Drains play an important role in seepage control in geotechnical engineering.The enormous number and one-dimensional(1D)geometry of drainage holes make their nature difficult to be accurately modeled in groundwater fl...Drains play an important role in seepage control in geotechnical engineering.The enormous number and one-dimensional(1D)geometry of drainage holes make their nature difficult to be accurately modeled in groundwater flow simulation.It has been well understood that drains function by presenting discharge boundaries,which can be characterized by water head,no-flux,unilateral or mixed water head-unilateral boundary condition.It has been found after years of practices that the flow simulation may become erroneous if the transitions among the drain boundary conditions are not properly considered.For this,a rigorous algorithm is proposed in this study to detect the onset of transitions among the water head,noflux and mixed water head-unilateral boundary conditions for downwards-drilled drainage holes,which theoretically completes the description of drain boundary conditions.After verification against a numerical example,the proposed algorithm is applied to numerical modeling of groundwater flow through a gravity dam foundation.The simulation shows that for hundreds of downwards-drilled drainage holes used to be prescribed with water head boundary condition,56%and 2%of them are transitioned to mixed water head-unilateral and no-flux boundary conditions,respectively.The phreatic surface around the drains will be overestimated by 25e33 m without the use of the mixed boundary condition.For the first time,this study underscores the importance of the mixed water head-unilateral boundary condition and the proposed transition algorithm in drain modeling,which may become more essential for simulation of transient flow because of groundwater dynamics.展开更多
Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation i...Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation in the Bandu Sub-watershed in Purulia,West Bengal,using the AHP model and RS&GIS methodologies.To achieve Goal 6 of the UN-initiated 17 SDGs,it is crucial to determine the spatial distribution of groundwater prospective zones village-by-village,with 1/3 of the regions falling under red alert zones for sustainable development.The 16 most crucial elements affecting groundwater prospective zones(GWPZs)were mapped using AHP,and the final prospective map was obtained through Weighted Overlay analysis.The study identified five different classes within the Sub-watershed as excellent,good,moderate,poor,and very poor.The validation results showed that the approach used to derive GWPZ is reliable,and the results can be applied to future sustainable developments to reduce water shortages through suitable management methods.The research aims to increase the effectiveness of sustainable groundwater zone management,ensuring long-term water management and access.展开更多
Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab&...Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab's complex hydrogeological conditions and Quaternary alluvial deposits present significant challenges for groundwater management.This study employs cost-effective numerical techniques as alternatives to traditional methods to safeguard groundwater quality,quantity,and accessibility.It introduces an edit-embedded transition frequency model that integrates regional datasets and utilizes algorithms such as GAMEAS,MCMOD,and TSIM to evaluate aquifer heterogeneity and simulate spatial variations using one-dimensional and three-dimensional Markov chains.Findings show that sand exhibits the highest self-transition(33.112 m),indicating strong stability,followed by silt,clay,and gravel,suggesting overall hydrofacies stability both horizontally and vertically.The model's predictions are largely consistent with actual material distribution,with a slight under-prediction of clay(-0.750%)and an over-prediction of sand(2.985%),which accounts for 58.77%of the aquifer material.It also highlights significant heterogeneity in the northern mountainous regions and minor variations in the south.The study emphasizes Punjab's severe water crisis,with groundwater reserves of 3502.3 BCM,declining water levels(0.38–33.62 m),and low hydraulic conductivity,urging government action on rainwater harvesting and sustainable groundwater management policies.展开更多
This paper, based on the analysis and calculation of the groundwater resources in an arid region from 1980 to 2001, put forward the concept of ecological groundwater level threshold for either salinity control or the ...This paper, based on the analysis and calculation of the groundwater resources in an arid region from 1980 to 2001, put forward the concept of ecological groundwater level threshold for either salinity control or the determination of ecological warning. The surveys suggest that soil moisture and soil salinity are the most important environmental factors in determining the distribution and changes in vegetation. The groundwater level threshold of ecological warning can be determined by using a network of groundwater depth observation sites that monitor the environmental moisture gradient as reflected by plant physiological characteristics. According to long-term field observations within the Ejin oases, the groundwater level threshold for salinity control varied between 0.5 m and 1.5 m, and the ecological warning threshold varied between 3.5 m and 4.0 m. The quantity of groundwater re- sources （renewable water resources, ecological water resources, and exploitable water resources） in arid areas can be calculated from regional groundwater level information, without localized hydrogeological data. The concept of groundwater level threshold of ecological warning was established according to water development and water re- sources supply, and available groundwater resources were calculated. The concept not only enriches and broadens the content of groundwater studies, but also helps in predicting the prospects for water resources development.展开更多
The optimal allocation model of regional water resources is built with the purpose of maximizing the comprehensive economic,social and environmental benefits of regional water consumption.In order to solve the problem...The optimal allocation model of regional water resources is built with the purpose of maximizing the comprehensive economic,social and environmental benefits of regional water consumption.In order to solve the problems that easily appear during the model solution of regional water resource optimal allocation with multiple water sources,multiple users and multiple objectives like"curse of dimensionality"or sinking into local optimum,this paper proposes a particle swarm optimization(PSO)algorithm based on immune evolutionary algorithm(IEA).This algorithm introduces immunology principle into particle swarm algorithm.Its immune memorizing and self-adjusting mechanism is utilized to keep the particles in the fitness level at a certain concentration and guarantee the diversity of population.Also,the global search characteristics of IEA and the local search capacity of particle swarm algorithm have been fully utilized to overcome the dependence of PSO on initial swarm and the deficiency of vulnerability to local optimum.After applying this model to the allocation of water resources in Zhoukou,we obtain the scheme for optimization allocation of water resources in the planning level years,i.e.2015and 2025 under the guarantee rate of 50%.The calculation results indicate that the application of this algorithm to solve the issue of optimal allocation of regional water resources is reliable and reasonable.Thus it ofers a new idea for solving the issue of optimal allocation of water resources.展开更多
