Odonata Aquatic Insects as Bioindicators in Water Quality Evaluation of Dianchi Lake Riparian Wetland

In order to select a more suitable water quality evaluation method for Dianchi Lake, the water quality monitoring data of Dianchi Lake were studied. Four water quality detection indicators, namely dissolved oxygen, high acid salt index, ammonia nitrogen and total phosphorus, were selected as evaluation indicators. Three common water quality evaluation methods based on single factor analysis, principal component analysis and grey correlation analysis were studied in detail. The annual average detection data values of ten water quality monitoring points deployed in Dianchi Lake from 2019 to 2021 were selected, According to the national surface water evaluation standard, the water quality grade is evaluated and compared. The three methods have their own evaluation emphases, and the grey correlation analysis method is closer to the publicized water quality grade, which is more suitable for the water quality evaluation of Dianchi Lake, and can provide decision support for water environment treatment.

In response to the rapid changes in the chlorophyll-a concentration and eutrophication issues in lakes, with Dianchi Lake as an example, a remote sensing estimation model for chlorophyll-a, total phosphorus, and total nitrogen in Dianchi Lake was constructed using the three band method and ratio band method based on the visible-light shortwave infrared (AHSI) hyperspectral satellite data from Gaofen 5 (GF-5) and the water quality data collected at Dianchi Lake. The model results were compared with the multispectral data from the Gaofen 1 (GF-1) wide field-of-view (WFV) camera. The accuracy evaluation results indicate that the overall mean absolute percentage error of the remote sensing estimation models for chlorophyll a, total phosphorus, and total nitrogen are 7.658%, 4.511%, and 4.577%, respectively, which can meet the needs of lake water quality monitoring and evaluation. According to the remote sensing simulation results, chlorophyll a is mainly distributed in the northern part of Dianchi Lake, with phosphorus and nitrogen pollution throughout Dianchi Lake and relatively more abundant in the central and southern regions. The pollution is mainly concentrated in the northern and southern regions of Dianchi Lake, which is consistent with the actual situation. Further confirming the feasibility of using GF-5 satellite AHSI data for water quality parameter retrieval can provide new technical means for relevant departments to quickly and efficiently monitor the inland lake water environment.

Biomonitoring studies focus on the component of biodiversity, its natural habitats, and species populations which display the ongoing variations in ecosystem and landscape. Physicochemical parameters are important water quality parameters of river water i.e., pH, temperature, turbidity, conductivity, total dissolved solids, total suspended solids, total alkalinity, sulfate, nitrate, heavy metals, and phosphate. This chapter focuses on assessing water quality through Physicochemical Parameters and Aquatic Insects Diversity. The case study investigated the effect of pollutants produced by the human dwelling, agricultural and industrial activities on aquatic invertebrate communities of water of part of Soan River, Pakistan. Four sites were selected based on variation in microhabitat accessibility to examine the pollution in water. Samples were collected from these sites during spring, 2015. Water samples for physio-chemical analysis and macroinvertebrates were collected from all sites. Results showed that conductivity, dissolved oxygen, sodium, and cadmium at all sites were higher than the drinking water quality of WHO standards while potassium, chromium, and manganese were higher in concentration at most downstream sites. However, all other studied parameters were within recommended range of WHO standards. A total of 412 individuals of aquatic insects were collected from the studied sites, belonged to 6 orders and they were the most abundant in April. Total abundance was used to estimate the quality of water at the sites. Most biotic indexes showed that water was of good quality at upstream stations rather than downstream stations, while water quality index (WQI) showed fair water quality at downstream sites. This study showed that aquatic insects could be useful as bioindicators for biomonitoring of water quality along with physiochemical parameters.

Water quality (WQ) evaluation is very important issue in human health and environment management. Many WQ evaluation (WQE) methods based on statistical methods and multi-criteria decision making (MCDM) methods have been developed and used. The common drawback is that they lack in visualization/intuitiveness of the WQE results. They evaluate the WQ level only quantitatively. To intuitively represent the WQ level, the previous WQE methods have applied some additional graphical methods such as concentration/distribution/contour maps combined with complicated interpolation techniques based on geographic information system. The objective of this research is to develop a new effective approach to evaluate the WQ level not only quantitatively but also intuitively without requiring additional complicated graphical technique. To do this, we proposed a new quadrant constellation graph-based water quality index (QCG-WQI) and map (QCG-WQM). The QCG-WQI evaluates the WQ level quantitatively, and QCG-WQM evaluates the WQ level intuitively. To demonstrate the effectiveness, three illustration cases were considered and compared with the results from some well-known MCDM methods. The results demonstrate that the new approach is very effective intuitive and quantitative WQE tool. It could be widely applied to not only WQE and environmental evaluation but also MCDM problems in many physical research works.

