Limited Impacts of Water Diversion on Micro-eukaryotic Community along the Eastern Route of China's South-to-North Water Diversion Project.

The Eastern Route of the South-to-North Water Diversion Project (ER-SNWDP) represents a crucial initiative aimed at alleviating water scarcity in China's northern region. Understanding the dynamics governing the composition and assembly processes of micro-eukaryotic communities within the canal during different water diversion periods holds paramount significance for the effective management of the ER-SNWDP. Our study systematically tracks the dynamics of the micro-eukaryotic community and its assembly processes along the 1045.4 km of canals and four impounded lakes, totaling 3455 km2, constituting the ER-SNWDP during a complete water diversion cycle, utilizing high-throughput sequencing, bioinformatics tools, and null modeling algorithms. The primary objectives of this study are to elucidate the spatial-temporal succession of micro-eukaryotic communities as the water diversion progresses, to delineate the relative importance of deterministic and stochastic processes in community assembly, and to identify the pivotal factors driving changes in micro-eukaryotic communities. Our findings indicate notable variations in the composition and diversity of micro-eukaryotic communities within the ER-SNWDP across different water diversion periods and geographic locations (P < 0.05). This variation is influenced by a confluence of temporal and environmental factors, with limited impacts from water diversion. In essence, the assembly of micro-eukaryotic communities within the ER-SNWDP primarily stemmed from heterogeneous selection driven by deterministic processes. Water diversion exhibited a tendency to decrease community beta diversity while augmenting the influence of stochastic processes in community assembly, albeit this effect attenuated over time. Furthermore, our analysis identified several pivotal environmental parameters, notably including nitrite-nitrogen, nitrate-nitrogen, orthophosphate, and water temperature, as exerting significant effects on micro-eukaryotic communities across different water diversion periods. Collectively, our study furnishes the inaugural comprehensive exploration of the dynamics, assembly processes, and influencing factors governing micro-eukaryotic communities within the ER-SNWDP, thus furnishing indispensable insights to inform the water quality management of this important project.

Contrasting nitrogen transport patterns in subtropical basins revealed by combined multiple isotopic analyzes and hydrological simulations.

Although enhancing the knowledge of nitrogen (N) dynamics in aquatic systems is crucial for basin N management, there is still a lack of theories on the patterns of basin N sources and transport because of the intricate influence of human activities, climatic conditions, landscape patterns, and topography on the trajectory of basin N. To shed new light on the patterns of basin N sources and transport in the Chinese subtropical monsoon region, this study provides a comprehensive approach combining multiple isotopes and hydrological model based on monthly records of hydro-chemistry and isotopes (18O-NO3- /15N-NO-3 and 18O-H2O /2H-H2O) for river water, groundwater and rainfall in three basins over multiple years. Our observations of hydro-chemistry showed that fluvial N levels in highly urbanized basins (3.05 ± 1.42 mg·L-1) were the highest and were characterized by higher levels in the dry season. In the agricultural basin, fluvial N levels in February and March were approximately 1.9 times higher than those in the other months. The fluvial N load was higher in agricultural basins (0.624-0.728 T N km -2 y -1) than in urban basins (0.558 T N km -2 y -1), primarily because of variations in sewage treatment rates and fertilizer application. In highly urbanized basin, manure and sewage (46.9 %) were the dominant sources of fluvial N, which were discharged into rivers after treatment. In the plain agricultural basin, a substantial portion of diffused residential sewage leaches into aquifers and is stored. In the hilly agro-forest mixed basin, the high baseflow coefficient (75.8 %) and the key role of groundwater N, mainly from soil N (27.3 %), chemical fertilizers (20.2 %), manure and sewage (46.6 %), to fluvial N (26.5 %) indicated that a high proportion of the N sources leached into the aquifer and were then transported to rivers. For the first time, this study integrated multiple methods to substantiate the proposed typical patterns of N sources and transport within the basins. These findings have significant implications for tailored basin-specific N management strategies.

Identification of nitrate sources of groundwater and rivers in complex urban environments based on isotopic and hydro-chemical evidence.

