19μg/g WW.This is the first report of MC accumulation in the grass shrimp Palaemonetes sp.during field collection.For the bivalve Corbicula sp.,the presence of analyzed MCs was consistent throughout the study period,except for March and September,with the highest concentrations in July at 0.77±0.1μg/g WW.Pearson correlation analysis revealed significant positive correlations between MCs in water and sediment with MC concentrations in aquatic animals,indicating the potential transfer of MCs across different trophic levels.The estimated daily intake values for analyzed MCs indicate that fish collected from the DTR are considered safe for consumption,as long as only the edible organs,such as the muscle,are consumed.However,bivalves or gastropods collected from the DTR are not safe for human consumption.This study underscored the importance of monitoring MC accumulation in aquatic animals used as food to mitigate adverse effects on human health.展开更多
The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the i...The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner.Hence,this study aimed at developing a user-friendly geographic information system(GIS)tool,Sub-Watershed Prioritization Tool(SWPT),using the Python programming language to decrease any possible uncertainty.It used geospatial-statistical techniques for analyzing morphometric and topohydrological factors and automatically identifying critical and priority sub-watersheds.In order to assess the capability and reliability of the SWPT tool,it was successfully applied in a watershed in the Golestan Province,Northern Iran.Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds.It provided a cost-effective approach for prioritization of sub-watersheds.Therefore,the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed.展开更多
In this study,the heat transfer optimization(evaporation)and the specification of the FX-70 zeotropic refrigerant flow inside a corrugated pipe have been investigated.Despite the low HTC(HTC),this type of refrigerant ...In this study,the heat transfer optimization(evaporation)and the specification of the FX-70 zeotropic refrigerant flow inside a corrugated pipe have been investigated.Despite the low HTC(HTC),this type of refrigerant is highly applicable in low or medium temperature engineering systems during the evaporation process.To eliminate this defect,high turbulence and proper mixing are required.Therefore,using heat transfer(HT)augmentation methods will be necessary and effective.In order to find the most favorable operating conditions that lead to the optimum combination of pressure drop(PD)and HTC,empirical data,neural networks,and genetic algorithms(GA)for multi-objective(MO)(NSGA II)are used.To investigate the mentioned cases,the geometric parameters of corrugated pipes,vapor quality,and mass velocity of refrigerant were studied.The results showed that with vapor quality higher than 0.8 and corrugation depth and pitch of 1.5 and 7 mm,respectively,we would achieve the desired optimum design.展开更多
Parametric effect of moisture and influence of operating variables on the adsorption behaviour of polyaspartamide during CO2 capture was investigated in this study using experimental and modelling approach. Individual...Parametric effect of moisture and influence of operating variables on the adsorption behaviour of polyaspartamide during CO2 capture was investigated in this study using experimental and modelling approach. Individual effects of operating conditions (e.g. pressure, temperature and gas flow rates) as well as the effect of moisture on the adsorption capacity of polyaspartamide were methodically investigated using Dubinin-Raduskevich model. Results from the investigations reveal that the presence of moisture in the flue gas had an incremental effect on the adsorption capacity of polyaspartamide;thereby showcasing the potential of polyaspartamide as a suitable hydrophilic material for CO2 capture in power plants. In addition, pressure, temperature and gas flow rates at 200 kPa, 403 K, and 1.5 mL/s, respectively, sig? nificantly influenced the CO2 adsorption capacity of polyaspartamide. Physisorption and chemisorption both governed the adsorption process while equilibrium studies at different temperatures showed that Langmuir isotherm could adequately describe the adsorption behaviour of the material with best fit with R^2>0.95.展开更多
The most heavily glacierized tropical range in the world– the Peruvian Cordillera Blanca-has been losing ice since the end of the Little Ice Age(LIA).In this study,the decline of the Churup glacier(9°28’18"...The most heavily glacierized tropical range in the world– the Peruvian Cordillera Blanca-has been losing ice since the end of the Little Ice Age(LIA).In this study,the decline of the Churup glacier(9°28’18"S;77°25’02"W)and associated processes were documented employing multi-proxy approach including the analysis of remotely sensed images(1948-2016),the Schmidt hammer rock test and lichenometric dating.It is shown that Churup glacier has lost the vast majority of its estimated LIA extent(1.05±0.1 km^2;45.0×10^6-57.4×10^6 m^3).The rate of glacier retreat is documented to vary in space(SE,SW and NW-facing slopes)and time,with the peak between 1986 and 1995.With an area of 0.045 km^2 in 2016,it is expected that the complete deglaciation of the Churup valley is inevitable in the near future.Recently(post-LIA)exposed bedrock surfaces have shown higher R-values(54.2-66.4,AVG 63.3,STDEV 2.9)compared to pre-LIA exposed surfaces(46.1-59.3,AVG 50.1,STDEV 4.9),confirming the links to the duration of rock weathering.The Lichenometric dating is applied to recently exposed areas and elevations above 4800 m a.s.l.,revealing only limited reliability and agreement with the age of deglaciation estimated from remotely-sensed images in such an environment.展开更多
Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia(Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat...Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia(Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat series images, a digital elevation model from SRTM, and previously published data were used. Estimated total glacier area in 1988, 1993, 1997 and 2004 was 3.85 km2±0.13 km2, 3.01 km2±0.08 km2, 2.49 km2±0.07 km2 and 1.725 km2 ±0.042 km2, respectively. Only 0.58 km2±0.016 km2 glacierized area remained in 2015 in Puncak Jaya, which is about 84.9% loss in just 27 years. If this rate continued, the remaining tropical glaciers in Australasia would disappear in the 2020 s. Timeseries analysis of climate variables showed significant positive trends in air temperature(0.009°C per year) and relative humidity(0.43% per year) but no considerable tendency was observed for precipitation. Warming climate together with mining activities would accelerate loss of glacier coverage in this region.展开更多
The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely.The nonlinear stres...The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely.The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods.In this study,a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method(NFEM),and linear regression method which is a soft computing technique(SC)was applied for evaluating the results of NFEM,and it supports engineering judgment because the design of the geostructures is usually considered to be an inaccurate process owing to high nonlinearity of the large-scale geostructures seismic response and such nonlinearity may induce the complexity for decision making in geostructures seismic design.The occurrence of nonlinear stress and nonlinear strain probability distribution can be observed and density of stress and strain are predicted by using the histogram.The results of both the simulation from the NFEM and the linear regression method confirm the nonlinearity of strain energy and stress behavior have a close value of R2 and root-mean-square error(RMSE).The linear regression and histogram simulation shows the accuracy of NFEM results.The outcome of this study guides to improve engineering judgment quality for seismic analysis of an embankment through validating results of NFEM by employing appropriate soft computing techniques.展开更多
Nanotechnology is widely used in heat transfer devices to improve thermal performance.Nanofluids can be applied in heat pipes to decrease thermal resistance and achieve a higher heat transfer capability.In the present...Nanotechnology is widely used in heat transfer devices to improve thermal performance.Nanofluids can be applied in heat pipes to decrease thermal resistance and achieve a higher heat transfer capability.In the present article,a comprehensive literature review is performed on the nanofluids’ applications in heat pipes.Based on reviewed studies,nanofluids have a high capacity to boost the thermal behavior of various types of heat pipes such as conventional heat pipes,pulsating heat pipes,and thermosyphons.Besides,it is observed that there must be a selected amount of concentration for the high-performance utilization of nanoparticles;high concentration of nanoparticles causes a higher thermal resistance which is mainly attributed to increment in the dynamic viscosity and the higher possibility of particles’ agglomeration.Enhancement in heat transfer performance is the result of increasing in nucleation sites and the intrinsically greater nanofluids’ thermal conductivity.展开更多
Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.Th...Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).展开更多
Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately use...Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately used by landuse planners and emergency managers.The main objective of this study is to prepare an accurate flood susceptibility map for the Haraz watershed in Iran using a novel modeling approach(DBPGA)based on Deep Belief Network(DBN)with Back Propagation(BP)algorithm optimized by the Genetic Algorithm(GA).For this task,a database comprising ten conditioning factors and 194 flood locations was created using the One-R Attribute Evaluation(ORAE)technique.Various well-known machine learning and optimization algorithms were used as benchmarks to compare the prediction accuracy of the proposed model.Statistical metrics include sensitivity,specificity accuracy,root mean square error(RMSE),and area under the receiver operatic characteristic curve(AUC)were used to assess the validity of the proposed model.The result shows that the proposed model has the highest goodness-of-fit(AUC=0.989)and prediction accuracy(AUC=0.985),and based on the validation dataset it outperforms benchmark models including LR(0.885),LMT(0.934),BLR(0.936),ADT(0.976),NBT(0.974),REPTree(0.811),ANFIS-BAT(0.944),ANFIS-CA(0.921),ANFIS-IWO(0.939),ANFIS-ICA(0.947),and ANFIS-FA(0.917).We conclude that the DBPGA model is an excellent alternative tool for predicting flash flood susceptibility for other regions prone to flash floods.展开更多
In this study, we evaluate the ecological impact of effluent cooling water from the Ninh Thuan nuclear power plant II, using a two-dimensional hydraulic model to simulate thermal diffusion from the effluent outfall. S...In this study, we evaluate the ecological impact of effluent cooling water from the Ninh Thuan nuclear power plant II, using a two-dimensional hydraulic model to simulate thermal diffusion from the effluent outfall. Sites selected for this study were Ninh Thuan nuclear power plant and Vinh Hai seawater in four different scenarios. This paper utilized the relationship between surface water temperature and the water temperature at a depth of -15 m to calculate the water temperature at intake and outlet at a depth of -14 m. A combination between the results of interpolated and results of model showed that effluent cooling water from Ninh Thuan plant affected the largest incidence about 2450 m in the North, 880 m in the South and 960 m in the West. It can be considered as safe distance to not to affect the coral reefs ecosystem in the North and sea turtle conservation area in the South. This study was first in this region to have an integrated approach using two-dimensional model.展开更多
