A method coupled with remote sensing data to evaluate non-point source pollution in the Xin'anjiang catchment of China

Rainfall impacts on nonpoint nitrogen and phosphorus dynamics in an agricultural river in subtropical montane reservoir region of southeast China

The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers. However, little information is available on how the rainfall affect nutrient dynamics in subtropical montane rivers with complex land use. This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu, a montane reservoir of southeast China. The results showed that riverine total nitrogen (TN) and total phosphorus (TP) concentrations increased continuously with increasing rainfall intensity, while TN:TP decreased. The heavy rainfall and rainstorm drove more than 30% of the annual N and P loading in only 5.20% of the total rainfall period, indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs. NO3--N is the primary nitrogen form lost, while particulate phosphorus (PP) dominated phosphorus loss. The main source of N is cropland, and the main source of P is residential area. Spatially, forested watersheds have better drainage quality, while it is still a potential source of nonpoint pollution during rainfall events. TN and TP concentrations were significantly higher at sites dominated by cropland and residential area, indicating their substantial contributions to deteriorating river water quality. Temporally, TN and TP concentrations reached high values in May-August when rainfall was most intense, while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities. The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads, providing guidance for nutrient load reduction planning for Lake Qiandaohu.

Transport dynamics of watershed discharged diffuse phosphorus pollution load to the lake in middle of Yangtze River Basin

Diffuse pollution, including that in the lower and middle reaches of the Yangtze River, is the primary source of pollution in several agricultural watersheds globally. As the largest river basin in China, the Yangtze River Basin has suffered from total phosphorus (TP) pollution in the past decade owing to diffuse pollution and aquatic ecology destruction, especially in the midstream tributaries and mid-lower reaches of the lakes. However, the transport dynamics of diffuse pollutants, such as phosphorus (P) from land to water bodies have not been well evaluated, which is of great significance for quantifying nutrient loss and its impact on water bodies. In this study, diffuse pollution estimation with remote sensing (DPeRS) model coupled with Soil and Water Assessment Tools (SWAT) was utilized to simulate the transport dynamics of P, investigate the spatial heterogeneity and P sources in the Poyang Lake Basin. Additionally, the P transport mechanism from land to water and the migration process in water bodies were considered to investigate the impact of each loss unit on the water body and evaluate the load generated by diverse pollution types. The estimated diffuse TP loss was 6016 t P·yr-1, and the load to inflow rivers and to Poyang Lake were 11,619 and 9812 t P·yr-1, respectively. Gan River Basin (51.09%) contributed most TP to Poyang Lake among five inflow rivers, while waterfront area demonstrated the highest TP load per unit area with 0.057 t km-2·yr-1. Our study also identified P sources in the sub-basins and emphasized agricultural diffuse sources, especially planting, as the most significant factor contributing to TP pollution. Additionally, to improve the aquatic environment and water ecological conditions, further nutrient management should be applied using a comprehensive approach that encompasses the entire process, from source transportation to the water body.

Comparison of different macroinvertebrates bioassessment indices in a large near-natural watershed under the context of metacommunity theory

The metacommunity theory proposes that community structure and biodiversity are influenced by both local processes (such as environmental filtering) and regional processes (such as dispersal). Despite the extensive use of traditional bioassessments based on species-environment relationships, the impact of dispersal processes on these assessments has been largely overlooked. This study aims to compare correlations between various bioassessment indices, including Shannon Weiner (H'), Biological Monitoring Working Party (BMWP), average score per taxon (ASPT), biotic index (BI), and EPT taxa index (EPT), based on macroinvertebrates collected from 147 sampling sites in a subtropical Chinese near-natural catchment. Modified indices were calculated by removing species strongly influenced by dispersal processes to address the influence of dispersal processes. Their relationship with environmental factors was then compared to the original indices. The study employed random forest regression (RFR) to compare the explanatory power of environmental factors using the two sets of indices. The spearman rank correlation analysis was conducted to examine the correlation between indices and environmental factors. The river health assessment was performed based on both modified and original indices. The results reveal significant differences between original and modified indices (especially H' and BI) providing a more accurate reflection of environmental conditions. Furthermore, the sensitivity of the different indices to various environmental factors varied, leading to differences in the bioassessment results between the modified and the original indices. Notably, original H', BMWP, and ASPT overestimated the bioassessment results, whereas the original BI underestimated them. These findings offer valuable insights into bioassessment and river health assessment evaluation within the catchment and other interconnected freshwater ecosystems, such as lakes, reservoirs, and wetlands. Our study underscores the importance of assessing and mitigating the impact of dispersal processes on bioassessment to obtain a more precise representation of the status of freshwater ecosystems.

