Applicability of borrowed diatom-based water quality assessment indices in streams around São Carlos-SP,Brazil

Diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. The applicability of regional and foreign diatom-based water quality assessment indices to streams around São Carlos-SP, Brazil, is discussed. The relationship between measured water quality variables and diatom index scores was assessed. The indices, when compared to chemical analyses, proved useful in providing an indication of the quality of the investigated waters. Though all borrowed indices were applicable to the study area because many widely distributed diatom species have similar environmental tolerances to those recorded for these species elsewhere, ecological requirements of some diatom species from Brazil need to be clarified and incorporated in a diatom-based water quality assessment protocol unique to the region.     

Dynamic Quality Index for agricultural soils based on fuzzy logic

The increasing number of successful applications of fuzzy logic and fuzzy sets theory to dealing with the uncertainty, imprecision and subjectivity inherent to environmental quality assessments, and the recent development of new procedures based on fuzzy logic for the design of environmental quality indexes open new ways to carry out more rigorous and realistic estimations of soil quality. With these considerations in mind, the aim of this work is to design an index based on fuzzy logic, which is especially addressed to assess the dynamic quality of agricultural soils – Soil Dynamic Quality Index (S-DQI). This index is described by a group of three indexes (S-DQI_PHYS, S-DQI_CHEM, S-DQI_BIOL), each one designed to evaluate the dynamic quality of agricultural soils with regard to their physical, chemical and biological characteristics, respectively. Each index is determined from the joint opinion of a panel of experts, which decides: (i) the attributes or properties of soil which determine its dynamic quality for farming; (ii) the most suitable indicator for quantifying each of them; (iii) the influence of the values taken by these indicators on the quality of agricultural soils, which is expressed by means of membership functions, and (iv) the relative importance of the attributes in the respective index, which is expressed by means of normalized priority vectors. The value of each of these indexes is finally obtained as a result of a fuzzy inference procedure, which is a crisp value ranging from 0 to 1. This procedure allows us to express the values taken by the indicators in a particular agroecosystem by means of both crisp values and fuzzy numbers, the latter being frequently a more rigorous and realistic way of representing the estimations of the soil properties in any emplacement. Verification tests show the satisfactory response capability of the index to changes in the soil properties. The use of the designed S-DQI for routine monitoring of the quality of farming soil allows the estimation of the changes induced in the soil due to use, which is helpful to assess systematically the sustainability of the agricultural practices.     

F-IND: A framework to design fuzzy indices of environmental conditions

Multivariable indices of environmental conditions summarize the information provided by several biotic or abiotic variables into a single value of immediate interpretability. Thus they are important instruments for monitoring. Developing new indices that combine different variables is not a trivial task: variables may be qualitative, or measured in different units, and the relationship between primitive components and quality may be ambiguous. Fuzzy logic has been repeatedly proposed as an effective technique to cope with such problems; however, the variety of choices that exist at each stage of the development of fuzzy models may present a problem for the index designer. In this paper we present F-IND, a framework to create fuzzy indices by means of a simplified and intuitive procedure. It allows to capture the expert knowledge of the system under study (air, soil, water) to easily generate a multivariable index of environmental conditions. F-IND is implemented in Java, to achieve an optimal portability on any operating system.     

Water quality index as a simple indicator of aquaculture effects on aquatic bodies

This paper proposes a water quality index (WQI) to subsidize management actions in the Médio Paranapanema Watershed in São Paulo State, Brazil, as a simple pollution indicator for aquaculture activity. Water quality of the Macuco and Queixada rivers was investigated for 2 years (from May 2003 to May 2005). The index proposed in this work is composed of three measurable environmental parameters—turbidity, total phosphorus and dissolved oxygen. Concentrations of these three variables were normalized on a scale from 0 to 100 and translated into statements of water quality (excellent, good, regular, fair and poor). The index was applied to seventeen monitoring points in the aquatic bodies described above and compared to others, one being that used by the Environmental Protection Agency of United States and proposed for the National Sanitation Foundation, other employing minimal index and the last one considering the minimum operator concept. The results show that the degradation in this watershed from aquaculture activity can be easily inferred with this index, which is more restricted than the others routinely used to infer water quality.     

