Assessment of Water Quality Using Chemometrics and Multivariate Statistics: A Case Study in Chaobai River Replenished by Reclaimed Water, North China

Characterizing the impact of reservoir storage and discharge on nitrogen dynamics in an upstream wetland using a δ15N and δ18O dual-isotope approach

The identification of nitrate sources in reservoir water is important for watershed-scale surface pollution management. Significant fluctuations in river water levels arising from reservoir storage and discharge influence nitrate sources and transport processes. The Sanmenxia Reservoir, in the middle reaches of the Yellow River in China, undergoes significant water level changes (290-316 m), altering the composition of the nitrogen sources. This study employed a δ15N and δ18O dual-isotope method and MixSIAR modeling to quantify the contributions of nitrate sources. This reveals the impact of reservoir water impoundment and discharge on nitrogen dynamics in the upstream region of the wetland and the model sensitivity for each nitrate source. The results showed that the average concentrations of nitrate‑nitrogen (NO- 3-N) were elevated during the impoundment period compared to the discharge period. Nitrogen sources exhibited varying proportions in surface water, groundwater, and soil water during both the impoundment and discharge periods. The predominant sources include manure and sewage (MS), with a maximum proportion of 57.4 % in surface water. Soil nitrogen (SN) accounted for 25.8 % of groundwater nitrogen and 32.1 % of soil water nitrogen during the impoundment period, whereas, during the discharge period, soil nitrogen made up 41.4 % of surface water nitrogen, manure and sewage contributed 44.8 % of groundwater nitrogen, and manure and sewage dominated with 56.7 % of soil water nitrogen. Sensitivity analysis of the MixSIAR model revealed that the isotopic composition of the manure and sewage primary source most significantly influenced the apportionment results of the riverine nitrate source. Reservoir discharge facilitates the dissimilatory nitrate reduction to ammonium (DNRA). The migration of NO- 3 from surface water to soil water and groundwater occurred from the impoundment period to the discharge period.

Biomanipulation as a strategy for minimizing ecological risks in river supplied with reclaimed water

Reclaimed water is an effective method for addressing water pollution and shortages. However, its use may contribute to the collapse of receiving water (algal blooms and eutrophication) owing to its unique characteristics. A three-year biomanipulation project was conducted in Beijing to investigate the structural changes, stability, and potential risks to aquatic ecosystems associated with the reuse of reclaimed water in rivers. During the biomanipulation, the proportion of Cyanophyta in the community structure of phytoplankton density in river supplied with reclaimed water decreased, and the community composition shifted from Cyanophyta and Chlorophyta to Chlorophyta and Bacillariophyta. The biomanipulation project increased the number of zoobenthos and fish species and significantly increased fish density. Despite the significant difference in aquatic organisms community structure, diversity index and community stability of aquatic organisms remained stable during the biomanipulation. Our study provides a strategy for minimizing the hazards of reclaimed water through biomanipulation by reconstructing the community structure of reclaimed water, thereby making it safe for large-scale reuse in rivers.

Impacts of anthropogenic groundwater recharge (AGR) on nitrate dynamics in a phreatic aquifer revealed by hydrochemical and isotopic technologies

Although anthropogenic groundwater recharge (AGR) can either elevate or decline the concentration of nitrate in the phreatic aquifer with high hydraulic conductivity, the long-term impact of AGR on nitrate dynamics in the phreatic aquifer and its reason is seldom disclosed. In this study, the hydrogen and oxygen stable isotopes (δ²H-H₂O and δ¹⁸O-H₂O) combined with mixing stable isotope analysis in R (MixSIAR) were used to group the study area into the dominant area of AGR by surface water (AGRSW) and the dominant area of natural groundwater recharged by precipitation (NGRP). Hydrochemical parameters and multiple stable isotopes, including δ²H-H₂O, δ¹⁸O-H₂O, δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, and δ¹³C-DIC, were applied to explore the impacts of AGR on the concentration, biogeochemical processes, and main sources of nitrate. The results showed that AGR by surface water with low nitrate content can reduce nitrate pollution in groundwater. The characteristic of δ¹⁸O-NO₃^- value revealed that nitrification was the primary biogeochemical process of nitrogen in groundwater. AGR may enhance nitrification as indicated by the δ¹⁸O-NO₃^- value closer to the nitrification theoretical line. Dual nitrate stable isotopes and MixSIAR revealed that chemical fertilizer (CF), soil nitrogen (SN), and surface water (SW) contributed 10.88%, 49.92%, and 27.64% to nitrate in AGRSW groundwater, respectively, which was significantly different from their contributions to NGRP groundwater (p < 0.05). Notably, AGR significantly increased the contribution of SW but decreased the contribution of CF and SN in groundwater. This study provided a basis and guidance for groundwater quality assessment and pollution control in the phreatic aquifer with high hydraulic conductivity.