Water resources issue in the Middle East is an important question related to the 4th June 1967 line in the Middle Eastpeace process. This paper focuses on possibilities within the Integrated Water Resources Management...Water resources issue in the Middle East is an important question related to the 4th June 1967 line in the Middle Eastpeace process. This paper focuses on possibilities within the Integrated Water Resources Management (IWRM) approach to contribute to the peace process between what is calledIsraeland Arab countries emphasizing fruitful cooperation to resolve the 4th June 1967 line issue. The paper shows that start of a possible cooperation could be founded on interest-based negotiations and built on IWRM principles by a simple geographical allocation plan for theLake Tiberiaswater together with a joint environmental protection plan to build cooperation instead of confrontation and integration instead of fragmentation. In a better cooperative climate, withdrawing from the 4th June 1967 line could be a possibility because negotiation results would incur safer access to sustainable water resources and a comprehensive peace.展开更多
Iraq is one of the riparian countries within basins of Tigris-Euphrates Rivers in the Middle East region. The region is currently facing water shortage problems due to the increase of the demand and climate changes. I...Iraq is one of the riparian countries within basins of Tigris-Euphrates Rivers in the Middle East region. The region is currently facing water shortage problems due to the increase of the demand and climate changes. In the present study, average monthly water flow measurements for 15 stream flow gaging stations within basins of these rivers in Iraq with population growth rate data in some of its part were used to evaluate the reality of the current situation and future challenges of water availability and demand in Iraq. The results showed that Iraq receives annually 70.92 km3 of water 45.4 and 25.52 km3 from River Tigris and Euphrates respectively. An amount of 18.04 km3 of the Tigris water comes from Turkey while 27.36 km3 is supplied by its tributaries inside Iraq. The whole amount of water in the Euphrates Rivers comes outside the Iraqi borders. Annual decrease of the water inflow is 0.1335 km3·year-1 for Tigris and 0.245 km3·year-1 for Euphrates. This implies that the annual percentage reduction of inflow rates for the two rivers is 0.294% and 0.960%, respectively. Iraq consumes annually 88.89% (63.05 km3) of incoming water from the two rivers, where about 60.43% and 39.57% are from Rivers Tigris and Euphrates respectively. Water demand increases annually by 1.002 km3, of which 0.5271 km3 and 0.475 km3 are within Tigris and Euphrates basins respectively. The average water demand in 2020 will increase to 42.844 km3·year-1 for Tigris basin and for Euphrates 29.225 km3·year-1 (total 72.069 km3·year-1), while water availability will decrease to 63.46 km3·year-1. This means that the overall water shortage will be restricted to 8.61 km3.展开更多
Karst collapse columns typically appear unpredictably and without a uniform spatial arrangement,posing challenges for mining operations and water inrush risk assessment.As major structural pathways for mine water inru...Karst collapse columns typically appear unpredictably and without a uniform spatial arrangement,posing challenges for mining operations and water inrush risk assessment.As major structural pathways for mine water inrush,they are responsible for some of the most frequent and severe water-related disasters in coal mining.Understanding the mechanisms of water inrush in these collapse columns is therefore essential for effective disaster prevention and control,making it a key research priority.Additionally,investigating the developmental characteristics of collapse columns is crucial for analyzing seepage instability mechanisms.In such a context,this paper provides a comprehensive review of four critical aspects:(1)The development characteristics and hydrogeological properties of collapse columns;(2)Fluid-solid coupling mechanisms under mining-induced stress;(3)Non-Darcy seepage behavior in fractured rock masses;(4)Flow regime transitions and mass variation effects.Key findings highlight the role of flow-solid coupling in governing the seepage mechanisms of fractured rock masses within karst collapse columns.By synthesizing numerous studies on flow pattern transitions,this paper outlines the complete seepage process-from groundwater movement within the aquifer to its migration through the collapse column and eventual inflow into mine roadways or working faces-along with the associated transformations in flow patterns.Furthermore,the seepage characteristics and water inrush behaviors influenced by particle migration are examined through both experimental and numerical simulation approaches.展开更多
With the depletion of shallow mineral resources,mining operations are extending to greater depths and larger scales,increasing the risk of water inrush disasters,particularly from confined aquifers intersected by faul...With the depletion of shallow mineral resources,mining operations are extending to greater depths and larger scales,increasing the risk of water inrush disasters,particularly from confined aquifers intersected by faults.This paper reviews the current state of research on fault-induced water inrushes in mining faces,examining the damage characteristics and permeability of fractured floor rock,the mechanical behavior of faults under mining stress,and the mechanisms driving water inrush.Advances in prevention technologies,risk assessment,and prediction methods are also summarized.Research shows that damage evolution in fractured floor rock,coupled with fluid-solid interactions,provides the primary pathways for water inrush.Stress-seepage coupling in porous media plays a decisive role in determining inrush potential.Mining-induced stress redistribution can activate faults,with parameters such as dip angle and internal friction angle controlling stress evolution and slip.Critical triggers include the hydraulic connectivity among faults,aquifers,and mining-induced fracture networks,followed by hydraulic erosion.A multi-pronged prevention framework has been developed,integrating precise fault detection,targeted grouting for water sealing,drainage to reduce water pressure,optimized waterproof coal pillar design,and dynamic risk assessment and prediction.However,gaps remain in understanding multi-physical field coupling under deep mining conditions,establishing quantitative criteria for fault activation-induced water inrush,and refining control technologies.Future work should focus on multi-scale numerical simulations,advanced active control measures,and intelligent,integrated prevention systems to clarify the mechanisms of fault-induced water inrush and enhance theoretical and technical support for mine safety.展开更多
reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution sce...reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution scenario more.Hence,water quality analysis(WQA)is an important task for researchers and policymakers to maintain sustainability and public health.This study aims to gather and discuss the methods used for WQA by the researchers,focusing on their advantages and limitations.Simultaneously,this study compares different WQA methods,discussing their trends and future directions.Publications from the past decade on WQA are reviewed,and insights are explored to aggregate them in particular categories.Three major approaches,namely—water quality indexing,water quality modeling(WQM)and artificial intelligence-based WQM,are recognized.Different methodologies adopted to execute these three approaches are presented in this study,which leads to formulate a comparative discussion.Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing.To achieve better results,WQMs are being modified to incorporate the physical processes influencing water quality more robustly.The utilization of artificial intelligence was primarily restricted to conventional networks,but in the last 5 years,implications of deep learning have increased rapidly and exhibited good results with the hybridization of feature extracting and time series modeling.Overall,this study is a valuable resource for researchers dedicated to WQA.展开更多
