Spatiotemporal trend analysis of recent river water quality conditions in Japan

Advancing methodologies for assessing the impact of land use changes on water quality: a comprehensive review and recommendations

With increasing scholarly focus on the ramifications of land use changes on water quality, although substantial research has been undertaken, the findings demonstrate pronounced spatial variability and the heterogeneity of research methodologies. To address this critical gap, this review offers a rigorous evaluation of the strengths and limitations of current research methodologies, providing targeted recommendations for refinement. It systematically assesses the existing body of literature concerning the influence of land use changes on water quality, with particular emphasis on the spatial heterogeneity of research results and the uniformity of employed methodologies. Despite variations in geographical contexts and research subjects, the methodological paradigms remain largely consistent, typically encompassing the acquisition and analysis of water quality and land use data, the delineation of buffer zones, and the application of correlation and regression analyses. However, these approaches encounter limitations in addressing regional disparities, nonlinear interactions, and real-time monitoring complexities. The review advocates for methodological advancements, such as the integration of automated monitoring systems and IoT technologies, alongside the fusion of deep learning algorithms with remote sensing techniques, to enhance both the precision and efficiency of data collection. Furthermore, it recommends the standardization of buffer zone delineation, the reinforcement of foundational water quality assessments, and the utilization of catchment-scale analyses to more accurately capture the influence of land use changes on water quality. Future inquiries should prioritize the development of interdisciplinary ecological models to elucidate the interaction and feedback mechanisms between land use, water quality, and climate change.

Longitudinal Chemical Gradients and the Functional Responses of Nutrients, Organic Matter, and Other Parameters to the Land Use Pattern and Monsoon Intensity

River water quality degradation is one of the hottest environmental issues worldwide. Therefore, monitoring water quality longitudinally and temporally is crucial for effective water management and contamination control. The main aim of this study was to assess the longitudinal variations in water quality in the mainstream of the Han River, Korea, from 2015 to 2019. The trophic state classification (TSC), microbial pollution indicator (MPI), and river pollution index (RPI) were calculated to characterize river water quality and revealed more serious pollution toward the downstream zone (Dz) due to agricultural and urban-dominated areas. The biodegradability index (BI) indicated that non-biodegradable organic pollutants are increasing in the water body from the urban and animal wastewater treatment plants. Nutrients, organic matter contents, total suspended solids, ionic factors, and algal chlorophyll were higher in the Dz than in any other zones and were markedly influenced by the summer monsoon. Empirical analysis showed that nutrients and organic matter had positive linear functional relations with agricultural and urban coverage and negative linear relations with forest coverage. The pollutant-transport function suggested that suspended solids act as TP and TN carriers. Regression analysis indicated that TP (R2 = 0.47) has more positive functional relations with algal growth than TN (R2 = 0.22). Our findings suggest that a combination of empirical models and pollution indices might be utilized to assess river water quality and that the resulting information could aid policymakers in managing the Han River.

Long-term nationwide spatiotemporal changes of freshwater temperature in Japan during 1982-2016

We analyzed freshwater temperature data from 1982 to 2016 throughout Japan to better understand how waters are warming in Japan. We used linear regression to determine the temperature change rate and Mann-Kendall tests to identify significant temporal trends in the annual maximum and mean temperatures. Among 11,240 monitoring sites screened, 159 with fewer missing values were selected for analysis. On the basis of this analysis, we identified and ranked the sites showing significant temporal increasing or decreasing trends for future management. At nearly half (42%) of the analyzed sites, the annual mean freshwater temperature was increasing; thus, in the future, adverse impacts from warm temperatures may increase in those aquatic ecosystems. The temperature change rate of fresh water was higher than that of air, indicating that the observed increases in freshwater temperature were not due to atmospheric warming only. Among individual sites, the annual maximum freshwater temperature change rate ranged from -1.27 to 1.91 °C/decade, and the annual mean rate ranged from -1.13 to 1.28 °C/decade. Few other studies have reported decreasing temperatures for fresh water. We expect our results will improve understanding of how freshwater temperatures are changing at a large scale, enhance understanding of human impacts on the aquatic environment, support effective management of ecosystems experiencing temperature changes, and help to minimize the loss of biodiversity over the next half century.