Comment on “Assessing water quality of five typical reservoirs in lower reaches of Yellow River,China: Using a water quality index method” by Wei Hou,Shaohua Sun,Mingquan Wang,Xiang Li,Nuo Zhang,Xiaodong Xin,Li Sun,Wei Li,and Ruibao Jia (2016) [Ecological Indicators, 61, 309–316]

Hou et al. (2016) recently developed a water quality index (WQI) for assessing water quality of five typical reservoirs. Despite all the merits of the practical WQI, it suffers from lack of uncertainty consideration; a fact that motivated the present discussion focusing on mitigation of uncertainty in water quality assessment. In this regard, superiority of employing fuzzy WQI (FWQI) rather than crisp WQI is emphasized. Due to robustness of FWQI in handling uncertainties surrounding data acquisition, employment of fuzzy concept can improve water quality assessment and monitoring to generate results which are more consistent with real world conditions.     

Use of macroinvertebrate-based multimetric indices for water quality evaluation in Spanish Mediterranean rivers: an intercalibration approach with the IBMWP index

For the European Parliament and Commission to implement the Water Framework Directive (WFD), the water-quality indices that are currently used in Europe need to be compared and calibrated. This will facilitate the comparative assessment of ecological status throughout the European Union. According to the WFD, biologic indices should respond consistently to human impacts, using multimetric approaches and water-quality classification boundaries adjusted to a common set of normative definitions. The European Commission has started an intercalibration exercise to review biologic indices and harmonize class boundaries. We used data from rivers in Spain to compare the IBMWP (Iberian Biological Monitoring Working Party) index, which is commonly used by water authorities in Spain and by several research centers, with the Intercalibration Common Multimetric Index (ICM-Star), which was used as a standard in the intercalibration exercise. We also used data from Spanish rivers to compare the multimetric indices ICM-7 (based on quantitative data) and ICM-9 (based on qualitative data) with the IBMWP. ICM-7 and ICM-9 were proposed by the Mediterranean Geographical Intercalibration Group (Med-GIG). Additionally, we evaluated two new multimetric indices, developed specifically for macroinvertebrate communities inhabiting Mediterranean river systems. One of these is based on quantitative data (ICM-10), while the other is based on qualitative data (ICM-11a). The results show that the IBMWP index responds well to the stressor gradient present in our data, and correlates well with ICM-Star. Moreover, the IBMWP quality class boundaries were consistent with the intercalibration requirements of the WFD. However, multimetric indices showed a more linear relation with the stressor gradient in our data, and less variation in reference values. In addition, they may provide more statistical power for detecting potential environmental impacts. Multimetric indices produced similar results for quantitative and qualitative data. Thus, ICM-10 (also named IMMi-T) and ICM-11a (also named IMMi-L) indices could be used to meet European Commission requirements for assessing the water quality in Spanish Mediterranean rivers. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users. Handling editor: Joel Trexler     

The fuzzy index of ecosystem integrity (FINE): a new index of environmental integrity for transitional ecosystems

The European Water Framework Directive (WFD) (2000/60/EC) requires assessing the ecological quality status of water bodies, and gives great importance to the biological components of the ecosystem. Within this framework, a multimetric, fuzzy-based index for the evaluation of environmental quality (FINE: fuzzy index of ecosystem integrity) has been developed using data from several Italian coastal lagoons, gathered with seasonal frequency at diverse sites in each lagoon. The rationale of FINE is that certain attributes, selected on the basis of established principles of benthic ecology, are fundamental for lagoon ecosystem function. FINE is composed of seven ecosystem attributes (variables) each of which have ecological relevance for lagoon ecosystems. Individually, all these attributes are themselves useful indices of environmental conditions. However, the combination of these attributes into a single fuzzy index, provides a more robust, overall index of the response of the natural communities to environmental perturbations and avoids misleading or ambiguous results. Each variable is not represented by a single numerical value, but by several categories that describe its properties: in the present model we considered a total of seven variables: two with four modalities (low–medium–high–very high), one with three (low–medium–high) and three with two (low–high), plus a qualitative variable (yes–no), that altogether generate 768 rules. FINE is a low-cost, flexible and robust routine index of lagoon ecosystem impairment and could be of particular benefit to environmental managers and policymakers who require tools capable of expressing the degree of degradation or environmental quality of different lagoon habitats. For its relative simplicity in the application, FINE could be a good candidate to assess the environmental quality of Mediterranean transitional ecosystems. Guest editors: A. Razinkovas, Z. R. Gasiūnaitė, J. M. Zaldivar & P. Viaroli European Lagoons and their Watersheds: Function and Biodiversity     