The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in...The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in a river reach remains unclear.In this study,various hydrological data collected from the Jingjiang Reach of the Yangtze River in China were statistically analyzed to determine the backwater degree and range with three representative mainstream discharges.The results indicated that the backwater degree increased with mainstream discharge,and a positive relationship was observed between the runoff ratio and backwater degree at specific representative mainstream discharges.Following the operation of the Three Gorges Project,the backwater effect in the Jingjiang Reach diminished.For instance,mean backwater degrees for low,moderate,and high mainstream discharges were recorded as 0.83 m,1.61 m,and 2.41 m during the period from 1990 to 2002,whereas these values decreased to 0.30 m,0.95 m,and 2.08 m from 2009 to 2020.The backwater range extended upstream as mainstream discharge increased from 7000 m3/s to 30000 m3/s.Moreover,a random forest-based machine learning model was used to quantify the backwater effect with varying mainstream and confluence discharges,accounting for the impacts of mainstream discharge,confluence discharge,and channel degradation in the Jingjiang Reach.At the Jianli Hydrological Station,a decrease in mainstream discharge during flood seasons resulted in a 7%–15%increase in monthly mean backwater degree,while an increase in mainstream discharge during dry seasons led to a 1%–15%decrease in monthly mean backwater degree.Furthermore,increasing confluence discharge from Dongting Lake during June to July and September to November resulted in an 11%–42%increase in monthly mean backwater degree.Continuous channel degradation in the Jingjiang Reach contributed to a 6%–19%decrease in monthly mean backwater degree.Under the influence of these factors,the monthly mean backwater degree in 2017 varied from a decrease of 53%to an increase of 37%compared to corresponding values in 1991.展开更多
The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers...The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers a solution without access to ground-based observations,it fails to address rain/no-rain classification and its suitability for assessing and merging lake precipitation has not been explored.This study combines categorical triple collocation(CTC)with standard TC to create an integrated framework(CTC-TC)tailored to evaluate and merge global gridded precipitation products(GPPs).We assess the efficacy of CTC-TC using six GPPs(ERA5-Land,SM2 RAIN-ASCAT,IMERG-Early,IMERG-Late,GSMaPMVK,and PERSIANN-CCS)across the five largest freshwater lakes in China.CTC-TC effectively captures the spatial patterns of metrics for all GPPs,and precisely estimates the correlation coefficient and root mean square error for satellite-based datasets apart from SM2 RAIN-ASCAT,but overestimates the classification accuracy indicator V for all GPPs.Regarding multi-source fusion,CTC-TC leverages the strengths of individual products of triplets,resulting in significant improvements in the critical success index(CSI)by over 11.9%and the modified Kling-Gupta efficiency(KGE')by more than 13.3%.Compared to baseline models,including standard TC,simple model averaging,one outlier removal,and Bayesian model averaging,CTC-TC achieves gains in CSI and KGE'of no less than 24.7%and 3.6%,respectively.In conclusion,the CTC-TC framework offers a thorough evaluation and efficient fusion of GPPs,addressing both categorical and continuous accuracy in data-scarce regions such as lakes.展开更多
Groundwater is the main water supply source in the Tarim Basin in China.Endemic disease caused by high iodine(I)groundwater in the Tarim Basin was reported previously.Therefore,it is crucial to systematically identify...Groundwater is the main water supply source in the Tarim Basin in China.Endemic disease caused by high iodine(I)groundwater in the Tarim Basin was reported previously.Therefore,it is crucial to systematically identify the distribution and genesis of groundwater I.Based on hydrochemical analysis of 717 groundwater samples collected in 2015–2018,spatial distribution and hydrogeochemistry characteristic of high I groundwater in different aquifers were analyzed.Results showed that groundwater I ranged between<10.00 and 4000.00μg/L(mean of 53.71μg/L).High I groundwater(I>100.00μg/L)accounted for 7.25%of the total samples.Horizontally,groundwater I significantly increased from recharge zone(RZ)to transition zone(TZ)and to evaporation zone(EZ).Vertically,groundwater in shallow confined aquifer(SCA)had the greatest I concentration,followed by single-structure phreatic aquifer(SSPA),phreatic aquifer in confined groundwater area(PACGA),while groundwater in deep confined aquifer(DCA)generally had low I concentration.Groundwater I enrichment in SSPA was mainly affected by organic matter(OM)decomposition and that in SCA was mainly affected by evaporite mineral dissolution,OM decomposition under alkaline environment.While I enrichment in groundwater of PACGA was restrained under neutral environment.Lacustrine sedimentary environment was crucial for I enrichment in groundwater.Besides,fine-grained lithology of aquifer,smooth topographic slope,shallow buried depth of groundwater,weak alkaline and reducing environment,reductive dissolution of iron oxide/hydroxide minerals and OM decomposition were advantageous to I enrichment in groundwater.展开更多
Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blas...Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blast furnace slag(GGBS),a byproduct of industrial production,is used as a mineral admixture to reduce concrete costs and provide excellent performance.This study aimed to investigate the impact of GGBS on the hydration properties of FCSA cement in seawater.Tests were conducted on heat of hydration,compressive strength,mass change,and pH value of pore solution of FCSA cement paste with a water-to-binder ratio of 0.45.X-ray diffraction(XRD)analysis and thermogravimetric analysis were used to determine the hydration products,while mercury intrusion porosimetry(MIP)was used to measure pore structure.The results indicated that the FCSA cement hydration showed a concentrated heat release at early age.The compressive strength of specimens consistently increased over time,where seawater curing enhanced the compressive strength of control samples.The pH value of pore solution decreased to 10.7−10.9 at 90 d when cured in seawater.The primary hydration products of FCSA cement included ettringite,iron hydroxide gel(FH_(3)),and aluminum hydroxide gel(AH_(3)).Moreover,when cured in seawater,Friedel’s salt was formed,which enhanced the compressive strength of the specimen and increased its coefficient of corrosion.Seawater curing gradually increased sample mass,and GGBS refined pore structure while reducing harmful pore proportions.These results suggest that while GGBS can refine pore structure and improve certain aspects of performance,its inclusion may also reduce compressive strength,highlighting the need for a balanced approach in its use for marine applications.展开更多
Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the...Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the reservoir water level is an essential physical indicator for the reservoirs.Forecasting the reservoir water level effectively assists the managers in making decisions and plans related to reservoir management policies.In recent years,deep learning models have been widely applied to solve forecasting problems.In this study,we propose a novel hybrid deep learning model namely the YOLOv9_ConvLSTM that integrates YOLOv9,ConvLSTM,and linear interpolation to predict reservoir water levels.It utilizes data from Sentinel-2 satellite images,generated from visible spectrum bands(Red-Blue-Green)to reconstruct true-color reservoir images.Adam is used as the optimization algorithm with the loss function being MSE(Mean Squared Error)to evaluate the model’s error during training.We implemented and validated the proposed model using Sentinel-2 satellite imagery for the An Khe reservoir in Vietnam.To assess its performance,we also conducted comparative experiments with other related models,including SegNet_ConvLSTM and UNet_ConvLSTM,on the same dataset.The model performances were validated using k-fold cross-validation and ANOVA analysis.The experimental results demonstrate that the YOLOv9_ConvLSTM model outperforms the compared models.It has been seen that the proposed approach serves as a valuable tool for reservoir water level forecasting using satellite imagery that contributes to effective water resource management.展开更多