Groundwater and rivers in Chinese cities suffer from severe nitrate pollution. The accurate identification of nitrate sources throughout aquatic systems is key to the water nitrate pollution management. This study investigated nitrogen components of groundwater for twelve years and analyzed the sources of nitrate in the aquatic system based on dual isotopes (δ15N-NO3- and δ18O-NO3-) in the city of Nanjing, a core city of the Yangtze River Delta region, China. Our results showed that the ratio of nitrate to the sum of ammonia and nitrate in groundwater show an increasing trend during 2010-2021. The nitrate concentration was positively correlated with the proportion of cultivated land and negatively correlated with the proportion of forest land in the buffer zone. The relationship between Cl- and NO3-/ Cl- showed that agriculture and sewage sources increased during 2010-2015, sewage sources increased during 2016-2018, agriculture sources increased during 2019-2021. Manure and sewage were the primary sources of groundwater nitrate (72 %). There was no significant difference between the developed land (78 %), cultivated land (69 %), and aquaculture area (72 %). This indicates that dense population and intensive aquaculture in the suburbs have a significant impact on nitrate pollution. The contributions of manure and sewage to the fluvial nitrate sources in the lower reaches of the Qinhuai River Basin were 61 %. The non-point sources, including groundwater N (39 %) and soil N (35 %), were 74 % over the upper reaches. This study highlights the necessity of developing different N pollution management strategies for different parts of highly urbanized watersheds and considers groundwater restoration and soil nitrogen management as momentous, long-term tasks.

[Long-term Succession Patterns and Driving Factors of Water Quality in a Flood-pulse System Lake: A Case Study of Lake Luoma, Jiangsu Province].

Lake Luoma is an important storage lake for the Eastern route of the South-to-North Water Diversion Project (NSBD), which has many functions including flood control and irrigation, drinking water supply, and ecological maintenance. In order to understand the succession patterns and driving factors of water quality in Lake Luoma, we used monthly monitoring data from 2009 to 2020 in combination with historical data from 1996 to 2008. The long-term succession patterns, seasonal dynamics, and spatial patterns of total nitrogen (TN), total phosphorus (TP), permanganate index, and ammonia nitrogen (NH+4-N) were examined, and the influence of meteorological and hydrological factors on water quality was explored through correlation analyses and generalized additive models. The results showed that it remained in the status of grade Ⅳ-inferior Ⅴ over the past 25 years. The concentration of TN, which was the main pollutant, changed significantly (1.06-3.49 mg·L-1), experiencing three stages of gradual decline (1996-2002), significant interannual fluctuation (2002-2015), and significant increase (2015-2020). Permanganate index decreased significantly (2.97-6.38 mg·L-1), whereas TP and NH+4-N concentration fluctuated slightly, ranging from 0.024-0.076 mg·L-1 and 0.11-0.69 mg·L-1, respectively. The concentration of TN and TP increased abnormally in the summer of 2017-2020, reaching 3.30 mg·L-1 and 0.14 mg·L-1 in August, respectively, which was approximately 1.5 and 2.4 times the annual average. In terms of seasonal dynamics, the seasonal variation in water quality between summer/autumn and winter/spring reversed after 2015, with water quality in summer/autumn being worse than that in winter and spring, indicating the exacerbation of eutrophication. The water quality in the southern area was obviously better than that in the northern area. The input of pollutants from the Yihe River and Middle Canal increased with water quantity since 2015, which drove the water quality deterioration through nutrients. Our results suggested that the water quality of Lake Luoma should be improved by strengthening exogenous pollution reduction, endogenous control, polder dismantling, and ecological restoration.

Improved Daily Spatial Precipitation Estimation by Merging Multi-Source Precipitation Data Based on the Geographically Weighted Regression Method: A Case Study of Taihu Lake Basin, China.

Accurately estimating the spatial and temporal distribution of precipitation is crucial for hydrological modeling. However, precipitation products based on a single source have their advantages and disadvantages. How to effectively combine the advantages of different precipitation datasets has become an important topic in developing high-quality precipitation products internationally in recent years. This paper uses the measured precipitation data of Multi-Source Weighted-Ensemble Precipitation (MSWEP) and in situ rainfall observation in the Taihu Lake Basin, as well as the longitude, latitude, elevation, slope, aspect, surface roughness, distance to the coastline, and land use and land cover data, and adopts a two-step method to achieve precipitation fusion: (1) downscaling the MSWEP source precipitation field using the bilinear interpolation method and (2) using the geographically weighted regression (GWR) method and tri-cube function weighting method to achieve fusion. Considering geographical and human activities factors, the spatial and temporal distribution of precipitation errors in MSWEP is detected. The fusion of MSWEP and gauge observation precipitation is realized. The results show that the method in this paper significantly improves the spatial resolution and accuracy of precipitation data in the Taihu Lake Basin.

