Impact of climate change and human activities on the spatiotemporal dynamics of surface water area in Gansu Province, China

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Target Detection on Water Surfaces Using Fusion of Camera and LiDAR Based Information

To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.

A method for detecting the breaking of wind-generated waves in deep water

The breaking of wind-generated waves is an important phenomenon in the ocean, having close relation to many aspects of the ocean, such as air-sea interaction, ocean wave dynamics, oceanic remote sensing and ocean engineering. The first problem encountered in both its theoretical study and practical measurement is how to detect the breaking of waves.

Detection and treatment of water inflow in karst tunnel：A case study in Daba tunnel

In a karst tunnel, fissures or cracks that are filled with weathered materials are a type of potential water outlet as they are easily triggered and converted into groundwater outlets under the influence of high groundwater pressure. A terrible water inrush caused by potential water outlets can seriously hinder the project construction. Potential water outlets and water sources that surrounding the tunnel must be detected before water inflow can be treated. This paper provides a successful case of the detection and treatment of water inflow in a karst tunnel and proposes a potential water outlet detection(PWOD) method in which heavy rainfall(>50 mm/d) is considered a trigger for a potential water outlet. The Daba tunnel located in Hunan province, China, has been constructed in a karst stratum where the rock mass has been weathered intensely by the influence of two faults. Heavy rain triggered some potential water outlets, causing a serious water inrush. The PWOD method was applied in this project for the treatment of water inflow, and six potential water outlets in total were identified through three heavy rains. Meanwhile, a geophysical prospecting technique was also used to detect water sources. The connections between water outlets and water sources were identified with a 3-D graphic that included all of them. According to the distribution of water outlets and water sources, the detection area was divided into three sections and separately treated by curtain grouting.

Bioinspired Adaptive,Elastic,and Conductive Graphene Structured Thin-Films Achieving High-Efficiency Underwater Detection and Vibration Perception

Underwater exploration has been an attractive topic for understanding the very nature of the lakes and even deep oceans.In recent years,extensive efforts have been devoted to developing functional materials and their integrated devices for underwater information capturing.However,there still remains a great challenge for water depth detection and vibration monitoring in a high-efficient,controllable,and scalable way.Inspired by the lateral line of fish that can sensitively sense the water depth and environmental stimuli,an ultrathin,elastic,and adaptive underwater sensor based on Ecoflex matrix with embedded assembled graphene sheets is fabricated.The graphene structured thin film is endowed with favourable adaptive and morphable features,which can conformally adhere to the structural surface and transform to a bulged state driven by water pressure.Owing to the introduction of the graphene-based layer,the integrated sensing system can actively detect the water depth with a wide range of 0.3-1.8 m.Furthermore,similar to the fish,the mechanical stimuli from land(e.g.knocking,stomping)and water(e.g.wind blowing,raining,fishing)can also be sensitively captured in real time.This graphene structured thin-film system is expected to demonstrate significant potentials in underwater monitoring,communication,and risk avoidance.

Fluorescence Quenching of a Novel Eu(Ⅲ) Coordination Compound for the Detection of Trace Amounts of Water： Synthesis, Structure and Photoluminescent Property

A novel luminescent coordination compound Eu（TTA）3（DEDAF）（1, TTA = 1,1,1-trifluoro-3-（2-thenoyl）acetone, DEDAF = 9,9-diethyl-4,5-diazafluoren） has been synthesized and fully characterized by infrared spectrum, elemental analysis, UV-vis spectrum, etc. X-ray single-crystal diffraction analysis reveals that compound 1 shows a mononuclear structure with the europium atom in coordinating to one DAF and three TTA ligands. The mononuclear structure units are assembled into a 3-D polymer by hydrogen bonds and π-π interactions. Photoluminescent property of 1 was investigated in detail at room temperature. Complex 1 emits strong red luminescence. However, it could be quenched even by small amount of water. The fluorescence intensity at 614 nm decreases linearly with the water content increasing（vol% in acetonitrile） in the range of 0.025~0.2% under 278 nm excitation. Thermogravimetric analysis has also been studied, which demonstrates good thermal stability of 1.