The capillary pressure curve provides fundamental insights into the dynamics of fluid-fluid displacement and phase distributions.Capillary scaling is crucial for extrapolating capillary pressure-saturation data from l...The capillary pressure curve provides fundamental insights into the dynamics of fluid-fluid displacement and phase distributions.Capillary scaling is crucial for extrapolating capillary pressure-saturation data from laboratory tests to field applications.However,the classic scaling method fails to capture the effect of wettability as the pore surface approaches neutral wetting.Here,inspired by the role of pore-filling events in controlling fluid-fluid displacement,we perform a theoretical analysis of the burst events occurring during drainage processes.We find that the median threshold capillary pressure,which corresponds to the occurrence of burst events for the median pore throat,is closely correlated with the capillary pressure curve across various contact angles.Using this concept,we propose a new scaling method for capillary pressure curves under various wetting conditions.We conduct microfluidic experiments and pore-network modeling across different contact angles,porosities,and disorders to evaluate the new scaling methods,indicating that the new scaling method performs better than the Leverett J-function as the contact angle approaches 90°.We further perform geometry analysis on the critical radius of curvature for burst events in an ideal tetrahedral arrangement and extend the new scaling method to 3D(three-dimensional)porous media.Model evaluation shows that the 3D version of the scaling method also performs well but requires fewer parameters compared to the Leverett J-function.Our work enhances the prediction and interpretation of experimental data for capillary pressure curves under various wet conditions,and more importantly,establishes a methodology that relates Darcy-scale flow behavior to pore-scale fluid displacements.展开更多
Accurate land surface temperature(LST)assessment is crucial for comprehending and reducing the impacts of climate change and understanding land use evolution.This study presents an innovative method by utilizing ensem...Accurate land surface temperature(LST)assessment is crucial for comprehending and reducing the impacts of climate change and understanding land use evolution.This study presents an innovative method by utilizing ensemble models,advanced correlation analysis,and trend analysis to investigate its environmental influences.Google Earth Engine(GEE)was utilized to process the datasets from Landsat-7 and Landsat-8 for the five big cities of Punjab,Pakistan,from 2001 to 2023.Results from this study show significant urban warming trends,and a strong correlation between environmental variables and LST was identified.The ensemble-based three machine learning models,including XGBoost,AdaBoost,and random forest(RF),were adopted to improve the accuracy of LST evaluation.Although XGBoost and AdaBoost attained modest levels of accuracy,with R^(2) values of 0.767 and 0.706,respectively,the RF model outperformed them by achieving an exceptional R^(2) of 0.796 and RMSE of 0.476.Moreover,Pearson correlation analysis revealed a negative relationship between LST and normalized difference latent heat index(NDLI)with r=-0.67,normalized difference vegetation index(NDVI)with r=-0.6,and modified normalized difference water index(MNDWI)with the value of r as -0.57.In addition,wavelet analysis showed that vegetation and water offer long-term LST cooling,lasting up to 64 months,while built-up areas and bare soil contribute to short-term warming,lasting 4 to 8 months.Latent heat indicated variable cooling periods,surpassing 60 months in cities.These findings enhance the understanding of LST changes and the impact of climate change on the environment.展开更多
The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we condu...The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we conducted a series of triaxial tests on calcareous sand with varying Dri and stress paths,examining particle breakage and critical state behavior.Key findingsinclude:(1)At a constant stress ratio(η),B follows a hyperbolic relationship with mean effective stress(p'),and for a given p',B increases proportionally withη;(2)The critical state line(CSL)moves downward with increasing Dri,whereas the critical state friction angle(φcs)decreases with increasing B.Based on these findings,we propose a unifiedbreakage evolution model to quantify particle breakage in calcareous sand under various loading conditions.Integrating this model with the Normal Consolidation Line(NCL)and CSL equations,we successfully simulate the steepening of NCL and CSL slopes as B increases with the onset of particle breakage.Furthermore,we quantitatively evaluate the effect of B onφcs.Finally,within the framework of Critical State Soil Mechanics and Hypoplasticity theory,we develop a hypoplastic model incorporating B and Dri.The model is validated through strong agreement with experimental results across various initial relative densities,stress paths and drainage conditions.展开更多
This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality...This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.展开更多
Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting...Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.展开更多
基金Financial support from the National Natural Science Foundation of China(Grant Nos.51925906 and U2340228)the Natural Science Foundation of Hubei Province(Grant No.2022CFA028)is acknowledged.
文摘Drains play an important role in seepage control in geotechnical engineering.The enormous number and one-dimensional(1D)geometry of drainage holes make their nature difficult to be accurately modeled in groundwater flow simulation.It has been well understood that drains function by presenting discharge boundaries,which can be characterized by water head,no-flux,unilateral or mixed water head-unilateral boundary condition.It has been found after years of practices that the flow simulation may become erroneous if the transitions among the drain boundary conditions are not properly considered.For this,a rigorous algorithm is proposed in this study to detect the onset of transitions among the water head,noflux and mixed water head-unilateral boundary conditions for downwards-drilled drainage holes,which theoretically completes the description of drain boundary conditions.After verification against a numerical example,the proposed algorithm is applied to numerical modeling of groundwater flow through a gravity dam foundation.The simulation shows that for hundreds of downwards-drilled drainage holes used to be prescribed with water head boundary condition,56%and 2%of them are transitioned to mixed water head-unilateral and no-flux boundary conditions,respectively.The phreatic surface around the drains will be overestimated by 25e33 m without the use of the mixed boundary condition.For the first time,this study underscores the importance of the mixed water head-unilateral boundary condition and the proposed transition algorithm in drain modeling,which may become more essential for simulation of transient flow because of groundwater dynamics.
文摘Groundwater,the world’s largest freshwater supply,is facing increasing strain due to various uses such as agriculture,industry,livestock,and household.This study aims to investigate groundwater prospective zonation in the Bandu Sub-watershed in Purulia,West Bengal,using the AHP model and RS&GIS methodologies.To achieve Goal 6 of the UN-initiated 17 SDGs,it is crucial to determine the spatial distribution of groundwater prospective zones village-by-village,with 1/3 of the regions falling under red alert zones for sustainable development.The 16 most crucial elements affecting groundwater prospective zones(GWPZs)were mapped using AHP,and the final prospective map was obtained through Weighted Overlay analysis.The study identified five different classes within the Sub-watershed as excellent,good,moderate,poor,and very poor.The validation results showed that the approach used to derive GWPZ is reliable,and the results can be applied to future sustainable developments to reduce water shortages through suitable management methods.The research aims to increase the effectiveness of sustainable groundwater zone management,ensuring long-term water management and access.
