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
Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base ...Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.展开更多
Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and ...Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.展开更多
While biochar amendment enhances plant productivity and water-use efficiency(WUE),particularly under waterlimited conditions,the specific mechanisms driving these benefits remain unclear.Thus,the present study aims to...While biochar amendment enhances plant productivity and water-use efficiency(WUE),particularly under waterlimited conditions,the specific mechanisms driving these benefits remain unclear.Thus,the present study aims to elucidate the synergistic effects of biochar and reduced irrigation on maize(Zea mays L.)plants,focusing on xylem composition,root-to-shoot signaling,stomatal behavior,and WUE.Maize plants were cultivated in splitroot pots filled with clay loam soil,amended by either wheat-straw biochar(WSB)or softwood biochar(SWB)at 2%(w/w).Plants received full irrigation(FI),deficit irrigation(DI),or partial root-zone drying rrigation(PRD)from the 4-leaf to the grain-filling stage.Our results revealed that the WSB amendment significantly enhanced plant water status,biomass accumulation,and WUE under reduced irrigation,particularly when combined with PRD.Although reduced irrigation inhibited photosynthesis,it enhanced WUE by modulating stomatal morphology and conductance.Biochar amendment combined with reduced rrigation significantly increased xylem K^(+),Ca^(2+),Mg^(2+),NO_(3)^(-),Cl^(-),PO_(4)^(3-),and SO_(4)^(2-)-but decreased Na+,which in turn lowered xylem pH.Moreover,biochar amendment and especially WSB amendment further increased abscisic acid(ABA)contents in both leaf and xylem sap under reduced irrigation conditions due to changes in xylem ionic constituents and pH.The synergistic interactions between xylem components and ABA led to refined adjustments in stomatal size and density,thereby affecting stomatal conductance and ultimately improving the WUE of maize plants at different scales.The combined application of WSB and PRD can,therefore,emerge as a promising approach for improving the overall plant performance of maize plants with increased stomatal adaptations and WUE,especially under water-limited conditions.展开更多
This study aims to evaluate the effectiveness of machine learning techniques for predicting groundwater fluctuations in arid and semi-arid regions using data from the Gravity Recovery and Climate Experiment satellite ...This study aims to evaluate the effectiveness of machine learning techniques for predicting groundwater fluctuations in arid and semi-arid regions using data from the Gravity Recovery and Climate Experiment satellite mission.The primary objective is to develop accurate predictive models for groundwa-ter level changes by leveraging the unique capabilities of GRACE satellite data in conjunction with advanced machine learning algorithms.Three widely-used machine learning models,namely DT,SVM and RF,were employed to analyze and model the relationship between GRACE satellite data and groundwater fluctuations in South Khorasan Province,Iran.The study utilized 151 months of GRACE data spanning from 2002 to 2017,which were correlated with piezometer well data available in the study area.The JPL 2 model was selected based on its strong correlation(R=0.9368)with the observed data.The machine learn-ing models were trained and validated using a 70/30 split of the data,and their performance was evaluated 2 using various statistical metrics,including RMSE,R and NSE.The results demonstrated the suitability of machine learning approaches for modeling groundwater fluctuations using GRACE satellite data.The DT 2 model exhibited the best performance during the calibration stage,with an R value of 0.95,RMSE of 20.655,and NSE of 0.96.The SVM and RF models achieved R values of 0.79 and 0.65,and NSE values of 0.86 and 0.71,respectively.For the prediction stage,the DT model maintained its high efficiency,with an 2 RMSE of 1.48,R of 0.87,and NSE of 0.90,indicating its robustness in predicting future groundwater fluc-tuations using GRACE data.The study highlights the potential of machine learning techniques,particularly Decision Trees,in conjunction with GRACE satellite data,for accurate prediction and monitoring of groundwater fluctuations in arid and semi-arid regions.The findings demonstrate the effectiveness of the DT model in capturing the complex relationships between GRACE data and groundwater dynamics,provid-ing reliable predictions and insights for sustainable groundwater management strategies.展开更多
Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models pla...Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.展开更多
