Nitrogen and phosphorus retention budgets of a semiarid plain basin under different human activity intensity

Impacts of environmental flow regulation on survival of aquatic organisms: a case study of Cyprinus Carpio in Baiyangdian, China

Decreasing water volume and increasing pollutants in wetlands pose challenges to aquatic life. While environmental flow regulation is widely applied to enhance aquatic habitats, its effectiveness needs to be evaluated. In this study, a hydrodynamic-water quality model was used to simulate the fields of flow, temperature, and pollutants. The Ecological Niche Modeling at the MetaLand EcologyLab (ENMTML) was utilized to evaluate the area of suitable habitats for aquatic organisms under both environmental flow regulation and no environmental flow regulation conditions. The typical Baiyangdian Wetland in northern China was taken as the study area, and the important economic fish, Cyprinus carpio, served as the indicator of aquatic species. The effectiveness of environmental flow regulation was evaluated from December 1, 2017, to June 30, 2018. The results indicated that the variables of water depth, dissolved oxygen (DO), ammonia nitrogen (NH4+-N) and Chlorophyll a (Chla) were the major environmental factors determining the variability of the suitable habitat area for Cyprinus carpio. The environmental flow regulation capacity of the Baiyangdian Wetland was 2.6 [Formula: see text] 108 m3, which produced a suitable habitat area of 135.538 km2 at the end of the water supply period. Compared with the no environmental flow regulation condition, the highly and moderately suitable habitat areas for Cyprinus carpio were enlarged by 56.30 km2 and 34.11 km2, respectively. The outcome provides not only a basic reference for wetland management, but also a scientific perspective for understanding the impact of environmental flow regulation on aquatic organisms. The proposed method demonstrates the important potential of evaluating the effectiveness of environmental flow regulation on aquatic organisms in wetlands.

Dynamic spatiotemporal change of net anthropogenic phosphorus inputs and its response of water quality in the Liao river basin

The Liao river is one of the seven major rivers in China, and the process of phosphorus (P) cycling and change of water quality in this basin are influenced to a considerable extent human activities. In this work, the traditional net anthropogenic phosphorus inputs (NAPI) model was improved by considering the dynamic change of wastewater treatment capacity and P deposition (PDEP) and reclassifying the sources of phosphorus into human P consumption (PHUM), agriculture P consumption (PAGR), livestock P consumption (PANIM) and PDEP to analyze its dynamic spatio-temporal change in the Liao river basin. The results showed that the annual mean NAPI was 785.53 kg P km^-2 yr^-1 (2001-2020), the maximum value was 940.49 kg P km^-2 yr^-1 in 2009, and the minimum value was 586.04 kg P km^-2 yr^-1 in 2001. The temporal variation of NAPI presented an increasing-fluctuation-increasing trend and was basically in line with that of the water quality throughout the three stages, and the spatial distribution of NAPI gradually increased from upstream to downstream. During the two decades, PANIM was the predominant component of NAPI with a share of 64.32%. PHUM, PAGR, and PDEP accounted for 15.97%, 11.54%, and 8.17%, respectively, and the point source NAPI (NAPIP) contributed to 4.95% of NAPI. Further, the INAPI (Improved NAPI) -MR (Multiple Regression) -SWAT (Soil and Water Assessment Tool) model was developed to predict the spatial distribution of P flux under two scenarios. The results showed that the Liao river basin experienced a reduction in P flux to different degrees due to the improvement of the wastewater treatment system, which was more significant in its downstream area. Long-term water quality monitoring is encouraged to develop refined water quality models in the future.

