Huai River Basin Research Articles

Impact of Control Measures on Nitrogen Oxides, Sulfur Dioxide and Particulate Matter Emissions from Coal-Fired Power Plants in Anhui Province, China

Anhui is one of the highest provincial emitters of air pollutants in China due to its large coal consumption in coal-fired plants. In this study, the total emissions of nitrogen oxides (NOx), sulfur dioxide (SO2) and particulate matter (PM) from coal-fired power plants in Anhui were investigated to assess the impact of control measures on the atmospheric emissions based upon continuous emission monitoring systems (CEMS). The total NOx, SO2 and PM emissions significantly decreased from 2013 to 2017 and they were estimated at 24.5 kt, 14.8 kt and 3.0 kt in 2017, respectively. The emission reductions of approximately 79.0%, 70.1% and 81.2% were achieved in 2017 compared with a 2013 baseline, respectively, due to the application of high-efficiency emission control measures, including the desulfurization, denitration and dust-removing devices and selective catalytic reduction (SCR). The NOx, SO2 and PM emission intensities were 0.125 g kWh−1, 0.076 g kWh−1 and 0.015 g kWh−1 in 2017, respectively, which were lower than the average of national coal-fired units. The coal-fired units with ≥600 MW generated 80.6% of the total electricity amount while they were estimated to account for 70.5% of total NOx, 70.1% of total SO2 and 71.9% of total PM. Their seasonal emissions showed a significant correlation to the power generation with the maximum correlation found in summer (July and August) and winter (January and December). The major regional contributors are the cities along the Huai River Basin and Yangtze River Basin, such as Huainan, Huaibei, Tongling, Maanshan and Wuhu, and the highest emission occurred in Huainan, accounting for approximately 26–40% of total emission from all the power plants. Our results indicated that the application of desulfurization, denitration and dust-removing devices has played an important role in controlling air pollutant emissions from coal-fired power plants.

基于多源遥感数据的农业干旱监测模型构建及应用

PDF HTML阅读 XML下载 导出引用 引用提醒 基于多源遥感数据的农业干旱监测模型构建及应用 DOI: 10.5846/stxb201711202068 作者: 作者单位: 安徽师范大学国土资源与旅游学院,安徽师范大学国土资源与旅游学院,北京师范大学减灾与应急管理研究院,北京师范大学减灾与应急管理研究院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41601023）；国家杰出青年科学基金项目（51425903）；地表过程与资源生态国家重点实验室开放基金资助项目（2017-KF-04）；安徽省自然科学基金（1808085QD117） An integrated agricultural drought monitoring model based on multi-source remote sensing data: model development and application Author: Affiliation: College of Territorial Resources and Tourism,College of Territorial Resources and Tourism,Academy of Disaster Reduction and Emergency Management，Beijing Normal University,Academy of Disaster Reduction and Emergency Management，Beijing Normal University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:干旱监测问题是干旱灾害模拟与预警及旱灾防灾减灾的关键。基于2001-2013年淮河流域40个气象站资料、28个土壤墒情站点和中分辨率成像光谱仪（MODIS）多源遥感数据，采用SEN趋势法和标准化降水蒸散指数（SPEI）等方法，综合了大气-植被-土壤相互作用等多元成因，构建了适用于淮河流域多源综合遥感干旱监测模型，探讨淮河流域干旱时空规律。研究表明：（1）基于多源数据构建综合干旱监测模型，利用土壤墒情和典型年份干旱监测对综合干旱监测模型适用性进行评价，通过了P < 0.01的显著性检验，构建的模型可综合反映出农业和气象干旱多源信息；（2）淮河流域干旱面积和干旱频率大都集中在4-5月和7-9月，9月份受旱面积最大。河南省是淮河流域受旱频率最高，其干旱面积占淮河流域多年平均干旱面积比重最大（38%），其次是安徽（22%），旱地受旱面积比重大于水田受旱面积比重；（3）淮河流域2、3和5月干旱有显著减弱趋势；而1、4和6月则有增强趋势。淮河流域小麦灌浆-成熟时期（4-6月）缺水对小麦粮食产量影响显著，综合淮河流域干旱趋势变化，需强化淮河流域4月份小麦的干旱监测与旱灾预警。 Abstract:Drought monitoring is crucial for the early warning of drought hazards. In this study, an attempt to develop an Integrated Remote Sensing Drought Monitoring Index (IRSDI) was made, based on multi-source remote sensing data, with the aim of investigating drought conditions across the Huai River basin in both space and time. The IRSDI relied on:meteorological data recorded from 2003 to 2013 at 40 stations, soil moisture data recorded at 16 stations, Moderate Resolution Imaging Spectroradiometer (MODIS) data obtained by linear trend detection, and on the Standardized Precipitation Evapotranspiration Index (SPEI). The results of this study indicate that:(1) the proposed IRSDI is able to describe and monitor drought conditions well in both space and time; (2) droughts and high drought frequency occur in the periods April-May and July-September. In particular, September is the month during which the largest area is dominated by droughts. In particular, droughts affect Henan province, which accounts for 38% of the total drainage area of the Huai River basin, followed by Anhui province, which accounts for 22% of the total drainage area of the Huai River basin; (3) droughts tend to decrease during February, March and May, whereas they increase during January, April and June. Wheat grouting and ripening occur in the period from April to June. Thus, droughts in these months can seriously affect wheat production, and a more careful allocation of water resources and irrigation management should be performed during this period. Nevertheless, spring droughts and autumn-winter droughts should receive proper attention as well, in order to manage and reduce drought-induced losses. 参考文献 相似文献 引证文献