Determining nitrate sources in storm runoff in complex urban environments based on nitrogen and oxygen isotopes.

Urban storm runoff, as the primary transport medium for nutrients entering urban rivers, contributes to urban water contamination. Accurate source identification is critical for controlling water pollution. Although some studies have used nitrate isotopic composition (δ15N-NO3- and δ18O-NO3-) to identify nitrate (NO3--N) in urban storm runoff, the relatively low frequency of collecting samples in surface runoff within a single functional area hinders the understanding of spatial variations and dynamic process of NO3--N sources over the runoff process. This study investigated the nitrogen (N) concentrations and analyzed dynamic changes of NO3--N sources in surface runoff in different urban functional areas, drainage pipeline runoff, and channels during the complete runoff process in Wuxi, east China. The results showed that N concentrations in pipeline runoff and channels were higher than those in surface runoff, indicating that high concentration of N pollutants were accumulated in drainage pipelines. Information of δ15N-NO3- and δ18O-NO3- suggested that the main NO3--N source varied between runoff stages. NO3--N contribution from atmospheric deposition decreased in the order: surface runoff (57%) > residential pipeline runoff (25%) > channels (14%), while the opposite trend was observed for the contributions from sewage, increasing from 10%, 26% to 39%. In urban storm runoff, more sewage, fertilizers, and soil N were carried into the surface runoff after 30% of cumulative runoff ratio and carried into pipeline runoff in the initial 25% of cumulative runoff ratio in the residential area. As the first attempt to identify nitrate sources over the cumulative runoff in different urban functional areas, this work expands our understanding of the primary nitrate source in urban storm runoff. The findings provide important insights for developing strategies to mitigate non-point source water pollution.

Terrestrial water storage regime and its change in the endorheic Tibetan Plateau.

Analogous to flow regime, this study proposed a new statistical framework to assess inter-annual and intra-annual terrestrial water storage (TWS) regime and its changes from the aspects of magnitude, variability, duration and components. The framework was applied to two endorheic basins, Inner Basin (IB) and Qaidam Basin (QB), in the Tibetan Plateau and their eight sub-regions. Our major findings are as follows: (1) TWS in the IB (2.09-2.35 mm/a, P < 0.05) and QB (0.05-0.52 mm/a, P > 0.1) increased in all seasons from 1989 to 2019 with regional climate warming and wetting. TWS showed high increase rates (>4.50 mm/a, P < 0.05) in northeastern IB but decrease rates (<-0.90 mm/a) in southern IB. Seasonal total storage in groundwater, lake, permafrost and glacier (GLPIA) also increased in both the IB (2.55-2.68 mm/a, P < 0.05) and QB (0.05-0.43 mm/a). Seasonal soil water storage (SWA) decreased in the IB (-0.39 to -0.26 mm/a) and slightly increased in the QB (0.002-0.08 mm/a); (2) Intra-annual TWS followed approximately a cosine curve. After mutation, monthly TWS showed a higher positive magnitude change (>50 mm), accompanied by a longer duration and higher variability in the IB and its northeastern sub-regions. There was a large reduction in low storage (-18.25 mm) combined with higher variability in southeastern IB; (3) SWA change dominated the storage surplus in summer (82%) and storage deficit in autumn (-78%) and winter (-51%) in the IB, while GLPIA change dominated the storage surplus in spring (57%). In the QB, TWS change was mainly contributed by SWA change in spring (94%) and by GLPIA change in summer (73%), autumn (-62%) and winter (-58%). Component contribution rates showed a significant change in spring and winter but not much change in summer and autumn, indicating that the TWS components were more sensitive to climate change in the cold season.

[Water Pollution Characteristics and Source Apportionment in Rapid Urbanization Region of the Lower Yangtze River: Considering the Qinhuai River Catchment].