Influence of anthropogenic nitrogen inputs and legacy nitrogen change on riverine nitrogen export in areas with high agricultural activity

Increased riverine nitrogen (N) concentrations due to human activities is one of the leading causes of water quality decline, worldwide. Therefore, quantitative information about the N exported from watershed to the river (TN exports) is essential for defining N pollution control practices. This paper evaluated the changes in net anthropogenic N inputs (NANI) and the N stored in land ecosystems (legacy N) in the Jianghan Plain (JHP) from 1990 to 2019 and their impacts on TN exports. Moreover, an empirical model was developed to estimate TN exports, trace its source, and predict its future variations in 2020-2035 under different scenarios. According to the results, NANI exhibited a rise-decrease-rise-decrease M-shaped trend, with N fertilizer application being the dominant driver for NANI change. In terms of the NANI components, non-point-source was the primary N input form (96%). Noteworthy is that the correlation between NANI and TN exports became weaker over time, and large differences in changing trends were observed after 2014. A likely cause for this abnormal trend was that the accumulation of N surplus in soil led to N saturation in agricultural areas. Legacy N was also an important source of TN exports. However, the contribution of legacy N has rarely been considered when defining N pollution control strategies. An empirical model, incorporating legacy N, agricultural irrigation water use, and cropland area ratio, was developed. Based on this model, legacy N contributed a large proportion (15-31%). Furthermore, the results of future predictions indicated that legacy N had a larger impact on future TN exports changes compared to other factors, and increased irrigation water would increase rather than decrease TN exports. Therefore, an integrated N management strategy considering the impact of NANI, legacy N, and irrigation water use is crucial to control N pollution in areas with intensive agriculture.

Long-term variations in external phosphorus inputs and riverine phosphorus export in a typical arid and semiarid irrigation watershed

Excessive phosphorus (P) along with drained water from farmland in the arid and semiarid watersheds when entering into water bodies brings about serious environmental problems in the aquatic ecosystem. It is critical to explore variations in watershed P balance and the relationship between anthropogenic P input and riverine total phosphorus (TP) export in a typical irrigation watersheds. In this study, long-term anthropogenic P variations in Ulansuhai Nur watershed (UNW), a typical irrigation watershed in Yellow River basin, was investigated using a quantitative Net Anthropogenic Phosphorus Input (NAPI) budget model. The results showed that annual NAPI exhibited a significant upward trend with a multi-year average of 2541.6 kg P km^-2 yr^-1 in the UNW. Hotspots for watershed NAPI were discovered in Linhe and Hangjin Houqi counties. Chemical P fertilizers and livestock breeding were two dominated sources of NAPI. Annual riverine TP export showed a significantly declined trend with a net decrease of 80.6%. The export ratio of watershed NAPI was 0.6%, lower than those reported for other watersheds worldwide. There was a significant positive linear correlation between NAPI and riverine TP export from 2005 to 2009. However, after 2009, riverine TP export exhibited a decreased trend with increasing watershed NAPI, which was attributed to environmental treatment measures. By reconstructing riverine TP export without the impact of pollution treatment measures, annual average reduction amount of riverine TP export from 2009 to 2019 was estimated to be 237.2 ton, 47.2% and 52.8% of which were attributed to the point and nonpoint sources measures. This study not only widens the application scope of NAPI budget method, but also provides useful information of nutrient management and control in the arid and semiarid irrigation watershed.

Effects of rainfall and land use on nutrient responses in rivers in the Brazilian semiarid region

This paper investigated whether rainfall promotes dilution or increase in nutrient concentrations and which land use indicators are the main predictors of nutrients in intermittent rivers in a large Brazilian semiarid region. The total phosphorus (TP) and total inorganic nitrogen (TIN) were monitored between 2013 and 2018 at 92 river water quality monitoring sites. The monthly rainfall (Rn) was obtained from 575 rain gauges. Pearson's correlation (R) between Rn and nutrient concentration was performed. The correlation patterns were also analysed based on land use data: urban area (%), agricultural field area (%), demographic density (inhabitants/km2), sewer system coverage (%), and reservoir density (reservoir/km2). Backward stepwise regression was performed to identify predictors of nutrient concentrations. The results revealed a marginal effect of rainfall on nutrients when the effects of urbanisation outweigh all other aspects. However, in regions with greater accumulated rainfall and lower reservoir density, the rainfall was related to a linear increase in nutrient concentrations (R > 0.8). Contrastingly, in the basins with less accumulated rainfall and greater inter-basin hydrological disconnection, there was a linear reduction in nutrient concentration (R < - 0.5). In the backward stepwise regression, sewer system coverage and Rn had the greatest influence for TP, and the urban area was the strongest predictor for TIN. Importantly, our results demonstrated that in semiarid rivers in densely populated regions, there is no single pattern of variability in nutrient concentration, on a wide scale of assessment. Therefore, adaptative and decentralised management can be more effective in improving water quality in these regions.

