The objective of this study is to evaluate the performance of three models for estimating daily evapotranspiration(ET) by employing flux observation data from three years(2007, 2008 and 2009) during the growing season...The objective of this study is to evaluate the performance of three models for estimating daily evapotranspiration(ET) by employing flux observation data from three years(2007, 2008 and 2009) during the growing seasons of winter wheat and rice crops cultivated in a farmland ecosystem(Shouxian County) located in the Huai River Basin(HRB), China. The first model is a two-step model(PM-Kc);the other two are one-step models(e.g., Rana-Katerji(R-K) and advection-aridity(AA)). The results showed that the energy closure degrees of eddy covariance(EC) data during winter wheat and rice-growing seasons were reasonable in the HRB, with values ranging from 0.84 to 0.91 and R2 of approximately 0.80. Daily ET of winter wheat showed a slow decreasing trend followed by a rapid increase, while that of rice presented a decreasing trend after an increase. After calibrating the crop coefficient(Kc), the PM–Kc model performed better than the model using the Kc recommended by the Food and Agricultural Organization(FAO). The calibrated key parameters of the R-K model and AA model showed better universality. After calibration, the simulation performance of the PM-Kc model was satisfactory. Both the R-K model and AA model underestimated the daily ET of winter wheat and rice. Compared with that of the R-K model, the simulation result of the AA model was better, especially in the simulation of daily ET of rice. Overall, this research highlighted the consistency of the PM-Kc model to estimate the water demand for rice and wheat crops in the HRB and in similar climatic regions in the world.展开更多
In this study,a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast(WRF) model.The simulation reprod...In this study,a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast(WRF) model.The simulation reproduces reasonably well the evolution of the rainfall during the study period's three successive rainy phases,especially the frequent heavy rainfall events occurring in the Huai River Basin.The model captures the major rainfall peak observed by the monitoring stations in the morning.Another peak appears later than that shown by the observations.In addition,the simulation realistically captures not only the evolution of the low-level winds but also the characteristics of their diurnal variation.The strong southwesterly(low-level jet,LLJ) wind speed increases beginning in the early evening and reaches a peak in the morning;it then gradually decreases until the afternoon.The intense LLJ forms a strong convergent circulation pattern in the early morning along the Yangtze-Huai River Basin.This pattern partly explains the rainfall peak observed at this time.This study furnishes a basis for the further analysis of the mechanisms of evolution of the LLJ and for the further study of the interactions between the LLJ and rainfall.展开更多
The Huai River Basin is a unique area in P.R.China with the highest densities of population and water projects.It is also subject to the most serious water pollution.We proposed a distributional SWAT(Soil and Water As...The Huai River Basin is a unique area in P.R.China with the highest densities of population and water projects.It is also subject to the most serious water pollution.We proposed a distributional SWAT(Soil and Water Assessment Tool) model coupled with a water quality-quantity balance model to evaluate dam impacts on river flow regimes and water quality in the middle and upper reaches of the Huai River Basin.We calibrated and validated the SWAT model with data from 29 selected cross-sections in four typical years(1971,1981,1991 and 1999) and used scenario analysis to compensate for the unavailability of historical data regarding uninterrupted river flows before dam and floodgate construction,a problem of prediction for ungauged basins.The results indicate that dam and floodgate operations tended to reduce runoff,decrease peak value and shift peaking time.The contribution of water projects to river water quality deterioration in the concerned river system was between 0 to 40%,while pollutant discharge contributed to 60% to 100% of the water pollution.Pollution control should therefore be the key to the water quality rehabilitation in the Huai River Basin.展开更多