基于SPEI指数的淮河流域干旱时空演变特征及影响研究

基于SPEI指数的淮河流域干旱时空演变特征及影响研究

Assessing Water Resources Vulnerability by Using a Rough Set Cloud Model: A Case Study of the Huai River Basin, China.

Assessing water resources vulnerability is the foundation of local water resources management. However, as one of the major water systems in China, there is no existing evaluation index system that can effectively assess water resource vulnerability for the Huai River basin. To address this issue, we identified key vulnerability factors, constructed an evaluation index system, and applied such system to evaluate water resources vulnerability for the Huai River basin empirically in this paper. Specifically, our evaluation index system consists of 18 indexes selected from three different aspects: water shortage, water pollution, and water-related natural disaster. Then, the improved blind deletion rough set method was used to reduce the size of the evaluation index while keep the evaluation power. In addition, the improved conditional information entropy rough set method was employed to calculate the weights of evaluation indexes. Based on the reduced index system and calculated weights, a rough set cloud model was applied to carry out the vulnerability evaluation. The empirical results show that the Huai River basin water resources were under severe vulnerability conditions for most of the time between 2000 and 2016, and the Most Stringent Water Resources Management System (MS-WRMS) established in 2012 did not work effectively as expected.

Spatial Heterogeneity in the Occurrence Probability of Rainstorms over China

Detecting the spatial heterogeneity in the potential occurrence probability of water disasters is a foremost and critical issue for the prevention and mitigation of water disasters. However, it is also a challenging task due to the lack of effective approaches. In the article, the entropy index was employed and those daily rainfall data at 520 stations were used to investigate the occurrences of rainstorms in China. Results indicated that the entropy results were mainly determined by statistical characters (mean value and standard deviation) of rainfall data, and can categorically describe the spatial heterogeneity in the occurrence of rainstorms by considering both their occurrence frequencies and magnitudes. Smaller entropy values mean that rainstorm events with bigger magnitudes were more likely to occur. Moreover, the spatial distribution of entropy values kept a good relationship with the hydroclimate conditions, described by the aridity index. In China, rainstorms are more to likely occur in the Pearl River basin, Southeast River basin, lower-reach of the Yangtze River basin, Huai River basin, and southwest corner of China. In summary, the entropy index can be an effective alternative for quantifying the potential occurrence probability of rainstorms. Four thresholds of entropy value were given to distinguish the occurrence frequency of rainstorms as five levels: very high, high, mid, low and very low, which can be a helpful reference for the study of daily rainstorms in other basins and regions.

Spatio-temporal dynamics of nitrogen and phosphorus input budgets in a global hotspot of anthropogenic inputs

The increased input of anthropogenic nitrogen (N) and phosphorus (P) to watershed ecosystems has been cited as among the most important reasons for widespread water pollution. Revealing spatio-temporal patterns of N and P input budgets in regions with intensified human activity can facilitate a better understanding of human-induced N and P cycles. Here, we present budget inventories including both anthropogenic non-point and point N and P inputs into the Huai River Basin, which has been identified as one of the hotspots of anthropogenic inputs across the world. On average, total anthropogenic N and P inputs in the year 2010 reached 28,000 kg N km−2 yr−1 and 2800 kg P km−2 yr−1, showing a 50% and 42% increases in comparison with 1990, respectively. Both non-point-source and point-source N & P inputs have exhibited a rapid increase from 1990 to 2010, which has been related to the increasing human population and socio-economic development. The intensive farming implemented to meet the growing food demand was responsible for continuous growth in non-point-source inputs. Meanwhile, rapid urbanization with lagged environmental management was the major reason for the increased point-source inputs. Spatial patterns of N & P inputs were similar across different periods, showing that the hotspots generally centralized in a few northern counties. By further interpreting the critical sources and their drivers of inputs to each region through time, our work provides insights for targeted management. Future mitigation strategies such as optimizing the farming methods, improving manure management and enhancing sewage treatment are necessary to address the environmental concerns of excessive inputs.

