Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

Introduction to the airborne marine surveillance platform and its application to water quality monitoring in China

China Marine Surveillance Force was equipped with modern aerial equipments for marine lawexecute with the advantage of functioning agilely at a large scale of surveillance coverage, providing powerful all-round safeguard, which is of benefit to the harmonious and sustainable development of coastal economy. Onboard the planes, three kinds of remote sensing sensors have been installed, including a marine airborne multi-spectrum scanner （MAMS）, an optical-electronic platform, and an airborne hyper-spectral system AISA＋. The specifications of remote sensing platforms were introduced briefly first, then examples of water quality monitoring by airborne remote sensing were presented, including the monitoring in coastal suspended material, oil-spill and abnormal warm water, etc.

Design and Analysis of a Water Quality Monitoring Data Service Platform

Water is one of the basic resources for human survival.Water pollution monitoring and protection have been becoming a major problem for many countries all over the world.Most traditional water quality monitoring systems,however,generally focus only on water quality data collection,ignoring data analysis and data mining.In addition,some dirty data and data loss may occur due to power failures or transmission failures,further affecting data analysis and its application.In order to meet these needs,by using Internet of things,cloud computing,and big data technologies,we designed and implemented a water quality monitoring data intelligent service platform in C#and PHP language.The platform includes monitoring point addition,monitoring point map labeling,monitoring data uploading,monitoring data processing,early warning of exceeding the standard of monitoring indicators,and other functions modules.Using this platform,we can realize the automatic collection of water quality monitoring data,data cleaning,data analysis,intelligent early warning and early warning information push,and other functions.For better security and convenience,we deployed the system in the Tencent Cloud and tested it.The testing results showed that the data analysis platform could run well and will provide decision support for water resource protection.

Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

Water resources are one of the basic resources for human survival,and water protection has been becoming a major problem for countries around the world.However,most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators,and ignored the analysis of water quality monitoring data and its value.In this paper,by adopting Laravel and AdminTE framework,we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts.Through the deployed water quality sensor,the collected water quality indicator data is transmitted to the big data processing platform that deployed on Tencent Cloud in real time through the 4G network.The collected monitoring data is analyzed,and the processing result is visualized by Baidu ECharts.The test results showed that the designed system could run well and will provide decision support for water resource protection.

A Study on Water Quality Monitoring in Urban Watercourse of Xinli River in Binzhou City

This paper aims to explore the pH,COD,ammonia nitrogen,total nitrogen,total phosphorus and other indices regarding Xinli River water in Binzhou City.The results show that the pH of the water quality index is between 7.3 and 7.8,slightly alkaline;the COD content of Xinli River is about 140-163 mg/L,and the COD pollution is serious in some water sections;the ammonia nitrogen content of Xinli River is 0.2-2.17 mg/L,the total nitrogen content is about 0.799-1.3 mg/L,the total phosphorus content is about 0.54-0.92 mg/L,suggesting that the water eutrophication is very serious.Due to the large amount of domestic sewage discharged into Xinli River without treatment,slow circulation of river water and other factors,the eutrophication is serious in the urban watercourse.

Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

Many countries are paying more and more attention to the protection of water resources at present,and how to protect water resources has received extensive attention from society.Water quality monitoring is the key work to water resources protection.How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection.In this paper,python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database(GEMStat)sites,and the multi-thread parallelism was added to improve the efficiency in the process of downloading and parsing.In order to analyze and process the crawled water quality data,Pandas and Pyecharts are used to visualize the water quality data to show the intrinsic correlation and spatiotemporal relationship of the data.

Composition analysis of colored dissolved organic matter in Taihu Lake based on three dimension excitation-emission fuorescence matrix and PARAFAC model, and the potential application in water quality monitoring

Taihu Lake is one of the five biggest lakes in China. Surface water samples from 26 sampling sites of Taihu Lake were collected. Furthermore wet chemical analysis （CODCr and BOD5） and measurement of three dimensional excitation-emission matrix （3DEEM） spectra in the laboratory have been conducted. Using parallel factor analysis （PARAFAC） model, three components of colored dissolved organic matter （CDOM） have been identified successfully, based on the analysis of 3DEEM data. The characteristics of the three components also have been described by comparing them to some components of CDOM, identified in earlier researches. Meanwhile, spatial variations of concentration for the three components in Taihu Lake have been analyzed, and the result indicates that the concentration of component 1 depends more on the situation of wastewater pollution and can be used as the indicator of wastewater pollution. The relationship between the concentrations of the three components and results of the wet chemical analysis show that none of the three components can be used as indicators of gross organic matter in water. However, the concentrations of all the three components have obvious linear relationships with the BOD5 value, especially for component 1 （r = 0.72878）. Finally, the potential applications of the composition analysis based on 3DEEM and PARAFAC model in water quality monitoring have been illuminated.

