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Diversion rivers are important water and biological connection channels, which provide valuable ecological services. However, diversion rivers are degraded owing to the construction and unreasonable operation of large-scale water conservancy projects. Quantifying and guaranteeing the ecological flow of diversion rivers is necessary to sustain the riverine ecosystems. Due to the lack of methods to verify the rationality of the existing hydrological series length for ecological flow calculation by hydrological methods, a Monte Carlo-length of record (MC-LOR) algorithm was proposed to analyze the accuracy level of the existing hydrological series. Taking the Dongjing River (DJR) in the lower Han River as an example, the result shows that the 15-year hydrological series can meet the accuracy level of 5/90 and 10/95. The flow changes and hydrological relationships between the Qianjiang hydrological station (QJS) and the Tianguan River (TGR) under the influence of the Middle Route of South-to-North Water Transfer (MSNW) project and the Yangtze–Han Water Diversion (YHWD) project were analyzed. It is found that the flow variation of QJS is large and shows a downward trend while TGR displays a significant upward trend through the M-K trend test. And the flow of QJS is drier and less than the water replenishment of TGR in the non-flood season after the operation of the MSNW project. This paper established an ecological flow threshold calculation method based on kernel density curves and quantiles. Compared with the minimum average monthly flow (MAMF) method, the monthly minimum ecological runoff (MMR) method, improved Q90 method, Tennant method, Tessmann method, distribution flow method (DFM), the method proposed in this paper can reduce the influence of extreme flow events and is suitable for the diversion river. Finally, the ecological water replenishment demands of TGR to meet the ecological flow target of DJR under different flow conditions in the Han River were analyzed by Bayesian network (BN) models. The results show that the minimum water requirement thresholds of DJR are 31.3m3/s and 15.85m3/s, 55.35m3/s and 30.85m3/s when the flows of Han River are 3/s and 654 ~ 770m3/s in non-flood season and 3/s and 875 ~ 1210m3/s in flood season, respectively. This research provides references for the ecological stability and sustainable development of diversion rivers.

The variation of water quality in long-distance water supply projects is often different from that in natural water bodies, especially the environmental risks of artificial open canal water transfer projects are seldom studied. The spatial heterogeneity of algae growth and the absence of universal reference standards for algae control often lead to water quality problems in these projects. The Middle Route (MR) of the South-to-North Water Transfer Project of China (SNWTPC), the world’s largest inter-basin water transfer project, has operated stably for six years. Its water resources have benefited more than 60 million people and an ecosystem cover more than 160,000 km2. To understand the water environment risk of this mega hydro-project, this study focused on the relationships among three key parameters: water temperature (T), water discharge (Q), flow rate (V) and analyzed the spatial–temporal variation characteristics of the algal cell density (ACD) in the MR of the SNWTPC from January 2016 to December 2018, 36 months in total. The Copula functions were applied to identify and evaluate the multivariate risk variation of the water environment. Our result demonstrated that there was a significant positive correlation between T and ACD, and the ACD at the downstream has a 50% risk higher than 700 × 104 cell/L in summer. Overall, the water quality status of the MR of the SNWTPC is quite well, and the ACD kept at an average level of 106 cells/L during the monitoring period. Additionally, the ACD increased from upstream to downstream, showing the relatively higher ACD in summer and autumn than in spring and winter, with the ranges of 500 ~ 700 × 104 cells/L and 200 ~ 300 × 104 cells/L, respectively. The water temperature affected the ACD over the early-warning thresholds at different canal sections were as follows: 29, 26, and 21℃ from upstream to downstream, respectively. The influences of the hydrodynamic factors, water discharge and flow rate, impact on the ACD variation were analyzed to achieve the purpose of specific algae control for different canal reaches. Our study verified that the growth probabilities of the ACD under higher water temperature and water discharge in the MR of the SNWTPC than other natural water bodies.

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

Biochar, has recently, been widely used as a potential soil additive to improve the quality of cultivated land. However, the effect of biochar on irrigation water use efficiency (IWUE) remains unclear in the Qinghai-Tibet Plateau (QTP). Therefore, the purpose of this study was to explore the effects of biochar on the soil properties, water infiltration, and irrigation water efficiency of QTP cultivated land. A column experiment with four biochar application levels (0, 3, 6, and 9 kg·m

Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconnection patterns, aimed at providing references for dealing with climate change and guiding agricultural activities. Both linear and multifactorial regression models were constructed based on the frequentist quantile regression and Bayesian quantile regression method, with the daily meteorological data sets of 17 national stations in the plain and teleconnection climate characteristic indices. The results showed that precipitation in JHP had stronger spatial variability than evapotranspiration. El Niño probably induced less precipitation in summer while the weakening Arctic Oscillation might lead to more summertime precipitation. The Nash-Sutcliffe efficiency (NSE) of the multifactorial and linear regression model at the median level were 0.42–0.56 and 0.12–0.18, respectively. The mean relative error (MRE) ranged −2.95–−0.26% and −7.83–0.94%, respectively, indicating the much better fitting accuracy of the multiple climatic factors model. Meanwhile it confirmed that the agricultural climate in JHP was under the influence from multiple teleconnection patterns.