Intelligent soft computational models integrated for the prediction of potentially toxic elements and groundwater quality indicators: a case study

Reports have shown that potentially toxic elements (PTEs) in air, water, and soil systems expose humans to carcinogenic and non-carcinogenic health risks. In southeastern Nigeria, works that have used data-driven algorithms in predicting PTEs in groundwater are scarce. In addition, only a few works have simulated water quality indices using machine learning modelling methods in the region. Therefore, in this study, physicochemical analyses were carried out on groundwater samples in southeastern Nigeria. The laboratory results were used to compute two water quality indices: pollution index of groundwater (PIG) and the water pollution index (WPI), to ascertain groundwater quality. In addition, the physicochemical parameters served as input variables for multiple linear regression (MLR) and artificial neural network (ANN) modelling and prediction of Cr, Fe, Ni, NO3−, Pb, Zn, WPI, and PIG. The results of WPI and PIG computation showed that about 30–35% of the groundwater samples were unsuitable for human consumption, whereas 65–70% of the samples were deemed suitable. The insights from the PIG and WPI model also revealed that lead (Pb) was the most influential PTE that degraded the quality of groundwater resources in the research area. The findings of the MLR and ANN models indicated strong positive prediction accuracies (R 2 = 0.856–1.000) with low modeling errors. The predictive MLR and ANN models of the PIG and WPI generally outperformed those of the PTEs. The models produced in this study predicted the PTEs better compared to previous studies. Thus, this work provides insights into effective water sustainability, management, and protection.

Spatial optimization of ecological ditches for non-point source pollutants under urban growth scenarios

Non-point source (NPS) pollution is regarded as the major threat to water quality worldwide, and ecological ditches (EDs) are considered an important and widely used method to collect and move NPS pollutants from fields to downstream water bodies. However, few studies have been conducted to optimize the spatial locations of EDs, particularly when the watershed experiences urbanization and rapid land-use changes. As land-use patterns change the spatial distribution of NPS loads, this study used a cellular automata-Markov method to simulate future land-use changes in a typical agricultural watershed. Three scenarios are included as follows: historical trend, rapid urbanization, and ecological protection scenarios. The spatial distributions of particulate phosphorus loads were simulated using the revised universal soil loss equation and sediment transport distribution model. The results suggested that the total particulate phosphorus (TP) load in the Zhuxi watershed decreased by 10,555.2 kg from 2000 to 2020, primarily because the quality and quantity of forests in Zhuxi County improved over the last 20 years. The TP load in Zhuxi watershed would be 2588.49, 2639.15, and 2553.32 kg in 2040 in historical trend, rapid urbanization, and ecological protection scenarios, respectively, compared with 2308.1 kg in 2020. This indicated that urban expansion increases the TP load, and the faster the expansion rate, the more the TP load. Consequently, the optimal locations of EDs were determined based on the intercepted loads and the period during which they existed during land-use changes. The results suggested that rapid urbanization would consequently reduce the space available for building EDs and also increase the cost of building EDs to control the NPS pollution in the watershed.

Coupling with high-resolution remote sensing data to evaluate urban non-point source pollution in Tongzhou, China

Urban non-point source (NPS) pollution has gradually become one of the important factors affecting the urban water environment. The quantitative evaluation of urban NPS pollution is the priority to identify key control area of urban NPS pollution. Current model applied in China is mainly focused on small-scale area, large-scale spatial continuous simulation is lacking. In this study A spatial continuous evaluation method coupled with high-resolution remote sensing data has been established and the method was applied to Tongzhou, China. With the spatial distribution of land-use type and built-up area which were been obtained by remote sensing technology, the accumulative and wash-off load of urban NPS nitrogen and phosphorus were estimated for the prominent problems of nitrogen and phosphorus nutrient pollution in the rivers in the study area. The main sources of urban NPS Nitrogen and phosphorus pollution are roof and road rainfall runoff respectively. Compared to other urban NPS pollution models, the method developed in this study can quickly realize spatial visualization assessment of urban NPS pollution and provide a means to estimate urban NPS loads in entire city or urban agglomeration, it is applicable for common urban NPS pollutants and also has advantages in areas without data.

Dynamics of nitrogen and phosphorus profile and its driving forces in a subtropical deep reservoir

Nitrogen and phosphorus stratification is crucial for ecosystem dynamics in deep lakes and reservoirs. It is critical for water quality management to understand the characteristics of nitrogen and phosphorus stratification and its driving forces. In this study, high-frequency total nitrogen (TN) and total phosphorus (TP) from January 2017 to October 2019 were estimated using the datasets of high-frequency buoy parameters, including water temperature, pH, chlorophyll-a, oxidation-reduction potential, dissolved oxygen, and fluorescent dissolved organic matter. The results revealed that both nitrogen and phosphorus in water column were periodically stratified. Specifically, the stratification of nitrogen and phosphorus occurred from April to December or January of the following year. Moreover, indices of TN stratification (IC-TN) and TP stratification (IC-TP) were - 0.29 ~ 0.05 and - 0.78 ~ 0.28, respectively. Significant (P < 0.01) positive correlations were observed between RWCS (an index of thermal stability) and IC-TN (or IC-TP), indicating thermal stratification may be the main driving force of nutrient stratification at inter-month scales. Further analysis indicated that the thermal stratification may affect nitrogen and phosphorus stratification though (1) influencing algal growth and (2) affecting the release of internal sources and the material exchange between water columns. Furthermore, precipitation is also suggested as an important factor affecting the stability of nitrogen and phosphorus vertical profile in the flood season. These findings may provide important information for optimizing water quality management efforts in Qiandaohu and other subtropical deep reservoirs. In addition, the knowledge of the effect of temperature and precipitation on nutrient stratification are essential to understand future ecosystem dynamics of deep reservoirs.