Characteristics of summer extreme precipitation in the Huai River basin and their relationship with East Asia summer monsoon during 1960–2014

Based on the daily precipitation data of the Huai River basin (HRB) and NCEP/NCAR reanalysis data from 1960 to 2014, the study examines the spatio‐temporal characteristics of summer extreme precipitation (SEP), explores the statistical relationship between the changes of SEP in the HRB and the East Asian summer monsoon (EASM), and further investigates the circulation characteristics which are most conducive to extreme precipitation under different EASM backgrounds. The main results are as follows: (a) summer extreme precipitation indices (SEPI) of PNL90 and PQ90 mainly increased (although not significant) in the HRB from 1960 to 2014, and the weakening of EASM may be the reason for the upwards trend. (b) The characteristics of SEP are quite different between the north and the south of the HRB, and SEPI mainly negatively correlates with East Asian summer monsoon index (EASMI) in the south but positively correlates in the north. (c) Extreme precipitation may occur under both strong and weak summer monsoon backgrounds in the HRB, but the circulation configurations are different. The differences between high and low SEP are mainly associated with the intensity of western Pacific subtropical high (WPSH) for the weak EASM years, while the differences mainly lie in the position of WPSH for the strong EASM years.

Shifting of phytoplankton assemblages in a regulated Chinese river basin after streamflow and water quality changes

Phytoplankton is critical to river ecosystems. These organisms are sensitive to streamflow and water quality changes and, therefore, used to determine stability of river ecosystems, especially in regulated rivers. However, exactly how such disturbances alter spatial distribution of phytoplankton remains unclear, particularly during different seasons. A thorough understanding of these mechanisms is required to better analyze impact of environmental factors on regulated rivers. Given this, phytoplankton communities, streamflow, and water quality factors were assessed in areas sampled four times from 2015 to 2016 in upper and middle Huai River Basin. Biodiversity indices, as well as cluster and rank analyses, were used to (1) determine phytoplankton composition and distribution and (2) clarify impacts of key streamflow and water quality factors on such communities. It was found phytoplankton composition deteriorated over time, with phyla number decreasing from six to three. Moreover, proportion of Bacillariophyta increased from 51.83% to 68.13%. Phytoplankton in three regions, upstream region (Shannon-Wiener index 1.39–2.95), midstream region (0.70–4.55), and downstream region (0.22 to 2.97), were spatially clustered. The most impact factors impacting variation in composition and distribution were water quality factors and then hydrological factors. Of these, the most important factors in wet seasons were total nitrogen and maximum runoff, while ammonia nitrogen and low flow discharge were the most important factors during dry seasons. Streamflow and water quality contributed the most in midstream region, which was significantly affected by numbers of high and low flow. Contributions of these factors to downstream region were the strongest during dry seasons, which were significantly affected by numbers of low flow. Collectively, these results reveal significant impact of streamflow and water quality factors on phytoplankton deterioration in upper and middle Huai River Basin. Critically, this study provides scientific and technological support for increased biomonitoring and ecohydrological studies in regulated river basins.

Spatio-temporal dynamics of water quality and their linkages with the watershed landscape in highly disturbed headwater watersheds in China.

The water quality of headwater streams is a worldwide concern because of their critical roles in supplying clean water for drinking and other consumptive uses. Here, we evaluate temporal trends and spatial dynamics of the permanganate index (COD), ammonia-nitrogen (AN), and total phosphorus (TP) for 31 sites in headwater watersheds of the Huai River Basin, China. The seasonal Mann-Kendall test and correlation and variance analyses were applied to long-term time series (2003-2010) of water quality data in order to investigate the patterns of water quality trends, as well as their linkages with the watershed landscape. The results indicated that (1) more than 1/3 of headwater monitoring sites have exhibited either significantly increasing or decreasing trends in COD, AN and TP, while only TP increased for most them; (2) obvious increasing concentration gradients were observed for all water quality parameters along the upstream to the downstream continuum. Such spatial patterns can be highly explained by land cover and landscape configuration metrics. The percent of urban land and urban-related landscape metrics (such as the Landscape Division Index) were the primary explanatory variables for AN, while the aggregation metrics of cropland and urban land cover were the main predictors of COD and TP; (3) historical dynamics of COD, AN, and TP were influenced by land cover transitions. The trends of COD and TP may be attributable to the change in the wetland landscape, while the trends of AN were likely related to changes in forestland area as well as environmental management. Overall, our study determined the spatial and temporal dynamics of water quality parameters in the headwater watersheds and interpreted the possible reasons behind their spatio-temporal dynamics, which can have important implications for sustainable landscape planning as well as headwater watershed management.

