Total Phosphorus Index Research Articles

Application of Time Serial Model in Water Quality Predicting

Water resources are an indispensable and valuable resource for human survival and development. Water quality predicting plays an important role in the protection and development of water resources. It is difficult to predict water quality due to its random and trend changes. Therefore, a method of predicting water quality which combines Auto Regressive Integrated Moving Average (ARIMA) and clustering model was proposed in this paper. By taking the water quality monitoring data of a certain river basin as a sample, the water quality Total Phosphorus (TP) index was selected as the prediction object. Firstly, the sample data was cleaned, stationary analyzed, and white noise analyzed. Secondly, the appropriate parameters were selected according to the Bayesian Information Criterion (BIC) principle, and the trend component characteristics were obtained by using ARIMA to conduct water quality predicting. Thirdly, the relationship between the precipitation and the TP index in the monitoring water field was analyzed by the K-means clustering method, and the random incremental characteristics of precipitation on water quality changes were calculated. Finally, by combining with the trend component characteristics and the random incremental characteristics, the water quality prediction results were calculated. Compared with the ARIMA water quality prediction method, experiments showed that the proposed method has higher accuracy, and its Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE) were respectively reduced by 44.6%, 56.8%, and 45.8%.

Exploring the pivotal response relationship between landscape composition–configuration–intensity metrics and water quality in Taihu basin, China

Declining water quality has exacerbated water scarcity worldwide, and effective water quality management requires a solid understanding of the factors of water quality. The response of water quality to landscape composition and configuration has been extensively studied, but landscape intensity has been disregarded. Therefore, constructing a comprehensive impact factor indicator and determining the pivotal factors are essential. This study focused on the response relationship of landscape composition, configuration, and intensity metrics to water quality. Water quality index included total nitrogen (TN) and total phosphorus (TP) from 43 monthly sites in the main rivers of the Taihu Lake Basin (TLB) in 2017. The TN:TP index was calculated. We used the partial least squares regression (PLS) method to explore the response strength between each index at different temporal and spatial scales, and the coefficient of determination (R2) calculated based on PLS was 0.4677 to 0.9039, in which the simulation effect was acceptable. In terms of pivotal influenced factors, industrial and domestic effluents for TN and TP showed a major effect in crop (CDR) and forest dominated region (FDR). For the TN:TP index, the pivotal influencing factors was merely industrial waste water discharge. In the fitting based on the pivotal factors of polynomial regression (PR), the landscape threshold of industrial and domestic effluents intensities to TN in CDR were higher than FDR, and landscape threshold substantially exceeded the water quality standard lines in CDR. This research can provide a reference for water quality precision management, distribution of pollutant emissions, and regional sustainable planning from the perspective of landscape regulation in TLB.

Design and Application of Automatic Monitoring System of Water Environment Using GIS

in order to achieve more effective management and monitoring of water environment, an automatic monitoring system is designed for the water environment of Heihe River Basin in Zhangye through GIS (geographic information system). The EFDC (environmental fluid dynamics code) model is used to establish the automatic monitoring model of water environment, and the annual average data of permanganate index of Yingluoxia, Gaoya hydrological station, and Liubaqiao in Heihe River Basin from 2015 to 2019 are used to fit and verify the water quality model. The trend suggests that the simulated data of the three observation points are close to the measured data. The fitting degree reveals that the R index of fitting curve of Liubaqiao is 0.793, while that of Yingluoxia, and Gaoya hydrological station is higher than 0.8, with good fitting degree. The average relative error between the simulated value and the measured value of permanganate index (mg/L) is small, the change trend is basically consistent, and the prediction error is small. The model is successfully established and applied to the automatic monitoring and early warning system of total phosphorus index.

Multidecadal water quality deterioration in the largest freshwater lake in China (Poyang Lake): Implications on eutrophication management

Poyang Lake is the largest freshwater lake in China and a globally important wetland with various functions. Exploring the multidecadal trend of water quality and hydroclimatic conditions is important for understanding the adaption of the lake system under the pressure from multiple anthropogenic and meteorological stressors. The present study applied the Mann–Kendall trend analysis and Pettitt test to detect the trend and breakpoints of hydroclimatic, and water quality parameters (from the 1980s to 2018) and the trend of monthly–seasonal ammonia (NH4-N) and total phosphorus (TP)concentrations (from 2002 to 2018) in Poyang Lake. Results showed that Poyang Lake had undergone a highly significant warming trend from 1980 to 2018, with a warming rate of 0.44 °C/decade in terms of annual daily mean air temperature. The wind speed and water level of the lake presented a highly significant decreasing trend, whereas no notable trend was detected for precipitation variations. The annual mean total nitrogen (TN), NH4-N, TP, and permanganate index (CODMn) concentrations showed significant upward trends from the 1980s to 2018. Remarkable abrupt shifts were detected for TN, NH4-N, and CODMn in around 2003. They were in accordance with the water level breakpoint of the lake, thus implying the important role of hydrological conditions in water quality variations in floodplain lakes. A significant increasing trend has been detected for Chl-a variations during wet season from 2008 to 2018, which could be attributed to the increasing trend of nutrient concentration during the nutrient-limited phase of Poyang Lake. These hydroclimatic and water quality trends suggest a high risk of increasing phytoplankton growth in Poyang Lake. This study thus emphasizes the need for adaptive lake eutrophication management for floodplain lakes, particularly the consideration of the strong trade-off and synergies between hydroclimatic conditions and water quality variations.