Desert lakes are an important link in the water cycle and an important reservoir of water resources in arid and semi-arid areas,playing an important role in maintaining the stability of the regional natural environmen...Desert lakes are an important link in the water cycle and an important reservoir of water resources in arid and semi-arid areas,playing an important role in maintaining the stability of the regional natural environment.However,studies on the hydrochemical evolution and transformation relationships between desert lake groups and potential water sources are limited.Taking the Qixing Lake,the only lake group within the Hobq Desert in China,as the area of interest,this study collected samples of precipitation water,Yellow River water,lake water,and groundwater at different burial depths in the Qixing Lake region from July 2023 to October 2024.The hydrochemistry of different water bodies was analyzed using a combination of Piper diagrams,Gibbs diagrams,ratio of ions,and MixSIAR mixing models to reveal the transformational relationships of lake water with precipitation,groundwater,and Yellow River water.Results showed that both groundwater and surface water in the study area are weakly-to-strongly alkaline,with HCO_(3)–as the dominant anion and Na^(+),Ca^(2+),and K^(+) as the main cations.The hydrochemical type of groundwater and some lakes was dominated by HCO3–-Na+,whereas that of other lakes was dominated by Cl–-Na^(+)and HCO3–-Mg^(2+).The hydrochemistry of groundwater and Yellow River water in the Qixing Lake region was controlled mainly by a combination of evaporite saline and silicate rock mineral dissolution.The local meteoric water line(LMWL)of the study area proved that regional water bodies are strongly affected by evaporative fractionation.The MixSIAR model revealed that shallow groundwater is the main recharge source of the lake group in the Qixing Lake region,accounting for 59.0%–64.2%of the total.The findings can provide references for the identification of water sources in desert lakes and the development and utilization of water resources in desert lake regions.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
Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 3...Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.展开更多
Cotton,as one of important economic crops,is widely planted in the saline-alkaline soil of southern Xinjiang,China.Moreover,in order to control the saline-alkaline content for seed germination and seedlings survive of...Cotton,as one of important economic crops,is widely planted in the saline-alkaline soil of southern Xinjiang,China.Moreover,in order to control the saline-alkaline content for seed germination and seedlings survive of cotton,farmers always adopt salt leaching during winter and spring seasons.However,excessive amount of salt leaching might result in the waste of water resources and unsuitable irrigation seasons might further increase soil salinization.In this study,a field experiment was conducted in the saline-alkaline soil in 2020 and 2021 to determine the effects of leaching amount and period on water-salinity dynamics and cotton yield.Five leaching amounts(0.0(W0),75.0(W1),150.0(W2),225.0(W3),and 300.0(W4)mm)and three leaching periods(seedling stage(P1),seedling and squaring stages(P2),and seedling,squaring,flowering,and boll setting stages(P3))were used.In addition,a control treatment(CK)with a leaching amount of 300.0 mm in spring was performed.The soil water-salt dynamics,cotton growth,seed cotton yield,water productivity(WP),and irrigation water productivity(WPI)were analyzed.Results showed that leaching significantly decreased soil electrical conductivity(EC),and W3P2 treatment reduced EC by 11.79%in the 0-100 cm soil depth compared with CK.Plant height,stem diameter,leaf area index,and yield under W3 and W4 treatments were greater than those under W1 and W2 treatments.Compared with W3P1 and W3P3 treatments,seed cotton yield under W3P2 treatment significantly enhanced and reached 6621 kg/hm^(2)in 2020 and 5340 kg/hm^(2)in 2021.Meanwhile,WP and WPI under W3P2 treatment were significantly higher than those under other leaching treatments.In conclusion,the treatment of 225.0 mm leaching amount and seedling and squaring stages-based leaching period was beneficial for the salt control,efficient water utilization,and yield improvement of cotton in southern Xinjiang,China.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 operation of cascade reservoirs in a watershed profoundly exerts river watersediment dynamics and topography evolution,and the terminal reservoir is the focus area for river and waterway management.This paper reve...The operation of cascade reservoirs in a watershed profoundly exerts river watersediment dynamics and topography evolution,and the terminal reservoir is the focus area for river and waterway management.This paper reveals the process and underlying factors of topography evolution and water level adjustment in the lower Hanjiang River under the action of cascade reservoirs.This study focused on the 263 km river channel downstream of the Xinglong Hydropower Conservancy Project on the Hanjiang River.Using measured flow,sediment,and topography data from 1977 to 2023,we analyzed the changing