Assessing spatiotemporal variation in water quality and heavy metals concentrations in wetlands and identifying metal contamination source are crucial steps for the protection and sustainable utilization of water resources. Using the water quality identification index (Iwq), heavy metal pollution index (HPI), hierarchical cluster analysis (HCA) and redundancy analysis (RDA), we evaluated spatiotemporal variation in water quality and heavy metals concentrations, and their interrelation in wetlands along the middle and lower Yellow River. The average Iwq was highest during flood season but the average HPI was lowest in the same season. Meanwhile, the trend in mean HPI across three hydrological seasons was the opposite to that of mean Iwq. There was significant variation in wetlands water pollution status across seasons. During the flood season, the wetlands in the affected area with hanging river were seriously polluted. In other seasons, pollution in the artificial wetlands was even more severe. Moreover, serious pollution of wetlands in belt transect #03 (Yuanyang-Zhongmu) was more frequent. Dissolved oxygen and chemical oxygen demand strongly influenced heavy metal concentrations, while other water quality parameters had different influences on heavy metal concentrations in different hydrological seasons. The causes of water pollution were divided into natural factors and human disturbance (with potential relationships between them). The polluted wetlands were greatly affected by the Yellow River during the flood season while they were more impacted by agricultural and domestic sewage discharge in other seasons. However, heavy metal deposition and leaching into riparian wetlands were still affected by diverse channel conditions. If this trend is allowed to continue unabated, wetlands along the middle and lower Yellow River are likely to lose their vital ecological and social functions.

Chapter 4 - Water Quality Evaluation

Copula-based framework for integrated evaluation of water quality and quantity: A case study of Yihe River, China

The quality of the water in a uranium-ore-mining area located in Caldas (Minas Gerais State, Brazil) and in a reservoir (Antas reservoir) that receives the neutralized acid solution leaching from the waste heaps generated by uranium mining was investigated. The samples were collected during four periods (October 2008, January, April and July 2009) from six sampling stations. Physical and chemical analyses were performed on the water samples, and the data obtained were compared with those of the Brazilian Environmental Standards and WHO standard. The water samples obtained from waste rock piles showed high uranium concentrations (5.62mg L(-1)), high manganese values (75mg L(-1)) and low average pH values (3.4). The evaluation of the water quality at the point considered the limit between the Ore Treatment Unit of the Brazilian Nuclear Industries and the environment (Consulta Creek) indicated contamination by fluoride, manganese, uranium and zinc. The Antas reservoir showed seasonal variations in water quality, with mean concentrations for fluoride (0.50mg L(-1)), sulfate (16mg L(-1)) and hardness (20mg L(-1)) which were low in January, evidencing the effect of rainwater flowing into the system. The concentrations for fluoride, sulfate and manganese were close or above to the limits established by current legislation at the point where the treated mining effluent was discharged and downstream from this point. This study demonstrated that the effluent discharged by the UTM affected the quality of the water in the Antas reservoir, and thus the treatments currently used for effluent need to be reviewed.