Preferred hierarchical control strategy of phosphorus from non-point source pollution at regional scale

Spatiotemporal heterogeneity poses challenges on prevention and control of non-point source (NPS) pollution. Treating pollution sources sequentially by prioritizing the critical periods (CPs) and critical source areas (CSAs) is essential for effective control of regional NPS pollution. In this study, the gird-based dual-structure export empirical model (DSEEM) was used to simulate phosphorus losses in the Danjiangkou Reservoir Basin (DRB) on a monthly scale. Based on the co-analysis of CPs and CSAs coupled with the point density analysis (PDA), a preferred hierarchical control strategy, which was connected with regional management units, was proposed to improve the pertinence for phosphorus loss control. CPs, sub-CPs, and non-CPs were identified on the temporal scale; CSAs, sub-CSAs, and non-CSAs were identified on the spatial scale. The results showed that CPs (July, April, and September), sub-CPs (May, March, and August), and non-CPs contributed 62.8%, 31.1%, and 6.1% of the annual TP loads, respectively. Furthermore, we proposed a hierarchical control strategy for NPS pollution: class I (CSAs in CPs) → class II (sub-CSAs in CPs, CSAs in sub-CPs) → class III (non-CPs, non-CSAs, sub- and non-CSAs in sub-CPs). Class I covered the periods and areas with the highest loads, contributing 26.2% of the annual loads within 14.5% of the area and 25.0% of the time. This study provides a reference for the targeted control of NPS pollution at regional scale, especially in environmental protection with limited funds.

Mapping spatio-temporal dynamics of main water parameters and understanding their relationships with driving factors using GF-1 images in a clear reservoir

Due to eutrophication and water quality deterioration in clear reservoirs, it is necessary to monitor and manage the main water parameters: concentration of total phosphorus (CTP), chemical oxygen demand (CCOD), chlorophyll-a (CChla), total suspended matter (CTSM), and Secchi disk depth (SDD). Five random forest (RF) models are developed to estimate these parameters in Xin'anjiang Reservoir, which is a clear drinking water resource in Zhejiang, China. Then, the spatio-temporal distributions of the parameters over 7 years (2013-2019) are mapped using GaoFen-1 (GF-1) images and the relationships with driving factors are analyzed. Our study demonstrates that the parameters' distributions exhibited a significant spatio-temporal difference in Xin'anjiang Reservoir. Spatially, relatively high CTP, CCOD, CChla, and CTSM but low SDD appear in riverine areas, showing strong evidence of impact from the incoming rivers. Temporally, CChla and CTSM reached high values in summer and winter, whereas SDD and CTP were higher in the summer and autumn, respectively. In contrast, no significant seasonal variations of CCOD could be observed. This may be why CCOD is not sensitive to hydrological or meteorological factors. However, precipitation had a significant impact on CChla, CTP, SDD, and CTSM in riverine areas, though these parameters were less sensitive to meteorological factors. Moreover, the geomorphology of the reservoir and anthropogenic interference (e.g., tourism activities) also have a significant impact on the water quality parameters. This study demonstrates that coupling long-term GF-1 images and RF models could provide strong evidence and new insights to understand long-term dynamics in water quality and therefore support the development of corresponding management strategies for freshwater reservoirs.

Using Principal Components Analysis and IDW Interpolation to Determine Spatial and Temporal Changes of Surface Water Quality of Xin'anjiang River in Huangshan, China

This study was aimed at assessing the spatial and temporal distribution of surface water quality variables of the Xin’anjiang River (Huangshan). For this purpose, 960 water samples were collected monthly along the Xin’anjiang River from 2008 to 2017. Twenty-four water quality indicators, according to the environmental quality standards for surface water (GB 3838-2002), were detected to evaluate the water quality of the Xin’anjiang River over the past 10 years. Principal component analysis (PCA) was used to comprehensively evaluate the water quality across eight monitoring stations and analyze the sources of water pollution. The results showed that all samples could be analyzed by three main components, which accounted for 87.24% of the total variance. PCA technology identified important water quality parameters and revealed that nutrient pollution and organic pollution are major latent factors which influence the water quality of Xin’anjiang River. It also showed that agricultural activities, erosion, domestic, and industrial discharges are fundamental causes of water pollution in the study area. It is of great significance for water quality safety management and pollution control of the Xin’anjiang River. Meanwhile, the inverse distance weighted (IDW) method was used to interpolate the PCA comprehensive score. Based on this, the temporal and spatial structure and changing characteristics of water quality in the Xin’anjiang River were analyzed. We found that the overall water quality of Xin’anjiang River (Huangshan) was stable from 2008 to 2017, but the pollution of the Pukou sampling point was of great concern. The results of IDW helped us to identify key areas requiring control in the Xin’anjiang River, which pointed the way for further delicacy management of the river. This study proved that the combination of PCA and IDW interpolation is an effective tool for determining surface water quality. It was of great significance for the control of water pollution in Xin’anjiang River and the reduction of eutrophication pressure in Thousand Island Lake.