Nonstationarity-based evaluation of flood frequency and flood risk in the Huai River basin, China

Using monthly streamflow data from 9 gauging stations covering a period of 1960–2014 across the Huai River basin, China, the Pettitt method and GAMLSS model were used to quantify flood frequency and related implications for flood hazards. Results indicated that: (1) no significant change points were observed in flood flows at the Huangchuan, Hengpaitou and Bengbu stations. However, significant hydrological alterations were detected for flood flows at other 6 stations with change points during ∼2000; (2) flood flows at the Bantai, Jiangjiaji and Hengpaitou stations were nonstationary but stationary flood flows were detected at other 6 stations. The Weibull distribution was the appropriate probability distribution describing flood flows across the Huai River basin and the lognormal distribution is the second best distribution; (3) no significant difference was detected for 10- and 20-year flood frequencies using the Pearson III type distribution function under the stationarity assumption. However, significant and increasing differences were expected for 30-, 50- and 100-year floods. It can be concluded that the assumption of stationarity, if the flood flows are actually nonstationary, can produce biased flood frequencies using Pearson III type distribution, and this result provides a critical reference for flood frequency analysis under the nonstationarity and/or stationarity assumption; (4) after 30 years, the flood magnification factor at Hengpaitou and Bengbu stations increased from 1 to 1.12 and from 1 to 1.06, respectively, implying higher flood risks at the Hengpaitou station. In addition, after 30 years, the return period of 100 year flood decreased from 100 years to less 70 years at the Hengpaitou station and from 100 years to nearly 78 years, implying higher frequency of floods with return periods of 100 years. Moreover, significant relations were detected between annual peak flood flow and flood-affected crop areas, implying that annual peak flood flow can be taken as an indicator of flood disasters across the Huai River basin and even in the Anhui province.

Dominant variation modes associated with Yangtze–Huai River Basin summer heavy rainfall events

ABSTRACTThe Yangtze–Huai River Basin (YHRB) always suffers from anomalously heavy rainfall during the warm season, and has been well explored as a whole area during the past several decades. In thi...

Arsenic pollution of sediments in China: An assessment by geochemical baseline

Arsenic (As) contamination in sediments has been reported worldwide. However, few studies have investigated As contamination on a national scale in China. This study aims to address this gap by analyzing the existing literature on As contamination and sediment samples collected from ten main river basins: the Songhua River Basin (SRB), Liao River Basin (LRB), Hai River Basin (HRB), Yellow River Basin (YRB), Huai River Basin (HuRB), Yangtze River Basin (YtRB), Pearl River Basin (PRB), Southeastern River Basin (SeRB), Southwestern River Basin (SwRB), and Northwestern River Basin (NwRB). Regional geochemical baseline (RGB) values of As in the sediments of river basins were calculated to estimate human contributions of As using normalization and cumulative frequency distribution curves. The established RGB values in the SRB, YtRB, and PRB were higher than the corresponding regional soil background (RSB), possibly because of the high intensity of human activities in the SRB, YtRB, and PRB. Taking RGB and RSB values as the background references, contamination assessment yielded important information on As contamination in China. With high As contributions from Yunnan province, the PRB suffered from the highest level of contamination, and the mean human contribution of As in the PRB was 64.4%. The contamination levels in the less developed southwestern regions were even higher than in some river basins in economically developed regions (e.g., YRB). In addition, As in the PRB and YtRB was found to be partially contributed by industrial wastewater discharge, and the response of As contamination in sediments to industrial wastewater discharge was analyzed. The temporal change (2004–2016) of As in sediments from the PRB, YtRB, and YRB corresponded well with that of As discharged in wastewater within the corresponding river basins. This study thus serves as a valuable foundation for policies focused on ameliorating As contamination in China.