Assessing the Water Pollution of the Brahmaputra River Using Water Quality Indexes

Water quality is continuously affected by anthropogenic and environmental conditions. A significant issue of the Indian rivers is the massive water pollution, leading to the spreading of different diseases due to its daily use. Therefore, this study investigates three aspects. The first one is testing the hypothesis of the existence of a monotonic trend of the series of eight water parameters of the Brahmaputra River recorded for 17 years at ten hydrological stations. When this hypothesis was rejected, a loess trend was fitted. The second aspect is to assess the water quality using three indicators (WQI)-CCME WQI, British Colombia, and a weighted index. The third aspect is to group the years and the stations in clusters used to determine the regional (spatial) and temporal trend of the WQI series, utilizing a new algorithm. A statistical analysis does not reject the hypothesis of a monotonic trend presence for the spatially distributed data but not for the temporal ones. Hierarchical clustering based on the computed WQIs detected two clusters for the spatially distributed data and two for the temporal-distributed data. The procedure proposed for determining the WQI temporal and regional evolution provided good results in terms of mean absolute error, root mean squared error (RMSE), and mean absolute percentage error (MAPE).

Impacts of storm events on chlorophyll-a variations and controlling factors for algal bloom in a river receiving reclaimed water

Harmful algal bloom is prevalent in the reclaimed-water-source (RWS) river caused by the excessive nutrient's inputs. Rainfall water may be the sole nutrient-diluted water source for the RWS river. However, the effects of storm events on the algal bloom in the RWS river are poorly understood. This study presents chlorophyll-a (Chl-a) variations before, during, and after the initial storm events (Pre-storm, In-storm, and Post-storm) at four representative sites with distinct hydraulic conditions in a dam-regulated RWS river system, Beijing. The response of Chl-a to the initial storm events mostly depends on the ecosystem status that caused by the river hydraulic properties. The upstream is more river-like and downstream is more lake-like. In the river-like system, elevated water temperature (WT, increased by 2 %) could support the dominating algae (diatom) growth (Chl-a increased by 130 %) from Pre-storm to In-storm period. In the lake-like system, the dominant algae (blue algae) declined (Chl-a sharply decreased by 96%-99 %) due to the lower WT (decreased by 3%-7%) and increased flow velocities from Pre-storm to In-storm period. During the Post-storm period, the dominant algae break out (Chl-a surged by 20%-319 %) in the lake-like system caused by the recovered WT (increased by 3%-6%) and flow velocity. The occurrence of algal bloom can be predicted by the Random Forest (RF) model based on water quality parameters such as total nitrogen (TN). The thresholds of algal bloom for the Pre-storm, In-storm, and Post-storm periods were identified as 30 μg/L, 10 μg/L, and 10 μg/L, respectively. The two driven factors were WT and nitrate (NO₃-N) for the Pre-storm period and were WT and TN for the In- & Post-storm periods. A higher risk of algal bloom is highlighted during the initial storm events in the RWS river. We propose recommendations for improving water quality in the RWS river systems under the climatic change.

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

The efficiency improvement of wastewater recycling has been prioritized by ‘Goal 6’ of the United Nations Sustainable Development initiative. A methodology is developed to synchronously profile multiple water-quality indices of a wastewater electrodialysis (ED) process. The non-linear multifactorial screener is exclusively synthesized by assembling proper R-based statistical freeware routines. In sync with current trends, the new methodology promotes convenient, open and rapid implementation. The new proposal unites the ‘small-and-fast’ data-sampling features of the fractional multifactorial designs to the downsizing, by microclustering, of the multiple water quality indices—using optimized silhouette-based classification. The non-linear multifactorial profiling process is catalyzed by the ‘ordinalization’ of the regular nominal nature of the resulting optimum clusters. A bump chart screening virtually eliminates weak performances. A follow-up application of the ordinal regression succeeds in assigning statistical significance to the resultant factorial potency. The rank-learning aptitude of the new profiler is tested and confirmed on recently published wastewater ED-datasets. The small ED-datasets attest to the usefulness to convert limited data in real world applications, wherever there is a necessity to improve the quality status of water for agricultural irrigation in arid areas. The predictions have been compared with other techniques and found to be agreeable.

Spatio-temporal variations in physicochemical water quality parameters of Lake Bunyonyi, Southwestern Uganda

The current study was carried out to examine the spatial and temporal variations of physicochemical water quality parameters of Lake Bunyonyi. The observations were made on the surface water of Lake Bunyonyi for 1 year to determine the water quality. The basic 12 variables used to determine the quality of water were measured monthly at nine stations. Water temperature, dissolved oxygen (DO), turbidity, electric conductivity (EC), pH and Secchi depth (SD) were measured in the field, while parameters like total nitrogen (TN), total phosphorus (TP), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N), soluble reactive phosphorus (SRP) were determined following APHA 2017 standard guidelines for physicochemical analysis. Taking into account standard guidelines for drinking water by the Uganda National Bureau of Standards (UNBS) and the World Health Organization (WHO), the water quality index (WQI) was used to determine the water quality. Temperature, DO, pH, turbidity and EC did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). Likewise, TN, TP, NO2-N, NO3-N and SRP did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). The WQI values ranged from 28.36 to 49 across and from 28.2 to 56.2 between study months with an overall mean value of 36.9. The measured water quality variables did not exceed the UNBS and WHO standards for drinking water in all months and at all stations. According to these values, the water quality of Lake Bunyonyi generally belongs to the ‘good’ class in terms of drinking water quality based on the WQI classification. The study findings are fundamentally important for policy makers in setting guidelines for effective lake management.

Assessing Water Quality by Statistical Methods

Water is one of the natural resources most affected by anthropogenic activities, like industry, agriculture, and traffic [...]