Site condition and bedrock depth play important roles in the determination of peak surface acceleration(PSA)values by earthquake motions.The soil parameters of shear wave velocity(Vs)and standard penetration test-numb...Site condition and bedrock depth play important roles in the determination of peak surface acceleration(PSA)values by earthquake motions.The soil parameters of shear wave velocity(Vs)and standard penetration test-number(N)value for Jakarta city are available up to 100 m below the Earth’s surface even though the typical depths to bedrock are in excess of 100 m.This study referred to the base motion peak ground acceleration(PGA)values of 0.100 g,0.218 g and 0.378 g to predict the PSA values using the Nonlinear Earthquake site Response Analysis(NERA)to analyse a simulated dataset for the bedrock depths of 100 m,200 m,300 m,400 m and 500 m with conditioned by clayey and sandy soils.A new empirical equation of Vs=102.48 N0.297(m/s)was proposed to calculate the values of Vsused as an input parameter in the NERA programme for the prediction of seismic wave propagation.The results showed that the PSA values are dependent on the amplitude of seismic waves,depths of bedrock and the local site conditions.Changes in the PSA values from 41.0%to 51.5%and from 46.1%to 79.8%for the bedrocks overlain by sand,from 20.0%to 42.1%and from 45.9%to 58.8%for the bedrocks overlain by clay with increasing of bedrock depths from 200 m to 300 m and from 400 m to 500 m,respectively,were predicted for a 2500-year return period earthquake.Decreases in the PSA values by 41.0%,51.5%,46.1%,79.8%for the bedrocks overlain by sand and by 20.0%,42.1%,45.9%,58.8%for the bedrocks overlain by clay were predicted for a 2500-year return period earthquake due to the bedrock depth changes of 200 m,300 m,400 m,500 m.Large-magnitude earthquake of Jakarta city has a significant effect on an increase or a decrease of the PSA value with depth of bedrock and may cause the vibration damage to buildings and other constructions on the ground.The analysis of the PSA value and PSA ratio influenced by the PGA value,bedrock depth and local soil conditions will make a contribution to the design of earthquake-safe building for Jakarta city in the future.展开更多
Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dyn...Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore,earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study,we applied and assessed two new hybrid ensemble models,namely Dagging and Random Subspace(RS)coupled with Artificial Neural Network(ANN),Random Forest(RF),and Support Vector Machine(SVM)which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin,the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points,which were transferred in a GIS environment.The information gain ratio,the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models,for the ability to predict the statistical appraisal measures such as Freidman,Wilcoxon signed-rank,and t-paired tests and Receiver Operating Characteristic Curve(ROC)were employed.The value of the Area Under the Curve(AUC)of ROC was above 0.80 for all models.For flood susceptibility modelling,the Dagging model performs superior,followed by RF,the ANN,the SVM,and the RS,then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.展开更多
Biochar has been introduced as an acceptable soil amendment due to its environmental benefits such as sequestering soil contaminants. However, the aging process in biochar amended soil probably decreases the adsorptio...Biochar has been introduced as an acceptable soil amendment due to its environmental benefits such as sequestering soil contaminants. However, the aging process in biochar amended soil probably decreases the adsorption capacity of biochar through changing its physico-chemical properties. Adsorption, leaching and bioavailability of fomesafen to corn in a Chinese soil amended by rice hull biochar after 0, 30, 90 and 180 days were investigated. Results showed that the addition of 0.5%-2% fresh biochar significantly increases the adsorption of fomesafen 4-26 times compare to unamended soil due to higher SSA of biochar. Biochar amendment also decreases fomesafen concentration in soil pore water by 5%-23% resulting lower risk of the herbicide for cultivated plants. However, the aging process decreased the adsorption capacity ofbiochar since the adsorption coefficient values which was 1.9-12.4 in 0.5%-2% fresh biochar amended soil, declined to 1.36-4.16, 1.13-2.78 and 0.95-2.31 in 1, 3 and 6-month aged treatments, respectively. Consequently, higher desorption, leaching and bioavailable fraction of fomesafen belonged to 6-month aged treatment. Nevertheless, rice hull biochar was effective for sequestering fomesafen as the adsorption capacity of biochar amended soil after 6 months of aging was still 2.5-5 times hi^her compared to that of unamended soil.展开更多
Significant changes in the area and snowline altitude of two glacierized mountains - Nevado Champara (Cordillera Blanca,Peru) and Cerro Tilata (Cordillera Real,Bolivia)- in the tropical Andes,before and after the rece...Significant changes in the area and snowline altitude of two glacierized mountains - Nevado Champara (Cordillera Blanca,Peru) and Cerro Tilata (Cordillera Real,Bolivia)- in the tropical Andes,before and after the recent El Nino in 2015/16 period,have been analysed using Sentinel 2A and Landsat data.It is seen that the recent El Nino has been accompanied by higher fluctuation in glacier coverage on Nevado Champara and the loss of glacier coverage on Cerro Tilata was very high during the past 16 years.Rise in snowline altitude of selected glaciers was very high after the 2015/16 El Nino.Increase in the area covered by snow and ice during the La Nina periods were not enough to cover the ice loss occurred during the previous El Nino events and the strongest El Nino in 2015/ 16 was followed by a significant loss of ice-covered areas in the tropical Andes.Freshwater resources in this region will be affected in the near future if the current trends in glacier decline continue.Adaptation strategies needs to be implemented to reduce the impacts of the continuing loss of glacierized on regional communities in the tropical Andean region.展开更多