Fuzzy evaluation of water quality classification

Traditional classification methods of the water quality parameters use crisp set, and the concentrations values which are close or far from the limits are considered in same classes. Moreover, usually, several parameters are considered in quality determination; therefore, differences of the classes of the parameters may be vagueness, especially, in public consideration.In this study, an index model for quality evaluation of surface water quality classification using fuzzy logic is proposed. In the method, traditional quality classes are transformed into continuous form and then the concentration values of the different quality parameters are summed using fuzzy rules, finally, defuzzyfication of this summed values develops the index. An application of this proposed index model for physical and inorganic chemical parameters in the Eber Lake water (in Turkey) are studied to demonstrate the practical application and feasibility of this index.     

Novel scales based on hydrophobicity indices for secondary protein structure

This paper is concerned with a branch of computational biology related to protein prediction and analysis of secondary structure of proteins. Although traditional methods use a simple amino acid composition to predict the secondary structure content, hydrophobicity has been recently found to improve the results in this and several related prediction tasks. To this end, we propose and analyze advantages of two new hydrophobicity index-based scales that incorporate information about long-range interactions along the protein sequence and contrast them with currently used raw hydrophobic index values. We also compare three leading hydrophobicity indices, i.e., Eisenberg's, Fauchere-Pliska's, and Cid's, using the proposed scales. The analysis is performed using fuzzy cognitive maps that quantify the strength of relation between the hydrophobicity scales/indices and the protein content values. A set of empirical tests that involve generation of fuzzy cognitive map models for a set of 200 low homology proteins have been performed. The results show that the secondary structure content along the protein sequence is characterized by about 2.5 times stronger relation with the two proposed hydrophobicity scales when compared with the currently used raw index values. The new scales exhibit stronger relation irrespective of the applied hydrobhobicity indices. Analysis of different scales shows superiority of the Eisenberg's hydrophobicity index, when used with the new scales. In contrast, the Fauchere-Pliska's index is found to perform better when compared with the two other indices when using raw hydrophobic index values that disregard the long-range interactions.     

Insights into discriminating water quality status using new biodiversity measures based on a trait hierarchy of body-size units

Biofilm-dwelling protozoa have successfully used as a feasible bioindicator for bioassessment of water quality status in marine ecosystems. Based on a dataset of biofilm-dwelling protozoa in coastal waters of the Yellow Sea, we demonstrated a spatial variation in body-size spectrum of protozoan communities along a gradient of increasing environmental pollution. Two biodiversity indices, as a new indicator of water quality, were proposed, first being body-size diversity (Δ′) logistically corresponded to taxonomic diversity index but with a trait hierarchy of body-size units based on Euclidean distance resemblance, and the second a modified body-size diversity index (Δ′_m) with a modified hierarchy based on the trait matrix. The values of both indices Δ′ and Δ′_m were found to be significantly correlated with the changes of environmental variables, especially the nutrients. Furthermore, the body-size diversity (Δ′_mrk) at body-size-rank-1 (“genus-level”) resolution might be used as a potential surrogate of those at “species-level” resolution. Thus, we suggest that the ecological parameters based on body-size spectrum may be used as potential bioindicator of water quality status, and that the body-size rank sufficiency might be an effective time-efficient protocol for monitoring programs by identifying taxa to “genus-level” body-size rank.     