Percolation in farmland increasingly is needed to be quantified to improve water use efficiency and mitigate accompanying nutrient loss. Experiments were conducted to measure the soil properties and moisture in a consolidated paddy field-bund landscape during the rice growing season in 2014–2015. The HYDRUS-2D model simulated soil water movement in the landscape with an excellent performance. In the study, the soil properties of the bund were similar to those of the paddy field after land consolidation. Modelling results showed that most percolation in the paddy field occurred along with water input (rainfall and irrigation). Groundwater capillary rise was detected in the coupled conditions of low soil moisture in the root zone and the shallow groundwater table. Percolation accounted for 23.2%–31.3% of water input, and groundwater capillary rise contributed 26.1%–31.2% to rice evapotranspiration. The variation of the soil water content of the bund indicated that lateral infiltration from the paddy field to the bund primarily occurred in the upper bund adjacent to the field, while the lateral seepage was only found in the lower bund below the groundwater level. Vertical percolation and lateral seepage accounted for 10.5%–14.8% of water input lost through the bund, in which the lateral seepage contributed 77.6%–88.4%. Scenario simulation with the calibrated model investigated the impacts of saturated hydraulic conductivity (Ks) and the irrigation amount on the percolation and lateral seepage in the landscape. The results implied that percolation increased with the increasing Ks of soil. The percolation in the paddy-bund landscape and lateral seepage were most influenced by the illuvial horizon layer of the paddy field. Furthermore, a higher irrigation amount decreased the groundwater capillary rise and aggravated percolation linearly, while it had few effects on lateral seepage. The research suggests a potential adjustment in making irrigation schedules and conducting land consolidation in the rice-planting areas with shallow groundwater depths.

The Middle Route of the South-to-North Water Diversion Project of China (MRSNWDPC), the longest trans-basin water diversion project in the world, has been in operation for over 6 years. The water quality of this mega hydro-project affects the safety of more than 60 million people and the health of an ecosystem over 160,000 km2. Abnormal algal proliferation can cause water quality deterioration, eutrophication, and hydro-project operation issues. However, few studies have investigated and reported planktonic algae and their relationship with the water quality of this trans-basin water diversion project. Here, spatio-temporal characteristics of algal cell density (ACD) and 11 water quality parameters, including water temperature (WT), pH, dissolved oxygen (DO), permanganate index (CODMn), 5-day biochemical oxygen demand (BOD5), fecal coliforms (F. coli), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3−N), fluoride (F−), and sulfate (SO42−) in the MRSNWDPC from May 2015 to February 2019 were determined using multivariate statistical approaches. Consistent seasonal variation in ACD was observed each year, which grew in spring and then continuously decreased from summer to winter. Summer and winter are the seasons with the highest and lowest ACDs, with average values of 572.95 × 104 cell/L and 157.09 × 104 cell/L, respectively. The NH3−N was positively correlated with ACD growth in all seasons, with Pearson correlation coefficients ranging from 0.594 to 0.738 (P

Understanding vegetation dynamics is necessary to address potential ecological threats and develop sustainable ecosystem management at high altitudes. In this study, we revealed the spatiotemporal characteristics of vegetation growth in the Lhasa River Basin using net primary productivity (NPP) and normalized difference vegetation index (NDVI) during the period of 2000–2005. The roles of climatic factors and specific anthropogenic activities in vegetation dynamics were also identified, including positive or negative effects and the degree of impact. The results indicated that the interannual series of NPP and NDVI in the whole basin both had a continuous increasing trend from 102 to 128 gC m−2 yr−1 and from 0.417 to 0.489 (p < 0.05), respectively. The strongest advanced trends (>2 gC m−2 yr−1 or >0.005 yr−1) were detected in mainly the southeastern and northeastern regions. Vegetation dynamics were not detected in 10% of the basin. Only 20% of vegetation dynamics were driven by climatic conditions, and precipitation was the controlling climatic factor determining vegetation growth. Accordingly, anthropogenic activities made a great difference in vegetation coverage, accounting for about 70%. The construction of urbanization and reservoir led to vegetation degradation, but the farmland practices contributed the vegetation growth. Reservoir construction had an adverse impact on vegetation within 6 km of the river, and the direct damage to vegetation was within 1 km. The impacts of urbanization were more serious than that of reservoir construction. Urban sprawl had an adverse impact on vegetation within a 6 km distance from the surrounding river and resulted in the degradation of vegetation, especially within a 3 km range. Intensive fertilization and guaranteed irrigation improved the cropland ecosystem conditions, creating a favorable effect on the accumulation of crop organic matter in a range of 5 km, with an NPP trend value of 1.2 gC m−2 yr−1. The highly intensive grazing activity forced ecological environmental pressures such that the correlation between livestock numbers and vegetation growth trend was significantly linear negative.