Disentangling the effects of phosphorus loading on food web stability in a large shallow lake

Excessive nutrient loads reduce ecosystem resilience, resulting in fundamental changes in ecosystem structure and function when exceeding a certain threshold. However, quantitative analysis of the processes by which nutrient loading affects ecosystem resilience requires further exploration. Food web stability is at the heart of ecosystem resilience. In this study, we simulated the dynamics of the food web under different phosphorus loads for Lake Baiyangdian using the PCLake model and calculated the food web stability. Our results showed that there was a good correspondence between the food web stability and ecosystem state response to phosphorus loads. This relationship confirmed that food web stability could be regarded as a signal for the state transition in a real lake ecosystem. Moreover, our estimates suggested that food web stability was influenced only by several functional groups and their interaction strength. Diatoms and zooplankton were the key functional groups that affected food web stability. Phosphorus loads alter the distribution of functional group biomass, which in turn affects energy delivery and, ultimately, the stability of the food web. Corresponding to functional groups, the interactions among zooplankton, diatoms and detritus had the greatest impact, and the interaction strength of the three was positively correlated with food web stability. Overall, our study explained that food-web stability was critical to characterize ecosystem resilience response to external disturbances and can be turned into a scientific tool for lake ecosystem management.

Spatiotemporal heterogeneity of nitrogen transformation potentials in a freshwater estuarine system

Under the influence of water diversion, the microbial community composition of estuarine waters and sediments might have complex spatiotemporal variations. Microbial interactions with N are significant for lake water quality. Therefore, the largest lake receiving seasonal water diversion in the North China Plain was selected as the study area. Based on 16S rRNA high-throughput sequencing and metagenomic sequencing techniques, this study analysed temporal (June-December) and spatial (estuary-pelagic zone) changes in the microbial community and functional gene composition of water and sediment. The results showed that the water microbial community composition had temporality, while sediment microbes had spatiality. The main causes of temporality in the aquatic microbial community were temperature and nitrate-N concentration, while those of sediment were flow velocity and N content. Additionally, there were complex interactions between microbial communities and N. In water, temporal variation in the relative abundance of N-related functional genes might have indirectly contributed to inorganic N composition in June (nitrite-N > ammonia-N > nitrate-N) and August (nitrite-N > nitrate-N > ammonia-N). High nitrate-N concentrations in December influenced the microbial community composition. In sediment, the estuary had higher N functional genes than the pelagic estuary, creating a relatively active N cycle and reducing total N levels in the estuary. This study revealed a potentially overlooked N sink and a flow velocity threshold that has great impacts on microbial community composition. This research contributes to a deeper understanding of the estuarine N cycle under the influence of water diversions, with implications for the calculation of global N balances and the management of lake water environments.

The characteristics of nitrogen and phosphorus output in China's highly urbanized Pearl River Delta region