A new plan quality index for nasopharyngeal cancer SIB IMRT

A new plan quality index integrating dosimetric and radiobiological indices was proposed to facilitate the evaluation and comparison of simultaneous integrated boost (SIB) intensity modulated radiotherapy (IMRT) plans for nasopharyngeal cancer (NPC) patients.Ten NPC patients treated by SIB-IMRT were enrolled in the study. Custom software was developed to read dose–volume histogram (DVH) curves from the treatment planning system (TPS). A plan filtering matrix was introduced to filter plans that fail to satisfy treatment protocol. Target plan quality indices and organ at risk (OAR) plan quality indices were calculated for qualified plans. A unique composite plan quality index (CPQI) was proposed based on the relative weight of these indices to evaluate and compare competing plans. Plan ranking results were compared with detailed statistical analysis, radiation oncology quality system (ROQS) scoring results and physician's evaluation results to verify the accuracy of this new plan quality index.The average CPQI values for plans with OAR priority of low, normal, high, and PTV only were 0.22 ± 0.08, 0.49 ± 0.077, 0.71 ± 0.062, and −0.21 ± 0.16, respectively. There were significant differences among these plan quality indices (One-way ANOVA test, p < 0.01). This was consistent with statistical analysis, ROQS results and physician's ranking results in which 90% OAR high plans were selected.Plan filtering matrix was able to speed up the plan evaluation process. The new matrix plan quality index CPQI showed good consistence with physician ranking results. It is a promising index for NPC SIB-IMRT plan evaluation.     

Geographic variation in mangrove flooding and accessibility for fishes and nektonic crustaceans

In the last decade, dozens of indices based on macroinvertebrates were developed to evaluate lotic ecosystems. In contrast, very few of these indices have been applied in lentic ecosystems. Natural wetlands in southern Brazil are increasingly threatened by the expansion of irrigated rice. The main objective of this study was to develop a multimetric index based on macroinvertebrates to evaluate the water quality of natural wetlands and rice fields in southern Brazil. Three samplings were carried out over the rice growth cycle in four conventional and four biodynamic rice fields, and four natural wetlands. The wetlands were considered as reference sites, and the conventional and biodynamic rice crops were considered as manipulated sites at different levels of degradation. Seven metrics were included in the final index after passing though sensitivity and correlation tests. The results indicated that our index has a power to detect a gradient of variation in water quality. Natural wetlands had the best water quality, biodynamic crops had intermediate water quality, and the conventional crops had the lowest water quality. We believe that development of this macroinvertebrate-based multimetric index of water quality could be an important tool for monitoring natural wetlands and rice crops in southern Brazil.     

Introducing a zooplanktonic index for assessing water quality of natural lakes in the Mediterranean region

In the pelagic food web of lakes, zooplankton offers the linkage between phytoplankton and fish, greatly affecting but also mirroring the functionality and stability of the ecosystem. Despite the increased interest on the development of water quality indices, incorporating zooplankton data on metrics used for the assessment of natural lakes remains a challenge. Here, we used information of natural lakes hosted in Eastern Mediterranean on zooplankton abundance, biomass, body weight and cladocerans' ratio to develop a novel zooplanktonic index (Zoo-IQ). Α 5-grade classification scheme was generated (Bad ≤6, 6 < Poor ≤10, 10 < Moderate ≤14, 14 < Good ≤18, 18 < High) for water quality assessment. The Zoo-IQ was originally parametrized based on data collected from 13 natural lakes, located in Greece and successfully classified hypertrophic lakes with poor quality and deep lakes with good quality, while it identified lakes subjected to restoration actions. Using independent data from five lakes hosted in Greece, Turkey and Croatia, Zoo-IQ successfully assessed their water quality. Specifically, from the 25 sampling cases, used for the development and the evaluation of the index, Zoo-IQ identified 5 as good, 8 as moderate, 11 as poor and 1 as bad. Our results demonstrate the potential of using Zoo-IQ for the assessment of lakes water quality in the Mediterranean. The proposed index could serve as a first step towards the development of similar indices in other climatic zones.     

Water quality indicators: Comparison of a probabilistic index and a general quality index. The case of the Confederación Hidrográfica del Júcar (Spain)

The main objective of this work is to measure water quality using a stochastic index built with tools of Probability Theory. Its great advantage is that it accounts for the underlying uncertainty in quality classification that results from variations in the data for individual physical and chemical characteristics, considering them as random variables.We compare the results obtained by measuring water quality with this index (the probabilistic index, PI) and a classical deterministic index (the general quality index, GQI). Also we do a comparison with other usual indices in order to validate the PI index.To demonstrate the application of PI and GQI indices, we used information from the Confederación Hidrográfica del Júcar (Spain) for the period between 1990 and 2005. Our analyses showed that GQI was positively correlated with PI throughout the study period. Because of its high potential, the PI index can be used to analyze possible temporal changes in water quality, as well as to determine the individual influence of each variable in water quality. The results suggested an improvement in water quality over time and that omitting individually, one at a time, five of the nine water quality variables from the PI calculation significantly improved the calculated water quality.Novelty of this paper is the design of an index that takes into account the uncertainty inherent to data, and its application for measuring water quality from a general perspective.     

