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Water is essential for human activities and economic development, and the water environment significantly influences ecological balance and global climate. China and Southeast Asia are the most populous areas in the world, and their water resources are deteriorating day by day. We focus on five representative cities such as, Beijing, Jakarta, Hanoi, Kathmandu and Manila to investigate water-environmental problems with the ultimate goal of providing recommendations for sustainable urban water management. The study found that (1) the water environment of all cities has been polluted to varying levels, while the pollution has improved in Beijing and Jakarta, and the situation in other regions is severe. (2) The aquatic biodiversity has reduced, and its pollution is mainly caused by organic pollutants and decreasing river flow. In addition, numerous people live in megacities without access to clean surface water or piped drinking water, which greatly increases the use of groundwater. Further, frequent floods in the world leads to serious damage to urban infrastructure and further deterioration of water environment quality. To address these problems, countries and organizations have begun to construct wastewater treatment plants and develop water-saving technology to ensure healthy and sustainable development of water environment. The results and practical recommendations of this study can provide scientific insights for future research and management strategies to address water quality challenges during ongoing policy debates and decision-making processes., (© 2021. The Author(s) under exclusive licence to Royal Swedish Academy of Sciences.)

Understanding wetland water quality dynamics and associated influencing factors is important to assess the numerous ecosystem services they provide. We present a combined self-organizing map (SOM) and linear mixed-effects model (LMEM) to relate water quality variation of multipond systems (MPSs, a common type of non-floodplain wetlands in agricultural regions of southern China) to their extrinsic and intrinsic influences for the first time. Across the 6 test MPSs with environmental gradients, ammonium nitrogen (NH 4 -N), total nitrogen (TN), and total phosphate (TP) almost always exceeded the surface water quality standard (2.0, 2.0, and 0.4 mg/L, respectively) in the up- and midstream ponds, while chlorophyll-a (Chl-a) exhibited hypertrophic state (≥28 μg/L) in the midstream ponds during the wet season. Synergistic influences explained 69±12% and 73±10% of the water quality variations in the wet and dry season, respectively. The adverse, extrinsic influences were generally 1.4, 6.9, 3.2, and 4.3 times of the beneficial, intrinsic influences for NH + -N), total nitrogen (TN), and total phosphate (TP) almost always exceeded the surface water quality standard (2.0, 2.0, and 0.4 mg/L, respectively) in the up- and midstream ponds, while chlorophyll-a (Chl-a) exhibited hypertrophic state (≥28 μg/L) in the midstream ponds during the wet season. Synergistic influences explained 69±12% and 73±10% of the water quality variations in the wet and dry season, respectively. The adverse, extrinsic influences were generally 1.4, 6.9, 3.2, and 4.3 times of the beneficial, intrinsic influences for NH 4 + -N, nitrate nitrogen (NO 3 - -N), TP, and potassium permanganate index (COD Mn ), respectively, although the influencing direction and degree of forest and water area proportion were spatiotemporally unstable. While COD Mn was primarily linked with rural residential areas in the midstream, higher TN and TP concentrations in the up- and midstream were associated with agricultural land, and NH 4 + -N reflected a small but non-negligible source of free-range poultry feeding. Pond surface sediments exhibited consistent, adverse effects with amplifications during rainfall, while macrophyte biomass can reflect the biological uptake of COD Mn and Chl-a, especially in the mid- and downstream during the wet season. Our study advances nonpoint source pollution (NPSP) research for small water bodies, explores nutrient "source-sink" dynamics, and provides a timely guide for rural planning and pond management. The modelling procedures and analytical results can inform refined assessment of similar NFWs elsewhere, where restoration efforts are required., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Megacities are facing serious water pollution problems due to urbanization, rapid population growth and economic development. Water is an essential resource for human activities and socio-economic development and water quality in urban settings has important implications for human and environmental health. Urbanization and lack of sewerage has left the water in Jakarta, Indonesia in a heavily polluted condition. Rigorous assessment of urban water quality is necessary to understand the factors controlling water quality conditions. We use trend analysis to assess the current water quality conditions in Jakarta, focusing on Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), and Total Suspended Solids (TSS). In most monitoring stations analyzed, BOD and TSS concentrations have decreased over time, but from large starting concentrations. DO in most monitoring stations has increased. Although Jakarta's water quality has shown some improvement, it remains heavily impaired. The average value of BOD is low in upper stream stations compared to middle and lower stream stations. BOD and TSS trends of some water quality stations in middle and lower streams show increasing trends. Cluster analysis results suggest three groups for BOD and TSS, and four groups for DO. Understanding water quality conditions and factors that control water quality suggest strategies for improving water quality given current trends in climate, population growth and urban development. Results from this study suggest research directions and management strategies to address water quality challenges., Competing Interests: RKR is affiliated with Environment & Resource Management Consultant (P) Ltd. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Comprehensive understanding of the long-term trends and seasonality of water quality is important for controlling water pollution. This study focuses on spatio-temporal distributions, long-term trends, and seasonality of water quality in the Yangtze River basin using a combination of the seasonal Mann-Kendall test and time-series decomposition. The used weekly water quality data were from 17 environmental stations for the period January 2004 to December 2015. Results show gradual improvement in water quality during this period in the Yangtze River basin and greater improvement in the Uppermost Yangtze River basin. The larger cities, with high GDP and population density, experienced relatively higher pollution levels due to discharge of industrial and household wastewater. There are higher pollution levels in Xiang and Gan River basins, as indicated by higher NH4-N and CODMn concentrations measured at the stations within these basins. Significant trends in water quality were identified for the 2004-2015 period. Operations of the three Gorges Reservoir (TGR) enhanced pH fluctuations and possibly attenuated CODMn, and NH4-N transportation. Finally, seasonal cycles of varying strength were detected for time-series of pollutants in river discharge. Seasonal patterns in pH indicate that maxima appear in winter, and minima in summer, with the opposite true for CODMn. Accurate understanding of long-term trends and seasonality are necessary goals of water quality monitoring system efforts and the analysis methods described here provide essential information for effectively controlling water pollution.