The nitrogen (N) and phosphorus (P) transportation due to the anthropogenic activities have strong correlations to the water pollution events. In the highly urbanized Pearl River Delta (PRD) region of China, the main input pathways for N and P have been changed. However, their main output pathways have not yet been understood. Based on the modified export coefficient model (ECM), we have quantified the N and P outputs and identified the main factors affecting the N and P outputs in highly urbanized areas such as PRD. The results showed that the N output intensity of the PRD has increased from 3010 to 3970 kg km^-2·a^-1 from 2008 to 2016. The P output exhibited a similar trend, from 549 to 769 kg km^-2·a^-1. In terms of spatial distribution, the output intensity gradually increased from economically underdeveloped regions to economically developed regions. N and P emissions in urban wastewater increased significantly with increasing urbanization rates, with output intensities increasing by 640 kg km^-2·a^-1 and 141 kg km^-2·a^-1 from 2008 to 2016, respectively. The correlation analysis showed that population density and urbanization rate were the most relevant factors with N and P outputs intensity in highly urbanized areas. This indicates that improving the effluent standards and utilization rates of wastewater treatment plants in these regions are effective measures to control N and P output. Our findings provide some new theoretical basis for the identification and management of pollution sources in highly urbanized areas for other regions, especially developing countries.

Assessing alterations of water level due to environmental water allocation at multiple temporal scales and its impact on water quality in Baiyangdian Lake, China

Lakes in arid/semiarid regions face problems of insufficient inflow and degradation of water quality, which threaten the health of the lake ecosystem. Baiyangdian Lake (BYDL), the largest lake in the North China Plain, is confronted with such challenges. The objective of this study was to improve understanding of how changes in water level influence water quality in the BYDL at different temporal scales, especially related to implementations of intermittent environmental water allocation activities in the past two decades, by using data on monthly lake water level, climate factors of precipitation and temperature, and lake water quality. The Mann-Kendall method and continuous wavelet analysis revealed that the lake water level shows a significant decreasing trend after 1967, and the period of 16-year was identified as the principal period for 1950-2018. Based on cross-wavelet transform and wavelet coherence analysis, the periodic agreement and coherence between water level and climatic factors decreased after 1997, when environmental water allocations started, indicating that the influences of climatic factors, i.e., precipitation and temperature, became weak. By utilizing the cross-wavelet transform and wavelet coherence analysis methods, the relationships between lake water level and water quality parameters of chemical oxygen demand, ammonia nitrogen, total nitrogen, and total phosphorus were investigated. We found that the change in source and amount of environmental water allocation is one possible reason for the temporal evolution in joint variability between lake water level and water quality. Meanwhile, a dilution effect of freshwater allocated to BYDL was detected in the time-frequency domain. However, the result also indicates that the driving mechanism of water quality is complex due to the combined impacts of water allocation, nonpoint source pollution in the rainy season, and nutrient release from lake sediment. Our findings improve the general understanding of changes in water level in lakes located in arid and semiarid regions under climate change and intensive human activities, and also provide valuable knowledge for decision making in aquatic ecosystem restoration of BYDL and other similar lakes.

Dynamic characteristics of net anthropogenic phosphorus input and legacy phosphorus reserves under high human activity - A case study in the Jianghan Plain

The increase of phosphorus (P) input related to human activities is one of the main reasons for eutrophication. Notably, in areas with high population densities and intensive agricultural activities, eutrophication has occurred frequently in the Jianghan Plain, so quantitative evaluation of anthropogenic P input is of great significance for the formulation of P pollution control measures. This study estimated net anthropogenic P input (NAPI), riverine total P exports (TP exports), and the pool of P stored in the terrestrial system (legacy P reserves) at the county scale from 1990 to 2019 in the Jianghan Plain. The results showed that NAPI increased from 2645 kg·km^-2·yr^-1 in 1991 to 5812 kg·km^-2·yr^-1 in 2014, and then decreased to 4509 kg·km^-2·yr^-1 in 2019. Non-point sources were the main form of NAPI, of which 75-96% came from agricultural systems. Meanwhile, P fertilizer input was the largest source of NAPI. It is worth noting that the contribution of seed P input in some counties, such as Jiangling County, is relatively high, even exceeding that of net food/feed P input. The P fertilizer application and livestock density were the main drivers for NAPI change. Only 3% of NAPI was exported into rivers, so a large amount of legacy P accumulated in the terrestrial system. An empirical model incorporating NAPI components, cultivated land area ratio, and annual precipitation was established. Based on this model, the average contribution of annual NAPI and the sum of legacy P and natural background sources to TP exports were calculated to be 71% and 29%, respectively. So it is necessary to control P pollution by improving fertilizer use efficiency and enhancing manure management. The results provide a scientific basis for targeted solutions to the sources of P nutrient and its control measures in the middle reach of the Yangtze River.