Spatiotemporal Variations in Nitrogen and Phosphorus in a Large Man-Made Lake and Their Relationships with Human Activities

Nitrogen and phosphorus excessive enrichment are major causes of water eutrophication, and variations in nutrients enrichment are strongly influenced by human activities. In this study, annual average water quality from 2001 to 2018 was used to explore the spatiotemporal variations in total nitrogen (TN) and total phosphorus (TP) and their relationships with human activities. Spatially, TN and TP concentrations exhibited significant variations across the five sub-lake zones, and their values were relatively higher in the NW lake zone than the other sub-lake zones. Temporally, TN concentration exhibited weak correlations with years in the NW (R2 = 0.37, p < 0.05) and NE (R2 = 0.43, p < 0.05) lake zones and significant and positive correlations with years in the SW (R2 = 0.62, p < 0.05), SE (R2 = 0.79, p < 0.05), and C (R2 = 0.84, p < 0.05) lake zones. TP concentration exhibited decreasing trends in all lake zones except the NW lake zone (R2 = 0.37, p < 0.05), its value shows a relatively low level and is the restrictive factor to algal growth. The trophic state of the Lake Qiandaohu was determined as mesotrophic. Gross domestic product (GDP) and construction land exhibited strong correlations with TN and TP. Moreover, agriculture nonpoint source pollution was the largest contributor to the excessive enrichment of TN and TP, resulting in water eutrophication. In addition, aquaculture was another major source of nutrients starting in 1999. Although the managers of Lake Qiandaohu implemented a protection-oriented fishery policy, good results cannot be easily achieved with a unilateral policy concerning environmental protection. Thus, comprehensive policies may be more effective than unilateral policies.

Spatiotemporal Dynamics of Nitrogen Transport in the Qiandao Lake Basin, a Large Hilly Monsoon Basin of Southeastern China

The Qiandao Lake Basin (QLB), which occupies low hilly terrain in the monsoon region of southeastern China, is facing serious environmental challenges due to human activities and climate change. Here, we investigated source attribution, transport processes, and the spatiotemporal dynamics of nitrogen (N) movement in the QLB using the Soil and Water Assessment Tool (SWAT), a physical-based model. The goal was to generate key localized vegetative parameters and agronomic variables to serve as credible information on N sources and as a reference for basin management. The simulation indicated that the basin’s annual average total nitrogen (TN) load between 2007 and 2016 was 11,474 tons. Steep slopes with low vegetation coverage significantly influenced the spatiotemporal distribution of N and its transport process. Monthly average TN loads peaked in June due to intensive fertilization of tea plantations and other agricultural areas and then dropped rapidly in July. Subsurface flow is the key transport pathway, with approximately 70% of N loads originating within Anhui Province, which occupies just 58% of the basin area. The TN yields of sub-basins vary considerably and have strong spatial effects on incremental loads entering the basin’ major stream, the Xin’anjiang River. The largest contributor to N loads was domestic sewage (21.8%), followed by livestock production (20.8%), cropland (18.6%), tea land (15.5%), forest land (10.9%), atmospheric deposition (5.6%), orchards (4.6%), industry (1.4%), and other land (0.8%). Our simulation underscores the urgency of increasing the efficiency of the wastewater treatment, conserving slope land, and optimizing agricultural management as components of a comprehensive policy to control N pollution in the basin.

Exploration of the critical factors influencing the water quality in two contrasting climatic regions

Over the past few decades, rivers have become severely polluted as a result of receiving vast quantities of domestic and industrial wastewater. The identification of the major factors that influence water quality is crucial to understand the interactions of anthropogenic and natural factors and develop river restoration projects. In this study, the QUAL2Kw water quality model was used to quantitatively evaluate the most critical factors for water quality at two sites with different meteorological conditions and urban scales. The genetic algorithm (GA) was used to optimize the parameters in the model. The Monte Carlo simulation (MCS) method was used to assess the model uncertainty and sensitivity in all reaches for five water quality outputs (temperature, CBOD, DO, TP, and TN) in two seasons. The K-means clustering method associated with the sensitivity results was used to identify the major factors influencing the water quality in all reaches from the input data and the model parameters. The results showed that CBOD, TN, and TP were most sensitive to headwater and tributary quality. DO tended to be affected by more natural reactions than the other water quality indicators. In the cold and dry seasons and the more urbanized areas, river pollution was more severe, and the impact of natural reactions was reduced. The simulation results revealed the reliability of QUAL2Kw in modeling the quantity and quality of all river reaches. The method applied in this study is beneficial for the improvement and management of the water environment.

Spatial Variation Pattern Analysis of Hydrologic Processes and Water Quality in Three Gorges Reservoir Area