characteristics of riverbed scouring and deposition intensity,thalweg,and cross-sections.Additionally,we evaluated the response relationship between riverbed scouring and deposition intensity and factors such as sediment transport,runoff,and human activities.From 1977 to 2023,the low-water channel in the Xinglong-Estuary reaches showed a scouring and cutting tendency,and the riverbed slop initially decreased and then increased.The main cause of the riverbed scouring along the Xinglong-Estuary reaches was the reduced sediment load in the watershed,with waterway engineering having a slightly larger influence than runoff in the Xinglong-Xiantao reaches;by contrast,runoff exerted a more significant effect than both waterway engineering and the Yangtze River water level decline in the Xiantao-Estuary reaches.During the autumn flood season from 1983 to 2023,the water level differences between the Hanjiang and Yangtze Rivers at the same flow rate showed an increasing trend,leading to an increase in water surface slope,which intensified scouring forces and riverbed scouring.This study improves our understanding of the impacts of dam construction on river topographical evolution,water level changes,and deep‐water waterway resources.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
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
In recent years,microplastics(MPs)in freshwater lake have been receiving increasing attention;however,the microbial communities on the surface of MPs have not been well studied.To investigate the potential risk posed ...In recent years,microplastics(MPs)in freshwater lake have been receiving increasing attention;however,the microbial communities on the surface of MPs have not been well studied.To investigate the potential risk posed by MPs to the lake ecosystem and its surface microbial community structure,MPs samples were collected in September 2023 in the freshwater Dongting Lake,Hunan,China,at five sites,and the differences in bacterial species community composition and structure between MPs and water samples were analyzed.Results show that MPs(13.71±3.32 items/L)in the samples were mostly black in color,fiber in shape,and PES in composition,and those<0.5 mm in size are dominant.The bacterial composition in water was different from that on MPs.At phylum level,Proteobacteria,Actinobacteria,Cyanobacteria,and Bacteroidetes were dominated in relative abundance in both water and MPs.Proteobacteria was more abundant in MPs than in water.The relative abundance of Bacteroidota and Actinobacteriota was significantly lower in MPs than in water.At genus level,Pantoea and Pseudomonas were potentially pathogenic genera in MPs surfaces.The presence of Cyanobacteria and pathogenic bacteria is undoubtedly a potential risk to the deterioration of the water quality.This study revealed the difference in the distribution of bacterial community in water and MPs in Dongting Lake and provided new perspectives to further understanding of MPs pollution in freshwater lakes.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
In recent years, the rational utilization of saline water resources for agricultural irrigation has emerged as an effective strategy to alleviate water scarcity. To safely and efficiently exploit saline water resource...In recent years, the rational utilization of saline water resources for agricultural irrigation has emerged as an effective strategy to alleviate water scarcity. To safely and efficiently exploit saline water resources over the long term, it is crucial to understand the effects of salinity on crops and develop optimal water-salinity irrigation strategies for processing tomatoes. A two-year field experiment was conducted in 2018 and 2019 to explore the impact of water salinity levels(S1: 1 g L^(–1), S2: 3 g L^(–1), and S3: 5 g L^(–1)) and irrigation amounts(W1: 305 mm, W2: 485 mm, and W3: 611 mm) on the soil volumetric water content and soil salinity, as well as processing tomato growth, yield, and water use efficiency. The results showed that irrigation with low to moderately saline water(<3 g L^(–1)) enhanced plant wateruptake and utilization capacity, with the soil water content(SWC) reduced by 6.5–7.62% and 10.52–13.23% for the S1 and S2 levels, respectively, compared to the S3 level in 2018. Under S1 condition, the soil salt content(SSC) accumulation rate gradually declined with an increase in the irrigation amount. For example, W3 decreased by 85.00 and 77.94% compared with W1 and W2 in 2018, and by 82.60 and 73.68% in 2019, respectively. Leaching effects were observed at the W3 level under S1, which gradually diminished with increasing water salinity and duration. In 2019, the salt contents of soil under each of the treatments increased by 10.81–89.72% compared with the contents in 2018. The yield of processing tomatoes increased with an increasing irrigation amount and peaked in the S1W3 treatment for the two years, reaching 125,304.85 kg ha^(–1)in 2018 and 128,329.71 kg ha^(–1)in 2019. Notably, in the first year, the S2W3 