2001-2010年洞庭湖生态系统质量遥感综合评价与变化分析

生态系统质量能够反映生态系统的重要特征,是表征生态环境质量和服务功能的重要指标。在生态系统质量的理论框架指导下,结合GIS综合指数法,利用遥感数据和土地覆被数据,对2001—2010年洞庭湖区域各生态系统类型进行生态系统质量综合评价和变化分析。以NPP年均值和变异系数构建生态系统生产能力指数(EPI)和稳定性指数(ESI),结合PSR模型和AHP层次分析法构建生态系统承载力指数(EBCI),并基于熵值权重法,构建生态系统质量遥感综合评价模型,实现对生态系统生产能力、稳定性和承载力三方面的综合评价。结果表明,洞庭湖区域生态系统质量综合评价分数达到59.81(总分100),而且在三项指数评价中,各指数均值分别为72.79、52.21和71.86,可见洞庭湖区域生态系统稳定性略差。三项指数在2001—2010年期间变化表现不同,EPI和EBCI分别下降8.85%和9.11%,ESI小幅度上升3.09%;整体生态系统质量在2001—2010年呈现逐年降低趋势,下降5.97%,平均变化率为-0.508/年。针对各生态系统类型的分析可知,森林生态系统质量高于其他生态系统类型,湿地生态系统质量最低,同时在这十年间,湿地生态系统质量下降最明显,降幅达12.97%,森林生态系统质量变化较小,降幅只有2.26%。     

Response of diatom indices to simulated water quality improvements in a river

Various diatom indices are routinely used in European countries to monitor water quality in waterways. In order to assess their sensitivities and their integration interval after a sudden and lasting environmental change, epilithic diatom biofilms were transferred from several polluted rivers to an unpolluted stream. To monitor the changes of the index values, the biofilms were sampled in a first experiment 20 and 40 days after transfer, and in a second experiment 30 and 60 days after transfer. Sensitivities of the indices to the water quality improvement were assessed calculating the differences between the index values of the reference and the transferred assemblages. Some indices have intermediate sensitivities (BDI, GDI, ILM, SLA), others higher sensitivities (CEE, EPI, ROT, SPI, TDI). The integration interval of these indices was 40–60 days. Some differences were observed between the indices, but their results were homogeneous when compared to those obtained with other metrics such as Bray-Curtis or Chord distances, used to assess the difference between the transferred and the reference diatom assemblages. These other metrics showed that even after 60 days, the transferred assemblages still differed from the reference. This underlines that metrics do not have the same integration intervals and do not assess the same stresses; the choice of the metric used to assess water quality is of prime importance.     

Combination of discretization regression with data-driven algorithms for modeling irrigation water quality indices

Forecasting water quality parameters helps plan crop selection and irrigation strategies but is often costly because many parameters are required, particularly in developing nations. Therefore, the current research objective is to estimate the irrigation water quality indices in the Nand Samand catchment by developing machine learning models. To accomplish this objective, six machine learning models (Regression by discretization REGD; Regression by discretization-Bagging, REGD-Bagging; Regression by discretization-Random Subspace, REGD-RSS; Regression by discretization-Additive Regression, REGD-AR; Regression by discretization-M5 Pruned, REGD-M5P; Regression by discretization-Random Forest, REGD-RF) were developed and the accuracy of these model's were checked by ten statistics models and validated for predicting four irrigation water quality indices (soluble sodium percentage, SSP; sodium adsorption ratio, SAR; magnesium hazards, MH; Kelly's ratio, KR). Eleven physicochemical variables were analyzed from 95 open wells of the research area for two different seasons in 2020, pre-monsoon and post-monsoon, respectively. Results revealed that the REGD-M5P model showed the best fit for all irrigation indices based on the correlation coefficient(r) for the SSP, MH, KR, and SAR index (0.947, 0.975, 0.950, and 0.956 during the training phase and 0.868, 0.966, 0.930, and 0.979 during the testing phase, respectively). Similarly, root mean square error (RMSE) values showed the best fit for the REGD-M5P model for all four irrigation indices, i.e., SSP, MH, KR, and SAR (3.696, 3.100, 0.115, and 0.393 in the training phase; 3.446, 3.772, 0.125 and 0.207 in the testing phase, respectively). It may be concluded that machine learning models may improve the parameters of irrigation water quality, and such findings are vital to farmers for crop selection and irrigation application planning. Additionally, the proposed machine learning models in predicting the irrigation water quality index and being fast decision tools for modeling irrigation water quality are also very important.     