Modelling of River Flow Using Particle Swarm Optimized Cascade-Forward Neural Networks: A Case Study of Kelantan River in Malaysia

Water resources management in Malaysia has become a crucial issue of concern due to its role in the economic and social development of the country. Kelantan river (Sungai Kelantan) basin is one of the essential catchments as it has a history of flood events. Numerous studies have been conducted in river basin modelling for the prediction of flow and mitigation of flooding events as well as water resource management. This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). The result is compared with those trained with the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithm. The outcome of this study indicates that there is a strong correlation between river flow and some meteorological and weather variables (weighted rainfall, average evaporation and temperatures). The correlation scores (R) obtained between the target variable (river flow) and the predictor variables were 0.739, −0.544, and −0.662 for weighted rainfall, evaporation, and temperature, respectively. Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. The reliable result and predictive performance of the model is useful for decision makers during water resource planning and river management. The constructed modelling procedure can be adopted for future applications.

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 (COD_Mn) concentrations showed significant upward trends from the 1980s to 2018. Remarkable abrupt shifts were detected for TN, NH₄-N, and COD_Mn 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.

Long-term spatiotemporal changes of 15 water-quality parameters in Japan: An exploratory analysis of countrywide data during 1982-2016

We conducted an exploratory analysis of 15 water-quality parameters collected countrywide during 1982-2016 to better understand human impacts on aquatic ecosystems in Japan. We used the Mann-Kendall test to identify temporal trends. On the basis of this analysis, we identified and ranked the sites for future management where there were trends toward lower water quality. The study showed general improvement of dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, Escherichia coli counts, n-hexane extracts, total nitrogen, total phosphorus, and total zinc. We concluded that management of wastewater has been effective throughout Japan, but with the caveat that conditions have deteriorated at some sites, which should be the focus of studies aimed at identifying the causes of the lower water quality. Concentrations of chloroform, formaldehyde, nonylphenol, and linear alkylbenzene sulfonates, which are toxic environmental pollutants that can have adverse effects on human and ecosystem health, showed significant increasing or decreasing temporal trends at only a few monitoring sites. Sites where concentrations of these toxicants increased should be targeted for further study to determine whether remedial actions are needed.

Water quality trend assessment in Jakarta: A rapidly growing Asian megacity

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.

Fine-scale geographic clustering pattern of human T-cell leukemia virus type 1 infection among blood donors in Kyushu-Okinawa, Japan

Human T‐cell leukemia virus type I (HTLV‐1) infection is endemic in Japan, particularly clustered in the southwestern district, Kyushu‐Okinawa, which consists of eight prefectures that further consist of 274 municipalities. However, no information is available about the fine‐scale distribution of HTLV‐1 infection within Kyushu‐Okinawa. To assess the municipal‐level distribution of people with HTLV‐1 infection in Kyushu‐Okinawa, we performed a cross‐sectional study using a fine‐scale geographic information system map based on HTLV‐1 screening test results from the Japanese Red Cross database from September 2012 to February 2014. Of the 881 871 (646 914 male, 234 957 female) screened blood donors, 981 were seropositive for HTLV‐1 by confirmatory test. The seroprevalence was 0.11% (95% confidence interval [CI] 0.10%‐0.12%) for all, 0.094% (95% CI, 0.09%‐0.10%) for male, and 0.16% (95% CI, 0.14%‐0.18%) for female individuals. The sex‐ and age‐specific HTLV‐1 seroprevalence varied significantly across municipalities; particularly, the seroprevalence among women aged 50 years was significantly higher than that of men in both the mainland of Kyushu‐Okinawa and the satellite island, in all of which the seroprevalence of HTLV‐1 was more than 1.2%. These results show that, even in the Kyushu‐Okinawa district, there are endemic clusters of HTLV‐1 in small areas. This suggests that public health education programs are needed to eliminate new HTLV‐1 infection in these areas.

Modelling the effects of meteorological parameters on water temperature using artificial neural networks

Water temperature affects all biological and chemical processes in water; therefore, it is an extremely important water quality parameter. Meteorological factors are among the most important factors that affect water temperatures. The aim of this study is to develop an artificial neural network (ANN) model to investigate the effects of meteorological parameters on water temperatures at Kızılırmak River in Turkey. Water temperature data were collected from gauging stations on Kızılırmak River, and meteorological data were acquired from the nearest meteorological stations. Air temperature, wind speed, relative humidity, and previous water temperatures were formed the input parameters. The model output included water temperatures. All data were available for the 1995-2007 period, with occasional missing records. The activation functions of the ANN model and the number of neurons in the hidden layer were selected by trial-and-error method to find the best results. The root mean square error and the correlation coefficient between observed and simulated water temperatures were used to assess the model success. The best results were obtained by using sigmoid activation function and scaled conjugate gradient algorithm. This study showed that meteorological data can be used to simulate water temperature with ANN model for Kızılırmak River.

Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China

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.

Spatiotemporal patterns and source attribution of nitrogen pollution in a typical headwater agricultural watershed in Southeastern China

Excessive nitrogen (N) discharge from agriculture causes widespread problems in aquatic ecosystems. Knowledge of spatiotemporal patterns and source attribution of N pollution is critical for nutrient management programs but is poorly studied in headwaters with various small water bodies and mini-point pollution sources. Taking a typical small watershed in the low mountains of Southeastern China as an example, N pollution and source attribution were studied for a multipond system around a village using the Hydrological Simulation Program-Fortran (HSPF) model. The results exhibited distinctive spatio-seasonal variations with an overall seriousness rank for the three indicators: total nitrogen (TN) > nitrate/nitrite nitrogen (NO_x^--N) > ammonia nitrogen (NH₃-N), according to the Chinese Surface Water Quality Standard. TN pollution was severe for the entire watershed, while NO_x^--N pollution was significant for ponds and ditches far from the village, and the NH₃-N concentrations were acceptable except for the ponds near the village in summer. Although food and cash crop production accounted for the largest source of N loads, we discovered that mini-point pollution sources, including animal feeding operations, rural residential sewage, and waste, together contributed as high as 47% of the TN and NH₃-N loads in ponds and ditches. So, apart from eco-fertilizer programs and concentrated animal feeding operations, the importance of environmental awareness building for resource management is highlighted for small farmers in headwater agricultural watersheds. As a first attempt to incorporate multipond systems into the process-based modeling of nonpoint source (NPS) pollution, this work can inform other hydro-environmental studies on scattered and small water bodies. The results are also useful to water quality improvement for entire river basins.

Estimating and Predicting Metal Concentration Using Online Turbidity Values and Water Quality Models in Two Rivers of the Taihu Basin, Eastern China

Turbidity (T) has been widely used to detect the occurrence of pollutants in surface water. Using data collected from January 2013 to June 2014 at eleven sites along two rivers feeding the Taihu Basin, China, the relationship between the concentration of five metals (aluminum (Al), titanium (Ti), nickel (Ni), vanadium (V), lead (Pb)) and turbidity was investigated. Metal concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). The linear regression of metal concentration and turbidity provided a good fit, with R(2) = 0.86-0.93 for 72 data sets collected in the industrial river and R(2) = 0.60-0.85 for 60 data sets collected in the cleaner river. All the regression presented good linear relationship, leading to the conclusion that the occurrence of the five metals are directly related to suspended solids, and these metal concentration could be approximated using these regression equations. Thus, the linear regression equations were applied to estimate the metal concentration using online turbidity data from January 1 to June 30 in 2014. In the prediction, the WASP 7.5.2 (Water Quality Analysis Simulation Program) model was introduced to interpret the transport and fates of total suspended solids; in addition, metal concentration downstream of the two rivers was predicted. All the relative errors between the estimated and measured metal concentration were within 30%, and those between the predicted and measured values were within 40%. The estimation and prediction process of metals' concentration indicated that exploring the relationship between metals and turbidity values might be one effective technique for efficient estimation and prediction of metal concentration to facilitate better long-term monitoring with high temporal and spatial density.

Mechanisms of basin-scale nitrogen load reductions under intensified irrigated agriculture

Irrigated agriculture can modify the cycling and transport of nitrogen (N), due to associated water diversions, water losses, and changes in transport flow-paths. We investigate dominant processes behind observed long-term changes in dissolved inorganic nitrogen (DIN) concentrations and loads of the extensive (465,000 km2) semi-arid Amu Darya River basin (ADRB) in Central Asia. We specifically considered a 40-year period (1960-2000) of large irrigation expansion, reduced river water flows, increased fertilizer application and net increase of N input into the soil-water system. Results showed that observed decreases in riverine DIN concentration near the Aral Sea outlet of ADRB primarily were due to increased recirculation of irrigation water, which extends the flow-path lengths and enhances N attenuation. The observed DIN concentrations matched a developed analytical relation between concentration attenuation and recirculation ratio, showing that a fourfold increase in basin-scale recirculation can increase DIN attenuation from 85 to 99%. Such effects have previously only been observed at small scales, in laboratory experiments and at individual agricultural plots. These results imply that increased recirculation can have contributed to observed increases in N attenuation in agriculturally dominated drainage basins in different parts of the world. Additionally, it can be important for basin scale attenuation of other pollutants, including phosphorous, metals and organic matter. A six-fold lower DIN export from ADRB during the period 1981-2000, compared to the period 1960-1980, was due to the combined result of drastic river flow reduction of almost 70%, and decreased DIN concentrations at the basin outlet. Several arid and semi-arid regions around the world are projected to undergo similar reductions in discharge as the ADRB due to climate change and agricultural intensification, and may therefore undergo comparable shifts in DIN export as shown here for the ADRB. For example, projected future increases of irrigation water withdrawals between 2005 and 2050 may decrease the DIN export from arid world regions by 40%.