Clarifying the current situation of regional water pollutants and the relationship between pollutants and pollution sources is considered essential for managing the water environment. Water quality identification index (WQI), cluster analysis (CA), positive matrix factorization (PMF), and stable isotope analysis in R (SIAR) were employed to interpret a large and complex water quality data set of the Qinhuai River catchment generated during 2015 to 2019 to monitor of 11 parameters at 29 different sampling sites. WQI analysis indicated that water quality in Qinhuai River catchment is considered to have "moderate pollution," and an improving trend of water quality was observed at the interannual scale. TN was the most deteriorated of all pollution parameters. CA and PMF results on the spatial scale revealed that sampling sites located at downtown of Nanjing and Lishui District or Jangling University town were highly polluted due to the sewage from domestic sewage and business service sewage (28.88%) as well as industrial wastewater (27.43%), while sampling sites located at Hushu Street Administrative District, Ergan River, and Sangan River were slightly polluted by rural domestic wastewater and garbage (28.79%), and agricultural non-point source pollution (24.3%). The middle-lower reaches (Jiangning Development Zone and Moling Street) and middle reaches (Lukou Street Administrative District) were moderately polluted by industrial wastewater (27.25%), sewage from domestic wastewater and business service wastewater (31.62%) as well as inner sources (24.76%). The SIAR results showed that NO3--N was the main nitrogen form, and the NO3--N mainly originated from sewage (61%) and soil (34%) in the Yuntaishan River sub-catchment. These results will aid in the development of measures required to control water pollution in river catchments.

Quantitative identification of non-point sources of nitrate in urban channels based on dense in-situ samplings and nitrate isotope composition.

Quantitative identification of non-point sources of nitrate in urban channels plays a critical role in effective nutrient management in urban regions. This is an emerging issue due to fast urbanization and the resultant complicated hydrological and hydraulic conditions in urban areas. In this study, we examine spatial-temporal characteristics of nitrogen concentration in urban channels based on dense in-situ samplings during a one-year period over a small urban catchment in China. We quantitatively identify nitrate sources into urban channels based on dual-isotope analyses and Bayesian isotope mixing model. Results show that nitrogen concentration peaks in winter as well as in urban channels and land surfaces in the urban core region. Sewage (47%) is the dominate contributor to NO3--N in urban channels, followed by NH4+ in fertilizer (30%) as the second contributor. Sewage (NH4+ in fertilizer) contributes more NO3--N to channels in winter (summer) with the proportion of 65% (44%), and more NO3--N to urban core (suburban) channels with the proportion of 59% (42%). The rainfall and distribution of rainwater drains explain the monthly and spatial variations of contribution of NO3--N sources well, respectively. In addition, less NO3--N in the urban channels derives from nitrification, which is consistent with the results of high properties of NH4+-N/TN in this region. Our results highlight the key roles of land use types and rainfall in NO3--N source apportionment, and provide support for the nitrogen management practices in urbanized regions.

An analytical reductionist framework to separate the effects of climate change and human activities on variation in water use efficiency.

Ecosystem water use efficiency (WUE) is a key indicator that depicts the carbon-water coupling relationship in terrestrial ecosystems. Separating the effects of climate change and human activities to the variation in WUE are essential for water resources and ecosystem management, especially for fragile ecosystems such as the Tibetan Plateau (TP). In this study, we introduced an analytical framework that combined the attribution approach with the elastic coefficient separation method to assess the impact of climate change and human activities on WUE variation in the TP from 1982 to 2015. The results are the following: (1) the multiyear mean annual WUE over the TP was 0.65 g C·kg-1 H2O and had a slightly increasing trend with a slope of 0.004 g C·kg-1 H2O yr-1 with about 87% of the vegetated area showed increasing trend. (2) WUE was positively correlated with temperature, precipitation and air pressure. The northwest TP tends to be a water-limited condition, while the thermal stress is spatially universal in the TP, climate warming and wetting promoted the gross primary productivity (GPP) and WUE enhancement in the TP. (3) WUE was more sensitive to GPP, and variation in WUE was mainly contributed by GPP. Climate change and human activities tend to cause more variations in GPP rather than evapotranspiration (ET), but great differences exist for different regions and vegetation types. (4) There was a good consistency between the WUE variation calculated by the framework and the actual WUE variation (R2 = 0.95). Climate change dominated the increase of WUE in the TP with a contribution rate of 79.8%, while human activities tend to reduce WUE (-20.2%). Ecological projects played a positive role in the ecological restoration of the TP, but there may be other human activities, which caused ecological degradation, that may need more attention in future ecological protections.