The Three Gorges Project (TGP) has greatly enhanced the heterogeneity of the underlying surface in the Three Gorges Reservoir Area (TGRA), thereby affecting the hydrologic processes and water quality. However, the influence of the differences of underlying surfaces on the hydrologic processes and water quality in the TGRA has not been studied thoroughly. In this research, the influence of the heterogeneity of landscape pattern and geographical characteristics on the spatial distribution difference of hydrologic processes and water quality in the different tributary basins of the TGRA was identified. The TGRA was divided into 23 tributary basins with 1840 sub-basins. The spatial differentiation of the hydrologic processes and water quality of the 23 tributary basins was examined by the Soil and Water Assessment Tool (SWAT). The observed data between 1 January 2010 and 31 December 2013 were used to calibrate and validate the model, after which the SWAT model was applied to further predict the runoff and water quality in the TGRA. There are 25 main model parameters, including CN2, CH_K2 and SOL_AWC, which were calibrated and validated with SWAT-Calibration and Uncertainty Procedures (SWAT-CUP). The landscape patterns and geomorphologic characteristics in 23 tributary basins were investigated and spatially visualized to correlate with surface runoff and nutrient losses. Due to geographical difference, the average total runoff depth (2010–2013) in the left bank area (538.6 mm) was 1.4 times higher than that in the right bank area (384.5 mm), total nitrogen (TN) loads in the left bank area (6.23 kg/ha) were 1.9 times higher than in the right bank area (3.27 kg/ha), and total phosphorus (TP) loads in the left bank area (1.27 kg/ha) were 2.2 times higher than in the right bank area (0.58 kg/ha). The total runoff depth decreased from the head region (553.3 mm) to the tail region (383.2 mm), while the loads of TN and TP were the highest in the middle region (5.51 kg/ha for TN, 1.15 kg/ha for TP), followed by the tail region (5.15 kg/ha for TN, 1.12 kg/ha for TP) and head region (3.92 kg/ha for TN, 0.56 kg/ha for TP). Owing to the different spatial distributions of land use, soil and geographical features in the TGRA, correlations between elevation, slope gradient, slope length and total runoff depth, TN and TP, were not clear and no consistency was observed in each tributary basin. Therefore, the management and control schemes of the water security of the TGRA should be adapted to local conditions.

Long-term change of total suspended matter in a deep-valley reservoir with HJ-1A/B: implications for reservoir management

The valley reservoirs service as a critical resource for society by providing drinking water, power generation, recreation, and maintaining biodiversity. Management and assessment of the water environment in valley reservoirs are urgent due to the recent eutrophication and water quality deterioration. As an essential component of the water body, total suspended matter (TSM) hinder the light availability to underwater and then affect the photosynthesis of aquatic ecosystem. We used long-term HJ-1A/B dataset to track TSM variation and elucidating the driving mechanism of valley reservoirs. Taking a typical deep-valley reservoir (Xin'anjing Reservoir) as our case study, we constructed a TSM model with satisfactory performance (R², NRMSE, and MRE values are 0.85, 18.57%, and 20%) and further derived the spatial-temporal variation from 2009 to 2017. On an intra-annual scale, the TSM concentration exhibited a significant increase from 2.13 ± 1.10 mg L^-1 in 2009 to 3.94 ± 0.82 mg L^-1 in 2017. On a seasonal scale, the TSM concentration in the entire reservoir was higher in the summer (3.36 ± 1.54 mg L^-1) and autumn (2.74 ± 0.82 mg L^-1) than in the spring (1.84 ± 1.27 mg L^-1) and winter (1.44 ± 2.12 mg L^-1). On a monthly scale, the highest and lowest mean TSM value occurred in June (4.66 ± 0.45 mg L^-1) and January (0.67 ± 1.50 mg L^-1), and the monthly mean TSM value increased from January to June, then dropped from June to December. Combing HJ-1A/B-derived TSM, climatological data, basin dynamic, and morphology of the reservoir, we elucidated the driving mechanism of TSM variation. The annual increase of TSM from long-term HJ-1A/B data indicated that the water quality of Xin'anjiang Reservoir was decreasing. The annual increase of phytoplankton jointed with an increase of built-up land and decrease of forest land in the basin may partially be responsible for the increasing trend in TSM. This study suggested that combining the long-term remote sensing data and in situ data could provide insight into the driving mechanism of water quality dynamic and improve current management efforts for local environmental management.

Can the watershed non-point phosphorus pollution be interpreted by critical soil properties? A new insight of different soil P states

The physicochemical properties of surface soil play a key role in the fate of watershed non-point source pollution. Special emphasis is needed to identify soil properties that are sensitive to both particulate P (PP) pollution and dissolved P (DP) pollution, which is essential for watershed environmental management. The Chaohu Lake basin, a typical eutrophic lake in China, was selected as the study site. The spatial features of the Non-point Source (NPS) PP loads and DP loads were calculated simultaneously based on the integration of sediment delivery distributed model (SEDD) and pollution loads (PLOAD) model. Then several critical physicochemical soil properties, especially various soil P compositions, were innovatively introduced to determine the response of the critical soil properties to NPS P pollution. The findings can be summarized: i) the mean PP load value of the different sub-basins was 5.87 kg, and PP pollution is regarded to be the primary NPS P pollution state, while the DP loads increased rapidly under the rapid urbanization process. ii) iron-bound phosphorus (Fe-P) and aluminum-bound phosphorus (Al-P) are the main components of available P and showed the most sensitive responses to NPS PP pollution, and the correlation coefficients were approximately 0.9. Otherwise, the residual phosphorus (Res-P) was selected as a sensitive soil P state that was significantly negatively correlated with the DP loads. iii) The DP and PP concentrations were represented differently when they were correlated with various soil properties, and the clay proportion was strongly negatively related to the PP loads. Meanwhile, there is a non-linear relationship between the DP loads and the critical soil properties, such as Fe and Total Nitrogen (TN) concentrations. Specifically, a strong inhibitory effect of TN concentration on the DP load was apparent in the Nanfei river (NF) and Paihe (PH) river basins where the R² reached 0.67, which contrasts with the relatively poor relationship within the other five basins. In addition, the degree of correlation between the Fe and DP loads severely degraded in the basins that were mostly covered by construction land or those that underwent a rapid urbanization process. The findings indicate that land use/cover change (LUCC), especially the distribution of agricultural land and construction land, as well as the soil background information (TN, Fe and Soil organic matters, etc.) can be considered as factors that influence NPS P pollution.