Scanning electron microscopy coupled with energydispersive X-ray spectrometry for quick detection of sulfuroxidizing bacteria in environmental water samples

Detection of sulfur-oxidizing bacteria has largely been dependent on targeted gene sequencing technology or traditional cell cultivation, which usually takes from days to months to carry out. This clearly does not meet the requirements of analysis for time-sensitive samples and/or complicated environmental samples. Since energy-dispersive X-ray spectrometry(EDS) can be used to simultaneously detect multiple elements in a sample, including sulfur, with minimal sample treatment, this technology was applied to detect sulfur-oxidizing bacteria using their high sulfur content within the cell. This article describes the application of scanning electron microscopy imaging coupled with EDS mapping for quick detection of sulfur oxidizers in contaminated environmental water samples, with minimal sample handling. Scanning electron microscopy imaging revealed the existence of dense granules within the bacterial cells, while EDS identified large amounts of sulfur within them. EDS mapping localized the sulfur to these granules. Subsequent 16S rRNA gene sequencing showed that the bacteria detected in our samples belonged to the genus Chromatium, which are sulfur oxidizers. Thus, EDS mapping made it possible to identify sulfur oxidizers in environmental samples based on localized sulfur within their cells, within a short time(within 24 h of sampling). This technique has wide ranging applications for detection of sulfur bacteria in environmental water samples.

Application of Optical Visualization Method in Observing Flow Field Around a Cylinder

In this paper, a free-surface synthetic schlieren(FS-SS) method was performed to detect the free surface disturbances. It is a purely optical method that uses refraction of light to reconstruct the height changes of water surface. The theory was developed based on Moisy's research, but has mainly been used in small-scale applications like painting and coating industry. Based on the methods and theories of the literature review, an in-depth investigation was conducted to optimize the FS-SS method and verify its feasibility on a relatively large-scale(e.g., wake region of shallow flow). The experimental setup was simplified which is approachable in most laboratories. Through proper experimental setting and an optimized post-processing routine, the quality of image was highly improved and ensured the accuracy of results. A drop test was performed proving the continuity of FS-SS method in the time domain. Also, a comparison test with flow around a cylinder at two speeds showed the ability of FS-SS method to reconstruct the irregular water surface in relative large-scale flow structures.

Deep learning based water leakage detection for shield tunnel lining

Shield tunnel lining is prone to water leakage,which may further bring about corrosion and structural damage to the walls,potentially leading to dangerous accidents.To avoid tedious and inefficient manual inspection,many projects use artificial intelligence(Al)to detect cracks and water leakage.A novel method for water leakage inspection in shield tunnel lining that utilizes deep learning is introduced in this paper.Our proposal includes a ConvNeXt-S backbone,deconvolutional-feature pyramid network(D-FPN),spatial attention module(SPAM).and a detection head.It can extract representative features of leaking areas to aid inspection processes.To further improve the model's robustness,we innovatively use an inversed low-light enhancement method to convert normally illuminated images to low light ones and introduce them into the training samples.Validation experiments are performed,achieving the average precision(AP)score of 56.8%,which outperforms previous work by a margin of 5.7%.Visualization illustrations also support our method's practical effectiveness.

Research on modeling method of continuous spectrum water quality online detection based on random forest

It's common to use the method of continuous spectroscopy in water quality testing. But there're some problems with it. For example, the scanning results have a large number of nonlinear signals, and the covariance between variables is serious, which can lead to a decrease in the model prediction accuracy. In this paper, the standard solutions of nitrate nitrogen(NO_(3)-N) and nitrite nitrogen(NO_(2)-N) were used as the subject to be tested, and the data of the scanned waves and absorbance were obtained by use of spectral detector. The data were processed by noise reduction first and then the random forest(RF) algorithm was adopted to establish the regression relationship between concentration and absorbance. For comparison, partial least squares(PLS) and support vector machine(SVM) algorithm models were also established. For the same given data, the three reverse models can make the projection of the concentration respectively. The experimental results show that the RF algorithm predicts NO_(2)-N concentrations significantly better than the SVM algorithm and PLS algorithm. This proves that the RF algorithm has good prediction ability in spectral water quality detection because of its high model accuracy and better adaptability, which could be a reference for similar research on continuous spectral water quality online detection.