Total phosphorus inference models and indices for coastal plain streams based on benthic diatom assemblages from artificial substrates

We investigated the potential for using diatoms to monitor and assess nutrient enrichment in coastal plain streams using weighted-averaging infer- ence models and diatom trophic indices. Samples were collected from low-gradient, clay- to sand-bottom streams in New Jersey (NJ), USA, using artificial substrates (diatometers). Multivariate analysis showed that conductivity was overall the most important explanatory variable. Total phosphorus (TP) expl- ained a significant proportion of the variation in diatom species composition. There was statistical justification for development of inference models for TP but not for total nitrogen (TN). We developed and tested models for inferring TP using weighted-aver- aging (WA) and weighted-averaging partial least squares (WA-PLS) regression and calibration tech- niques. We also created a diatom TP index by rescaling the inferred TP values. WA-PLS provided the best model (n = 38), which showed moderate predictive ability (rboot = 0.43; RMSEPboot = 0.30 log10 l gl -1 TP); it performed best at lower TP concentrations and tended to underestimate values above 100 l gl -1 . The TP index performed well; it assigned the majority of the index scores to the correct nutrient category. TP models and indices developed for the Coastal Plain had lower predictive ability than those developed for northern NJ and streams in other comparable geographic regions of the US. This lower performance can be attributed primarily to a data gap in the TP gradient in the calibration dataset (lack of sites with TP concentrations between 240 and 560 l gl -1 ), and a smaller number of samples. We conclude that diatom-based TP inference models and artificial substrate sampling are useful for assessing and monitoring nutrient enrichment in coastal plain streams. Given the worldwide distribution of streams similar to those in this study, these tools should be widely applicable.

Phytoplankton Community and Chlorophyll a as Trophic State Indices of Lake Skadar (Montenegro, Balkan) (7 pp)

Phytoplankton, as a first step in trophic cascades of lakes, can be a good indicator of trophic states, considering that every environmental change affects this community and many species of this community are sensitive to changes, and that they response very quickly. In this study, we tried to assess and predict the trophic state of Lake Skadar according to phytoplankton data. Water samples were collected using Ruttner sampling bottle. Temperature, dissolved oxygen, ph, conductivity and transparence were measured in situ using portable equipment. Nutrients and chlorophyll a were measured using standard spectrophotometric methods. A determination of phytoplankton species was performed using relevant keys and the counting of cells was performed using sedimentation methods. The species composition of Lake Skadar revealed 95 taxa, with Chlorophyceae and Bacillariophyceae being represented best. According to an average chlorophyll a concentration of 5.9 pg/l, Lake Skadar belongs to the mesotrophic level of the trophic scale. Developed prediction equation for chlorophyll a revealed a good prediction (R2 = 0.71) and the parameter Secchi depth was primarily correlated with chlorophyll a concentration. Trophic state indices derived from chlorophyll a and transparency, were close together, but both were below the phosphorous index. Values of trophic state indices rank the Lake Skadar as being mesotrophic. This study also showed that indices of diversity based on phytoplankton are weak indicators of trophic status and that they can well characterize only differences between assemblages and associations. According to calculated saprobic indices (ranging from 1.5 to 2.15), Lake Skadar is on betamesosaprobic level of saprobity, which means that it is moderately polluted with organic compounds. Total phosphorus is not the main limiting factor for the phytoplankton community in Lake Skadar. Disagreements between chlorophyll and the transparency index, on the one hand, and the total phosphorus index, on the other, suggest that the phytoplankton in Lake Skadar is probably limited by other factors than phosphorus, such as nitrogen, toxic substances or intense zooplankton grazing. According to the majority of investigated parameters and indices derived from phytoplankton data, Lake Skadar is mesotrophic, with tendencies toward eutrophic levels during the summer period. Long-term monitoring is required for a better estimation of state and the conditions of Lake Skadar. Further studies on factors influencing the phytoplankton community, especially zooplankton grazing and toxic substances, which were not included in this study, should be continued in the future to improve the efficiency of phytoplankton usage in estimating the ecological and trophic conditions of Lake Skadar.

Solid–liquid separation of livestock slurry: efficiency and cost

Environmental problems may arise on specialized livestock farms, which produce a surplus of nutrients in relation to crop requirements. Separation of this slurry into a liquid fraction and a dry-matter and nutrient-rich fraction, followed by transporting the nutrient-rich fraction to farms with fewer animals, may alleviate the problem. This study showed that the most informative index of separation is the reduced separation efficiency index; where an index value of 0 indicates that the nutrients are distributed equally between the solid fraction and the liquid fraction, and a value of 1 indicates that the nutrients are concentrated in the solid fraction. The reduced separation efficiency values obtained when using simple mechanical screen separators were 0.07–0.5 for dry matter (DM), 0.01–0.1 for total N (TN) and 0–0.2 for total phosphorus (TP). In comparison, decanting centrifuges were very efficient in removing DM (index: 0.36–0.74) and TP (index: 0.4–0.82), but not in separating TN (index: 0.11–0.19). The costs of a treating 4000 tonnes of slurry with a mechanical screen separator or with a decanting centrifuge are £0.44 and £2.21/tonne p.a., respectively.