Design and Realization of a Novel Hybrid-Drive Robotic Fish for Aquaculture Water Quality Monitoring

Thunniform swimmers(tuna)have a swinging narrow sequence stalk and a moon-shaped tail fin,which performs poorly at slow speed,higher acceleration and turning maneuverability.In most cases,faster speed and higher maneuverability are mutually rejection for most marine creatures and their robotic opponents.This paper presents a novel hybrid tuna-like swimming robot for aquaculture water quality monitoring,which interleaves faster speed and higher maneuverability.The robotic prototype emphasizes on streamlining and enhanced maneuverability mechanism designs in conjunction with a narrow caudal propeller to the tail.The innovative design endows the robot to easily execute the multi-mode swimming gait,including forward swimming,turning,diving/surfacing.The capabilities of our robot are validated through a series of indoor swimming pool and field breeding ponds.The robotic fish can achieve a maximum speed up to about 1.16 m/s and a minimum turning radius less than 0.46 Body Lengths(BL)and its maximum turning speed can reach 78.6∘/s.Due to its high speed,maneuverability and relatively small size,the robotic fish shed light on intelligent monitoring in complex aquatic environments.

First testing of an AUV mission planning and guidance system for water quality monitoring and fish behavior observation in net cage fish farming

Recently,underwater vehicles have become low cost,reliable and affordable platforms for performing various underwater tasks.While many aquaculture systems are closed with no harmful output,open net cage fish farms and land-based fish farms can discharge significant amounts of wastewater containing nutrients,chemicals,and pharmaceuticals that impact on the surrounding environment.Although aquaculture development has often occurred outside a regulatory framework,government oversight is increasingly common at both the seafood quality control level,and at baseline initiatives addressing the basic problem of pollution generated by culture operations,e.g.the European marine and maritime directives.This requires regular,sustainable and cost-effective monitoring of the water quality.Such monitoring needs devices to detect the water quality in a large sea area at different depths in real time.This paper presents a concept for a guidance system for a carrier(an autonomous underwater vehicle)of such devices for the automated detection and analysis of water quality parameters.

Automatic cruise system for water quality monitoring

The range of unit fixed-point measurement on water quality monitoring system is limited,and the cost for multipoint measurement is high.In order to solve these problems,the automatic cruise system for water quality monitoring was designed.Sage-Husa adaptive Kalman filtering algorithm was adopted to correct the error in GPS positioning.The boat was equipped with ship control module,water quality parameters acquisition module,power-supply module,GPS module and GPRS-DTU packet data transmission module.An Android application was developed so that individual users can use smartphone to communicate with the boat at all time and places.The results show that the boat can basically cruise in the set route to monitor the water quality.In a 4 m^(2) aquatic plants areas,the dissolved oxygen monitored in different time were about 10.2%,8.5%and 8.3%,respectively,higher than other areas,and the pH values were 4.1%,3.8%and 3.7%higher than those in other waters,which shown that plants photosynthesis released oxygen consumption of carbon dioxide will affect the dissolved oxygen content and pH value.This system can widen the measurement range,and lower the measuring cost that can be widely used in the water quality monitoring in aquaculture and river management.

An Analysis of the Value of Additional Information Provided by Water Quality Measurement Network

European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the Bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.

同时测定无机离子的改良离子色谱法在河水和废水质量监控中的应用(英文)

In this study,our recent work on advanced ion chromatographic methods for the simultaneous determination of inorganic ionic species such as common anions(SO2-4,Cl-and NO-3) and cations(Na+,NH+4,K+,Mg2+,and Ca2+),nutrients(phosphate and silicate) and hydrogen ion/alkalinity are summarized first.Then,the applications using these methods for monitoring environmental water quality are also presented.For the determination of common anions and cations with nutrients,the separation was successfully performed by a polymethacrylate-based weakly acidic cation-exchange column of TSKgel Super IC-A/C(Tosoh,150 mm×6.0 mm i.d.) and a mixture solution of 100 mmol/L ascorbic acid and 4 mmol/L 18-crown-6 as acidic eluent with dual detection of conductivity and spectrophotometry.For the determination of hydrogen ion/alkalinity,the separation was conducted by TSKgel ODS-100Z column(Tosoh,150 mm×4.5 mm i.d.) modified with lithium dodecylsulfate and an eluent of 40 mmol/L LiCl/0.1 mmol/L lithium dodecylsulfate/0.05 mmol/L H2SO4 with conductivity detector.The differences of ion concentration between untreated and treated wastewater showed the variation of ionic species during biological treatment process in a sewage treatment plant.Occurrence and distribution of water-quality conditions were related to the bioavailability and human activity in watershed.From these results,our advanced ion chromatographic methods have contributed significantly for water quality monitoring of environmental waters.