Water quality trends in New Zealand rivers: 1989-2009

Recent assessments of water quality in New Zealand have indicated declining trends, particularly in the 40 % of the country's area under pasture. The most comprehensive long-term and consistent water quality dataset is the National Rivers Water Quality Network (NRWQN). Since 1989, monthly samples have been collected at 77 NRWQN sites on 35 major river systems that, together, drain about 50 % of New Zealand's land area. Trend analysis of the NRWQN data shows increasing nutrient concentrations, particularly nitrogen (total nitrogen and nitrate), over 21 years (1989-2009). Total nitrogen and nitrate concentrations were increasing significantly over the first 11 years (1989-2000), but for the more recent 10-year period, only nitrate concentrations continued to increase sharply. Also, the increasing phosphorus trends over the first 11 years (1989-2000) levelled off over the later 10-year period (2000-2009). Conductivity has also increased over the 21 years (1989-2009). Visual clarity has increased over the full time period which may be the positive result of soil conservation measures and riparian fencing. NRWQN data shows that concentrations of nutrients increase, and visual clarity decreases (i.e. water quality declines), with increasing proportions of pastoral land in catchments. As such, the increasing nutrient trends may reflect increasing intensification of pastoral agriculture.

Spatiotemporal evaluation of water quality incidents in Japan between 1996 and 2007

We present a spatiotemporal evaluation of water quality incidents in Japan considering incident numbers, incident causes, pollutant categories, and pollution effects. Water pollution incidents in first-class river systems almost tripled to about 1487 in the 12 years from 1996 to 2007. In addition, oil makes up the largest proportion of pollutants nationwide (76.61%) and the major source of pollution for each region in Japan. Moreover, every category shows a growth trend, especially since 2005. The main cause of incidents was "Unknown" (43%), followed by "Poor working practice" (24%), and then by "Accident" (10%) and "Other" (10%). In Hokuriku, however, the main cause of incidents was "Poor working practice" (36%), which is greater than "Unknown" (30%). Finally, waterworks (approximately 60%) was the largest of four kinds of water supply infrastructure affected by pollution incidents, followed by simplified waterworks. The population affected by offensive odors and tastes peaked in 1990 and has been decreasing. Overall, the results show the characteristics of incidents from 1996 to 2007, with significant implications for adaptation measures, strategies and policies to reduce water quality incidents.

Spatial and temporal trends in estimates of nutrient and suspended sediment loads in the Ishikari River, Japan, 1985 to 2010

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.

Statistical analysis and estimation of annual suspended sediments of major rivers in Japan

We evaluate the spatiotemporal trends of recent suspended sediment conditions in Japanese rivers. Statistical and spatiotemporal trend analysis is conducted on the 92 major rivers in Japan based on water quality monitoring data from 1992 to 2005. The Mann-Kendall non-parametric method was used to investigate the spatial and temporal trends for the suspended sediment indicator. Results show that the mean concentration of suspended sediments in Japanese rivers has generally declined in recent years, although there are still water quality problems at some monitoring sites (Kanto, Chubu, Kinki and Kyushu regions). A positive relationship between observed yearly discharge and suspended sediment load was found. Land use maps with 100 meter spatial resolution were used to apply an empirical model and develop a regression model for estimating annual suspended sediment loads directly from land use and hydrologic data. Rivers were assigned to three groups according to statistical cluster analysis of suspended sediment (SS) concentration. The correlation between the simulation result from the empirical model and the observed data had R(2) values of 0.62 and 0.71 for groups 2 and 3, and the correlation between the simulation result from the regression model and the observed data had R(2) values of 0.48 and 0.34 for groups 2 and 3. Results show that the proposed simulation technique can be used to predict the pollutant loads to river basins in Japan. Results also suggest prioritization methods and strategies that policy-makers can use to address suspended sediment pollution in rivers and water quality management in general.