Five reanalysis datasets—National Centers for Environmental Prediction reanalysis II (NCEP-2), NCEP Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), Japanese 55-year Reanalysis Project (JRA-55), and National Aeronautics and Space Administration (NASA) Modern Era Reanalysis for Research and Applications Version-2 (MERRA-2)—are selected to estimate meteorological droughts of China using three drought indices—the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), and Standardized Precipitation Evapotranspiration Index (SPEI). Drought indices, drought areas and drought severity estimated for China from these reanalysis datasets are assessed against corresponding results obtained from observed climate dataset of China using Nash–Sutcliffe efficiency (NSE), correlation coefficient, and the analysis of time series. Further, temperature, precipitation and potential evapotranspiration data of the five reanalysis datasets are also compared against the observed dataset. Drought indices and drought areas estimated from reanalysis datasets are generally more representative of historical droughts that had occurred in eastern China than in western China. However, the performance of these five reanalysis datasets in representing the drought severity is unsatisfactory in both western China and eastern China. SPEI is generally more representative than PDSI and SPI partly because temperature and potential evapotranspiration data of reanalysis datasets are generally better than precipitation data. PDSI is also based on a supply-and-demand model of soil moisture but estimating the demand of soil moisture is complicated. Therefore, SPEI is preferred over PDSI and SPI as the drought index to characterize the meteorological droughts of China. Climate data and meteorological drought characteristics of eastern China are best represented by JRA-55, while that of western China are best represented by MERRA-2. From 1980 to 2014, statistically significant increasing trends in annual drought areas and drought severity are detected from JRA-55 and observed climate datasets in eastern China, but they are only detected from observed dataset in western China.

Alternate wetting and drying (AWD) irrigation is widely adopted to save water in rice production. AWD practice shifts lowland paddy fields from being continuously anaerobic to being alternately anaerobic and aerobic, thus affecting nitrogen (N) transformations in paddy field soils. Using the barometric process separation technique, a large number of soil cores sampled from lowland paddy field soil profiles were measured for gross nitrification and denitrification rates under different temperature and soil moisture conditions. The gross nitrification and denitrification rates vary with rice growth stages and range between 1.18–30.8 and 0.65–13.54 mg N m−3 h−1, respectively. Results indicate that both gross nitrification and denitrification rates increased with the increase in temperature in all three studied soil layers. Gross nitrification rates significantly decrease with increasing soil moisture while denitrification rates increase, and different soil layers demonstrated different rates of variation to the increase in soil moisture. Gross nitrification rates in the cultivated horizon layer decreased more sharply with the increase in soil moisture. High soil water content is favorable to denitrification of all soil layers.

On-Farm Ponds (OFPs) are an important irrigation facility in rice-based irrigation systems. An OFP water reuse system in paddy field districts is composed of upstream commanded paddy fields, irrigation and drainage ditches, cascaded OFPs and downstream irrigated paddy fields. This study assesses the performance of an OFP water reuse system and explores potential water management strategies to enhance return flow reuse for rice production. A cascaded model including a modified two-tank module and a pond water balance module is developed to describe hydrologic characteristics of the water reuse system. Model calibration and validation show that the measured and simulated data are in a good agreement and the proposed model can be used to hydrologic analyses of OFP water reuse systems. The water reuse system has high water reuse efficiency as the return flow regulated by OFPs was reused several times from the upstream to downstream of the paddy fields. Return flow and actual reuse water increase with the maximum ponded depth of paddy fields. As the water level in a drainage ditch decreases, the available return flow increases and local water shortage can be alleviated. The supply-and-demand gap between seasons becomes more harmonized when the regulated water level in pond increases, resulting in a decrease in water shortage. The reuse of return flow is a quick-response water supply solution to meet the rice water demand during peak demand periods.