Quantitative assessment of water quality and its spatial variation identification, as well as the discernment of primary factors affecting water quality are in its urgent in water environment management. In this study...Quantitative assessment of water quality and its spatial variation identification, as well as the discernment of primary factors affecting water quality are in its urgent in water environment management. In this study, four key water quality indicators,namely, ammonia nitrogen(NH_4^+-N), permanganate index(COD_(Mn)), total phosphorus(TP) and total nitrogen(TN) at 71 sampling sites were selected to evaluate water quality and its spatial variation identification. More concerns were emphasized on the anthropogenic factors(land use pattern) and natural factors(river density, elevation and precipitation) to quantify the overall water quality variations at different spatial scales. Results showed that the Yi-Shu-Si River sub-basin had a better water quality status than the Huai River sub-basin. The moderate polluted area nearly distributed in the upper and middle reaches of the Shaying River and Guo River. The high cluster centers which were surrounded with COD_(Mn), NH_4^+-N, TN and TP mainly also distributed in the upper and middle reaches of the Shaying River and Guo River. Redundancy analysis showed that the 200 m buffer area acted as the most sensitive area, which was easily subjected to pollution. The precipitation was identified as the most important variables among all the studied hydrological units, followed by farmland, urban land or elevation. The point source pollution was still existed although the non-point source pollution was also identified. The urban surface runoff pollution was severer than farmland fertilizer loss at the sub-basin scale in flood season, while the farmland showed "small-scale" effects for explaining overall water quality variations. This research is helpful for identifying the overall water quality variations from the scale-process interactions and providing a scientific basis for pollution control and decision making for the Huai River Basin.展开更多
基金supported by the National Natural Science Foundation of China (41905100)the Anhui Provincial Natural Science Foundation, China (1908085QD171)+3 种基金the Anhui Agricultural University Science Foundation for Young Scholars, China (2018zd07)the Anhui Agricultural University Introduction and Stabilization of Talent Fund, China (yj2018-57)the National Key Research and Development Program of China (2018YFD0300905)the Postgraduate Research and Practice Innovation Program of Jiangsu Province, China (KYCX17_0885)。
文摘The objective of this study is to evaluate the performance of three models for estimating daily evapotranspiration(ET) by employing flux observation data from three years(2007, 2008 and 2009) during the growing seasons of winter wheat and rice crops cultivated in a farmland ecosystem(Shouxian County) located in the Huai River Basin(HRB), China. The first model is a two-step model(PM-Kc);the other two are one-step models(e.g., Rana-Katerji(R-K) and advection-aridity(AA)). The results showed that the energy closure degrees of eddy covariance(EC) data during winter wheat and rice-growing seasons were reasonable in the HRB, with values ranging from 0.84 to 0.91 and R2 of approximately 0.80. Daily ET of winter wheat showed a slow decreasing trend followed by a rapid increase, while that of rice presented a decreasing trend after an increase. After calibrating the crop coefficient(Kc), the PM–Kc model performed better than the model using the Kc recommended by the Food and Agricultural Organization(FAO). The calibrated key parameters of the R-K model and AA model showed better universality. After calibration, the simulation performance of the PM-Kc model was satisfactory. Both the R-K model and AA model underestimated the daily ET of winter wheat and rice. Compared with that of the R-K model, the simulation result of the AA model was better, especially in the simulation of daily ET of rice. Overall, this research highlighted the consistency of the PM-Kc model to estimate the water demand for rice and wheat crops in the HRB and in similar climatic regions in the world.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-04)the National High Technology Research and Development Program of China (863 Program, Grant No. 2010AA012304)+2 种基金the National Natural Science Foundation of China (Grant No. 40905049)the LASG State Key Laboratory special fundthe LASG free exploration fund
文摘In this study,a 47-day regional climate simulation of the heavy rainfall in the Yangtze-Huai River Basin during the summer of 2003 was conducted using the Weather Research and Forecast(WRF) model.The simulation reproduces reasonably well the evolution of the rainfall during the study period's three successive rainy phases,especially the frequent heavy rainfall events occurring in the Huai River Basin.The model captures the major rainfall peak observed by the monitoring stations in the morning.Another peak appears later than that shown by the observations.In addition,the simulation realistically captures not only the evolution of the low-level winds but also the characteristics of their diurnal variation.The strong southwesterly(low-level jet,LLJ) wind speed increases beginning in the early evening and reaches a peak in the morning;it then gradually decreases until the afternoon.The intense LLJ forms a strong convergent circulation pattern in the early morning along the Yangtze-Huai River Basin.This pattern partly explains the rainfall peak observed at this time.This study furnishes a basis for the further analysis of the mechanisms of evolution of the LLJ and for the further study of the interactions between the LLJ and rainfall.