基金supported by the K.C.Wong Education Foundation(GJTD-2020-14)the National Natural Science Foundation of China(42071245)+3 种基金Third Xinjiang Scientific Expedition Program(2021XJKK1400)the China-Pakistan Joint Research Center on Earth Sciences that supported the implementation of this studythe Chinese Academy of Sciences(CAS)the CSC Scholarship for Young Talents(Doctor Program)for the financial support of this study。
文摘Effective groundwater management is crucial for economic sustainable development,particularly as climate change and population growth increase the uncertainty of aquifer dynamics.Due to limited geological data,Punjab's complex hydrogeological conditions and Quaternary alluvial deposits present significant challenges for groundwater management.This study employs cost-effective numerical techniques as alternatives to traditional methods to safeguard groundwater quality,quantity,and accessibility.It introduces an edit-embedded transition frequency model that integrates regional datasets and utilizes algorithms such as GAMEAS,MCMOD,and TSIM to evaluate aquifer heterogeneity and simulate spatial variations using one-dimensional and three-dimensional Markov chains.Findings show that sand exhibits the highest self-transition(33.112 m),indicating strong stability,followed by silt,clay,and gravel,suggesting overall hydrofacies stability both horizontally and vertically.The model's predictions are largely consistent with actual material distribution,with a slight under-prediction of clay(-0.750%)and an over-prediction of sand(2.985%),which accounts for 58.77%of the aquifer material.It also highlights significant heterogeneity in the northern mountainous regions and minor variations in the south.The study emphasizes Punjab's severe water crisis,with groundwater reserves of 3502.3 BCM,declining water levels(0.38–33.62 m),and low hydraulic conductivity,urging government action on rainwater harvesting and sustainable groundwater management policies.
基金funded by the National Natural Science Foundation of China(9102500230970492)+2 种基金the Fundamental Research Funds for the Central Universities(GK201101002)the Key Project of the Chinese Academy of Sciences(KZZDEW-04-05)the National Key Technology R & D Program(2012BAC08B05)
文摘This paper, based on the analysis and calculation of the groundwater resources in an arid region from 1980 to 2001, put forward the concept of ecological groundwater level threshold for either salinity control or the determination of ecological warning. The surveys suggest that soil moisture and soil salinity are the most important environmental factors in determining the distribution and changes in vegetation. The groundwater level threshold of ecological warning can be determined by using a network of groundwater depth observation sites that monitor the environmental moisture gradient as reflected by plant physiological characteristics. According to long-term field observations within the Ejin oases, the groundwater level threshold for salinity control varied between 0.5 m and 1.5 m, and the ecological warning threshold varied between 3.5 m and 4.0 m. The quantity of groundwater re- sources （renewable water resources, ecological water resources, and exploitable water resources） in arid areas can be calculated from regional groundwater level information, without localized hydrogeological data. The concept of groundwater level threshold of ecological warning was established according to water development and water re- sources supply, and available groundwater resources were calculated. The concept not only enriches and broadens the content of groundwater studies, but also helps in predicting the prospects for water resources development.
基金the National Natural Science Foundation of China(No.40839902)
文摘The optimal allocation model of regional water resources is built with the purpose of maximizing the comprehensive economic,social and environmental benefits of regional water consumption.In order to solve the problems that easily appear during the model solution of regional water resource optimal allocation with multiple water sources,multiple users and multiple objectives like"curse of dimensionality"or sinking into local optimum,this paper proposes a particle swarm optimization(PSO)algorithm based on immune evolutionary algorithm(IEA).This algorithm introduces immunology principle into particle swarm algorithm.Its immune memorizing and self-adjusting mechanism is utilized to keep the particles in the fitness level at a certain concentration and guarantee the diversity of population.Also,the global search characteristics of IEA and the local search capacity of particle swarm algorithm have been fully utilized to overcome the dependence of PSO on initial swarm and the deficiency of vulnerability to local optimum.After applying this model to the allocation of water resources in Zhoukou,we obtain the scheme for optimization allocation of water resources in the planning level years,i.e.2015and 2025 under the guarantee rate of 50%.The calculation results indicate that the application of this algorithm to solve the issue of optimal allocation of regional water resources is reliable and reasonable.Thus it ofers a new idea for solving the issue of optimal allocation of water resources.
文摘Water resources issue in the Middle East is an important question related to the 4th June 1967 line in the Middle Eastpeace process. This paper focuses on possibilities within the Integrated Water Resources Management (IWRM) approach to contribute to the peace process between what is calledIsraeland Arab countries emphasizing fruitful cooperation to resolve the 4th June 1967 line issue. The paper shows that start of a possible cooperation could be founded on interest-based negotiations and built on IWRM principles by a simple geographical allocation plan for theLake Tiberiaswater together with a joint environmental protection plan to build cooperation instead of confrontation and integration instead of fragmentation. In a better cooperative climate, withdrawing from the 4th June 1967 line could be a possibility because negotiation results would incur safer access to sustainable water resources and a comprehensive peace.
基金financially supported by Lulea University of Technology,Sweden and by“Swedish Hydropower Centre—SVC”established by the Swedish Energy Agency,Elforsk and Svenska Kraftnat together with Lulea University of Technology,The Royal Institute of Technology,Chalmers University of Technology and Uppsala University.
文摘Iraq is one of the riparian countries within basins of Tigris-Euphrates Rivers in the Middle East region. The region is currently facing water shortage problems due to the increase of the demand and climate changes. In the present study, average monthly water flow measurements for 15 stream flow gaging stations within basins of these rivers in Iraq with population growth rate data in some of its part were used to evaluate the reality of the current situation and future challenges of water availability and demand in Iraq. The results showed that Iraq receives annually 70.92 km3 of water 45.4 and 25.52 km3 from River Tigris and Euphrates respectively. An amount of 18.04 km3 of the Tigris water comes from Turkey while 27.36 km3 is supplied by its tributaries inside Iraq. The whole amount of water in the Euphrates Rivers comes outside the Iraqi borders. Annual decrease of the water inflow is 0.1335 km3·year-1 for Tigris and 0.245 km3·year-1 for Euphrates. This implies that the annual percentage reduction of inflow rates for the two rivers is 0.294% and 0.960%, respectively. Iraq consumes annually 88.89% (63.05 km3) of incoming water from the two rivers, where about 60.43% and 39.57% are from Rivers Tigris and Euphrates respectively. Water demand increases annually by 1.002 km3, of which 0.5271 km3 and 0.475 km3 are within Tigris and Euphrates basins respectively. The average water demand in 2020 will increase to 42.844 km3·year-1 for Tigris basin and for Euphrates 29.225 km3·year-1 (total 72.069 km3·year-1), while water availability will decrease to 63.46 km3·year-1. This means that the overall water shortage will be restricted to 8.61 km3.
