Prediction of E. coli Concentrations in Agricultural Pond Waters: Application and Comparison of Machine Learning Algorithms

The microbial quality of irrigation water is an important issue as the use of contaminated waters has been linked to several foodborne outbreaks. To expedite microbial water quality determinations, many researchers estimate concentrations of the microbial contamination indicator Escherichia coli (E. coli) from the concentrations of physiochemical water quality parameters. However, these relationships are often non-linear and exhibit changes above or below certain threshold values. Machine learning (ML) algorithms have been shown to make accurate predictions in datasets with complex relationships. The purpose of this work was to evaluate several ML models for the prediction of E. coli in agricultural pond waters. Two ponds in Maryland were monitored from 2016 to 2018 during the irrigation season. E. coli concentrations along with 12 other water quality parameters were measured in water samples. The resulting datasets were used to predict E. coli using stochastic gradient boosting (SGB) machines, random forest (RF), support vector machines (SVM), and k-nearest neighbor (kNN) algorithms. The RF model provided the lowest RMSE value for predicted E. coli concentrations in both ponds in individual years and over consecutive years in almost all cases. For individual years, the RMSE of the predicted E. coli concentrations (log10 CFU 100 ml−1) ranged from 0.244 to 0.346 and 0.304 to 0.418 for Pond 1 and 2, respectively. For the 3-year datasets, these values were 0.334 and 0.381 for Pond 1 and 2, respectively. In most cases there was no significant difference (P > 0.05) between the RMSE of RF and other ML models when these RMSE were treated as statistics derived from 10-fold cross-validation performed with five repeats. Important E. coli predictors were turbidity, dissolved organic matter content, specific conductance, chlorophyll concentration, and temperature. Model predictive performance did not significantly differ when 5 predictors were used vs. 8 or 12, indicating that more tedious and costly measurements provide no substantial improvement in the predictive accuracy of the evaluated algorithms.

Assessment of correlation amongst physico-chemical, topographical, geological, lithological and soil type parameters for measuring water quality of Rawal watershed using remote sensing

The quality of water is traditionally assessed by the collection of physico-chemical parameters, i.e., pH, turbidity, dissolved oxygen of the water bodies. However, the variations in environmental factors may have an impact on the quality of water, as changes in these attributes may affect the water bodies. These factors include the topographical, geological, lithological and soil type parameters of the watershed. In this study, the relationship amongst the physico-chemical, topographical, geological, lithological and soil type parameters of Rawal watershed was evaluated. The parameters included in the present study could be classified as follows: (a) water quality parameters (b) topographical parameters, (c) geological parameters, (d) lithological parameters, and (e) soil type parameters. Water quality parameters consisted of dissolved oxygen, pH, turbidity and temperature. The topographical parameters include the slope and aspect of the watershed while the lithological, geological and soil type parameters include the lithology, geology and soil type of the watershed. Pearson's correlation was used to determine the relationship amongst these different parameters. The results have revealed that the correlations of the topographical, lithological, geological parameters with the water quality parameters in the Rawal watershed for the monsoon seasons of June to August mostly have the same trend. Throughout the four year time period, turbidity and temperature parameters had positive correlations with soil type (ranging 0.03–0.24), however had weak correlation with geological and lithological parameters. Dissolved oxygen did not show any relationship with topographical and lithological parameters. The results for pH show that it has weak to fair positive correlations with topographical parameters. However, this analysis is based on the Landsat 8 images extracted for the monsoon seasons of the years of 2017–2020, and to examine a more prominent impact of geographical or environmental factors on the physico-chemical features, a large dataset should be considered.

Water Quality and Anthropogenic Pressures in a Changing Environment: The Arges River Basin, Romania

The objective of this work was to present several benchmarks regarding the water quality at hydrological basin level under increasing anthropogenic pressures. The first part briefly describes the sources of water pollution, the hydromorphological pressures, and the main water quality parameters widely used for the assessment. The second part presents as an example the dynamics of several water quality parameters recorded between 2007 and 2014 downstream of Argeș River, Romania, near the confluence with the Danube River. Argeș River supplies water for several important Romanian cities including Bucharest, and from here comes the rationale of the work, which envisages characterizing water quality status to substantiate proper water management. The following parameters were statistically analyzed: water temperature, suspended solids, pH, dissolved oxygen, biochemical oxygen demand, ammonium, nitrates, nitrites, and dissolved heavy metals. The factor analysis results showed that the first factor contains temperature and dissolved oxygen, the second has the heavy metals, the third groups have the ammonium and pH, the fourth contains the TSS and nitrites, while the fifth is formed by BOD5 and nitrates. Water quality plays a significant role in promoting socioeconomic development and maintaining viable ecosystems. The protection of water quality requires improved monitoring and reliable watershed management plans.