In this article, we review the current knowledge of the glacial recession and related glacial lake development in the Andes of South America. Since the mid-1980 s, hundreds of glacial lakes either expanded or formed, ...In this article, we review the current knowledge of the glacial recession and related glacial lake development in the Andes of South America. Since the mid-1980 s, hundreds of glacial lakes either expanded or formed, and predictions show that additional hundreds of lakes will form throughout the 21 st century. However, studies on glacial lakes in the Andes are still relatively rare. Many glacial lakes pose a potential hazard to local communities, but glacial lake outburst floods(GLOFs) are understudied. We provide an overview on hazards from glacial lakes such as GLOFs and water pollution, and their monitoring approaches. In real-time monitoring, the use of unmanned aerial systems(UASs) and early warning systems(EWSs) is still extremely rare in the Andes, but increasingly authorities plan to install mitigation systems to reduce glacial lake risk and protect local communities. In support, we propose an international remote sensing-based observation initiative following the model of, for example, the Global Land Ice Measurements from Space(GLIMS) one, with the headquarters in one of the Andean nations.展开更多
The objective of this research is to propose and confirm a new machine learning approach of Best-First tree(BFtree),AdaBoost(AB),MultiBoosting(MB),and Bagging(Bag)ensembles for potential groundwater mapping and assess...The objective of this research is to propose and confirm a new machine learning approach of Best-First tree(BFtree),AdaBoost(AB),MultiBoosting(MB),and Bagging(Bag)ensembles for potential groundwater mapping and assessing role of influencing factors.The Yasuj-Dena area(Iran)is selected as a case study.For this regard,a Yasuj-Dena database was established with 362 springs locations and 12 groundwater-influencing factors(slope,aspect,elevation,stream power index(SPI),length of slope(LS),topographic wetness index(TWI),topographic position index(TPI),land use,lithology,distance from fault,distance from river,and rainfall).The database was employed to train and validate the proposed groundwater models.The area under the curve(AUC)and statistical metrics were employed to check and confirm the quality of the models.The result shows that the BFTree-Bag model(AUC=0.810,kappa=0.495)has the highest prediction performance,followed by the BFTree-MB model(AUC=0.785,kappa=0.477),and the BFTree-MB model(AUC=0.745,kappa=0.422).Compared to the benchmark of Random Forests,the BFTree-Bag model performs better;therefore,we conclude that the BFtree-Bag is a new tool should be used for modeling of groundwater potential.展开更多
Understanding impacts of typhoons due to storm surge plays an important role in reducing damage in coastal areas.This study used the SWAN wave model to simulate the typhoon waves and the SuWAT model to simulate storm ...Understanding impacts of typhoons due to storm surge plays an important role in reducing damage in coastal areas.This study used the SWAN wave model to simulate the typhoon waves and the SuWAT model to simulate storm surge and inundation caused by Typhoon Xangsane in 2006 which landed in the Central Coast of Vietnam from Nghe An to Phu Yen Provinces.The wind-pressure f ield was calculated by the Fujita’s model and reanalysis data were inputted to the SWAN and SuWAT models.The simulated results of the typhoon wave showed that Typhoon Xangsane caused 5-7 m height waves in the coastal areas with a radius of 600 km.The results of the storm surge combined with the simulations of wind,pressure,wave,and tide in the coastal areas were estimated at 2 m.The simulated and calculated results of storm surge and inundation maps will help the decision makers in the Committee for Natural Disaster Prevention and Control to reduce the impacts of natural disasters induced to storm surge in the near future.展开更多
文摘This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).Vietnam.Highperformance liquid chromatography(HPLC)was employed to measure MC concentrations in various target samples.Results indicate that Microcystis spp.dominates as the primary MC producer in the DTR.The average concentrations of analyzed MCs in surface water ranged from 1.10 to 5.54μg/L,temporally and spatially.In sediment,average concentrations varied from 0.15 to 1.13μg/g wet weight(WW)temporally and from 0.41 to 0.72μg/g WW spatially.MCs were detected in different organs of fish species(Oreochromis sp.and Labiobarbus sp.)and in the entire soft tissues of bivalve(Corbicula sp.)and gastropod(Assiminea sp.).The highest observed MC concentration in July was 0.83±0.22μg/g WW in the intestines of fish Oreochromis sp.The presence of MCs in grass shrimp Palaemonetes sp.was observed solely in June,reaching a concentration of 0.28±0.19μg/g WW.This is the first report of MC accumulation in the grass shrimp Palaemonetes sp.during field collection.For the bivalve Corbicula sp.,the presence of analyzed MCs was consistent throughout the study period,except for March and September,with the highest concentrations in July at 0.77±0.1μg/g WW.Pearson correlation analysis revealed significant positive correlations between MCs in water and sediment with MC concentrations in aquatic animals,indicating the potential transfer of MCs across different trophic levels.The estimated daily intake values for analyzed MCs indicate that fish collected from the DTR are considered safe for consumption,as long as only the edible organs,such as the muscle,are consumed.However,bivalves or gastropods collected from the DTR are not safe for human consumption.This study underscored the importance of monitoring MC accumulation in aquatic animals used as food to mitigate adverse effects on human health.