Impact of climatic change on water resources in Huia river basin, China

Research on the impact of climate change on water resources has attracted the attention of academician and policy makers. This paper tends to analyze the impact of changes in air temperature and rainfall factors on the amount of water resources in the Huai River Basin from 1980 to 2014. Air temperature and rainfall data were collected from six meteorological stations. Hydrological and water resources evaluation data were collected from the Bengbu Hydrological Station in the Huai River Basin. Research findings revealed an increasing trend of average annual air temperature, with the highest increase of 0.293oC recorded at Bengbu in Anhui Province. The western part of the study area has shown a rising rainfall while the eastern part (the middle reaches of the Huai River) witnessed a declining rainfall. The rainfall in the Huai River Basin was significantly influenced by the natural fluctuations as the average rainfall in the study area was in a vaguely declining trend. This resulted in gradual decrease in the quantity of the Basin’s water resources due to decreasing rainfall and rising air temperature. Regression and sensitivity analyses were employed to develop a mathematical model between water resources quantity and changes in air temperature and rainfall. Based on regression analysis findings, changes in rainfall have a much bigger impact on its water resources quantity than changes in its air temperature.

Tracking Jianghuai Cyclones in China and Their Climate Characteristics

A Jianghuai cyclone is an extratropical cyclone, which influences the middle and lower reaches of the Yangtze River and Huai River basins in China. According to the definition of Jianghuai cyclones, statistics of their climate characteristics from 1979 to 2010 are obtained by an objective detection and tracking algorithm using ERA-Interim reanalysis data. The results show that the frequency of Jianghuai cyclones has a strong year-to-year variability but no obvious trend. Jianghuai cyclones are most frequent in May but fewest in December. As the cold air is active in spring, which interacts with the warm air from the southwest of the subtropical high at the Yangtze-Huai River region, it makes Jianghuai cyclones occur more frequently in this season. The main origins of Jianghuai cyclones are located in the Poyang Lake region, Dongting Lake region, and Dabie Mountain area. The maximum deepening rate of 0–2 hPa/6h is featured in 66.4% of Jianghuai cyclones. Over 40% of Jianghuai cyclones have a mean deepening rate of 0–1 hPa/6h. The lifetime of Jianghuai cyclones is short, mainly lasting for one to two days. In addition, background characteristics are compared between the formation, climax, and decaying periods of Jianghuai cyclones.

A Pilot‐Scale Diatomite Membrane Bioreactor for Slightly Polluted Surface Water Treatment

In the Huai River basin in China, seasonal pollution, especially excess ammonia nitrogen (NH4+‐N), threatens the water quality. This study investigates the performance of a pilot‐scale diatomite membrane bioreactor (DE‐MBR) for treating slightly polluted surface water (Huai River). Removal efficiencies for the chemical oxygen demand (CODMn), NH4+‐N, and turbidity, as well as the molecular weight (MW) of the raw water, mixed liquor and effluent, particle size of the bio‐diatomite, trans‐membrane pressure (TMP) of the system, and microscopic characteristics of the membrane, are monitored for 135 days. The results shows that (1) with the diatomite addition of 4 g L−1, the DE‐MBR contributes to significant removals of CODMn and NH4+‐N; (2) the TMP increases at an average rate of 0.04 kPa/day during the running period; (3) the MW distributions and natural organic matter fraction demonstrates that a significant increase of biopolymers occurs in the mixed liquor; (4) the highest removal rate of the charged hydrophilic acids indicates that aromatic proteins are more likely to be removed by the DE‐MBR compared to humic‐like substances; and (5) microscopic observations shows that hydrophobic micromolecular organics are the main contributors leading to hydraulically irreversible membrane fouling.

The Holocene optimum (HO) and the response of human activity: A case study of the Huai River Basin in eastern China

There is a controversy regarding the timing of the onset of the Holocene optimum (HO) in the Huai River Basin in eastern China, reflecting the scarcity of well-dated high-resolution sedimentary records in the region. In this study we validate the time-transgressive onset of the HO in the East Asian Monsoon (EAM) region and update a regression model of the onset of the HO versus latitude. We also estimate the onset time of the HO in the Huai River Basin to 9100-8000 yr BP, which is confirmed by other well-dated geological records from within and around the basin. We also compared our age estimate with data from archaeological sites in the Huai River Basin and with the record of rice remains in eastern China. The result indicates that a dramatic increase in the number of archaeological sites and the northward expansion of rice cultivation, which eventually occupied the entire Huai River Basin, corresponds temporally to the onset of the HO. Thus our results suggest that the prosperity of prehistoric culture in the Huai River Basin was enhanced by the initiation of the HO. Our findings reveal a close relationship between the onset of the HO in the Huai River Basin and human activity, and they provide an improved understanding of the response of human activity to climate change in eastern China.

ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin

The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods.

Spatiotemporal Patterns of Extreme Temperature across the Huai River Basin, China, during 1961–2014, and Regional Responses to Global Changes

Global warming and its relevant effects have aroused increasing human concerns in recent decades. These anomalies are likely influencing vegetation dynamics and ecosystem stability. This paper aims to dissect extreme temperature variations in both space and time, and related regional responses to global warming in the Huai River Basin. Using the daily maximum and minimum air temperature at 153 stations across the Huai River Basin, China, covering the period of 1961–2014, trends and relations amongst extreme air temperature indices were analyzed, and regional responses of the Huai River Basin to global warming process were also investigated. The results indicated that: (1) widespread increasing trends can be observed in maximum and minimum air temperature, with the largest increasing magnitude of 0.4 °C per decade and 1.3 °C per decade, respectively. The minimum air temperature regimes have a larger increasing magnitude than the maximum air temperatures. (2) There is an increasing trend in the extreme maximum temperature indices, and the increasing rates of TN90p and TR20 are greater than those of the other extreme maximum temperature indices. However, the extreme minimum temperature indices, except for consecutive icy days (CID), show significant decreasing trends. The growing season length (GSL) would increase due to the joint action of (i) an increase in maximum temperature indices, and (ii) a decrease in minimum temperatures indices. Although increases in the GSL would be beneficial for increasing the growing time of crops, a decreased extreme minimum temperature and increased extreme maximum temperature may reduce the winter wheat yield. (3) Extreme low temperature indices show a larger changing magnitude than the extreme high temperature indices. Temporally, a larger changing magnitude can be identified for temperature indices during night-time than during daytime. Moreover, a larger changing magnitude and higher significance of trends of extreme temperature indices can be observed in the eastern Huai River Basin than in the western Huai River Basin. Particularly, we detect an even higher changing rate of extreme temperature indices in the southeastern Huai River Basin. These findings can be well explained by urban heat island effects resulting from urban aggregation across the Yangtze Delta. (4) The correlation between the extreme low temperature indices is slightly higher than that of the extreme high temperature indices. The changing trends of the most extreme temperature indices are closely related to latitude and altitude. Trends in the main extreme temperature indices of the Huai River Basin are essentially similar to those in other regions around the world, implying consistent spatial patterns of extreme temperature indices across the globe.

Reference Evapotranspiration Variation Analysis and Its Approaches Evaluation of 13 Empirical Models in Sub-Humid and Humid Regions: A Case Study of the Huai River Basin, Eastern China

Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman–Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash–Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961–2000 and 2001–2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April–October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.

Ecological risks posed by ammonia nitrogen (AN) and un-ionized ammonia (NH3) in seven major river systems of China

Previous studies showed that continuous exposure to ammonia nitrogen (AN) contributed to regional losses of benthic invertebrate diversity in China. Yet, the overall ecological risk of AN to aquatic organisms in major riverine systems of China has not been appropriately studied. Our research then investigated temporal (seasonally/yearly) and spatial distributions of AN and un-ionized ammonia (NH3) in major Chinese river basins using historic data generated between 2007 and 2014, and developed risk assessment criteria. Our results showed that the highest average AN concentrations occurred during winter (0.82–2.76 mg/L) and the lowest during summer (0.36–0.78 mg/L). NH3 exhibited the opposite trend with the highest average concentrations mostly observed during spring (15.13–92.84 μg/L) and the lowest concentrations mainly during winter (10.53–45.43 μg/L). Both AN and NH3 concentrations steadily increased and reached maximum levels in 2008 (AN: 1.22 mg/L and NH3: 50.65 μg/L), and then decreased. Temporal trends showed that the Yellow, Hai, and Huai river basins had the highest AN and NH3 concentrations. Subsequently, conventional (hazard quotients) and probabilistic (joint probability curves) methods were applied to assess the hazards and risks posed by AN and NH3. The results showed that the probability of exceeding the acute toxicity threshold for 5% of species (exposed to AN or NH3) was less than 13.3% and gradually decreased over time. To protect aquatic organisms, an acute criterion of 51.4 μg NH3/L and a chronic criterion of 1.14 mg AN/L at pH = 7.5, 20 °C were developed and are recommended for future risk assessment studies.