Education And Training of Bengawan Solo Water Cleaning Using Filtration Method in Karanggeneng Village, Karanggeneng District, Lamongan Regency

The northern part of Lamongan Regency is an area that is geologically and geographically vulnerable to freshwater. The condition of the existing water sources is not suitable for use as a source of clean water, because the water is brackish and green in color. The eutrophication process occurs due to excessive use of fertilizers for pond business, so that the nitrogen and phosphate content is high. The community in Karanggeneng village uses water from the Bengawan Solo River for daily use. The water condition of Bengawan Solo in the rainy season is dark brown in color because it contains a lot of soil, while in the dry season it is green because it contains a lot of pesticide or fertilizer residues discarded by farmers. From the problems above, it is necessary to socialize the water purification of Bengawan Solo by using the filtration method. Socialization activities are carried out directly to the Karanggeneng village community. This activity is carried out in two stages, the first is the preparation of tools and materials, the second stage is socialization to the community. In the first stage, chemical and physical water quality parameters were tested. In the second stage, the community was very enthusiastic about the implementation of this activity. The use of filtration methods is easy and inexpensive to be applied on a household scale. Suggestions, it is necessary to disseminate information to the wider community so that all people can access clean water for their daily needs. the second stage is socialization to the community. In the first stage, chemical and physical water quality parameters were tested. In the second stage, the community was very enthusiastic about the implementation of this activity. The use of filtration methods is easy and inexpensive to be applied on a household scale. Suggestions, it is necessary to disseminate information to the wider community so that all people can access clean water for their daily needs. the second stage is socialization to the community. In the first stage, chemical and physical water quality parameters were tested. In the second stage, the community was very enthusiastic about the implementation of this activity. The use of filtration methods is easy and inexpensive to be applied on a household scale. Suggestions, it is necessary to disseminate information to the wider community so that all people can access clean water for their daily needs.

A systematic study of uranium in groundwater and its correlation with other water quality parameters

A parametric investigation was carried out to estimate the Uranium concentration and other associated water quality parameters for the groundwater in Deoghar district, Jharkhand. Total 150 groundwater samples have been collected from dig wells, hand pumps, tube wells, etc. for the pre and post-monsoon seasons. A Quantalase Uranium analyzer was used to measure the uranium concentration. The distribution of pH, TDS, DO, nitrate, sulfate, uranium along with the radiation has been determined. It was found that the uranium concentration in groundwater varies from 0.10 to 11.30ppb in pre-monsoon and 0.15–6.50ppb in the post-monsoon which is well below the normal tolerance limit (i.e.30 μg/l WHO). This low availability of Uranium has been attributed due to the existence of a lesser number of rocks containing uranium as a source in that area. An attempt has been made to correlate the uranium concentration with the water quality parameters for both seasons. The correlation data reveals that ORP, nitrate, phosphate, calcium, and magnesium show a positive correlation with uranium concentration for both seasons on the other hand TDS, EC, temperature, DO, fluoride, and chloride show negative correlation. The positive correlation implies that uranium may be present in groundwater as a dissolved salt of these parameters. Comparative studies for the parameters have been done for both the seasons and various factors have been discussed for the occurrence of the same. The annual effective dose associated with the ingestion of uranium by the population of the region has been estimated using USPEA equations.

Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters.

Assessment of Spatio-temporal Variations of Selected Water Quality Parameters of Lake Ziway, Ethiopia Using Multivariate Techniques

Lake Ziway is shallow freshwater located in Northern part of Ethiopian Rift Valley. It is characterized as semi-arid to sub-humid type of climate. Expansions of the flower industry, widespread fisheries, intensive agricultural activities, fast population growth lead to deterioration of water quality and depletion of aquatic biota. In this study, spatial and temporal variations of selected water quality parameters of Lake Ziway were evaluated using multivariate statistical techniques in the study periods of 2014 and 2015. Monthly water quality data were collected from nine sampling stations during dry and wet seasonal basis for analysis of 15 water quality parameters. Mean nutrient concentrations showed increasing trend and were higher in Floriculture effluent (Fb) and Floriculture effluent after mixing in the lake (Fa) in all seasons. These sites were also characterized by high electrical conductivity (EC) and total dissolved solid (TDS). All the nine sampling sites were categorized into three pollution levels according to their water quality features using cluster analysis (CA). Accordingly, sampling sites Fb and Ketar River (Kb) are highly and moderately polluted in both seasons, respectively. On the other hand, sampling sites at the center (C), Meki river mouth (Ma), Ketar river mouth (Ka), Meki River (Mb), Korekonch (Ko) and Fa in dry season and Ka, C, Ma, Ko, Bulbula river mouth (B) and Fa during wet season were less polluted. Principal component analysis (PCA) analysis also showed the pollutant sources were mainly from Fb during dry season Mb and Kb during wet season. The values of comprehensive pollution index illustrated the lake is moderately and slightly polluted in dry and wet seasons, respectively. Comparatively, the pollution status of the lake is high around floriculture effluent discharge site and at the two feeding rivers (Kb and Mb) due to increasing trends in agrochemical loads. This may lead to long term ecological changes in the lake unless possible measures taken.