Spatial-temporal characteristics of nitrogen degradation in typical Rivers of Taihu Lake Basin, China.

In this study, we focus on the measurement of different nitrogen (N) forms and investigate the spatial-temporal variability of degradation coefficient in river channels. We aim to provide a new approach of deriving in-situ degradation coefficients of different N forms, and highlight factors that determine the spatial-temporal variability of degradation coefficients. Our results are based on a two-year field survey in 34 channels around the Taihu Lake Basin, eastern China. The derived degradation coefficients of different N forms based our newly-developed experimental device are: degradation coefficients of TN, NH4+-N and NO3-N range from 0.006-0.449 d-1, 0.022-1.175 d-1 and -0.096-2.402 d-1, respectively. The degradation coefficients of N show strong dependence on N concentration and water temperature. The seasonal difference of water temperature and N concentration leads to spatial-temporal variability of degradation coefficients. The derived degradation coefficients of N are further verified through one-dimensional water quality model simulations. The degradation coefficient obtained in this study and the influencing factors of its spatial-temporal variability provide invaluable reference for studies in aquatic environment.

Spatio-Temporal Differences in Nitrogen Reduction Rates under Biotic and Abiotic Processes in River Water of the Taihu Basin, China.

Understanding spatio-temporal differences in nitrogen (N) transformation, transport and reduction rates in water bodies is critical to achieve effective mitigation of river eutrophication. We performed culture experiments in six rivers in the Taihu Basin using a custom made in-situ experimental apparatus. We investigated spatio-temporal differences in reduce processes and rates of different N forms and assessed the contribution of biological processes to dissolved inorganic N (DIN) reduce. Results showed that biological processes played a major role in N reduction in summer, while non-microbial processes were dominant in winter. We observed significant spatial and temporal differences in the studied mechanisms, with reduction rates of different N compounds being significantly higher in summer and autumn than spring and winter. Reduction rates ranged from 105.4 ± 25.3 to 1458.8 ± 98.4 mg·(m³·d)-1 for total N, 33.1 ± 12.3 to 440.9 ± 33.1 mg·(m³·d)-1 for ammonium, 56.3 ± 22.7 to 332.1 ± 61.9 mg·(m³·d)-1 for nitrate and 0.4 ± 0.3 to 31.8 ± 9.0 mg·(m³·d)-1 for nitrite across four seasons. Mean DIN reduction rates with and without microbial activity were 96.0 ± 46.4 mg·(m³·d)-1 and 288.1 ± 67.8 mg·(m³·d)-1, respectively, with microbial activity rates accounting for 29.7% of the DIN load and 2.2% of the N load. Results of correlation and principal component analysis showed that the main factors influencing N processing were the concentrations of different N forms and multiple environmental factors in spring, N concentrations, DO and pH in summer, N concentrations and water velocity in autumn and N concentrations in winter.

A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

A kriging and entropy-based approach to raingauge network design.

Hydrological data, such as precipitation, is fundamental for planning, designing, developing, and managing water resource projects as well as for hydrologic research. An optimal raingauge network leads to more accurate estimates of mean or point precipitation at any site over the watershed. Some studies in the past have suggested increasing gauge network density for reducing the estimation error. However, more stations mean more cost of installation and monitoring. This study proposes an approach on the basis of kriging and entropy theory to determine an optimal network design in the city of Shanghai, China. Unlike the past studies using kriging interpolation and entropy theory for network design, the approach developed in the current study not only used the kriging method as an interpolator to determine rainfall data at ungauged locations but also incorporated the minimum kriging standard error (KSE) and maximum net information (NI) content. The approach would thus lead to an optimal network and would enable the reduction of kriging standard error of precipitation estimates throughout the watershed and achieve an optimum rainfall information. This study also proposed an NI-KSE-based criterion which is dependent on a single-objective optimization. To evaluate the final optimal gauge network, areal average rainfall was estimated and its accuracy was compared with that obtained with the existing rain gauge network.