Arable land suitability evaluation (ALSE) is one of the tools to ensure sustainable agricultural production and achieve the global food security goal. Determining the relationship between the suitability score of arable land (AL) and the corresponding influencing factors (e.g. precipitation and temperature) is the key step to ALSE. However, the traditional method gets discontinuous suitability scores by classification based on expert knowledge, which contains considerable subjective uncertainty. This study proposes a proportion-based method, aiming to construct the suitability function based on the rule of “survival of the fittest”, thus the suitability score can be expressed in continuous curves with less uncertainty. ALSE can be concluded in three steps. First, the evaluation objects, i.e., current arable land (CAL) and potential arable land (PAL), and influencing factors are determined by environmental constraints and screening principles respectively. Second, the suitability functions of the influencing factors are constructed by counting the proportion of CAL to AL. Third, the suitability order and class for AL are divided respectively by influencing factors and Jenks classification. The results show that: (1) The development of CAL basically adapts to local natural conditions in China's Qinghai-Tibet Plateau (QTP). Suitable CAL is mainly distributed in the river valleys, where the elevation is low. Unsuitable CAL is mainly distributed in the Hengduan Mountains, where the slope is steep and the gravel content is high. (2) The area of suitable PAL is 5.3 times of suitable CAL, with grassland accounting for 95.2% and bare land accounting for 4.8%, meaning that there is great potential to exploit PAL. The proposed suitability function is easy to generalize and use, and ALSE in QTP can provide support for land use planning.

Unplanned indirect (de facto) wastewater reuse occurs when wastewater is discharged into surface waters upstream of potable drinking water treatment plant intakes. This paper aims to predict percentages and trends of de facto reuse throughout the Yangtze River watershed in order to understand the relative contribution of wastewater discharges into the river and its tributaries towards averting water scarcity concerns. The Yangtze River is the third longest in the world and supports more than 1/15 of the world's population, yet the importance of wastewater on the river remains ill-defined. Municipal wastewater produced in the Yangtze River Basin increased by 41% between 1998 and 2014, from 2580m3/s to 3646m3/s. Under low flow conditions in the Yangtze River near Shanghai, treated wastewater contributions to river flows increased from 8% in 1998 to 14% in 2014. The highest levels of de facto reuse appeared along a major tributary (Han River) of the Yangtze River, where de facto reuse can exceed 20%. While this initial analysis of de facto reuse used water supply and wastewater data from 110 cities in the basin and 11 gauging stations with >50years of historic streamflow data, the outcome was limited by the lack of gauging stations at more locations (i.e., data had to be predicted using digital elevation mapping) and lack of precise geospatial location of drinking water intakes or wastewater discharges. This limited the predictive capability of the model relative to larger datasets available in other countries (e.g., USA). This assessment is the first analysis of de facto wastewater reuse in the Yangtze River Basin. It will help identify sections of the river at higher risk for wastewater-related pollutants due to presence of-and reliance on-wastewater discharge that could be the focus of field studies and model predictions of higher spatial and temporal resolution.

Understanding soil water percolation in paddy fields is helpful to optimize irrigation schedule for rice production and improve water use efficiency under various irrigation practices and groundwater depths. Calibrated HYDRUS-1D model was used to simulate soil water movement and water balance in this study. We conducted scenario analyses based on the model to evaluate the combined effects of irrigation amount in an irrigation event (irrigation amount), irrigation duration, antecedent soil moisture, and groundwater depth on deep percolation (DP) in paddy fields. Results showed that during an irrigation event, there would be higher DP in paddy fields with higher antecedent soil moisture (≥−10 kPa), larger irrigation amount (7 cm) and/or free drainage in the bottom of rice root zones. We also used a classification and regression tree model to analyze the relative contribution of different factors to DP. Results indicated that antecedent soil moisture was the primary factor that contributed 46.3% of DP variation. Groundwater depth contributed 32.5% of DP variation, while irrigation amount (18.7%) and irrigation duration (2.5%) contributed least for DP variation. Furthermore, effects of these factors on DP interacted with each other. In scenario analysis, the contribution of antecedent soil moisture increased from 16.1% to 65.2% as the groundwater depth increased. When irrigation amount rose from 1 cm to 5 cm, the contributions of antecedent soil moisture increased to 77.6% from 57.1%; when irrigation amount was 7 cm, the contributions of antecedent soil moisture decreased to 46.4%. The contribution of irrigation amount rose to 55.7% from 28.4% with the increase of antecedent soil moisture, while the contributions of groundwater depth to DP showed opposite variation to irrigation amount as antecedent soil moisture altered. Based on relative contribution of these factors, optimal combinations of irrigation practices, antecedent soil moisture and groundwater depth were screened out to control DP for promoting rice growth and improving water use efficiency.