基金supported by the Natural Science Foundation of Henan Province(242300421246,222300420007,232300421134)the National Natural Science Foundation of China(52004082,52174073,52274079,42402255)+4 种基金the Science and Technology Project of Henan Province(232102321098)Zhongyuan Science and Technology Innovation Leading Talent Program(244200510005)the Program for Science&Technology Innovation Talents in Universities of Henan Province(24HASTIT021)the Program for the Scientific and Technological Innovation Team in Universities of Henan Province(23IRTSTHN005)the National Postdoctoral Researchers Program Foundation of China(GZC20230709)。
文摘Karst collapse columns typically appear unpredictably and without a uniform spatial arrangement,posing challenges for mining operations and water inrush risk assessment.As major structural pathways for mine water inrush,they are responsible for some of the most frequent and severe water-related disasters in coal mining.Understanding the mechanisms of water inrush in these collapse columns is therefore essential for effective disaster prevention and control,making it a key research priority.Additionally,investigating the developmental characteristics of collapse columns is crucial for analyzing seepage instability mechanisms.In such a context,this paper provides a comprehensive review of four critical aspects:(1)The development characteristics and hydrogeological properties of collapse columns;(2)Fluid-solid coupling mechanisms under mining-induced stress;(3)Non-Darcy seepage behavior in fractured rock masses;(4)Flow regime transitions and mass variation effects.Key findings highlight the role of flow-solid coupling in governing the seepage mechanisms of fractured rock masses within karst collapse columns.By synthesizing numerous studies on flow pattern transitions,this paper outlines the complete seepage process-from groundwater movement within the aquifer to its migration through the collapse column and eventual inflow into mine roadways or working faces-along with the associated transformations in flow patterns.Furthermore,the seepage characteristics and water inrush behaviors influenced by particle migration are examined through both experimental and numerical simulation approaches.
基金supported by the Natural Science Foundation of Henan Province(242300421246)the National Natural Science Foundation of China(52004082,U24B2041,52174073,52274079)+2 种基金the Key Research and Development Program of Henan Province(251111320400)the Program for Science&Technology Innovation Talents in Universities of Henan Province(24HASTIT021)the Program for the Scientific and Technological Innovation Team in Universities of Henan Province(23IRTSTHN005).
文摘With the depletion of shallow mineral resources,mining operations are extending to greater depths and larger scales,increasing the risk of water inrush disasters,particularly from confined aquifers intersected by faults.This paper reviews the current state of research on fault-induced water inrushes in mining faces,examining the damage characteristics and permeability of fractured floor rock,the mechanical behavior of faults under mining stress,and the mechanisms driving water inrush.Advances in prevention technologies,risk assessment,and prediction methods are also summarized.Research shows that damage evolution in fractured floor rock,coupled with fluid-solid interactions,provides the primary pathways for water inrush.Stress-seepage coupling in porous media plays a decisive role in determining inrush potential.Mining-induced stress redistribution can activate faults,with parameters such as dip angle and internal friction angle controlling stress evolution and slip.Critical triggers include the hydraulic connectivity among faults,aquifers,and mining-induced fracture networks,followed by hydraulic erosion.A multi-pronged prevention framework has been developed,integrating precise fault detection,targeted grouting for water sealing,drainage to reduce water pressure,optimized waterproof coal pillar design,and dynamic risk assessment and prediction.However,gaps remain in understanding multi-physical field coupling under deep mining conditions,establishing quantitative criteria for fault activation-induced water inrush,and refining control technologies.Future work should focus on multi-scale numerical simulations,advanced active control measures,and intelligent,integrated prevention systems to clarify the mechanisms of fault-induced water inrush and enhance theoretical and technical support for mine safety.
基金State University Research Excellence(SURE),SERB,GOI,Grant/Award Number:SUR/2022/001557。
文摘reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution scenario more.Hence,water quality analysis(WQA)is an important task for researchers and policymakers to maintain sustainability and public health.This study aims to gather and discuss the methods used for WQA by the researchers,focusing on their advantages and limitations.Simultaneously,this study compares different WQA methods,discussing their trends and future directions.Publications from the past decade on WQA are reviewed,and insights are explored to aggregate them in particular categories.Three major approaches,namely—water quality indexing,water quality modeling(WQM)and artificial intelligence-based WQM,are recognized.Different methodologies adopted to execute these three approaches are presented in this study,which leads to formulate a comparative discussion.Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing.To achieve better results,WQMs are being modified to incorporate the physical processes influencing water quality more robustly.The utilization of artificial intelligence was primarily restricted to conventional networks,but in the last 5 years,implications of deep learning have increased rapidly and exhibited good results with the hybridization of feature extracting and time series modeling.Overall,this study is a valuable resource for researchers dedicated to WQA.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFC3209504)the National Natural Science Foundation of China(Grants No.U2040215 and 52479075)the Natural Science Foundation of Hubei Province(Grant No.2021CFA029).
文摘The backwater effect caused by tributary inflow can significantly elevate the water level profile upstream of a confluence point.However,the influence of mainstream and confluence discharges on the backwater effect in a river reach remains unclear.In this study,various hydrological data collected from the Jingjiang Reach of the Yangtze River in China were statistically analyzed to determine the backwater degree and range with three representative mainstream discharges.The results indicated that the backwater degree increased with mainstream discharge,and a positive relationship was observed between the runoff ratio and backwater degree at specific representative mainstream discharges.Following the operation of the Three Gorges Project,the backwater effect in the Jingjiang Reach diminished.For instance,mean backwater degrees for low,moderate,and high mainstream discharges were recorded as 0.83 m,1.61 m,and 2.41 m during the period from 1990 to 2002,whereas these values decreased to 0.30 m,0.95 m,and 2.08 m from 2009 to 2020.The backwater range extended upstream as mainstream discharge increased from 7000 m3/s to 30000 m3/s.Moreover,a random forest-based machine learning model was used to quantify the backwater effect with varying mainstream and confluence discharges,accounting for the impacts of mainstream discharge,confluence discharge,and channel degradation in the Jingjiang Reach.At the Jianli Hydrological Station,a decrease in mainstream discharge during flood seasons resulted in a 7%–15%increase in monthly mean backwater degree,while an increase in mainstream discharge during dry seasons led to a 1%–15%decrease in monthly mean backwater degree.Furthermore,increasing confluence discharge from Dongting Lake during June to July and September to November resulted in an 11%–42%increase in monthly mean backwater degree.Continuous channel degradation in the Jingjiang Reach contributed to a 6%–19%decrease in monthly mean backwater degree.Under the influence of these factors,the monthly mean backwater degree in 2017 varied from a decrease of 53%to an increase of 37%compared to corresponding values in 1991.