Variations of Runoff and Sediment Load in the Middle and Lower Reaches of the Yangtze River, China (1950-2013).

On the basis of monthly runoff series obtained in 1950-2013 and annual sediment load measured in 1956--2013 at five key hydrological stations in the middle and lower reaches of the Yangtze River basin, this study used the Mann-Kendall methods to identify trend and abrupt changes of runoff and sediment load in relation to human activities. The results were as follows: (1) The annual and flood season runoffs showed significant decreasing trends at Yichang station, and showed slight downward trends at Hankou and Datong stations, while the abrupt changes of dry season runoff at Yichang, Hankou and Datong stations occurred in about 2007 and the change points were followed by significant increasing trends. The construction of the Three Gorges Dam, which began to operate in 2003, influenced the variations of runoff in the mainstream of Yangtze River, but the effect weakened with the distance along the downstream direction from TGD. (2) Since the 1990s, annual sediment loads at Yichang, Hankou, and Datong stations have been decreasing significantly, and after 2002, the annual sediment load at Yichang dropped below that of Hankou and Datong. The dams and deforestation/forestation contributed to the significant decreasing trend of the sediment load. In addition, the Three Gorges Dam aggravated the downward trend and caused the erosion of the riverbed and riverbanks in the middle and lower reaches. (3) The runoff and sediment load flowing from Dongting Lake into the mainstream of the Yangtze River showed significant decreasing trends at Chenglingji station after 1970s, and in contrast, slight increase in the sediment flow from Poyang Lake to the mainstream of the Yangtze River at Hukou station were detected over the post-TGD period (2003-2013). The result of the study will be an important foundation for watershed sustainable development of the Yangtze River under the human activities.

A multidimension cloud model-based approach for water quality assessment.

Lakes are vitally important, because they perform a multitude of functions, such as water supply, recreation, fishing, and habitat. However, eutrophication limits the ability of lakes to perform these functions. In order to reduce eutrophication, the first step is its evaluation. The process of evaluation entails randomness and fuzziness which must therefore be incorporated. This study proposes an eutrophication evaluation method, named Multidimension Normal Cloud Model (MNCM). The model regards each evaluation factor as a one-dimension attribute of MNCM, chooses reasonable parameters and determines the weights of evaluation factors by entropy. Thus, all factors of MNCM belonging to each eutrophication level are generated and the final eutrophication level is determined by the certainty degree. MNCM is then used to evaluate eutrophication of 12 typical lakes and reservoirs in China and its results are compared with those of the reference method, one-dimension normal cloud model, related weighted nutrition state index method, scoring method, and fuzzy comprehensive evaluation method. Results of MNCM are found to be consistent with the actual water status; hence, MNCM can be an effective evaluation tool. With respect to the former one-dimension normal cloud model, parameters of MNCM are improved without increasing its complexity. MNCM can directly determine the eutrophication level according to the degree of certainty and can determine the final degree of eutrophication; thus, it is more consistent with the complexity of water eutrophication evaluation.

A cloud model-based approach for water quality assessment.

Water quality assessment entails essentially a multi-criteria decision-making process accounting for qualitative and quantitative uncertainties and their transformation. Considering uncertainties of randomness and fuzziness in water quality evaluation, a cloud model-based assessment approach is proposed. The cognitive cloud model, derived from information science, can realize the transformation between qualitative concept and quantitative data, based on probability and statistics and fuzzy set theory. When applying the cloud model to practical assessment, three technical issues are considered before the development of a complete cloud model-based approach: (1) bilateral boundary formula with nonlinear boundary regression for parameter estimation, (2) hybrid entropy-analytic hierarchy process technique for calculation of weights, and (3) mean of repeated simulations for determining the degree of final certainty. The cloud model-based approach is tested by evaluating the eutrophication status of 12 typical lakes and reservoirs in China and comparing with other four methods, which are Scoring Index method, Variable Fuzzy Sets method, Hybrid Fuzzy and Optimal model, and Neural Networks method. The proposed approach yields information concerning membership for each water quality status which leads to the final status. The approach is found to be representative of other alternative methods and accurate.