In regional water management, various uncertainties such as randomness, non-stationarities, dynamics and complexities, lead to difficulties for water managers. To deal with the above problems, a new methodology is proposed by introducing two methods nonstationary analysis, where the generalized additive model is selected to analyze and fit the distribution of water inflow; and model optimization, where an interval multistage water classified-allocation model (IMWCA) is formulated to optimally allocate the available water. By incorporating multistage stochastic programming, interval parameter programming and classification thought, the IMWCA model can tackle both stochastic and imprecise uncertainties, realize inter-seasonal dynamic allocation, and address the complexity of various water users. The methodology is applied to the Zhanghe Irrigation District to optimize water allocation for municipality, industry, hydropower and agriculture among winter, spring, summer and autumn. The Zhanghe Reservoir seasonal inflow is found to be nonstationary for all the seasons and can be well fitted by the corresponding distributions, showing the sense of nonstationary analysis. Additionally, the comparison with the other model demonstrates the need for classification. From the results, municipality and industry are more competitive than hydropower. The Dongbao, Dangyang and Zhanghe districts have a higher priority than the Jingzhou and Shayang districts for irrigation water. Water requirements are more likely to be satisfied in autumn. These solutions of optimal targets and optimal water allocation are valuable for optimizing inter- and intra-seasonal water resource allocation under uncertainty.

Slowly varying (trend) and abrupt (change points) changes in annual maximum daily precipitation (AMP) and seasonal maximum daily precipitation (SMP) across Canada for 223 stations in six regions during four periods (1900–2010, 1930–2010, 1950–2010 and 1970–2010) were analyzed. Variants of the Mann-Kendall (MK) test considering influences of short-term persistence (STP), long-term persistence (LTP) and large-scale climate anomalies on trend detection were applied to detect trends, and the Pettitt test was used to evaluate change points. The results indicate that there was a mix of increasing and decreasing trends for Canadian AMPs and SMPs. Most regions in Pacific Maritime, central Boreal regions and the Atlantic Maritime showed an increase in AMP, while a decrease in Canadian Prairies and most Boreal regions. More stations showing statistically significant increases than decreases in spring, summer and autumn SMPs were found while there was a statistically significant decrease (increase) in winter SMP over southern (northern) Canada. LTP significantly increased the likelihood of trends detected in AMPs and SMPs. The effects of STP on the trend detection were also evident as shown by the differences in results obtained from the MK tests with and without considering the effect of STP. The effects of large-scale climate anomalies on trends were significant for winter SMPs. More than 1/4 of stations were detected with statistically significant change points in AMPs and SMPs which occurred around 1960–1990. More stations showed significant change points than trends, and winter showed more evident trends and change points in SMPs than other three seasons. Trends and change points detected were field-significant.

Inter-basin water transfer projects are usually considered as one of the most effective facilities to balance the non-uniform temporal and spatial distribution of water resources and water demands by diverting water from surplus to deficient area. However, the operation of these projects are always daunting, especially for projects with multi-donor reservoirs but only one recipient reservoir. In this study, a set of water transfer rule curves are firstly proposed to determine when, where and how much water should be diverted from each donor reservoir. In addition, a simulation-optimization model with the objective to minimize both water shortage risk and vulnerability is established to derive the optimal operation rule curves. Following that, the new transfer rules are applied to provide guidelines for the operation of a water transfer-supply project with two donor reservoirs in central China. The effects of water diversion on each reservoir are evaluated under different scenarios including no diversion, diversion from the donor reservoir with relatively sufficient water, diversion from the donor reservoir with relatively limited water, and diversion from both donor reservoirs. The results show the advantages of improving the performance of whole water diversion system and demonstrate the feasibility of the proposed approach.

Recently, the outbreak of a serious infectious disease of unknown etiology was noted in Percocypris pingi (Tchang, 1930) farms in Yunnan province. Due to currently limited information, we aimed to identify the pathogen isolates, determine the susceptibility of the isolates, evaluate the pathogenicity and analyze the genome of the representative strain. Ten strains of Gram-negative rods were isolated from diseased P. pingi and the isolates were identified as Plesiomonas shigelloides based on biochemical characteristics, 16S rRNA gene sequencing and species-specific PCR detection. The results of susceptibility analysis showed that two selected strains LS1 and LL2 were resistant to ampicillin, penicillin G, trimethoprim/sulfamethoxazole, tetracycline, enrofloxacin, nalidixic acid and enoxacin. A virulence assay indicated that the pathogen was virulent to zebrafish. Genomic analysis revealed that the LS1 isolate was closely related to strain GN7, which was isolated from animal farms. To the best of our knowledge, this is the first report of P. shigelloides as a pathogen of P. pingi. This study will provide a rational framework for exploration of epidemiological analysis of P. shigelloides in fish diseases and would further benefit conservation of the species.