基金National Key R&D Program of China,No.2022YFC3202802National Natural Science Foundation of China,No.52009081,No.52121006,No.52279071Special Funded Project for Basic Scientific Research Operation Expenses of the Central Public Welfare Scientific Research Institutes of China,No.Y524017。
文摘The sparsity of ground gauges poses a significant challenge for evaluating and merging satellite-based and reanalysis-based precipitation datasets in lake regions.While the standard triple collocation(TC)method offers a solution without access to ground-based observations,it fails to address rain/no-rain classification and its suitability for assessing and merging lake precipitation has not been explored.This study combines categorical triple collocation(CTC)with standard TC to create an integrated framework(CTC-TC)tailored to evaluate and merge global gridded precipitation products(GPPs).We assess the efficacy of CTC-TC using six GPPs(ERA5-Land,SM2 RAIN-ASCAT,IMERG-Early,IMERG-Late,GSMaPMVK,and PERSIANN-CCS)across the five largest freshwater lakes in China.CTC-TC effectively captures the spatial patterns of metrics for all GPPs,and precisely estimates the correlation coefficient and root mean square error for satellite-based datasets apart from SM2 RAIN-ASCAT,but overestimates the classification accuracy indicator V for all GPPs.Regarding multi-source fusion,CTC-TC leverages the strengths of individual products of triplets,resulting in significant improvements in the critical success index(CSI)by over 11.9%and the modified Kling-Gupta efficiency(KGE')by more than 13.3%.Compared to baseline models,including standard TC,simple model averaging,one outlier removal,and Bayesian model averaging,CTC-TC achieves gains in CSI and KGE'of no less than 24.7%and 3.6%,respectively.In conclusion,the CTC-TC framework offers a thorough evaluation and efficient fusion of GPPs,addressing both categorical and continuous accuracy in data-scarce regions such as lakes.
基金financially supported by the National Natural Science Foundation of China(Nos.42067035 and 42007161)Water Conservancy Engineering Key Discipline Project of Xinjiang Agricultural University(No.SLXK2019-10)the Opening Project of Xinjiang Key Laboratory of Hydraulic Engineering Security and Water Disasters Prevention in 2021(No.ZDSYS-JS-2021-10)。
文摘Groundwater is the main water supply source in the Tarim Basin in China.Endemic disease caused by high iodine(I)groundwater in the Tarim Basin was reported previously.Therefore,it is crucial to systematically identify the distribution and genesis of groundwater I.Based on hydrochemical analysis of 717 groundwater samples collected in 2015–2018,spatial distribution and hydrogeochemistry characteristic of high I groundwater in different aquifers were analyzed.Results showed that groundwater I ranged between<10.00 and 4000.00μg/L(mean of 53.71μg/L).High I groundwater(I>100.00μg/L)accounted for 7.25%of the total samples.Horizontally,groundwater I significantly increased from recharge zone(RZ)to transition zone(TZ)and to evaporation zone(EZ).Vertically,groundwater in shallow confined aquifer(SCA)had the greatest I concentration,followed by single-structure phreatic aquifer(SSPA),phreatic aquifer in confined groundwater area(PACGA),while groundwater in deep confined aquifer(DCA)generally had low I concentration.Groundwater I enrichment in SSPA was mainly affected by organic matter(OM)decomposition and that in SCA was mainly affected by evaporite mineral dissolution,OM decomposition under alkaline environment.While I enrichment in groundwater of PACGA was restrained under neutral environment.Lacustrine sedimentary environment was crucial for I enrichment in groundwater.Besides,fine-grained lithology of aquifer,smooth topographic slope,shallow buried depth of groundwater,weak alkaline and reducing environment,reductive dissolution of iron oxide/hydroxide minerals and OM decomposition were advantageous to I enrichment in groundwater.
基金Project(2023DJC182)supported by the Department of Science and Technology of Hubei Province,ChinaProjects(51608402,51602229)supported by the National Natural Science Foundation of ChinaProject(2021-2075-38)supported by the Department of Housing and Urban-Rural Development of Hubei Province,China。
文摘Ferrite-rich calcium sulfoaluminate(FCSA)cement is often used in special projects such as marine engineering due to its excellent resistance of seawater attack although the cost is a little high.Ground granulated blast furnace slag(GGBS),a byproduct of industrial production,is used as a mineral admixture to reduce concrete costs and provide excellent performance.This study aimed to investigate the impact of GGBS on the hydration properties of FCSA cement in seawater.Tests were conducted on heat of hydration,compressive strength,mass change,and pH value of pore solution of FCSA cement paste with a water-to-binder ratio of 0.45.X-ray diffraction(XRD)analysis and thermogravimetric analysis were used to determine the hydration products,while mercury intrusion porosimetry(MIP)was used to measure pore structure.The results indicated that the FCSA cement hydration showed a concentrated heat release at early age.The compressive strength of specimens consistently increased over time,where seawater curing enhanced the compressive strength of control samples.The pH value of pore solution decreased to 10.7−10.9 at 90 d when cured in seawater.The primary hydration products of FCSA cement included ettringite,iron hydroxide gel(FH_(3)),and aluminum hydroxide gel(AH_(3)).Moreover,when cured in seawater,Friedel’s salt was formed,which enhanced the compressive strength of the specimen and increased its coefficient of corrosion.Seawater curing gradually increased sample mass,and GGBS refined pore structure while reducing harmful pore proportions.These results suggest that while GGBS can refine pore structure and improve certain aspects of performance,its inclusion may also reduce compressive strength,highlighting the need for a balanced approach in its use for marine applications.
基金funded by International School,Vietnam National University,Hanoi(VNU-IS)under project number CS.2023-10.
文摘Global climate change,along with the rapid increase of the population,has put significant pressure on water security.A water reservoir is an effective solution for adjusting and ensuring water supply.In particular,the reservoir water level is an essential physical indicator for the reservoirs.Forecasting the reservoir water level effectively assists the managers in making decisions and plans related to reservoir management policies.In recent years,deep learning models have been widely applied to solve forecasting problems.In this study,we propose a novel hybrid deep learning model namely the YOLOv9_ConvLSTM that integrates YOLOv9,ConvLSTM,and linear interpolation to predict reservoir water levels.It utilizes data from Sentinel-2 satellite images,generated from visible spectrum bands(Red-Blue-Green)to reconstruct true-color reservoir images.Adam is used as the optimization algorithm with the loss function being MSE(Mean Squared Error)to evaluate the model’s error during training.We implemented and validated the proposed model using Sentinel-2 satellite imagery for the An Khe reservoir in Vietnam.To assess its performance,we also conducted comparative experiments with other related models,including SegNet_ConvLSTM and UNet_ConvLSTM,on the same dataset.The model performances were validated using k-fold cross-validation and ANOVA analysis.The experimental results demonstrate that the YOLOv9_ConvLSTM model outperforms the compared models.It has been seen that the proposed approach serves as a valuable tool for reservoir water level forecasting using satellite imagery that contributes to effective water resource management.