Impact assessment of projected climate change on diffuse phosphorous loss in Xin'anjiang catchment, China

Diffuse nutrient loss is a serious threat to water security and has severely deteriorated water quality throughout the world. Xin'anjiang catchment, as a main drinking water source for Hangzhou City, has been a national concern for water environment protection with payment for watershed services construction. Detection of diffuse phosphorous (DP) pollution dynamics under climate change is significant for sustainable water quality management. In this study, the impact of projected climate change on DP load was analyzed using SWAT to simulate the future changes of diffuse components (carriers: water discharge and sediment; nutrient: DP) at both station and sub-catchment scales under three climate change scenarios (RCP2.6, RCP4.5, and RCP8.5). Results showed that wetting and warming years were expected with increasing tendencies of both precipitation and temperature in the two future periods (2020s: 2021~2030, 2030s: 2031~2040) except in the 2020s in the RCP2.6 scenario, and the annual average increasing ratios of precipitation and temperature reached - 1.79~3.79% and 0.48~1.27 °C, respectively, comparing with those in the baseline (2000s: 2001~2010). Climate change evidently altered annual and monthly average water discharge and sediment load, while it has a remarkable impact on the timing and monthly value of DP load at station scale. DP load tended to increase in the non-flood season at Yuliang due to strengthened nutrient flushing from rice land into rivers with increasing precipitation and enhanced phosphorous cycle in soil layers with increasing temperature, while it tended to decrease in the flood season at Yuliang and in most months at Tunxi due to restricted phosphorous reaction with reduced dissolved oxygen content and enhanced dilution effect. Spatial variability existed in the changes of sediment load and DP load at sub-catchment scale due to climate change. DP load tended to decrease in most sub-catchments and was the most remarkable in the RCP8.5 scenario (2020s, - 9.00~2.63%; 2030s, - 11.16~7.89%), followed by RCP2.6 (2020s, - 10.00~2.90%; 2030s, - 9.00~6.63%) and RCP4.5 (2020s, - 6.81~5.49%, 2030s, - 10.00~9.09%) scenarios. Decreasing of DP load mainly aggregated in the western and eastern mountainous regions, while it tended to increase in the northern and middle regions. This study was expected to provide insights into diffuse nutrient loss control and management in Xin'anjiang catchment, and scientific references for the implementation of water environmental protection in China.

Monitoring spatiotemporal variations in nutrients in a large drinking water reservoir and their relationships with hydrological and meteorological conditions based on Landsat 8 imagery

Nutrient enrichment is a major cause of water eutrophication, and variations in nutrient enrichment are influenced by environmental changes and anthropogenic activities. Accurately estimating nutrient concentrations and understanding their relationships with environmental factors are vital to develop nutrient management strategies to mitigate eutrophication. Landsat 8 Operational Land Imager (OLI) data is used to estimate nutrient concentrations and analyze their responses to hydrological and meteorological conditions. Two well-accepted empirical models are developed and validated to estimate the total nitrogen (TN) and total phosphorus (TP) concentrations (C_TN and C_TP) in the Xin'anjiang Reservoir using Landsat 8 OLI data from 2013 to 2016. Spatially, C_TN decreased from the transition zone to the riverine zone and the lacustrine zone. On the other hand, C_TP decreased from the riverine zone to the transition zone and the lacustrine zone. Temporally, C_TN displayed elevated values during the late fall and winter and had lower values during the summer and early fall, whereas C_TP was higher during the spring and lower during the winter. Among the environmental factors, the rainfall and the inflow rate have strong positive correlations with the nutrient concentrations. TN is more sensitive to meteorological factors (wind speed, temperature, sunshine duration), and the spatial driving forces vary among the different sections of the reservoir. However, TP is more easily influenced by human activities, such as fishery and agricultural activities. Current results would improve our understanding of the drivers of nutrients spatiotemporal variability and the approach in this study can be applicable to other similar reservoir to develop related strategies to mitigate eutrophication.

Mapping the scientific research on non-point source pollution: a bibliometric analysis

A bibliometric analysis was conducted to examine the progress and future research trends of non-point source (NPS) pollution during the years 1991-2015 based on the Science Citation Index Expanded (SCI-Expanded) of Web of Science (WoS). The publications referencing NPS pollution were analyzed including the following aspects: document type, publication language, publication output and characteristics, subject category, source journal, distribution of country and institution, author keywords, etc. The results indicate that the study of NPS pollution demonstrated a sharply increasing trend since 1991. Article and English were the most commonly used document type and language. Environmental sciences and ecology, water resources, and engineering were the top three subject categories. Water science and technology ranked first in distribution of journal, followed by Science of the total environment and Environmental Monitoring and Assessment. The USA took a leading position in both quantity and quality, playing an important role in the research field of NPS pollution, followed by the UK and China. The most productive institution was the Chinese Academy of Sciences (Chinese Acad Sci), followed by Beijing Normal University and US Department of Agriculture's Agricultural Research Service (USDA ARS). The analysis of author keywords indicates that the major hotspots of NPS pollution from 1991 to 2015 contained "water," "model," "agriculture," "nitrogen," "phosphorus," etc. The results provide a comprehensive understanding of NPS pollution research and help readers to establish the future research directions.