Water presence detection in a concrete crack using smart aggregates

Liquid migrating into existing concrete cracks is a serious problem for the reliability of concrete structures and can sometimes induce full concrete structural failures.In this paper,the authors present recent research on water presence detection in concrete cracks using piezoceramic-based smart aggregate(SA)transducers.The active sensing approach,in which one piezoceramic transducer is used to generate stress waves and others are used to detect the stress wave responses,is adopted in this research.Cracks formed in concrete structures act as stress reliefs,which attenuate the energy of the signals received by the SAs.In case of a crack being filled with liquid,which changes the wave impedance,the piezoceramic transducers will report higher received energy levels.A wavelet packet-based approach is developed to provide calculated energy values of the received signal.These different values can help detect the liquid presence in a concrete crack.A concrete beam specimen with three embedded SAs was fabricated and tested.Experimental results verified that the SA-based active sensing approach can detect a concrete crack and further detect the liquid presence in the concrete crack.

Rapid and non-destructive detection method for water status and water distribution of rice seeds with different vigor

In this study,newly harvested and aged rice seeds were analyzed to determine their aging process,identify the difference between artificially and naturally aged seeds,and develop a rapid,accurate,and non-destructive detection method for water status and water distribution of rice seed with different vigor.To this end,an artificially accelerated aging test was conducted on the newly harvested rice seeds.Then,low-field nuclear magnetic resonance(LF-NMR)technology was applied to test the new(Shennong No.9816,2018),old(Shennong No.9816,2017),and artificially aged seeds(Shennong No.9816,2018).A standard germination test was conducted for three types of seeds.Finally,the differences of water status and distribution between rice seeds of different vigor were analyzed based on the standard germination test results and wave spectrometry information collected using LF-NMR.The results indicated that new seeds,old seeds,and the artificially accelerated aging rice seeds all exhibited two water phases,and the vigor of rice seeds after the artificial accelerated aging test was lower than that of new seeds.There were significant differences between the frequencies of bound water at the time of the peak and the time at the end of the peak for the three types of seeds.The two times showed an increasing trend for rice seeds with poor vigor,indicating that the ability of the water in the rice seeds having poor vigor to combine with other substances was weakened.There were significant differences between the distributions of free water peak end time for the three types of seeds.All the rice seeds with poor vigor exhibited a decreasing trend at this time,indicating that the freedom of free water inside the rice seed samples with poor vigor was weakened.The total water content of the artificially aged seeds and the aged seeds was higher than that of the new seeds,but the free water content increased from artificially aged seeds to new seeds to aged seeds.This indicates that LF-NMR technology is an effective detection method that can simply compare the differences in seed vitality with respect to water distribution as well as differentiate the seed internal water content of artificially aged and naturally aged seeds.

Wide Absorption Spectrum Measuring Methods by DFB-LDs in Water Vapor Detection System

Two measuring methods of the wide absorption spectrum by distributed feedback laser diodes （DFB-LDs） are presented in detecting the water vapor absorption line. One is the subsection scanning method, and it takes advantage of the wide spectrum tuning range by the temperature modulation and fast spectrum tuning speed by current modulation. Specifically, this method is realized by dividing a target spectral region into several sections which correspond to the specific temperature of DFB-LD, scanning every section by current modulation for hundreds times, and averaging the data to raise the signal to noise ratio （SNR）, then combining all sections to get the whole spectrum. An accuracy of 10ppmv had been obtained in the measurement of water vapor with a 10-cm path length by this method. Another is data fitting method, based on the absorption line-shape function; the absorption line can be described by fitting with partial measured data. The fitting absorption line was fitted well with the measured data, and the square of correlation coefficient （R-square） was no less than 0.99.

Construction of self-sensitized LiErF4:0.5%Tm^3+@LiYF4 upconversion nanoprobe for trace water sensing

LiErF4 was commonly used as a dipolar-coupled antiferromagnet,and was rarely considered as a luminescent material.Herein,we achieved the strong red upconversion emission of LiErF4 simply by an inert shell coating,i.e.,LiErF4@LiYF4.Owing to the unique and intrinsic ladder-like energy levels of Er3+ions,this LiErF4 core–shell nanostructures present red emission(~650 nm)under multi-band excitation in the near-infrared(NIR)region(~808,~980,and^1,530 nm).A brighter and monochromic red emission can be further obtained via doping 0.5%Tm3+into the LiErF4 core,i.e.,LiErF4:0.5%Tm3+@LiYF4.The enriched Er3+ions and strong monochromic red emission natures make LiErF4:0.5%Tm3+@LiYF4 nanocrystals very sensitive for trace water probing in organic solvents with detection limit of 30 ppm in acetonitrile,50 ppm in dimethyl sulfoxide(DMSO),and 58 ppm in N,N-dimethylformamide(DMF)under excitation of 808 nm.Due to their superior chemical and physical stability,these nanoprobes exhibit excellent antijamming ability and recyclability,offering them suitable for real-time and long-term water monitoring.