基金supported by the Geographic Information Science Research Group,Ton Duc Thang University,Ho Chi Minh City,Viet Nam
文摘The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner.Hence,this study aimed at developing a user-friendly geographic information system(GIS)tool,Sub-Watershed Prioritization Tool(SWPT),using the Python programming language to decrease any possible uncertainty.It used geospatial-statistical techniques for analyzing morphometric and topohydrological factors and automatically identifying critical and priority sub-watersheds.In order to assess the capability and reliability of the SWPT tool,it was successfully applied in a watershed in the Golestan Province,Northern Iran.Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds.It provided a cost-effective approach for prioritization of sub-watersheds.Therefore,the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed.
文摘In this study,the heat transfer optimization(evaporation)and the specification of the FX-70 zeotropic refrigerant flow inside a corrugated pipe have been investigated.Despite the low HTC(HTC),this type of refrigerant is highly applicable in low or medium temperature engineering systems during the evaporation process.To eliminate this defect,high turbulence and proper mixing are required.Therefore,using heat transfer(HT)augmentation methods will be necessary and effective.In order to find the most favorable operating conditions that lead to the optimum combination of pressure drop(PD)and HTC,empirical data,neural networks,and genetic algorithms(GA)for multi-objective(MO)(NSGA II)are used.To investigate the mentioned cases,the geometric parameters of corrugated pipes,vapor quality,and mass velocity of refrigerant were studied.The results showed that with vapor quality higher than 0.8 and corrugation depth and pitch of 1.5 and 7 mm,respectively,we would achieve the desired optimum design.
文摘Parametric effect of moisture and influence of operating variables on the adsorption behaviour of polyaspartamide during CO2 capture was investigated in this study using experimental and modelling approach. Individual effects of operating conditions (e.g. pressure, temperature and gas flow rates) as well as the effect of moisture on the adsorption capacity of polyaspartamide were methodically investigated using Dubinin-Raduskevich model. Results from the investigations reveal that the presence of moisture in the flue gas had an incremental effect on the adsorption capacity of polyaspartamide;thereby showcasing the potential of polyaspartamide as a suitable hydrophilic material for CO2 capture in power plants. In addition, pressure, temperature and gas flow rates at 200 kPa, 403 K, and 1.5 mL/s, respectively, sig? nificantly influenced the CO2 adsorption capacity of polyaspartamide. Physisorption and chemisorption both governed the adsorption process while equilibrium studies at different temperatures showed that Langmuir isotherm could adequately describe the adsorption behaviour of the material with best fit with R^2>0.95.
基金the Ministry of Education, Youth and Sports of the Czech Republic within the framework of the National Sustainability Programme Ⅰ(NPU Ⅰ), Grant No. LO1415
文摘The most heavily glacierized tropical range in the world– the Peruvian Cordillera Blanca-has been losing ice since the end of the Little Ice Age(LIA).In this study,the decline of the Churup glacier(9°28’18"S;77°25’02"W)and associated processes were documented employing multi-proxy approach including the analysis of remotely sensed images(1948-2016),the Schmidt hammer rock test and lichenometric dating.It is shown that Churup glacier has lost the vast majority of its estimated LIA extent(1.05±0.1 km^2;45.0×10^6-57.4×10^6 m^3).The rate of glacier retreat is documented to vary in space(SE,SW and NW-facing slopes)and time,with the peak between 1986 and 1995.With an area of 0.045 km^2 in 2016,it is expected that the complete deglaciation of the Churup valley is inevitable in the near future.Recently(post-LIA)exposed bedrock surfaces have shown higher R-values(54.2-66.4,AVG 63.3,STDEV 2.9)compared to pre-LIA exposed surfaces(46.1-59.3,AVG 50.1,STDEV 4.9),confirming the links to the duration of rock weathering.The Lichenometric dating is applied to recently exposed areas and elevations above 4800 m a.s.l.,revealing only limited reliability and agreement with the age of deglaciation estimated from remotely-sensed images in such an environment.