A Bayesian approach of high impaired river reaches identification and total nitrogen load estimation in a sparsely monitored basin

In this study, a modeling framework based on the theory of SPAtially Referenced Regression On Watershed attributes (SPARROW) model was developed to identify impaired river reaches with respect to total nitrogen (TN) and estimate the TN sources in the Xin'anjiang River basin, which had limited monitoring sites. A Bayesian approach was applied to estimate the mean values and uncertainties of parameters, including land use export coefficients and in-stream attention rates. Based on the parameters, the midranges (25-75 %) of annual TN concentrations were assessed by the model and 4.5 % of river reaches in the basin were found to be with higher impaired probabilities (namely [TN] > 1.5 mg/l) than other reaches. The amount and yields of TN discharged from diffuse sources were estimated for each county in the basin. The results suggested that Tunxi City had the highest TN yields from farm land and population, while the highest TN yields in Huangshan City were from tea plantations. The outcomes of this study will guide the implementation of practical management measures to reduce TN loads.

Inflow rate-driven changes in the composition and dynamics of chromophoric dissolved organic matter in a large drinking water lake

Drinking water lakes are threatened globally and therefore in need of protection. To date, few studies have been carried out to investigate how the composition and dynamics of chromophoric dissolved organic matter (CDOM) in drinking water lakes are influenced by inflow rate. Such CDOM can lead to unpleasant taste and odor of the water and produce undesirable disinfection byproducts during drinking water treatment. We studied the drinking water Lake Qiandao, China, and found that the concentrations of suspended particulate matter (SPM) in the lake increased significantly with inflow rate (p < 0.001). Similarly, close relationships between inflow rate and the CDOM absorption coefficient at 350 nm a(350) and with terrestrial humic-like fluorescence C3 and a negative relationship between inflow rate and the first principal component (PC1) scores, which, in turn, were negatively related to the concentrations and relative molecular size of CDOM (p < 0.001), i.e. the concentration and molecular size of CDOM entering the lake increased proportionately with inflow rate. Furthermore, stable isotopes (δD and δ(18)O) were depleted in the upstream river mouth relative to downstream remaining lake regions, substantiating that riverine CDOM entering the lake was probably driven by inflow rate. This was further underpinned by remarkably higher mean chlorophyll-a and in situ measured terrestrial CDOM fluorescence (365/480 nm) and apparent oxygen utilization (AOU), and notably lower mean PC1 and CDOM spectral slope (S275-295) recorded in the upstream river mouth than in the downstream main lake area. Strong negative correlations between inflow rate and a(250):a(365), S275-295, and the spectral slope ratio (SR) implied that CDOM input to the lake in rainy period was dominated by larger organic molecules with a more humic-like character. Rainy period, especially rainstorm events, therefore poses a risk to drinking water safety and requires higher removal efficiency of CDOM during drinking water treatment processes.

Seasonal-Spatial Distribution and Long-Term Variation of Transparency in Xin'anjiang Reservoir: Implications for Reservoir Management

Water transparency is a useful indicator of water quality or productivity and is widely used to detect long-term changes in the water quality and eutrophication of lake ecosystems. Based on short-term spatial observations in the spring, summer, and winter and on long-term site-specific observation from 1988 to 2013, the spatial, seasonal, long-term variations, and the factors affecting transparency are presented for Xin’anjiang Reservoir (China). Spatially, transparency was high in the open water but low in the bays and the inflowing river mouths, reflecting the effect of river runoff. The seasonal effects were distinct, with lower values in the summer than in the winter, most likely due to river runoff and phytoplankton biomass increases. The transparency decreased significantly with a linear slope of 0.079 m/year, indicating a 2.05 m decrease and a marked decrease in water quality. A marked increase occurred in chlorophyll a (Chla) concentration, and a significant correlation was found between the transparency and Chla concentration, indicating that phytoplankton biomass can partially explain the long-term trend of transparency in Xin’anjiang Reservoir. The river input and phytoplankton biomass increase were associated with soil erosion and nutrient loss in the catchment. Our study will support future management of water quality in Xin’anjiang Reservoir.

Dissolved oxygen stratification and response to thermal structure and long-term climate change in a large and deep subtropical reservoir (Lake Qiandaohu, China)

From January 2010 to March 2014, detailed depth profiles of water temperature, dissolved oxygen (DO), and chromophoric dissolved organic matter (CDOM) were collected at three sites in Lake Qiandaohu, a large, deep subtropical reservoir in China. Additionally, we assessed the changes in DO stratification over the past 61 years (1953-2013) based on our empirical models and long-term air temperature and transparency data. The DO concentration never fell below 2 mg/L, the critical value for anoxia, and the DO depth profiles were closely linked to the water temperature depth profiles. In the stable stratification period in summer and autumn, the significant increase in CDOM in the metalimnion explained the decrease in DO due to the oxygen consumed by CDOM. Well-developed oxygen stratification was detected at the three sites in spring, summer and autumn and was associated with thermal stratification. Oxycline depth was significantly negatively correlated with daily air temperature and thermocline thickness but significantly positively correlated with thermocline depth during the stratification weakness period (July-February). However, there were no significant correlations among these parameters during the stratification formation period (March-June). The increase of 1.67 °C in yearly average daily air temperature between 1980 and 2013 and the decrease of 0.78 m in Secchi disk depth caused a decrease of 1.65 m and 2.78 m in oxycline depth, respectively, facilitating oxygen stratification and decreasing water quality. Therefore, climate warming has had a substantial effect on water quality through changing the DO regime in Lake Qiandaohu.