Robust water hazard detection for autonomous off-road navigation

Existing water hazard detection methods usually fail when the features of water surfaces are greatly changed by the surroundings, e.g., by a change in illumination. This paper proposes a novel algorithm to robustly detect different kinds of water hazards for autonomous navigation. Our algorithm combines traditional machine learning and image segmentation and uses only digital cameras, which are usually affordable, as the visual sensors. Active learning is used for automatically dealing with problems caused by the selection, labeling and classification of large numbers of training sets. Mean-shift based image segmentation is used to refine the final classification. Our experimental results show that our new algorithm can accurately detect not only ‘common’ water hazards, which usually have the features of both high brightness and low texture, but also ‘special’ water hazards that may have lots of ripples or low brightness.

Nontargeted identification of peptides and disinfection byproducts in water

A broad range of organic compounds are known to exist in drinking water sources and serve as precursors of disinfection byproducts（DBPs）.Epidemiological findings of an association of increased risk of bladder cancer with the consumption of chlorinated water has resulted in health concerns about DBPs.Peptides are thought to be an important category of DBP precursors in water.However,little is known about the actual presence of peptides and their DBPs in drinking water because of their high sample complexity and low concentrations.To address this challenge and identify peptides and non-chlorinated/chlorinated peptide DBPs from large sets of organic compounds in water,we developed a novel high throughput analysis strategy,which integrated multiple solid phase extraction（SPE）,high performance liquid chromatography（HPLC）separation,and non-target identification using precursor ion exclusion（PIE）high resolution mass spectrometry（MS）.After MS analysis,structures of candidate compounds,particularly peptides,were obtained by searching against the Human Metabolome Database（HMDB）.Using this strategy,we successfully detected 625 peptides（out of 17,205 putative compounds）and 617 peptides（out of 13,297）respectively in source and finished water samples.The source and finished water samples had 501 peptides and amino acids in common.The remaining 116 peptides and amino acids were unique to the finished water.From a subset of 30 putative compounds for which standards were available,25 were confirmed using HPLC-MS analysis.By analyzing the peptides identified in source and finished water,we successfully confirmed three disinfection reaction pathways that convert peptides into toxic DBPs.

A water-stable metal-organic framework： serving as a chemical sensor of PO43– and a catalyst for CO2 conversion

A new 2D Eu-BTB framework(1) with stratified gridding structure of about 14.6×16.9was synthesized and characterized.Compound 1 displays excellent water stability with the pH 2–12. The luminescent investigations suggest that 1 could represent a chemical sensor of PO43. with high sensitivity and selectivity. Importantly, 1 as a sensor of PO_4^(3-) can be reused at least five times.On the other hand, the catalytic investigations of 1 were carried out, indicating that 1 could be demonstrated as a recyclable catalyst for CO_2 conversion with epoxides.

HIRFL cooling water-monitoring system design and construct

Background HIRFL is a heavy ion accelerator built by the Institute of Modern Physics,Chinese Academy of Sciences,which constitutes a total length of over 900 m by the SFC,SSC,CSRm,CSRe and so on.It bears a lot of research task of the country,so to ensure its safe operation is very important.Purpose Cool-water system is a key part in HIRFL,and the parameters of the cool-water system need to be monitored before an accident occurs.Methods This article describes three aspects of the system,from the water leakage detection,pressure monitoring,to the water-level monitoring.A complete monitor system was designed and constructed,including the hardware structure;the data transfer mode,as well as specific control program.C++,FLASH and SCADA are used in the monitoring system.Results Fault alarm was performed timely and accurately by the monitoring system,and many accidents were avoided.Conclusion Water system monitoring is an important part of the accelerator control system.It will also play a major role in the construction of large-scale scientific device named HIAF in the further.