treatment achieved relatively high yields, exhibiting only a 2.85% reduction compared to the S1W3 treatment. However, the yield of the S2W3 treatment declined significantly in two years, and it was 15.88% less than that of the S1W3 treatment. Structural equation modeling(SEM) revealed that soil environmental factors(SWC and SSC) directly influence yield while also exerting indirect impacts on the growth indicators of processing tomatoes(plant height, stem diameter, and leaf area index). The TOPSIS method identified S1W3, S1W2, and S2W2 as the top three treatments. The single-factor marginal effect function also revealed that irrigation water salinity contributed to the composite evaluation scores(CES) when it was below 0.96 g L^(–1). Using brackish water with a salinity of 3 g L^(–1)at an irrigation amount of 485 mm over one year ensured that processing tomatoes maintained high yields with a relatively high CES(0.709). However, using brackish water for more than one year proved unfeasible.展开更多
As an energy and carbon saving process for nitrogen removal from wastewater,the partial nitrification and denitrification process(PN/D)has been extensively researched.However,achieving stable PNinmunicipalwastewater h...As an energy and carbon saving process for nitrogen removal from wastewater,the partial nitrification and denitrification process(PN/D)has been extensively researched.However,achieving stable PNinmunicipalwastewater has always been challenging.In this study,a gel immobilized PN/D nitrogen removal process(GI-PN/D)was established.A 94 days pilot-scale experiment was conducted using real municipal wastewater with an ammonia concentration of 43.5±5.3mg N/L at a temperature range of 11.3–28.7◦C.The nitrogen removal performance and associated pathways,shifts in the microbial community as well as sludge yield were investigated.The results were as follows:the effluent TN and COD were 0.6±0.4mg/L and 31.1±3.8 mg/L respectively,and the NAR exceeding 95%.GI-PN/D achieved deep nitrogen removal ofmunicipalwastewater through stable PN without taking any othermeasures.The primary pathways for nitrogen removal were identified as denitrification,simultaneous nitrification-denitrification,and aerobic denitrification.High-throughput sequencing analysis revealed that the immobilized fillers facilitated the autonomous enrichment of functional bacteria in each reactor,effectively promoting the dominance and stability of the microbial communities.In addition,GI-PN/D had the characteristic of low sludge yield,with an average sludge yield of 0.029 kg SS/kg COD.This study provides an effective technical for nitrogen removal from municipal wastewater through PN.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
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.
基金Under the National Key R&D Program Key Project(No.2021YFC3201201)National Natural Science Foundation of China(No.52360032)+2 种基金Basic Scientific Research Business Fee Project of Colleges And Universities Directly Under the Inner Mongolia Autonomous Region(No.JBYYWF2022001)Development Plan of Innovation Team of Colleges And Universities in Inner Mongolia Autonomous Region(No.NMGIRT2313)the Innovation Team of‘Grassland Talents’。
文摘Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.
基金funded by the Postdoctoral Research Startup Foundation of University of Jinan(Grant No.100389917).
文摘Climate change and anthropogenic activities have driven significant terrestrial water storage changes(TWSC)in the Three Rivers Source Region(TRSR),exerting profound impacts on freshwater availability across China and broader Asia.However,long-term TWSC characterization remains challenging due to limited observational data in this alpine region.Here,we integrate GRACE observations(2002-2020),ERA5-Land reanalysis,and GLDAS data to reconstruct TWSC using two methods:(1)the water balance method(PER)and(2)the component summation method(SS),applied to three input datasets(ERA5-Land,GLDAS,and their average,GLER).Comparative analysis reveals that the SS method applied to GL-ER yields the highest consistency with GRACE-derived TWSC.Using this optimal approach,we extend the analysis to 1951~2020,uncovering spatiotemporal TWSC patterns.Although annual TWSC trends appear negligible due to strong seasonality,we introduce the intra-year TWSC fluctuation(TWSCF)index to quantify cumulative variability.A significant(p<0.05)transition occurred in 1980,with TWSCF shifting from a declining trend(-0.39 mm/yr)to an increasing trend(0.56 mm/yr),primarily driven by soil moisture changes.However,Hurst exponent analysis suggests this upward trend may not persist.Drought and vegetation assessments indicate concurrent wetting and greening in the TRSR.TWSC correlates strongly with meteorological drought,acting as a reliable drought indicator while its linkage with vegetation dynamics suggests a potential contribution to greening.Our findings provide a robust framework for understanding long-term TWSC evolution and its hydrological-ecological interactions under climate change.