In this article, a data matrix of 20 indicators (6960 observations) was obtained from 29 water quality monitoring stations of the Middle Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC). Multivariate statistical techniques including analysis of variance (ANOVA), correlation analysis (CA), and principal component analysis (PCA) were applied to understand and identify the interrelationships between the different indicators and the most contributive sources of anthropogenic and natural impacts on water quality. The water quality index (WQI) was used to assess the classification and variation of water quality. The distributions of the indicators revealed that six heavy-metal indicators including arsenic (As), mercury (Hg), cadmium (Cd), chromium (Cr), selenium (Se), and lead (Pb) were within the Class I standard, while the As, Pb, and Cd displayed spatial variation. Moreover, some physicochemical indicators such as dissolved oxygen, 5-day biochemical oxygen demand (as BOD5), and total phosphorus (TP) had spatio-temporal variability. The correlation analysis result demonstrated that As, Hg, Cd, Cr, Se, Pb, copper (Cu), and zinc (Zn) had high correlation coefficients. The PCA result extracted three principal components (PC) accounting for 82.67% of the total variance, while the first PC was indicative of the mixed sources of anthropogenic and natural contributions, the second and the third PCs were mainly controlled by human activities and natural sources, respectively. The calculation results of the WQI showed an excellent water quality of the MR of the SNWDPC where the values of the stations ranged from 10.49 to 17.93, while Hg was the key indicator to determine the WQI &gt, 20 of six stations, which indicated that the Hg can be the main potential threat to water quality and human health in this project. The result suggests that special attention should be paid to the monitoring of Hg, and the investigation and supervision within the areas of high-density human activities in this project should be taken to control the impacts of urban and industrial production and risk sources on water quality.

Due to climate change and human activities, the assumption of the stationarity of hydrological variables will no longer hold. Moreover, the stochastic uncertainty of hydrological variables ...

The safety of water delivery and water quality in the South to North Water Transfer Project is important to China. When sudden pollution accidents happen in this project, a high-accuracy water quality model is needed to simulate contaminant transport. Data assimilation algorithm can be used to improve the accuracy of model, and a water quality model with three dimensional variational data assimilation (3DVAR-WQM), are developed in this paper. A contaminant transport experiment has been conducted for verifying the feasibility and accuracy of this model. After analyzing the simulated results in 3DVAR-WQM and the standard water quality model without assimilation, it has been found that the model with simulation estimates the arrival time and value of the peak concentration more accurately, and that the error between the simulated and observed data in this model is little. At the same time, the root mean square error of this model are smaller. This paper increases forecasting skills through data assimilation techniques, and it provides a tool for improving water quality management in the South to North Water Transfer Project of China.

Precipitation in Xinjiang, China, was modelled with covariates, such as time and climate indices, using quantile regressions. Compared to a frequentist quantile regression, a Bayesian quantile regression tended to generate smoother and narrower band confidence intervals of quantile regression coefficients, especially at extremely high and low quantile levels. A full picture of temporal trends at quantile levels from 0.01 to 0.99 indicates that the wet season (May to August) precipitation in Northern Xinjiang and the western regions of Southern Xinjiang showed statistically significant increases with different magnitudes over all quantile levels. However, the wet season precipitation in South-eastern Xinjiang decreased at some quantile levels. The Eastern Atlantic/Western Russia (EAWR) pattern was the most significant large-scale climate pattern that influenced wet season precipitation when compared to other studied patterns, i.e. the El Nino–Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO), the Pacific Decadal Oscillation (PDO), the Northern Oscillation (NO), the Arctic Oscillation (AO) and the North Atlantic Oscillation (NAO). The quantile regression coefficients associated with the EAWR index positively increased from low to high quantile levels. The ENSO significantly affected the extremely high wet season precipitation in Xinjiang. El Nino increased and La Nina decreased wet season precipitation in Northern Xinjiang, with different magnitudes at different quantile levels. Other climate patterns, i.e. the AMO, PDO, NO, NAO and AO, did not evidently affect the wet season precipitation conditional on the ENSO and EAWR. These findings suggest that the predictability of seasonal precipitation over Xinjiang can be improved by incorporating indices associated with the ENSO and EAWR as model predictors.

Seasonal drought has become an important factor in agricultural production in humid and semi-humid areas. In this study, to mitigate the impact of seasonal drought, a new integrated mathematical model is proposed for optimal multi-crop irrigation scheduling, which is associated with conjunctive operation of reservoirs and ponds to maximize the annual returns for a reservoir-pond irrigation system. This objective is achieved via the use of two models: an operating policy model, which considers the regulatory role of ponds and optimizes reservoirs and ponds releases in one third of a month, and an allocation model, which optimizes irrigation allocations across crops by addressing water production function. The uneven distribution of ponds is also considered by dividing the irrigation district into many sub-districts. Artificial bee colony algorithm is innovatively improved by incorporating differential evolution algorithm and particle swarm optimization algorithm to solve this nonlinear, high-dimensional and complex optimization problem. The methodology is applied to the Zhanghe Irrigation Distict, which is located in Hubei Province of China, to demonstrate its applicability, and three additional models are simulated to demonstrate the validity of the integrated model. The results indicate that the integrated model can alleviate the impact of the seasonal drought and has remarkable optimization effect, especially for drought years. The average annual return calculated by the integrated model is 7.9, 7.0 and 3.1 % higher than that of the remaining three models, respectively. And in the special dry year, in which the frequency of rainfall is 95 %, the annual return calculated by the integrated model is 24.5, 21.8 and 10.1 % higher than that of the remaining three models, respectively.