基金supported by the National Natural Science Foundation of China(Grant Nos.52379107 and 52309141).
文摘The capillary pressure curve provides fundamental insights into the dynamics of fluid-fluid displacement and phase distributions.Capillary scaling is crucial for extrapolating capillary pressure-saturation data from laboratory tests to field applications.However,the classic scaling method fails to capture the effect of wettability as the pore surface approaches neutral wetting.Here,inspired by the role of pore-filling events in controlling fluid-fluid displacement,we perform a theoretical analysis of the burst events occurring during drainage processes.We find that the median threshold capillary pressure,which corresponds to the occurrence of burst events for the median pore throat,is closely correlated with the capillary pressure curve across various contact angles.Using this concept,we propose a new scaling method for capillary pressure curves under various wetting conditions.We conduct microfluidic experiments and pore-network modeling across different contact angles,porosities,and disorders to evaluate the new scaling methods,indicating that the new scaling method performs better than the Leverett J-function as the contact angle approaches 90°.We further perform geometry analysis on the critical radius of curvature for burst events in an ideal tetrahedral arrangement and extend the new scaling method to 3D(three-dimensional)porous media.Model evaluation shows that the 3D version of the scaling method also performs well but requires fewer parameters compared to the Leverett J-function.Our work enhances the prediction and interpretation of experimental data for capillary pressure curves under various wet conditions,and more importantly,establishes a methodology that relates Darcy-scale flow behavior to pore-scale fluid displacements.
基金supported by the National Natural Science Foundation of China(Grant Nos.52479045,52279042)the Key Research and Development Program in Guangxi(Grant No.AB23026021)the Open Research Fund of Guangxi Key Laboratory of Water Engineering Materials and Structures,Guangxi Institute of Water Resources Research(Grant No.GXHRIWEMS-2022-07).
文摘Accurate land surface temperature(LST)assessment is crucial for comprehending and reducing the impacts of climate change and understanding land use evolution.This study presents an innovative method by utilizing ensemble models,advanced correlation analysis,and trend analysis to investigate its environmental influences.Google Earth Engine(GEE)was utilized to process the datasets from Landsat-7 and Landsat-8 for the five big cities of Punjab,Pakistan,from 2001 to 2023.Results from this study show significant urban warming trends,and a strong correlation between environmental variables and LST was identified.The ensemble-based three machine learning models,including XGBoost,AdaBoost,and random forest(RF),were adopted to improve the accuracy of LST evaluation.Although XGBoost and AdaBoost attained modest levels of accuracy,with R^(2) values of 0.767 and 0.706,respectively,the RF model outperformed them by achieving an exceptional R^(2) of 0.796 and RMSE of 0.476.Moreover,Pearson correlation analysis revealed a negative relationship between LST and normalized difference latent heat index(NDLI)with r=-0.67,normalized difference vegetation index(NDVI)with r=-0.6,and modified normalized difference water index(MNDWI)with the value of r as -0.57.In addition,wavelet analysis showed that vegetation and water offer long-term LST cooling,lasting up to 64 months,while built-up areas and bare soil contribute to short-term warming,lasting 4 to 8 months.Latent heat indicated variable cooling periods,surpassing 60 months in cities.These findings enhance the understanding of LST changes and the impact of climate change on the environment.
基金support to this study from the National Natural Science Foundation of China,NSFC(Grant No.52278367)The Belt and Road Special Foundation of the National Key Laboratory ofWater Disaster Prevention(Grant No.2024nkms08).
文摘The stress-strain behavior of calcareous sand is significantly influencedby particle breakage(B)and initial relative density(Dri),but few constitutive models consider their combined effects.To bridge this gap,we conducted a series of triaxial tests on calcareous sand with varying Dri and stress paths,examining particle breakage and critical state behavior.Key findingsinclude:(1)At a constant stress ratio(η),B follows a hyperbolic relationship with mean effective stress(p'),and for a given p',B increases proportionally withη;(2)The critical state line(CSL)moves downward with increasing Dri,whereas the critical state friction angle(φcs)decreases with increasing B.Based on these findings,we propose a unifiedbreakage evolution model to quantify particle breakage in calcareous sand under various loading conditions.Integrating this model with the Normal Consolidation Line(NCL)and CSL equations,we successfully simulate the steepening of NCL and CSL slopes as B increases with the onset of particle breakage.Furthermore,we quantitatively evaluate the effect of B onφcs.Finally,within the framework of Critical State Soil Mechanics and Hypoplasticity theory,we develop a hypoplastic model incorporating B and Dri.The model is validated through strong agreement with experimental results across various initial relative densities,stress paths and drainage conditions.
基金National Natural Science Foundation of China under Grant Nos.51979205 and 51939008。
文摘This research is focused on the calculation of a reasonable detonator delay time for realizing cut blast vibration control.First,the viscoelastic rock mass parameters corresponding to the engineering rock mass quality classification were determined based on wave theory of Kelvin medium.Then,a calculation model was obtained for the millisecond-delay cut blast vibration in Kelvin media using the Starfield charge superposition principle.Further,the influence of the delay time on the cut blast vibration was quantitatively analyzed and a method for calculating the reasonable cut blasting millisecond delay time is proposed according to the principle of dimensional analysis.Finally,field tests were used to verify the applicability of the method.The results show that 5 ms to 20 ms is a better detonator delay time range and cut blasting vibration can be effectively controlled using the delay time calculated by the calculation model described in this paper.
基金National Key Research and Development Program of China,No.2023YFC3006704National Natural Science Foundation of China,No.42171047CAS-CSIRO Partnership Joint Project of 2024,No.177GJHZ2023097MI。
文摘Accurate prediction of flood events is important for flood control and risk management.Machine learning techniques contributed greatly to advances in flood predictions,and existing studies mainly focused on predicting flood resource variables using single or hybrid machine learning techniques.However,class-based flood predictions have rarely been investigated,which can aid in quickly diagnosing comprehensive flood characteristics and proposing targeted management strategies.This study proposed a prediction approach of flood regime metrics and event classes coupling machine learning algorithms with clustering-deduced membership degrees.Five algorithms were adopted for this exploration.Results showed that the class membership degrees accurately determined event classes with class hit rates up to 100%,compared with the four classes clustered from nine regime metrics.The nonlinear algorithms(Multiple Linear Regression,Random Forest,and least squares-Support Vector Machine)outperformed the linear techniques(Multiple Linear Regression and Stepwise Regression)in predicting flood regime metrics.The proposed approach well predicted flood event classes with average class hit rates of 66.0%-85.4%and 47.2%-76.0%in calibration and validation periods,respectively,particularly for the slow and late flood events.The predictive capability of the proposed prediction approach for flood regime metrics and classes was considerably stronger than that of hydrological modeling approach.