基金supported by the Natural Science Basic Research Program of Shaanxi Province,China(2024JCYBQN-0491)Heng Wan would like to thank the Chinese Scholarship Council(CsC)(202206300064)。
文摘While biochar amendment enhances plant productivity and water-use efficiency(WUE),particularly under waterlimited conditions,the specific mechanisms driving these benefits remain unclear.Thus,the present study aims to elucidate the synergistic effects of biochar and reduced irrigation on maize(Zea mays L.)plants,focusing on xylem composition,root-to-shoot signaling,stomatal behavior,and WUE.Maize plants were cultivated in splitroot pots filled with clay loam soil,amended by either wheat-straw biochar(WSB)or softwood biochar(SWB)at 2%(w/w).Plants received full irrigation(FI),deficit irrigation(DI),or partial root-zone drying rrigation(PRD)from the 4-leaf to the grain-filling stage.Our results revealed that the WSB amendment significantly enhanced plant water status,biomass accumulation,and WUE under reduced irrigation,particularly when combined with PRD.Although reduced irrigation inhibited photosynthesis,it enhanced WUE by modulating stomatal morphology and conductance.Biochar amendment combined with reduced rrigation significantly increased xylem K^(+),Ca^(2+),Mg^(2+),NO_(3)^(-),Cl^(-),PO_(4)^(3-),and SO_(4)^(2-)-but decreased Na+,which in turn lowered xylem pH.Moreover,biochar amendment and especially WSB amendment further increased abscisic acid(ABA)contents in both leaf and xylem sap under reduced irrigation conditions due to changes in xylem ionic constituents and pH.The synergistic interactions between xylem components and ABA led to refined adjustments in stomatal size and density,thereby affecting stomatal conductance and ultimately improving the WUE of maize plants at different scales.The combined application of WSB and PRD can,therefore,emerge as a promising approach for improving the overall plant performance of maize plants with increased stomatal adaptations and WUE,especially under water-limited conditions.
文摘This study aims to evaluate the effectiveness of machine learning techniques for predicting groundwater fluctuations in arid and semi-arid regions using data from the Gravity Recovery and Climate Experiment satellite mission.The primary objective is to develop accurate predictive models for groundwa-ter level changes by leveraging the unique capabilities of GRACE satellite data in conjunction with advanced machine learning algorithms.Three widely-used machine learning models,namely DT,SVM and RF,were employed to analyze and model the relationship between GRACE satellite data and groundwater fluctuations in South Khorasan Province,Iran.The study utilized 151 months of GRACE data spanning from 2002 to 2017,which were correlated with piezometer well data available in the study area.The JPL 2 model was selected based on its strong correlation(R=0.9368)with the observed data.The machine learn-ing models were trained and validated using a 70/30 split of the data,and their performance was evaluated 2 using various statistical metrics,including RMSE,R and NSE.The results demonstrated the suitability of machine learning approaches for modeling groundwater fluctuations using GRACE satellite data.The DT 2 model exhibited the best performance during the calibration stage,with an R value of 0.95,RMSE of 20.655,and NSE of 0.96.The SVM and RF models achieved R values of 0.79 and 0.65,and NSE values of 0.86 and 0.71,respectively.For the prediction stage,the DT model maintained its high efficiency,with an 2 RMSE of 1.48,R of 0.87,and NSE of 0.90,indicating its robustness in predicting future groundwater fluc-tuations using GRACE data.The study highlights the potential of machine learning techniques,particularly Decision Trees,in conjunction with GRACE satellite data,for accurate prediction and monitoring of groundwater fluctuations in arid and semi-arid regions.The findings demonstrate the effectiveness of the DT model in capturing the complex relationships between GRACE data and groundwater dynamics,provid-ing reliable predictions and insights for sustainable groundwater management strategies.
文摘Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.
基金supported by the Inner Mongolia Autonomous Region"Unveiling the List of Commanders"Project(2024JBGS0019)the Inner Mongolia Autonomous Region Graduate Student Research Innovation Project(KC2024036B)+1 种基金the Innovative Team on Desertification Control and Sandy Area Resource Conservation and Utilization(BR241301)the Desert Sand Ecological Protection and Management Technology Innovation Team(NMGIRT2408).