Accurate estimation of reference evapotranspiration (ET0) is important for water resource management and irrigation scheduling design. Limited by data availability of the numerical weather prediction (NWP), the public weather forecasting (PWF) has been widely used to forecast daily ET0 in China. Recently, two Chinese independently developed NWP products have been open to the public, namely, the Global/Regional Assimilation and Prediction System (GRAPES) and the T639 Global Medium-term Numerical Forecast Model (T639L60). In this paper, the forecast of ET0 is evaluated based on the recently released NWP outputs and the PWF using the FAO-56 PM equation. The daily ET0 forecast of the two datasets was compared against the ET0 that was calculated using weather variables observed from 31 automatic weather stations across a wide range of climate zones in China, including the temperate continental zone (TC), temperate monsoon zone (TM), mountain plateau zone (MP) and subtropical monsoon zone (SM). The results showed that the forecast performance of NWP for maximum and minimum air temperature (Tmax, Tmin) was worse due to the large errors in the altitude estimation process. The forecast performance of NWP for net radiation (Rnet) forecasted was better than that of PWF in the MP, TC and TM, while slightly worse in the SM. The VPD from the NWP was more accurate in TC and TM, while showed little difference with that from PWF in MP and SM. For the wind speed (u2), the NWP showed better forecast accuracy than PWF in all climate zones. Furthermore, the better forecast performance of ET0 was obtained by the NWP in the MP and TC. In the TM and SM, the PWF can provide a more accurate ET0 forecast compared to the NWP. Overall, the NWP can serve as a promising data source to generate acceptable ET0 forecasts across China. The high spatial resolution of the NWP provides the ability to capture the high resolution of the spatial variability in ET0, especially in the MP and TC where weather stations are sparse.

The world’s longest trans-basin water diversion project, the Middle-Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC), has officially been in operation for over 5 years since December 2014. Its water quality status has always attracted special attention because it is related to the health and safety of more than 58 million people and the integrity of an ecosystem covering more than 155,000 km2. This study presented and analysed the spatio-temporal variations and trends of 16 water quality parameters, including pH, water temperature (WT), dissolved oxygen (DO), permanganate index (PI), five-day biochemical oxygen demand (BOD5), fecal coliform (F. coli), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3−N), sulphate (SO42−), fluoride (F−), mercury (Hg), arsenic (As), selenium (Se), copper (Cu), and zinc (Zn), which were determined monthly from samples collected at 27 water quality monitoring stations in the MR of the SNWDPC from March 2016 to February 2019. The water quality index (WQI) was used to evaluate the seasonal and spatial water quality changes during the monitoring period, and a new WQImin model consisting of five crucial parameters, i.e., TP, F. coli, Hg, WT, and DO, was built by using stepwise multiple linear regression analysis. The results demonstrated that the water quality status of the MR of the SNWDPC has been steadily maintained at an “excellent” level during the monitoring period, with an overall average WQI value of 90.39 and twelve seasonal mean WQI values ranging from 87.67 to 91.82. The proposed WQImin model that uses the selected five key parameters and the weights of those parameters has exhibited excellent performance in the water quality assessment of the project, with the coefficient of determination (R2), Root Mean Square Error (RMSE), and Percentage Error (PE) values of 0.901, 2.21, 1.93%, respectively, showing that the proposed WQImin model is a useful and efficient tool to evaluate and manage the water quality. For the management department, the risk sources near certain stations with abnormally high values should be carefully inspected and strictly managed to maintain excellent water quality. The potential risks of algae proliferation in this project should be of concern in future research.