基金Ton Duc Thang University, Ho Chi Minh City, Vietnam, for research support
文摘Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia(Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat series images, a digital elevation model from SRTM, and previously published data were used. Estimated total glacier area in 1988, 1993, 1997 and 2004 was 3.85 km2±0.13 km2, 3.01 km2±0.08 km2, 2.49 km2±0.07 km2 and 1.725 km2 ±0.042 km2, respectively. Only 0.58 km2±0.016 km2 glacierized area remained in 2015 in Puncak Jaya, which is about 84.9% loss in just 27 years. If this rate continued, the remaining tropical glaciers in Australasia would disappear in the 2020 s. Timeseries analysis of climate variables showed significant positive trends in air temperature(0.009°C per year) and relative humidity(0.43% per year) but no considerable tendency was observed for precipitation. Warming climate together with mining activities would accelerate loss of glacier coverage in this region.
文摘The nonlinearity of the strain energy at an interval period of applying seismic load on the geostructures makes it difficult for a seismic designer to makes appropriate engineering judgments timely.The nonlinear stress and strain analysis of an embankment is needed to evaluate by using a combination of suitable methods.In this study,a large-scale geostructure was seismically simulated and analyzed using the nonlinear finite element method(NFEM),and linear regression method which is a soft computing technique(SC)was applied for evaluating the results of NFEM,and it supports engineering judgment because the design of the geostructures is usually considered to be an inaccurate process owing to high nonlinearity of the large-scale geostructures seismic response and such nonlinearity may induce the complexity for decision making in geostructures seismic design.The occurrence of nonlinear stress and nonlinear strain probability distribution can be observed and density of stress and strain are predicted by using the histogram.The results of both the simulation from the NFEM and the linear regression method confirm the nonlinearity of strain energy and stress behavior have a close value of R2 and root-mean-square error(RMSE).The linear regression and histogram simulation shows the accuracy of NFEM results.The outcome of this study guides to improve engineering judgment quality for seismic analysis of an embankment through validating results of NFEM by employing appropriate soft computing techniques.
文摘Nanotechnology is widely used in heat transfer devices to improve thermal performance.Nanofluids can be applied in heat pipes to decrease thermal resistance and achieve a higher heat transfer capability.In the present article,a comprehensive literature review is performed on the nanofluids’ applications in heat pipes.Based on reviewed studies,nanofluids have a high capacity to boost the thermal behavior of various types of heat pipes such as conventional heat pipes,pulsating heat pipes,and thermosyphons.Besides,it is observed that there must be a selected amount of concentration for the high-performance utilization of nanoparticles;high concentration of nanoparticles causes a higher thermal resistance which is mainly attributed to increment in the dynamic viscosity and the higher possibility of particles’ agglomeration.Enhancement in heat transfer performance is the result of increasing in nucleation sites and the intrinsically greater nanofluids’ thermal conductivity.
文摘Hazards and disasters have always negative impacts on the way of life.Landslide is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout theworld.The present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,Slovakia.In this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were considered.Initially,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,respectively.The geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover factors.The ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model building.Consequently,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier models.Finally,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and models.The results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).
基金financial supported by the Iran National Science Foundation(INSF)through research project No.96004000the GIS research group(Ton Duc Thang University)for supports via the research project“GIS-based applications for solving realworld problems”。
文摘Flash floods are responsible for loss of life and considerable property damage in many countries.Flood susceptibility maps contribute to flood risk reduction in areas that are prone to this hazard if appropriately used by landuse planners and emergency managers.The main objective of this study is to prepare an accurate flood susceptibility map for the Haraz watershed in Iran using a novel modeling approach(DBPGA)based on Deep Belief Network(DBN)with Back Propagation(BP)algorithm optimized by the Genetic Algorithm(GA).For this task,a database comprising ten conditioning factors and 194 flood locations was created using the One-R Attribute Evaluation(ORAE)technique.Various well-known machine learning and optimization algorithms were used as benchmarks to compare the prediction accuracy of the proposed model.Statistical metrics include sensitivity,specificity accuracy,root mean square error(RMSE),and area under the receiver operatic characteristic curve(AUC)were used to assess the validity of the proposed model.The result shows that the proposed model has the highest goodness-of-fit(AUC=0.989)and prediction accuracy(AUC=0.985),and based on the validation dataset it outperforms benchmark models including LR(0.885),LMT(0.934),BLR(0.936),ADT(0.976),NBT(0.974),REPTree(0.811),ANFIS-BAT(0.944),ANFIS-CA(0.921),ANFIS-IWO(0.939),ANFIS-ICA(0.947),and ANFIS-FA(0.917).We conclude that the DBPGA model is an excellent alternative tool for predicting flash flood susceptibility for other regions prone to flash floods.