文摘Desert lakes are an important link in the water cycle and an important reservoir of water resources in arid and semi-arid areas,playing an important role in maintaining the stability of the regional natural environment.However,studies on the hydrochemical evolution and transformation relationships between desert lake groups and potential water sources are limited.Taking the Qixing Lake,the only lake group within the Hobq Desert in China,as the area of interest,this study collected samples of precipitation water,Yellow River water,lake water,and groundwater at different burial depths in the Qixing Lake region from July 2023 to October 2024.The hydrochemistry of different water bodies was analyzed using a combination of Piper diagrams,Gibbs diagrams,ratio of ions,and MixSIAR mixing models to reveal the transformational relationships of lake water with precipitation,groundwater,and Yellow River water.Results showed that both groundwater and surface water in the study area are weakly-to-strongly alkaline,with HCO_(3)–as the dominant anion and Na^(+),Ca^(2+),and K^(+) as the main cations.The hydrochemical type of groundwater and some lakes was dominated by HCO3–-Na+,whereas that of other lakes was dominated by Cl–-Na^(+)and HCO3–-Mg^(2+).The hydrochemistry of groundwater and Yellow River water in the Qixing Lake region was controlled mainly by a combination of evaporite saline and silicate rock mineral dissolution.The local meteoric water line(LMWL)of the study area proved that regional water bodies are strongly affected by evaporative fractionation.The MixSIAR model revealed that shallow groundwater is the main recharge source of the lake group in the Qixing Lake region,accounting for 59.0%–64.2%of the total.The findings can provide references for the identification of water sources in desert lakes and the development and utilization of water resources in desert lake regions.
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.
文摘Accurate estimation of evapotranspiration(ET)is crucial for efficient water resource management,particularly in the face of climate change and increasing water scarcity.This study performs a bibliometric analysis of 352 articles and a systematic review of 35 peer-reviewed papers,selected according to PRISMA guidelines,to evaluate the performance of Hybrid Artificial Neural Networks(HANNs)in ET estimation.The findings demonstrate that HANNs,particularly those combining Multilayer Perceptrons(MLPs),Recurrent Neural Networks(RNNs),and Convolutional Neural Networks(CNNs),are highly effective in capturing the complex nonlinear relationships and tem-poral dependencies characteristic of hydrological processes.These hybrid models,often integrated with optimization algorithms and fuzzy logic frameworks,significantly improve the predictive accuracy and generalization capabilities of ET estimation.The growing adoption of advanced evaluation metrics,such as Kling-Gupta Efficiency(KGE)and Taylor Diagrams,highlights the increasing demand for more robust performance assessments beyond traditional methods.Despite the promising results,challenges remain,particularly regarding model interpretability,computational efficiency,and data scarcity.Future research should prioritize the integration of interpretability techniques,such as attention mechanisms,Local Interpretable Model-Agnostic Explanations(LIME),and feature importance analysis,to enhance model transparency and foster stakeholder trust.Additionally,improving HANN models’scalability and computational efficiency is crucial,especially for large-scale,real-world applications.Approaches such as transfer learning,parallel processing,and hyperparameter optimization will be essential in overcoming these challenges.This study underscores the transformative potential of HANN models for precise ET estimation,particularly in water-scarce and climate-vulnerable regions.By integrating CNNs for automatic feature extraction and leveraging hybrid architectures,HANNs offer considerable advantages for optimizing water management,particularly agriculture.Addressing challenges related to interpretability and scalability will be vital to ensuring the widespread deployment and operational success of HANNs in global water resource management.
基金supported by the National Key Research and Development Program of China(2021YFD1900805,2022YFD1900401)the Science and Technology Project,Xinjiang Production and Construction Corps,China(2021AB009,2024AB030).