Sudden water pollution accidents in surface waters occur with increasing frequency. These accidents significantly threaten people’s health and lives. To prevent the diffusion of pollutants, identifying these pollution sources is necessary. The identification problem of pollution source, especially for multi-point source, is one of the difficulties in the inverse problem area. This study examines this issue. A new method is designed by combining differential evolution algorithm (DEA) and Metropolis–Hastings–Markov Chain Monte Carlo (MH–MCMC) based on Bayesian inference to identify multi-point sudden water pollution sources. The effectiveness and accuracy of this proposed method is verified through outdoor experiments and comparison between DEA and MH–MCMC. The average absolute error of the sources’ position and intensity, the relative error and the average standard deviations obtained using the proposed method are less than those of DEA and MH–MCMC. Moreover, the relative error and the sampling relative error under four different standard deviations of measurement error (σ = 0.01, 0.05, 0.1, 0.15) are less than 2 and 0.11 %, respectively. The proposed method (i.e., DEMH–MCMC) is effective even when the standard deviation of the measurement error increases to 0.15. Therefore, the proposed method can identify sources of multi-point sudden water pollution accidents efficiently and accurately.

River classification has emerged as a major application of environmental science, which can overcome the defects of traditional methods in focusing on the single objective of maintaining specified, valued features of ecosystems. However, current efforts to classify rivers by hydrologic processes may result in a growing temptation to ignore ecological variability across basins. Thus, an eco-functional classification is proposed for river management in the Pearl River Basin. This method views ecological functions as fundamental characteristics of riverine systems and provides a framework for dividing a basin into eco-specific categories according to the heterogeneity of the primary ecological functions. In addition, we proposed specific environmental flow methodologies corresponding to three typical river reaches of the basin by perceiving the key attributes of flow variability. In the upstream region of the West River, flow velocity and wetted perimeter are considered as the key attributes of maintaining fish habitat; in a small-sized mountainous tributary of the North river, we choose water surface area to maintain the continuity and biodiversity of the river; while for the aspect of river landscape in the midstream reach of the East River, water level is crucial for maintaining the aesthetic value. This research highlights the ecologically relevant heterogeneity that occurs within and among regions of a basin, and is expected to contribute to a simpler and more comprehensive river management.

Water scarcity in China has long been discussed and studied, mostly in arid and semi-arid Northern China. However, temporary water scarcity caused by seasonal droughts hasn’t drawn enough attention still, while some humid regions in South China are readily to be encountered with seasonal droughts, especially in the background of climate change. In this study, a method based on System Dynamics (SD) and mathematical optimization is developed to analyze the situation of temporary water scarcity and optimize the water allocation under seasonal droughts, considering rapid urbanization, industrialization, and increasing food demand. And a case study in Nanchang Municipality, a typical humid region in Southern China, is presented. The simulation results show that conventional management scenarios including enforcing demand reduction strategies and increasing local water supply will not fill the water shortage gap, and the total water shortage rate will retain more than 9.0 % in special drought condition. Thus, we examine the water transfer scenario, and it proves to be effective in coping with the water shortage gap. The optimization results indicate that the water transferred from Ganjiang River to Fuhe River Water Demand Subsystem may account for 50.21 % of the total fresh water supply of Fuhe River Water Demand Subsystem, in September, under a certain drought condition. In addition, the current situation reveals fierce competition between social economic water needs and eco-environmental water requirements in local scale in dry condition. The situation argues that management of the distribution of water in space must be involved, and the simulation of the inter-basin transfer scenario proves it a necessary and effective countermeasure.

a b s t r a c t With the wide adoption of alternate wetting and drying (AWD) irrigation for rice production, the water and nitrogen (N) fate in lowland paddy fields under AWD irrigation was needed to be investigated for assessing the water saving and environmental effects of AWD, compared to traditional continuously flooded (CF) irrigation. The HYDRUS-1D software package was used to simulate water movement, and N transport and transformations in experimental paddy fields under AWD and CF irrigation during 2007 and 2008. The variation in N transformation between AWD and CF paddy fields due to different water regimes in soil profiles were represented by time-varying boundary conditions and N transformation parameters that are dependent on soil water content. Simulations show that AWD irrigation decreased 27.8 and 19.0% of percolation, 5.0-11.2% and 3.0-23.5% of N leaching losses in 2007 and 2008, respectively, compared to CF irrigation. However, AWD irrigation increased 6.0-22.0% and 2.5-11.7% of N losses of volatilization, and 6.3-9.4% and 4.5-7.6% of nitrification, as well as 6.7-19.8% and 4.1-11.2% of denitrification in 2007 and 2008, respectively. These results reflect the intensified nitrification-denitrification processes that were caused by the relatively high ammonium concentration, and alternate aerobic and anaerobic environment in AWD paddy fields. The increased nitrate, which was formed from nitrification of ammonium in drying (aerobic) phase, can be easily denitrified to N2 or N2O in the wetting (anaerobic) phase. Therefore, the practice of AWD irrigation should consider its side effects on increasing N emissions from paddy fields that may also decrease the N use efficiency. Simulation of water and N regime together using HYDRUS-1D is an alternative system approach to improve water and N management for sustainable rice production. © 2014 Elsevier B.V. All rights reserved.