Nutrients and suspended sediment in surface water play important roles in aquatic ecosystems and contribute strongly to water quality with implication for drinking water resources, human and environmental health. Estimating loads of nutrients (nitrogen and phosphorus) and suspended sediment (SS) is complicated because of infrequent monitoring data, retransformation bias, data censoring, and non-normality. To obtain reliable unbiased estimates, the Maintenance of Variance-Extension type 3 (MOVE. 3) and the regression model Load Estimator (LOADEST) were applied to develop regression equations and to estimate total nitrogen (TN), total phosphorus (TP) and SS loads at five sites on the Ishikari River, Japan, from 1985 to 2010. Coefficients of determination (R(2)) for the best-fit regression models for loads of TN, TP, and SS for the five sites ranged from 71.86% to 90.94%, suggesting the model for all three constituents successfully simulated the variability in constituent loads at all studied sites. Estimated monthly average loads at Yishikarikakou-bashi were larger than at the other sites, with TN, TP, and SS loads ranging from 8.52×10(3) to 2.00×10(5) kg/day (Apr. 1999), 3.96×10(2) to 5.23×10(4) kg/ day (Apr. 1999), and 9.21×10(4) to 9.25×10(7) kg/day (Sep. 2001), respectively. Because of variation in river discharge, the estimated seasonal loads fluctuated widely over the period 1985 to 2010, with the greatest loads occurring in spring and the smallest loads occurring in winter. Estimated loads of TN, TP, and especially SS showed decreasing trends during the study period. Accurate load estimation is a necessary goal of water quality monitoring efforts and the methods described here provide essential information for effectively managing water resources., (Copyright © 2013 Elsevier B.V. All rights reserved.)

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.

The Qinling Mountains are located in a transition zone between (semi)-arid regions in north China and humid regions in south China. The water resource and water ecology of regional rivers are strongly affected by climate change and human activity. In this paper, the stochastic simulation of river water regulation was performed and an optimal water regulation scheme of rubber dam projects was developed by establishing a multi-objective stochastic constraint water regulation model of rubber dam projects based on the coupling of a distributed hydrological model and a water balance model. Results show that a 40% reduction of water occurred in the lower river channel due to the operation of water supply project in the upper reach and impoundment by rubber dam projects in the lower reaches. This water reduction was associated with decreased water environment selfpurification capacity and serious deterioration of water quality for smaller ecological basic flow and mean flow velocity. By establishing a multi-objective stochastic constraint programming model, the average velocity and the ecological basic flow at different adjusting heights of rubber dams are determined. The regulation scheme of rubber dam projects we propose in this paper may optimize the current river water management strategies and help to improve the river water quality environment in urban rivers. [ABSTRACT FROM AUTHOR]

Vegetated floodplains and wetlands trap particles, a process that is important for water quality and wetland function and morphology. The rates of particle removal by vegetation remain poorly characterized, especially for small particles and vegetation coated with biofilm. In this study, we measured capture rates of road dust by arrays of grass-like synthetic vegetation in a laboratory flume. We performed 40 experiments in which stem density, flow velocity, the presence of biofilm, and initial particle concentration varied, and used an in situ particle size analyzer to measure the concentration of a continuous particle size distribution (1.25-250 μm diameter). We fit first-order decay models to the particle concentration measurements to determine particle capture rates and found that capture rates increased with particle size, stem density, and the presence of biofilm. Capture rates decreased with increasing flow velocity, which suggests that fast flows may resuspend particles from stems. We also calculated percent particle capture efficiencies and fit a new empirical model for capture efficiency to our results. We found that particle capture efficiency was highest for low stem density treatments and propose that stem density affects capture by altering turbulent kinetic energy. [ABSTRACT FROM AUTHOR]

Two algorithms (the fractal (FPA) and the solid (SPA) particle aggregation) simulating fine particle dynamics were developed and incorporated in the Dynamic Lake Model with Water Quality (DLM-WQ). The previous aggregation model in DLM-WQ required a value for the probability of aggregation independent of particle size distribution (PSD) and concentration. In this study, we developed an algorithm that estimates the probability of aggregation based on PSD, sediment concentration and algal concentration. DLM-WQ was calibrated and validated using measured event-based fine particle data from two Lake Tahoe monitoring sites (1999-2010) and estimated external nutrient and fine particle loadings. Secchi depths estimated using the two algorithms with new aggregation rates varied slightly although predictions were very close to each other and to measured Secchi depths. However, Secchi depths and fine particles estimated by the two algorithms with constant aggregation rates deviate largely from those of measured values. Results using measured data and fine particles predicted by the two algorithms showed that fine particles account for approximately 50% of the total light scattering for all sources making it the most significant contributor. Because approximately 70-75% of the scattering is due to fine particles between 0.5 and 8 µm, management efforts should be targeted to control the transport of fine particles from the watershed to the lake. The updated DLM-WQ can be used to simulate lake response in terms of Secchi depth clarity to different fine sediment and nutrients inputs, and inform development of lake management guidelines to facilitate TMDL implementation where water quality is a concern. [ABSTRACT FROM AUTHOR]

Highlights: [•] A spatiotemporal evaluation of water quality incidents in Japan has been analyzed. [•] Water pollution incidents almost tripled in the 12years from 1996 to 2007. [•] Oil makes up the largest proportion of pollutants nationwide (76.61%). [•] The main cause was “Unknown” (43%), followed by “Poor working practice”. [Copyright &y& Elsevier]