文摘In this study, we evaluate the ecological impact of effluent cooling water from the Ninh Thuan nuclear power plant II, using a two-dimensional hydraulic model to simulate thermal diffusion from the effluent outfall. Sites selected for this study were Ninh Thuan nuclear power plant and Vinh Hai seawater in four different scenarios. This paper utilized the relationship between surface water temperature and the water temperature at a depth of -15 m to calculate the water temperature at intake and outlet at a depth of -14 m. A combination between the results of interpolated and results of model showed that effluent cooling water from Ninh Thuan plant affected the largest incidence about 2450 m in the North, 880 m in the South and 960 m in the West. It can be considered as safe distance to not to affect the coral reefs ecosystem in the North and sea turtle conservation area in the South. This study was first in this region to have an integrated approach using two-dimensional model.
基金the financial support from the Universitas Syiah Kuala and Ministry of Research,Technology and Higher Education,Indonesia,for Professors Research Scheme Grant No.268/UN11/SPK/PNBP/2020 awarded to MMTon Duc Thang University,Vietnam,for Research Funding Contract No.551/2019/TDT-HDLV-NCV awarded to MAF
文摘Site condition and bedrock depth play important roles in the determination of peak surface acceleration(PSA)values by earthquake motions.The soil parameters of shear wave velocity(Vs)and standard penetration test-number(N)value for Jakarta city are available up to 100 m below the Earth’s surface even though the typical depths to bedrock are in excess of 100 m.This study referred to the base motion peak ground acceleration(PGA)values of 0.100 g,0.218 g and 0.378 g to predict the PSA values using the Nonlinear Earthquake site Response Analysis(NERA)to analyse a simulated dataset for the bedrock depths of 100 m,200 m,300 m,400 m and 500 m with conditioned by clayey and sandy soils.A new empirical equation of Vs=102.48 N0.297(m/s)was proposed to calculate the values of Vsused as an input parameter in the NERA programme for the prediction of seismic wave propagation.The results showed that the PSA values are dependent on the amplitude of seismic waves,depths of bedrock and the local site conditions.Changes in the PSA values from 41.0%to 51.5%and from 46.1%to 79.8%for the bedrocks overlain by sand,from 20.0%to 42.1%and from 45.9%to 58.8%for the bedrocks overlain by clay with increasing of bedrock depths from 200 m to 300 m and from 400 m to 500 m,respectively,were predicted for a 2500-year return period earthquake.Decreases in the PSA values by 41.0%,51.5%,46.1%,79.8%for the bedrocks overlain by sand and by 20.0%,42.1%,45.9%,58.8%for the bedrocks overlain by clay were predicted for a 2500-year return period earthquake due to the bedrock depth changes of 200 m,300 m,400 m,500 m.Large-magnitude earthquake of Jakarta city has a significant effect on an increase or a decrease of the PSA value with depth of bedrock and may cause the vibration damage to buildings and other constructions on the ground.The analysis of the PSA value and PSA ratio influenced by the PGA value,bedrock depth and local soil conditions will make a contribution to the design of earthquake-safe building for Jakarta city in the future.
基金supported by a PhD scholarship granted by Fundacao para a Ciencia e a Tecnologia,I.P.(FCT),Portugal,under the PhD Programme FLUVIO–River Restoration and Management,grant number:PD/BD/114558/2016。
文摘Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore,earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study,we applied and assessed two new hybrid ensemble models,namely Dagging and Random Subspace(RS)coupled with Artificial Neural Network(ANN),Random Forest(RF),and Support Vector Machine(SVM)which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin,the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points,which were transferred in a GIS environment.The information gain ratio,the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models,for the ability to predict the statistical appraisal measures such as Freidman,Wilcoxon signed-rank,and t-paired tests and Receiver Operating Characteristic Curve(ROC)were employed.The value of the Area Under the Curve(AUC)of ROC was above 0.80 for all models.For flood susceptibility modelling,the Dagging model performs superior,followed by RF,the ANN,the SVM,and the RS,then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.
基金supported by the National High Technology R&D Program of China(Nos.2013AA102804,2012AA06A204)the National Natural Science Foundation of China(Nos.21177111,41271489)Zhejiang Provincial Natural Science Foundation(No.LZ13D010001)
文摘Biochar has been introduced as an acceptable soil amendment due to its environmental benefits such as sequestering soil contaminants. However, the aging process in biochar amended soil probably decreases the adsorption capacity of biochar through changing its physico-chemical properties. Adsorption, leaching and bioavailability of fomesafen to corn in a Chinese soil amended by rice hull biochar after 0, 30, 90 and 180 days were investigated. Results showed that the addition of 0.5%-2% fresh biochar significantly increases the adsorption of fomesafen 4-26 times compare to unamended soil due to higher SSA of biochar. Biochar amendment also decreases fomesafen concentration in soil pore water by 5%-23% resulting lower risk of the herbicide for cultivated plants. However, the aging process decreased the adsorption capacity ofbiochar since the adsorption coefficient values which was 1.9-12.4 in 0.5%-2% fresh biochar amended soil, declined to 1.36-4.16, 1.13-2.78 and 0.95-2.31 in 1, 3 and 6-month aged treatments, respectively. Consequently, higher desorption, leaching and bioavailable fraction of fomesafen belonged to 6-month aged treatment. Nevertheless, rice hull biochar was effective for sequestering fomesafen as the adsorption capacity of biochar amended soil after 6 months of aging was still 2.5-5 times hi^her compared to that of unamended soil.