Virtual water flows in the international trade of agricultural products of China.

With the rapid development of the economy and population, water scarcity and poor water quality caused by water pollution have become increasingly severe in China. Virtual water trade is a useful tool to alleviate water shortage. This paper focuses on a comprehensive study of China's international virtual water flows from agricultural products trade and completes a diachronic analysis from 2001 to 2013. The results show that China was in trade surplus in relation to the virtual water trade of agricultural products. The exported virtual water amounted to 29.94billionm(3)/yr. while 155.55billionm(3)/yr. was embedded in imported products. The trend that China exported virtual water per year was on the decline while the imported was on a rising trend. Virtual water trade of China was highly concentrated. Not all of the exported products had comparative advantages in virtual water content. Imported products were excessively concentrated on water intensive agricultural products such as soya beans, cotton, and palm oil. The exported virtual water mainly flowed to the Republic of Korea, Hong Kong of China and Japan, while the imported mainly flowed from the United States of America, Brazil and Argentina. From the ethical point of view, the trade partners were classified into four types in terms of "net import" and "water abundance": mutual benefit countries, such as Australia and Canada; unilateral benefit countries, such as Mongolia and Norway; supported countries, such as Egypt and Singapore; and double pressure countries, such as India and Pakistan. Virtual water strategy refers to water resources, agricultural products and human beings. The findings are beneficial for innovating water resources management system, adjusting trade structure, ensuring food security in China, and promoting the construction of national ecological security system.

[Spatio-temporal characteristics and source identification of water pollutants in Wenruitang River watershed].

Identifying the temp-spatial distribution and sources of water pollutants is of great significance for efficient water quality management pollution control in Wenruitang River watershed, China. A total of twelve water quality parameters, including temperature, pH, dissolved oxygen (DO), total nitrogen (TN), ammonia nitrogen (NH4+ -N), electrical conductivity (EC), turbidity (Turb), nitrite-N (NO2-), nitrate-N(NO3-), phosphate-P(PO4(3-), total organic carbon (TOC) and silicate (SiO3(2-)), were analyzed from September, 2008 to October, 2009. Geographic information system(GIS) and principal component analysis(PCA) were used to determine the spatial distribution and to apportion the sources of pollutants. The results demonstrated that TN, NH4+ -N, PO4(3-) were the main pollutants during flow period, wet period, dry period, respectively, which was mainly caused by urban point sources and agricultural and rural non-point sources. In spatial terms, the order of pollution was tertiary river > secondary river > primary river, while the water quality was worse in city zones than in the suburb and wetland zone regardless of the river classification. In temporal terms, the order of pollution was dry period > wet period > flow period. Population density, land use type and water transfer affected the water quality in Wenruitang River.

Impact of Yangtze river water transfer on the water quality of the Lixia river watershed, China.

To improve water quality and reduce the negative impacts of sudden inputs of water pollution in the Lixia River watershed, China, a series of experimental water transfers from the Yangtze River to the Lixia River were conducted from 2 December 2006 to 7 January 2007. Water samples were collected every six days at 55 monitoring sites during this period. Eight water parameters (water temperature, pH, dissolved oxygen (DO), chemical oxygen demand (COD), potassium permanganate index (CODMn), ammonia nitrogen (NH4+-N), electrical conductivity (EC), and water transparency (WT)) were analyzed to determine changes in nutrient concentrations during water transfers. The comprehensive pollution index (Pi) and single-factor (Si) evaluation methods were applied to evaluate spatio-temporal patterns of water quality during water transfers. Water quality parameters displayed different spatial and temporal distribution patterns within the watershed. Water quality was improved significantly by the water transfers, especially for sites closer to water intake points. The degree of improvement is positively related to rates of transfer inflow and drainage outflow. The effects differed for different water quality parameters at each site and at different water transfer times. There were notable decreases in NH4+-N, DO, COD, and CODMn across the entire watershed. However, positive effects on EC and pH were not observed. It is concluded that freshwater transfers from the Yangtze River can be used as an emergency measure to flush pollutants from the Lixia River watershed. Improved understanding of the effects of water transfers on water quality can help the development and implementation of effective strategies to improve water quality within this watershed.