Nitrogen flow in the food production and consumption system within the Yangtze River Delta city cluster: Influences of cropland and urbanization

Intensive anthropogenic activities associated with the food production and consumption system (FPC) drive massive reactive nitrogen inputs to city clusters resulting in serious nitrogen (N) pollution. We conducted a substance flow analysis to examine N flows in the FPC within the Yangtze River Delta city cluster from 2011 to 2019. The total N input and output showed parabolic downward trends, with decreases from 4008.27 to 3472.57 Gg N yr^-1 and 3518.65 to 3061.29 Gg N yr^-1, respectively; chemical fertilizer (54.7%-57.3%) and N loss (87.1%-90.9%) were the primary components of N input and output, respectively. The decreased total N input was related to reductions in chemical fertilizers and livestock numbers. However, a notable increase in N input to the human subsystem was observed, and urbanization was associated with increased N inputs within the human subsystem via higher amounts of food N consumed per capita and proportions of animal-based food N consumed. Total N loss initially increased then decreased; Nantong, Jiaxing, Shanghai, Yancheng, Taizhou, and Yangzhou were the top six cities in N loss intensity. The proportion of cultivated land area, livestock numbers per unit area, and population density were important factors influencing the spatial heterogeneity of N loss intensity. Twenty-six cities were divided into six groups based on their N loss composition, and various N management strategies were proposed. This study highlights the strong influences of cropland and urbanization on N flows within the FPC, which can be used as a reference for N management at a city cluster scale.

Nitrogen and Phosphorus Retention Risk Assessment in a Drinking Water Source Area under Anthropogenic Activities

Excessive nitrogen (N) and phosphorus (P) input resulting from anthropogenic activities seriously threatens the supply security of drinking water sources. Assessing nutrient input and export as well as retention risks is critical to ensuring the quality and safety of drinking water sources. Conventional balance methods for nutrient estimation rely on statistical data and a huge number of estimation coefficients, which introduces uncertainty into the model results. This study aimed to propose a convenient, reliable, and accurate nutrient prediction model to evaluate the potential nutrient retention risks of drinking water sources and reduce the uncertainty inherent in the traditional balance model. The spatial distribution of pollutants was characterized using time-series satellite images. By embedding human activity indicators, machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), and Multiple Linear Regression (MLR), were constructed to estimate the input and export of nutrients. We demonstrated the proposed model’s potential using a case study in the Yanghe Reservoir Basin in the North China Plain. The results indicate that the area information concerning pollution source types was effectively established based on a multi-temporal fusion method and the RF classification algorithm, and the overall classification low-end accuracy was 92%. The SVM model was found to be the best in terms of predicting nutrient input and export. The determination coefficient (R2) and Root Mean Square Error (RMSE) of N input, P input, N export, and P export were 0.95, 0.94, 0.91, and 0.93, respectively, and 32.75, 5.18, 1.45, and 0.18, respectively. The low export ratios (2.8–3.0% and 1.1–2.2%) of N and P, the ratio of export to input, further confirmed that more than 97% and 98% of N and P, respectively, were retained in the watershed, which poses a pollution risk to the soil and the quality of drinking water sources. This nutrient prediction model is able to improve the accuracy of non-point source pollution risk assessment and provide useful information for water environment management in drinking water source regions.