巢湖流域生态安全评价研究

目前,巢湖流域的生态安全问题非常突出,已严重影响流域社会经济的可持续发展。基于巢湖流域社会经济、水体环境质量及水生生态系统的数据资料,应用驱动力-压力-状态-影响-响应(DPSIR)模型,提出了基于水环境和水生态的巢湖流域生态安全评价框架模型和指标体系,并采用熵权物元模糊评价法进行巢湖流域生态安全评价研究。研究结果表明,2003和2007年巢湖流域整体处于生态安全中度风险状态,水体环境质量的变化和水生生态系统的演替将严重威胁巢湖流域的生态安全,水体中的TP浓度、NH-N浓度以及TN浓度是决定巢湖流域生态安全的最关键因子。     

Ecological quality scales based on phytoplankton for the implementation of Water Framework Directive in the Eastern Mediterranean

Structural changes of phytoplankton communities, often expressed through ecological indices, constitute one of the metrics for the implementation of the European Water Framework Directive (WFD). In the current study a thorough analysis of the efficiency of 22 ecological indices was performed and a small number was selected for the development of five-level water quality scales (High, Good, Moderate, Poor, and Bad). The analysis was performed on simulated communities free of the noise of field communities due to uncontrolled factors or stochastic processes. Two criteria were set for the sensitivity of indices, namely their monotonicity and linearity across the studied eutrophication spectrum. The whole procedure was based on the development of a five-level quality assessment scheme based on phytoplankton abundance. Among the indices tested, the Menhinick diversity index and three indices of evenness were the most efficient, showing consistency (monotonic behavior) and linearity and were therefore used for the development of quality scales for the WFD. An Integrated Phytoplankton Index (IPI) based on three phytoplankton metrics, chlorophyll a, abundance, and diversity is also proposed. The efficiency of these indices was evaluated for a number of sites in the Aegean, already classified in the past by various methods based on nutrient concentrations or phytoplankton data. The results indicate that the various phytoplankton metrics (chlorophyll a, abundance, and diversity) assessed or proposed in the current study, carry their own information showing differences in the final classification of areas. Therefore the establishment of synthetic indices as the IPI seems to be advantageous for the integrated assessment of coastal water quality in the framework of European policies as the WFD.     

黄河三角洲石油生产对东营湿地底栖动物群落结构和水质生物评价的影响

为了解石油开采对湿地生态系统的影响,2009年10月调查了黄河三角洲东营湿地34个样点的水体物理化学属性和大型底栖无脊椎动物群落结构。共获得3门6纲12目41科70属84个大型底栖无脊椎动物分类单元。Shannon-Wiener多样性指数(r=-0.446,P=0.02)和TN显著负相关,BI指数与理化指标无显著相关性;软体动物分类单元数与盐度(r=-0.422,P=0.028)显著负相关,与pH值(r=0.435,P=0.023)显著正相关;软体动物个体百分数同样与盐度(r=-0.395,P=0.041)呈显著负相关,与pH值(r=0.565,P=0.002)呈极显著正相关;寡毛类分类单元数与TN(r=0.524,P=0.005)极显著正相关。水体石油含量与生物指数无显著相关性。典范对应分析(CCA)显示,TN、pH、盐度是影响东营湿地底栖动物群落结构的主要环境变量,水体石油污染并不是主要的胁迫因子。寡毛类和软体动物是该地区对环境变化的主要指示生物类群。Shannon-Wiener多样性指数水质生物评价结果显示,溢洪河支流、广利河上游、挑河上游、东张水库属于清洁;轻污点位有9个,其余点位为中污或重污。