文摘Cotton,as one of important economic crops,is widely planted in the saline-alkaline soil of southern Xinjiang,China.Moreover,in order to control the saline-alkaline content for seed germination and seedlings survive of cotton,farmers always adopt salt leaching during winter and spring seasons.However,excessive amount of salt leaching might result in the waste of water resources and unsuitable irrigation seasons might further increase soil salinization.In this study,a field experiment was conducted in the saline-alkaline soil in 2020 and 2021 to determine the effects of leaching amount and period on water-salinity dynamics and cotton yield.Five leaching amounts(0.0(W0),75.0(W1),150.0(W2),225.0(W3),and 300.0(W4)mm)and three leaching periods(seedling stage(P1),seedling and squaring stages(P2),and seedling,squaring,flowering,and boll setting stages(P3))were used.In addition,a control treatment(CK)with a leaching amount of 300.0 mm in spring was performed.The soil water-salt dynamics,cotton growth,seed cotton yield,water productivity(WP),and irrigation water productivity(WPI)were analyzed.Results showed that leaching significantly decreased soil electrical conductivity(EC),and W3P2 treatment reduced EC by 11.79%in the 0-100 cm soil depth compared with CK.Plant height,stem diameter,leaf area index,and yield under W3 and W4 treatments were greater than those under W1 and W2 treatments.Compared with W3P1 and W3P3 treatments,seed cotton yield under W3P2 treatment significantly enhanced and reached 6621 kg/hm^(2)in 2020 and 5340 kg/hm^(2)in 2021.Meanwhile,WP and WPI under W3P2 treatment were significantly higher than those under other leaching treatments.In conclusion,the treatment of 225.0 mm leaching amount and seedling and squaring stages-based leaching period was beneficial for the salt control,efficient water utilization,and yield improvement of cotton in southern Xinjiang,China.
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 Natural Science Foundation of China,Grant/Award Numbers:52279066,U2340217Fundamental Research Funds for Central Welfare Research Institutes,Grant/Award Number:TKS20240402National Key Research and Development Program of China,Grant/Award Number:2023YFC3209500。
文摘The operation of cascade reservoirs in a watershed profoundly exerts river watersediment dynamics and topography evolution,and the terminal reservoir is the focus area for river and waterway management.This paper reveals the process and underlying factors of topography evolution and water level adjustment in the lower Hanjiang River under the action of cascade reservoirs.This study focused on the 263 km river channel downstream of the Xinglong Hydropower Conservancy Project on the Hanjiang River.Using measured flow,sediment,and topography data from 1977 to 2023,we analyzed the changing characteristics of riverbed scouring and deposition intensity,thalweg,and cross-sections.Additionally,we evaluated the response relationship between riverbed scouring and deposition intensity and factors such as sediment transport,runoff,and human activities.From 1977 to 2023,the low-water channel in the Xinglong-Estuary reaches showed a scouring and cutting tendency,and the riverbed slop initially decreased and then increased.The main cause of the riverbed scouring along the Xinglong-Estuary reaches was the reduced sediment load in the watershed,with waterway engineering having a slightly larger influence than runoff in the Xinglong-Xiantao reaches;by contrast,runoff exerted a more significant effect than both waterway engineering and the Yangtze River water level decline in the Xiantao-Estuary reaches.During the autumn flood season from 1983 to 2023,the water level differences between the Hanjiang and Yangtze Rivers at the same flow rate showed an increasing trend,leading to an increase in water surface slope,which intensified scouring forces and riverbed scouring.This study improves our understanding of the impacts of dam construction on river topographical evolution,water level changes,and deep‐water waterway resources.
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Supported by the National Natural Science Foundation of China(Nos.52209048,52109083)the Hunan Provincial Natural Science Foundation(Nos.2024JJ5207,2021JJ40100)+1 种基金the Special Fund for Building Chenzhou National Sustainable Development Agenda Innovation Demonstration Zone in Hunan Province(No.2022sfq51)the China National University Student Innovation&Entrepreneurship Development Program(No.S202310536023)。
文摘In recent years,microplastics(MPs)in freshwater lake have been receiving increasing attention;however,the microbial communities on the surface of MPs have not been well studied.To investigate the potential risk posed by MPs to the lake ecosystem and its surface microbial community structure,MPs samples were collected in September 2023 in the freshwater Dongting Lake,Hunan,China,at five sites,and the differences in bacterial species community composition and structure between MPs and water samples were analyzed.Results show that MPs(13.71±3.32 items/L)in the samples were mostly black in color,fiber in shape,and PES in composition,and those<0.5 mm in size are dominant.The bacterial composition in water was different from that on MPs.At phylum level,Proteobacteria,Actinobacteria,Cyanobacteria,and Bacteroidetes were dominated in relative abundance in both water and MPs.Proteobacteria was more abundant in MPs than in water.The relative abundance of Bacteroidota and Actinobacteriota was significantly lower in MPs than in water.At genus level,Pantoea and Pseudomonas were potentially pathogenic genera in MPs surfaces.The presence of Cyanobacteria and pathogenic bacteria is undoubtedly a potential risk to the deterioration of the water quality.This study revealed the difference in the distribution of bacterial community in water and MPs in Dongting Lake and provided new perspectives to further understanding of MPs pollution in freshwater lakes.