Nitrogen legacies in anthropogenic landscapes: a case study in the Mondego Basin in Portugal

Nitrogen (N) legacies have built up in anthropogenic landscapes over decades of agricultural intensification, and these legacies lead to time lags in water quality change measurable even beyond the moment of application of N. It is important to understand these legacies to quantify the relationship between N inputs and N concentrations in streams and implement best management practices for water quality improvement; however, little is known about the magnitude of legacies in various landscape elements like soils and groundwater. Here, we have used the ELEMeNT (Exploration of Long-tErM Nutrient Trajectories) model to explore the buildup and depletion of N legacies over a 216-year period, across the Mondego River Basin, a 6645-km2 watershed in Portugal, where human interventions have considerably changed the characteristics of the basin to prevent floods and improve farming conditions in recent decades. The results show that the increase in the amount of inorganic fertilizer applied was the main driver for the anthropogenic N loads in the watershed from 1950 until the beginning of the 1990s. The N inputs have been decreasing since then, but N loads in the river did not document any decrease till the 1990s; after which there was a decline. This time lag between the N inputs to the watershed and the N loads in the river (about two decades) is a function of accumulation of N legacy.

What is the pollution limit? Comparing nutrient loads with thresholds to improve water quality in Lake Baiyangdian

Ecological thresholds are useful indicators for water quality managers to define limits to nutrient pollution. A common approach to estimating ecological thresholds is using critical nutrient loads. Critical nutrient loads are typically defined as the loads at which the phytoplankton chlorophyll-a exceeds a certain concentration. However, national policies, such as in China, use chemical indicators (nitrogen and phosphorus concentrations) rather than ecological indicators (phytoplankton chlorophyll-a) to assess water quality. In this study, we uniquely define the critical nutrient loads based on maximum allowable nutrient concentrations for lake Baiyangdian. We assess whether current and future nutrient loads in this lake comply with the Chinese Water Quality standards. To this end, we link two models (MARINA-Lakes and PCLake+). The PCLake+ model was applied to estimate the critical nutrient loads related to ecological thresholds for total nitrogen, total phosphorus and chlorophyll-a. The current (i.e., 2012) and future (i.e., 2050) nutrient loads were derived from the water quality MARINA-Lakes model. Nitrogen loads exceeded the nitrogen threshold in 2012. Phosphorus loads were below all ecological thresholds in 2012. Ecological thresholds are exceeded in 2050 with limited environmental policies, and urbanization may increase nutrient loads above the ecological thresholds in 2050. Recycling and reallocating animal manure is needed to avoid future water pollution in Lake Baiyangdian. Our study highlights the need for effective policies for clean water based on policy-relevant indicators.

The long-term changes in food web structure and ecosystem functioning of a shallow lake: Implications for the lake management

The food web structure (FWS) and ecosystem functioning (EF) of lakes worldwide are impacted by multiple disturbances. The historical evolution of the FWS and EF are not well understood due to the lack of sufficient long-term records of biotic variations. This study reconstructed the food web models in the 1950s, 1980s, 1990s, 2000s, and 2010s for Baiyangdian Lake (BYDL), the largest shallow lake in northern China, using the Linear Inverse Modeling (LIM) and investigated EF in different periods. Our results confirmed that the FWS and EF of BYDL have undergone significant changes. The biomass of phytoplankton continuously increased, and the primary productivity of phytoplankton began to replace the primary productivity of submerged macrophytes in the 2000s and became the largest energy flow in the food web. Changes in the energy flow of primary producers are transmitted to high-trophic functional groups, which affects the diet composition of fish. Based on the ecological network analysis indices and food web stability indicators, it was concluded that after a turning point in the 1990s, the ecosystem showed initial stability and then gradually became unstable. Water level fluctuations and nutrient enrichment may be the key driving factors for changes in ecosystem state. Therefore, to maintain a good state of the ecosystem, we recommend implementing comprehensive management measures of hydrological management, nutrient-loading reduction, and biomanipulation. Furthermore, this study extended LIM to lake ecosystems, which may provide a new method for lake ecological environment management.