文摘Significant changes in the area and snowline altitude of two glacierized mountains - Nevado Champara (Cordillera Blanca,Peru) and Cerro Tilata (Cordillera Real,Bolivia)- in the tropical Andes,before and after the recent El Nino in 2015/16 period,have been analysed using Sentinel 2A and Landsat data.It is seen that the recent El Nino has been accompanied by higher fluctuation in glacier coverage on Nevado Champara and the loss of glacier coverage on Cerro Tilata was very high during the past 16 years.Rise in snowline altitude of selected glaciers was very high after the 2015/16 El Nino.Increase in the area covered by snow and ice during the La Nina periods were not enough to cover the ice loss occurred during the previous El Nino events and the strongest El Nino in 2015/ 16 was followed by a significant loss of ice-covered areas in the tropical Andes.Freshwater resources in this region will be affected in the near future if the current trends in glacier decline continue.Adaptation strategies needs to be implemented to reduce the impacts of the continuing loss of glacierized on regional communities in the tropical Andean region.
文摘In this article, we review the current knowledge of the glacial recession and related glacial lake development in the Andes of South America. Since the mid-1980 s, hundreds of glacial lakes either expanded or formed, and predictions show that additional hundreds of lakes will form throughout the 21 st century. However, studies on glacial lakes in the Andes are still relatively rare. Many glacial lakes pose a potential hazard to local communities, but glacial lake outburst floods(GLOFs) are understudied. We provide an overview on hazards from glacial lakes such as GLOFs and water pollution, and their monitoring approaches. In real-time monitoring, the use of unmanned aerial systems(UASs) and early warning systems(EWSs) is still extremely rare in the Andes, but increasingly authorities plan to install mitigation systems to reduce glacial lake risk and protect local communities. In support, we propose an international remote sensing-based observation initiative following the model of, for example, the Global Land Ice Measurements from Space(GLIMS) one, with the headquarters in one of the Andean nations.
文摘The objective of this research is to propose and confirm a new machine learning approach of Best-First tree(BFtree),AdaBoost(AB),MultiBoosting(MB),and Bagging(Bag)ensembles for potential groundwater mapping and assessing role of influencing factors.The Yasuj-Dena area(Iran)is selected as a case study.For this regard,a Yasuj-Dena database was established with 362 springs locations and 12 groundwater-influencing factors(slope,aspect,elevation,stream power index(SPI),length of slope(LS),topographic wetness index(TWI),topographic position index(TPI),land use,lithology,distance from fault,distance from river,and rainfall).The database was employed to train and validate the proposed groundwater models.The area under the curve(AUC)and statistical metrics were employed to check and confirm the quality of the models.The result shows that the BFTree-Bag model(AUC=0.810,kappa=0.495)has the highest prediction performance,followed by the BFTree-MB model(AUC=0.785,kappa=0.477),and the BFTree-MB model(AUC=0.745,kappa=0.422).Compared to the benchmark of Random Forests,the BFTree-Bag model performs better;therefore,we conclude that the BFtree-Bag is a new tool should be used for modeling of groundwater potential.
基金supported the funding of the project"Research on the valuation of economic losses caused by extreme hydro-meteorological phenomena in the context of climate change and propose risk management solutions for coastal provinces of Central Vietnam"partially funded by Ministry of Science and Technology under grant number DTDL-C.35/15(a coupled numerical model)
文摘Understanding impacts of typhoons due to storm surge plays an important role in reducing damage in coastal areas.This study used the SWAN wave model to simulate the typhoon waves and the SuWAT model to simulate storm surge and inundation caused by Typhoon Xangsane in 2006 which landed in the Central Coast of Vietnam from Nghe An to Phu Yen Provinces.The wind-pressure f ield was calculated by the Fujita’s model and reanalysis data were inputted to the SWAN and SuWAT models.The simulated results of the typhoon wave showed that Typhoon Xangsane caused 5-7 m height waves in the coastal areas with a radius of 600 km.The results of the storm surge combined with the simulations of wind,pressure,wave,and tide in the coastal areas were estimated at 2 m.The simulated and calculated results of storm surge and inundation maps will help the decision makers in the Committee for Natural Disaster Prevention and Control to reduce the impacts of natural disasters induced to storm surge in the near future.