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funded by the National Key R&D Program of China (2022YFD1900405)。
文摘In recent years, the rational utilization of saline water resources for agricultural irrigation has emerged as an effective strategy to alleviate water scarcity. To safely and efficiently exploit saline water resources over the long term, it is crucial to understand the effects of salinity on crops and develop optimal water-salinity irrigation strategies for processing tomatoes. A two-year field experiment was conducted in 2018 and 2019 to explore the impact of water salinity levels(S1: 1 g L^(–1), S2: 3 g L^(–1), and S3: 5 g L^(–1)) and irrigation amounts(W1: 305 mm, W2: 485 mm, and W3: 611 mm) on the soil volumetric water content and soil salinity, as well as processing tomato growth, yield, and water use efficiency. The results showed that irrigation with low to moderately saline water(<3 g L^(–1)) enhanced plant wateruptake and utilization capacity, with the soil water content(SWC) reduced by 6.5–7.62% and 10.52–13.23% for the S1 and S2 levels, respectively, compared to the S3 level in 2018. Under S1 condition, the soil salt content(SSC) accumulation rate gradually declined with an increase in the irrigation amount. For example, W3 decreased by 85.00 and 77.94% compared with W1 and W2 in 2018, and by 82.60 and 73.68% in 2019, respectively. Leaching effects were observed at the W3 level under S1, which gradually diminished with increasing water salinity and duration. In 2019, the salt contents of soil under each of the treatments increased by 10.81–89.72% compared with the contents in 2018. The yield of processing tomatoes increased with an increasing irrigation amount and peaked in the S1W3 treatment for the two years, reaching 125,304.85 kg ha^(–1)in 2018 and 128,329.71 kg ha^(–1)in 2019. Notably, in the first year, the S2W3 treatment achieved relatively high yields, exhibiting only a 2.85% reduction compared to the S1W3 treatment. However, the yield of the S2W3 treatment declined significantly in two years, and it was 15.88% less than that of the S1W3 treatment. Structural equation modeling(SEM) revealed that soil environmental factors(SWC and SSC) directly influence yield while also exerting indirect impacts on the growth indicators of processing tomatoes(plant height, stem diameter, and leaf area index). The TOPSIS method identified S1W3, S1W2, and S2W2 as the top three treatments. The single-factor marginal effect function also revealed that irrigation water salinity contributed to the composite evaluation scores(CES) when it was below 0.96 g L^(–1). Using brackish water with a salinity of 3 g L^(–1)at an irrigation amount of 485 mm over one year ensured that processing tomatoes maintained high yields with a relatively high CES(0.709). However, using brackish water for more than one year proved unfeasible.
基金supported by Beijing Municipal Commission of Education(No.Z161100004516015)the Open Project Program of Hebei Center for Ecological and Environmental Geology Research(No.JSYF-202304).
文摘As an energy and carbon saving process for nitrogen removal from wastewater,the partial nitrification and denitrification process(PN/D)has been extensively researched.However,achieving stable PNinmunicipalwastewater has always been challenging.In this study,a gel immobilized PN/D nitrogen removal process(GI-PN/D)was established.A 94 days pilot-scale experiment was conducted using real municipal wastewater with an ammonia concentration of 43.5±5.3mg N/L at a temperature range of 11.3–28.7◦C.The nitrogen removal performance and associated pathways,shifts in the microbial community as well as sludge yield were investigated.The results were as follows:the effluent TN and COD were 0.6±0.4mg/L and 31.1±3.8 mg/L respectively,and the NAR exceeding 95%.GI-PN/D achieved deep nitrogen removal ofmunicipalwastewater through stable PN without taking any othermeasures.The primary pathways for nitrogen removal were identified as denitrification,simultaneous nitrification-denitrification,and aerobic denitrification.High-throughput sequencing analysis revealed that the immobilized fillers facilitated the autonomous enrichment of functional bacteria in each reactor,effectively promoting the dominance and stability of the microbial communities.In addition,GI-PN/D had the characteristic of low sludge yield,with an average sludge yield of 0.029 kg SS/kg COD.This study provides an effective technical for nitrogen removal from municipal wastewater through PN.
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.