Modeling water quantity and quality for a typical agricultural plain basin of northern China by a coupled model

Water crisis across the globe has placed high pressure on social development due to the need to balance the water consumption between sustainable economy and functioning ecosystem. Integrated process-based modeling has been reported as an effective tool to better understand the complex mechanisms of water issues on a basin scale. Considering that it is still relatively difficult to simulate the water quantity-quality processes simultaneously, this study proposed an integrated modeling framework by coupling a hydrological model with a water quality model. Taking the Xiaoqing River Basin in the Shandong Province of northern China as an example, this study coupled a distributed hydrological model, SWAT, with a one-dimensional hydrodynamic-water quality model, HEC-RAS, to investigate its ability to simulate water quality and quality at the basin scale. The coupling of the two models adopted the "output-input" scheme, where the runoff modeling results from SWAT are input into HEC-RAS for hydrodynamic and water quality simulations of the river channel. The results show that the SWAT model can adequately reproduce runoff with accepted accuracy for the calibration and validation periods with acceptable R² and Nash-Sutcliffe coefficients for the two hydrological stations. Further analysis also shows that the coupled model can simulate the concentration of ammonia nitrogen (NH₄-N) and the chemical oxygen demand (COD) in the middle and upper stream of the river for both low and high flow periods. The coupling of the hydrological and hydraulic models in this study provides a good tool for identifying the spatial patterns of the water pollutants over the basin and, thus, helps simplify precision water management.

Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

Effects of hydrological and climatic variables on cyanobacterial blooms in four large shallow lakes fed by the Yangtze River

Shallow lakes, one of the most widespread water bodies in the world, are easily shifted to a new trophic state due to external interferences. Shifting hydrologic conditions and climate change can cause cyanobacterial harmful algal blooms (CyanoHABs) in shallow lakes, which pose serious threats to ecological integrity and human health. This study analyzed the effects of hydrologic and meteorological variables on cyanobacterial blooms in Yangtze-connected lakes (Lake Dongting and Poyang) and isolated lakes (Lake Chao and Tai). The results show that (i) chlorophyll-a (Chl-a) concentration tends to decrease exponentially with increasing relative lake level fluctuations (RLLF) and precipitation, but to increase linearly with increasing wind speed and air temperature; (ii) Chl-a concentrations in lakes were significantly higher when RLLF < 100, precipitation < 2.6 mm, wind speed > 2.6 m s^-1, or air temperature > 17.8 °C; (iii) the Chl-a concentration of Yangtze-isolated lakes was more significantly affected by water level amplitude, precipitation, wind speed and air temperature than the Yangtze-connected lakes; (iv) the RLLF and the ratio of wind speed to mean water depth could be innovative coupling factors to examine variation characteristics of Chl-a in shallow lakes with greater correlation than single factors.

Assessment of Spatial Variation in River Water Quality of the Baiyangdian Basin (China) during Environmental Water Release Period of Upstream Reservoirs

Baiyangdian Lake, the largest freshwater body in Northern China, is facing water shortage and eutrophication problems that threaten the lake’s ecosystem. Environmental water releases from upstream reservoirs to the lake are important measures to provide the freshwater resources demanded by the lake ecosystem. However, knowledge is limited regarding the influences of such water allocations on the water quality of the upstream rivers that receive the reservoir water and transport it into Baiyangdian Lake. To improve our understanding of possible influences of environmental water releases from upstream reservoirs, the spatial variation of water quality in rivers upstream of the lake during environmental water release periods from reservoirs was explored in this study. Water samples were collected along the two routes of water allocation: the WangKuai reservoir route (WKR) and the XiDaYang reservoir route (XDYR) and water quality parameters related to organic pollutants, nitrogen and phosphorus were analyzed. In the WKR, the pollutant concentrations generally increased from upstream to downstream. Chemical oxygen demand, total nitrogen, and total phosphorous at the sampling site closest to Baiyangdian Lake could not meet the water quality target of the water function zone. For the XDYR, pollutant concentrations peaked downstream of the major urban region of Baoding city and then decreased or remained at a similar level further downstream and only the total nitrogen concentration was worse than the target. The dissimilarities in spatial variation patterns of water quality may be caused by the different spatial distribution of wastewater treatment plants in the two routes.