To investigate the differences in water quality response to landscape features at multiple spatial and temporal scales for different lake types， the Dianchi Lake （Tectonic Lake） in Kunming， Yunnan Province and Fushun West Lake （Hecheng Lake） in Zigong， Sichuan Province were used as the objects of the study. Land use types and landscape pattern indices were extracted at five spatial scales of 200， 400， 600， 800， and 1 000 m buffer zones of the Dianchi Lake basin in Kunming and 20， 40， 60， 80， and 100 m buffer zones of the Fushun West Lake Basin. Combined with lake water quality data from the wet season （July 2022） and dry season （April 2023）， the correlation analysis and the redundancy analysis （RDA） were used to quantitatively compare the differences in the multi-temporal and spatial scale responses of water quality to landscape characteristics between two types of lakes. The results showed that： ① All land use types of Fushun West Lake were urban land， and the land use types of Kunming Dianchi were richer， in which urban land was dominant. The landscape fragmentation of both lakes decreased with the increase of spatial scale. Due to the different landscape characteristics of the two lake basins， their water quality was better in the dry season than in the wet season， and the water quality of Fushun West Lake was better than that of Kunming Dianchi. ② Fushun West Lake had the highest explanation rate of the landscape characteristics to the water quality at the scale of 60 m lakeshore buffer zone in the dry season， whereas Kunming Dianchi had the strongest response to the landscape characteristics in the wet season and 800 m lakeshore buffer zone. The response of water quality to the landscape characteristics of Kunming Dianchi was higher than that of Fushun West Lake. ③ There were significant differences in the response of water quality of varying lake types to different landscape features at different spatial and temporal scales. In this study， the urban land was a "sink" landscape of water quality in the Dianchi Lake basin in both dry and wet seasons， while the Fushun West Lake basin was a typical "source" landscape. Forest land was a "source" of polluted water quality at multiple spatial and temporal scales in the Kunming Dianchi basin， with a negative correlation between buffer scale and most water quality indicators at more distant lakeshore zones during the dry season. Patch density was the most critical indicator affecting water quality in Dianchi and Fushun West Lake watersheds. Moreover， the landscape shape index had a greater impact on the water quality of Fushun West Lake than that of Kunming Dianchi. By studying the differences in the response of water quality of different lake types at multiple spatial and temporal scales， this study helps to better predict and respond to the potential impacts of environmental changes on water resources and ecosystems. It also provides a scientific basis for the development of more precise and effective water resource management and protection policies by optimizing the allocation of water resources and strengthening ecological protection and environmental governance.

In order to timely grasp the status and change trend of the irrigated agricultural water environment, we refer to the farmland irrigation water quality evaluation standards, and select 11 monitoring items in different basins to monitor the agricultural irrigation water quality for 2 consecutive years. The article uses the pollution index method to evaluate the monitoring results. The results show that the comprehensive pollution index of surface irrigation water and underground irrigation water quality is less than 1, but there is a rising trend; the concentration of some pollutants in the irrigation return water is higher than that of the irrigation water, and some individual indicators exceed the standard, but they do not constitute comprehensive pollution. Finally, through the design of the remote sensing image water quality monitoring and evaluation system (RWQMES), the unified management of the three functions of water quality remote sensing image analysis and processing, water quality prediction and evaluation is realized.

Objective evaluation of surface water quality and quantitative analysis of water quality spatial characteristics are crucial for the sustainable utilization of surface water. This article innovatively proposes a method based on (Self-organizing maps) SOM, principal component analysis (PCA), and water quality index(WQIM) to evaluate the water quality of the Luan River Basin (LRB). Firstly, SOM an PCA were used to reduce the dimensionality characterize the hydrochemical characteristics of LRB, spatial variations, and establish the correlation between water quality indicators. In addition, a comprehensive evaluation the water quality of LRB monitoring sections through WQIM and quantify their water quality results. Then, SOM indicates that influencing factors of water quality were pH and TN (total nitrogen). PCA further validated the strong correlation between pH and TN. Finally, the comprehensive evaluation of LRB water quality was achieved using WQIM. This study qualitatively quantified the correlation between different water quality indicators, providing support for improving the accuracy of water quality evaluation.

Aiming at the eutrophication state of Dian Lake, based on hydrodynamics principle, and some available information about Dian Lake, such as eco-environmental construction planning, the previous work, and so on, a vertical-averaged 2-D hydrodynamic model of ecosystem is established under combination of wetland plants, bed mud, and water change. The model is applied to simulate flow and concentration fields of present lake water, and lake waters after breakwater removal and wetland build. It is also used to simulate concentration field of wastewater discharged into Dian Lake which meets the discharge standard. The influences of wetland plants and water expanding on flow field and water quality are analyzed, and the effect of wastewater discharged into Dian Lake which meets the discharge standard on water quality is analyzed, too. The results show that: The influence of water expanding on flow field is local; and the influence of wetland plants on flow field occurs primarily at wetland areas; and the influence of water expanding on water quality is not great because the total phosphorus(TP) and the total nitrogen(TN) reduce to 1.69mg/L and 0.16mg/L from 2.08mg/L and 0.19mg/L respectively; and the influence of ecological wetland on water quality is great, because the TP and the TN reduce to 0.76mg/L and 0.05mg/L respectively, which could make the water quality of Dian Lake reach Ⅲ class of The National Surface Water Standards; and the influence of wastewater discharged into Dian Lake which meets the discharge standard on water quality is big, because the TP and the TN reduce to 0.17mg/L and 0.01mg/L respectively, which could obviously improve the water quality. Therefore, wastewater discharged into Dian Lake which meets the discharge standard and artificial wetland play an important role in the improvement of the ecological environment of Dian Lake.