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

Absorption and fluorescence properties of chromophoric dissolved organic matter: implications for the monitoring of water quality in a large subtropical reservoir

The development of techniques for real-time monitoring of water quality is of great importance for effectively managing inland water resources. In this study, we first analyzed the absorption and fluorescence properties in a large subtropical reservoir and then used a chromophoric dissolved organic matter (CDOM) fluorescence monitoring sensor to predict several water quality parameters including the total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), dissolved organic carbon (DOC), and CDOM fluorescence parallel factor analysis (PARAFAC) components in the reservoir. The CDOM absorption coefficient at 254 nm (a(254)), the humic-like component (C1), and the tryptophan-like component (C3) decreased significantly along a gradient from the northwest to the lake center, northeast, southwest, and southeast region in the reservoir. However, no significant spatial difference was found for the tyrosine-like component (C2), which contributed only four marked peaks. A highly significant linear correlation was found between the a(254) and CDOM concentration measured using the CDOM fluorescence sensor (r(2) = 0.865, n = 76, p < 0.001), indicating that CDOM concentrations could act as a proxy for the CDOM absorption coefficient measured in the laboratory. Significant correlations were also found between the CDOM concentration and TN, TP, COD, DOC, and the maximum fluorescence intensity of C1, suggesting that the real-time monitoring of CDOM concentrations could be used to predict these water quality parameters and trace the humic-like fluorescence substance in clear aquatic ecosystems with DOC <2 mg/L and total suspended matter (TSM) concentrations <15 mg/L. These results demonstrate that the CDOM fluorescence sensor is a useful tool for on-line water quality monitoring if the empirical relationship between the CDOM concentration measured using the CDOM fluorescence sensor and the water quality parameters is calibrated and validated.

Simulation of spatial and temporal distributions of non-point source pollution load in the Three Gorges Reservoir Region

Non-point source (NPS) pollution has become the largest threat to water quality in recent years. Major pollutants, particularly from agricultural activities, which include nitrogen, phosphorus and sediment that have been released into aquatic environments, have caused a range of problems in the Three Gorges Reservoir Region (TGRR), China. It is necessary to identify the spatial and temporal distributions of NPS pollutants and the highly polluted areas for the purpose of watershed management. In this study, the NPS pollutant load was simulated using the Soil and Water Assessment Tool (SWAT) and the small-scale watershed extended method (SWEM). The simulation results for four typical small catchments were extended to the entire watershed leading to estimates of the NPS load from 2001 to 2009. The results demonstrated that the NPS pollution load in the western area was the highest and that agricultural land was the primary pollutant source. The similar annual variation trends of runoff and sediment loads demonstrated that the sediment load was closely related to runoff. The loads of total nitrogen (TN) and total phosphorus (TP) were relatively stable from 2001 to 2007, except for high loads in 2006. The increase in pollution source strength was an important reason for the significant upward trend of TN and TP loads from 2008 to 2009. The rainfall from April to October contributed to the largest amount of runoff, sediment and nutrient loads for the year. The NPS load intensities in each sub-basin reveal large variations in the spatial distribution of different pollutants. It was shown that the temporal and spatial distributions of pollutant loads were positively correlated with the annual rainfall amounts and with human activities. Furthermore, this finding illustrates that conservation practices and nutrient management should be implemented in specific sites during special periods for the purpose of NPS pollution control in the TGRR.

Integrated hydrological and water quality model for river management: a case study on Lena River

The Hydrologic Simulation Program FORTRAN (HSPF) model was used to assess the impact of wastewater discharges on the water quality of a Lis River tributary (Lena River), a 176 km(2) watershed in Leiria region, Portugal. The model parameters obtained in this study, could potentially serve as reference values for the calibration of other watersheds in the area or with similar climatic characteristics, which don't have enough data for calibration. Water quality constituents modeled in this study included temperature, fecal coliforms, dissolved oxygen, biochemical oxygen demand, total suspended solids, nitrates, orthophosphates and pH. The results were found to be close to the average observed values for all parameters studied for both calibration and validation periods with percent bias values between -26% and 23% for calibration and -30% and 51% for validation for all parameters, with fecal coliforms showing the highest deviation. The model revealed a poor water quality in Lena River for the entire simulation period, according to the Council Directive concerning the surface water quality intended for drinking water abstraction in the Member States (75/440/EEC). Fecal coliforms, orthophosphates and nitrates were found to be 99, 82 and 46% above the limit established in the Directive. HSPF was used to predict the impact of point and nonpoint pollution sources on the water quality of Lena River. Winter and summer scenarios were also addressed to evaluate water quality in high and low flow conditions. A maximum daily load was calculated to determine the reduction needed to comply with the Council Directive 75/440/EEC. The study showed that Lena River is fairly polluted calling for awareness at behavioral change of waste management in order to prevent the escalation of these effects with especially attention to fecal coliforms.