基金Funded by the Key Project of International Cooperation of the Natural Science Foundation of China (No. 40721140020)the Key Project of the Natural Science Foundation of China (No. 40730632)
文摘The Huai River Basin is a unique area in P.R.China with the highest densities of population and water projects.It is also subject to the most serious water pollution.We proposed a distributional SWAT(Soil and Water Assessment Tool) model coupled with a water quality-quantity balance model to evaluate dam impacts on river flow regimes and water quality in the middle and upper reaches of the Huai River Basin.We calibrated and validated the SWAT model with data from 29 selected cross-sections in four typical years(1971,1981,1991 and 1999) and used scenario analysis to compensate for the unavailability of historical data regarding uninterrupted river flows before dam and floodgate construction,a problem of prediction for ungauged basins.The results indicate that dam and floodgate operations tended to reduce runoff,decrease peak value and shift peaking time.The contribution of water projects to river water quality deterioration in the concerned river system was between 0 to 40%,while pollutant discharge contributed to 60% to 100% of the water pollution.Pollution control should therefore be the key to the water quality rehabilitation in the Huai River Basin.
基金supported by the National Grand Science and Technology Special Project of Water Pollution Control and Improvement (Grant No. 2014ZX07204-006)the National Natural Science Foundation of China (Grant No. 41571028)the Key Point Deploy Project of Chinese Academy of Sciences (Grant No.KFZD-SW-301)
文摘Quantitative assessment of water quality and its spatial variation identification, as well as the discernment of primary factors affecting water quality are in its urgent in water environment management. In this study, four key water quality indicators,namely, ammonia nitrogen(NH_4^+-N), permanganate index(COD_(Mn)), total phosphorus(TP) and total nitrogen(TN) at 71 sampling sites were selected to evaluate water quality and its spatial variation identification. More concerns were emphasized on the anthropogenic factors(land use pattern) and natural factors(river density, elevation and precipitation) to quantify the overall water quality variations at different spatial scales. Results showed that the Yi-Shu-Si River sub-basin had a better water quality status than the Huai River sub-basin. The moderate polluted area nearly distributed in the upper and middle reaches of the Shaying River and Guo River. The high cluster centers which were surrounded with COD_(Mn), NH_4^+-N, TN and TP mainly also distributed in the upper and middle reaches of the Shaying River and Guo River. Redundancy analysis showed that the 200 m buffer area acted as the most sensitive area, which was easily subjected to pollution. The precipitation was identified as the most important variables among all the studied hydrological units, followed by farmland, urban land or elevation. The point source pollution was still existed although the non-point source pollution was also identified. The urban surface runoff pollution was severer than farmland fertilizer loss at the sub-basin scale in flood season, while the farmland showed "small-scale" effects for explaining overall water quality variations. This research is helpful for identifying the overall water quality variations from the scale-process interactions and providing a scientific basis for pollution control and decision making for the Huai River Basin.
基金financially supported by the National Natural Science Foundation of China(52079026)the National Key Research and Development Program of China(2021YFC3201100)+4 种基金the National Natural Science Foundation of China(41830863 and 61976044)Sichuan Science and Technology Program(2020YFH0037)the Belt and Road Fund on Water and Sustainability of the State Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering(2019nkzd02)the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin(IWHR-SKL-201911)the Fundamental Research Funds for the Central Universities(ZYGX2019Z014)。
文摘径流预报对防洪具有重要意义。然而,由于径流过程的复杂性和随机性,对日径流量进行准确预测是困难的,尤其是对峰值径流量的预测。为了解决这一问题,本研究提出了一种用于径流预测的增强型长短期记忆(LSTM)模型,其中引入了新的损失函数并集成了特征提取器。设计了峰值误差tanh(peak error tanh,PET)和峰值误差swish(peak error swish,PES)两个损失函数,增强了峰值径流预测的重要性,弱化了正常径流预测的权重。为每个气象站建立由3个LSTM网络组成的特征提取器,目的是提取每个气象站输入数据的时间特征。以中国淮河上游为例,利用增强型LSTM模型对1960—2016年的日径流量进行了预测。结果表明,改进后的LSTM模型表现良好,在验证期内(2005年11月至2016年12月),Nash-Sutcliffe效率(NSE)系数在0.917-0.924之间,优于广泛使用的集总水文模型(Australian Water Balance model(AWBM)、Sacramento、Sim Hyd和Tank模型)和数据驱动模型(人工神经网络(ANN)、支持向量回归(SVR)和门控循环单元(GRU))。以PES为损失函数的增强型LSTM对洪水极端径流的预测效果最好,平均NSE为0.873。此外,海拔较高的气象站降水对径流预测的贡献比最近的气象站更大。该研究为流域日径流预测提供了有效工具,有利于流域防洪和水安全管理。