Evaluation of ground water quality and hydro-geochemistry of shallow and deep aquifer (with respect to guideline values of WHO 2004, geochemical classifications, ion exchange processes and mechanisms controlling ground water chemistry) and evaluation of water quality (with respect to different sodium hazards, Ca2+/Mg2+ ratio) for irrigation purpose in mining area were the aims of the present study. Accordingly ground water samples were collected from shallow, deep aquifers of Gadchandur, Chandrapur in pre and post monsoon seasons 2010. Quality of the water samples collected from the deep aquifer found satisfactory in comparison with water samples collected from the shallow aquifer. Geochemical nature of shallow aquifer was earth alkaline with increased portion of alkalis with prevailing bicarbonate, followed by chloroalkaline disequilibrium type of ion exchange process. Chemical weathering of rock forming minerals was the major driving force controlling shallow aquifer water chemistry. Hydro-geochemistry of deep aquifer in pre-monsoon season hydrogeochemistry of the deep aquifer shifted towards alkaline with sulphate and bicarbonate. Ion exchange process in this aquifer showed complete dominance of base exchange reaction in both the seasons. Chemical weathering along with evaporation was the two major driving forces controlling the water chemistry of the shallow and deep aquifer in pre-monsoon and post-monsoon seasons. RSC (residual sodium carbonate), %Na, SAR (sodium adsorption ratio), Ca2+/Mg2+ ratio and concentration of Cl, F in irrigation water revealed that some water samples were not good enough for irrigation in pre-monsoon season in comparison to that of post monsoon season.

Treated water disposed from an alternative wastewater treatment system, named johkasou, contains several contaminants that may affect the quality of the local water environment. Thus, the evaluation of water quality, along with sediment content, may provide quantitative information about the effects of johkasou effluent in the open channels. Here, the physicochemical and microbial parameters were comprehensively examined in both the water and sediments of a johkasou drainage channel and open channels. Throughout the 3-year study period, the concentrations of physicochemical parameters were lower in the open channels compared to the johkasou drainage channel because of the high mixing ratio of the flow rate between the two channels. However, microbial parameters were consistently high in both the water and sediments of open channels. Microbial concentrations were not significantly different between upstream and downstream channels in any season, except for Escherichia coli (E. coli) in winter (the concentrations of which increased in the downstream channel that received johkasou effluent). Heterotrophic plate count bacteria and E. coli were positively correlated between water and sediments, indicating that microbial indicators may interact with the water and sediments in open channels.

KEYWORD: The Water Quality ; The Water Environment; Fuzzy Theory; Artificial Neural Network ABSTRACT: Throughout the development process of the water quality evaluation method, the pa- per outlines several water quality evaluation methods, summarizes them and points out the advantag- es and disadvantages. Finally the paper points out that water quality evaluation method will be fur- ther improved with the wide application of computer technology combined with various subjects of mutual cross-penetration. Water quality assessment evaluates qualitatively or quantitatively the water quality elements on some water environment monitoring data and in accordance with the evaluation criteria and evaluation me- thods. The water quality assessment is the basis for the calculation of the capacity of the water envi- ronment and water resources planning and management. It is also a prerequisite for the water control planning. Water quality assessment results can determine the water quality model and provide para- meters and information for model identification and parameter identification(1). It can accurately re- flect the water quality situation, understand and master the water pollution impact and development trends and provide a scientific basis for the protection of the water environment and water resources planning and management. Water quality assessment is not only the water quality of the scientific de- scription of reality, but also points out the objectives and direction for water pollution control pro- grams. We can build the appropriate water quality model for water pollution control programs by the information provided by the water quality assessment. In the 1960s, Jacobs proposed the water quality index of concepts and formulas of the water quality evaluation. Because it is simple and easy to operate, until today people still use it in the domestic wa- ter quality evaluation practice. Later, water quality experts at home and abroad also raised various comprehensive water quality index methods. Which the Nemerow mode, mean square error mode(2) and vector mode(3) are more typical. Since the 1980s, Some uncertainty, the emergence of the nonlinear theory method and the promotion and application of computer technology provides a theo- retical basis and technical support for the new model of water quality assessment(4). Some of the commonly used methods can be summarized into the following categories throughout the develop- ment process of the water quality evaluation method.