改进的离子色谱系统监测重庆嘉陵江水质(英文)

The w ater quality monitoring operation to evaluate the w ater quality of polluted river is an extremely im po rtant task fo r the river-w atershed m anagem ent/co ntro l based o n the enviro nm ental po licy.In this study,the no vel,sim ple and co nvenient w ater quality m o nito ring o f Jialing-River in Cho ngqing,China w as carried o ut using an advanced io n chro m ato graphy(IC) co nsisting o f io n-ex clusio n/catio n-ex change chro m ato graphy(IEC/CEC) with conductivity detection for determining simultaneously the common anions such as SO 2 4,Cl,and NO 3 and the catio ns such as Na +,NH + 4,K +,Mg 2 +,and Ca 2 +,the ion-exclusion chromatography(IEC) w ith visible detectio n fo r determ ining sim ultaneo usly the nutrient co m po nents such as pho sphate and silicate io ns,and the IEC w ith the enhanced co nductivity detectio n using a po st co lum n o f K +-fo rm catio n-ex change resin fo r determ ining HCO 3-alkalinity as an ino rganic-carbo n so urce fo r bio m ass synthesis in bio lo gical reactio n pro cess under the aero bic co nditio ns.Acco rding to the io nic balance theo ry betw een the to tal equivalent co ncentratio ns o f anio ns and catio ns,the w ater quality evaluatio n o f the Jialing-River w aters taking at different sam pling sites in Cho ngqing m etro po litan area w as carried o ut using the advanced IC system.As a result,the effectiveness o f this no vel w ater quality m o nito ring m etho do lo gy using the IC system w as dem o nstrated o n the several practical applicatio ns to a typical bio lo gical sew age treatm ent plant o n Jialing-River o f Cho ngqing.

Water-induced luminescence improvement in a lanthanide β-diketone complex for monitoring water purity

Water-caused luminescence quenching is a well-known and intractable issue for luminescence lanthanide complexes, greatly confining their broad application as sensing and displaying devices in water system.Herein, an anionic and coordination-saturated lanthanide complex with a nanosheet-like structure has been prepared. It exhibits excellent photophysical properties both in solid state and in aqueous suspension. Noteworthily, a 13% improvement for sensitization efficiency from organic ligand to central lanthanide ion has been realized, indicating an exceptional phenomenon of water-induced luminescence improvement which is rarely reported previously. Moreover, the aqueous suspension of as-prepared luminophore could act as a chemo-sensor responding to various organic solvents in water. Both of waterinduced luminescence improvement and extended sensing behavior in this work provide a new platform for developing highly performant and practical luminescent materials in the water system.

Prediction of dissolved oxygen content changes based on two-dimensional behavior features of fish school and T-S fuzzy neural network

Dissolved oxygen(DO)content is an important index of river water quality.Water quality sensors have been used in China for urban river water monitoring and DO content prediction.However,water quality sensors are expensive and difficult to maintain,and have a short operation period and difficult to maintain.This study developed a scientific and accurate method for prediction of DO content changes using fish school features.The behavioral features of the Carassius auratus fish school were described using two-dimensional fish school images.The degree of DO content decline was graded into five levels,and the corresponding numerical ranges of cluster characteristic parameters were determined by considering the opinions of ichthyologists.Finally,the variation of DO content was predicted using the characteristic parameters of the fish school and the multiple-input single-output Takagi-Sugeno fuzzy neural network.The prediction results were basically consistent with the actual variations of DO content.Therefore,it is feasible to use the behavioral features of the fish school to dynamically predict the level of DO content in water,and this method is especially suitable for prediction of sharp decline of DO content in a relatively short time.

Aquaphotomics determination of nutrient biomarker for spectrophotometric parameterization of crop growth primary macronutrients using genetic programming

Water quality assessment is currently based on time-consuming and costly laboratory pro-cedures and numerous expensive physicochemical sensors deployment.In response to the trend of device minimization and reduced outlays in sustainable aquaponic water monitoring,the integration of aquaphotomics and computational intelligence is presented in this paper.This study used the combination of temperature,pH,and electrical conductivity sensors in predicting crop growth primary macronutrient concentration(nitrate,phos-phate,and potassium(NPK)),thus,limiting the number of deployed sensors.A total of 220 water samples collected from an outdoor artificial aquaponic pond were temperature perturbed from 16 to 36℃ with 2℃ increments to mimic ambient range,which varies water compositional structure.Aquaphotomics was applied on ultraviolet,visible light,and near-infrared spectral regions,100 to 1000 nm,to determine NPK compounds.Princi-pal component analysis emphasized nutrient dynamics through selecting the highly corre-lated water absorption bands resulting in 250 nm,840 nm,and 765 nm for nitrate,phosphate,and potassium respectively.These activated water bands were used as wave-length protocols to spectrophotometrically measure macronutrient concentrations.Exper-iments have shown that multigene symbolic regression genetic programming(MSRGP)obtained the optimal performance in parameterizing and predicting nitrate,phosphate,and potassium concentrations based on water physical properties with an accuracy of 87.63%,88.73%,and 99.91%,respectively.The results have shown the established 4-dimensional nutrient dynamics map reveals that temperature significantly strengthens nitrate and potassium above 30℃ and phosphate below 25℃ with pH and electrical con-ductivity ranging between 7 and 8 and 0.1 to 0.2 mS cm^(-1) respectively.This novel approach of developing a physicochemical estimation model predicted macronutrient concentra-tions in real-time using physical limnological sensors with a 50%reduction of energy consumption.This same approach can be extended to measure secondary macronutrients and micronutrients.