To understand the CH_(4) flux variations and their climatic drivers in the rice-wheat agroecosystem in the Huai River Basin of China,the CH_(4) flux was observed by using open-path eddy covariance at a typical rice-wh...To understand the CH_(4) flux variations and their climatic drivers in the rice-wheat agroecosystem in the Huai River Basin of China,the CH_(4) flux was observed by using open-path eddy covariance at a typical rice-wheat rotation system in Anhui Province,China from November 2019 to October 2021.The variations and their drivers were then analyzed with the Akaike information criterion method.CH_(4) flux showed distinct diurnal variations with single peaks during 9:00-13:00 local time.The highest peak was 2.15μg m^(-2)s^(-1)which occurred at 11:00 in the vegetative growth stage in the rice growing season(RGS).CH_(4) flux also showed significant seasonal variations.The average CH_(4)flux in the vegetative growth stage in the RGS(193.8±74.2 mg m^(-2)d^(-1))was the highest among all growth stages.The annual total CH_(4) flux in the non-rice growing season(3.2 g m^(-2))was relatively small compared to that in the RGS(23.9 g m^(-2)).CH_(4) flux increased significantly with increase in air temperature,soil temperature,and soil water content in both the RGS and the non-RGS,while it decreased significantly with increase in vapor pressure deficit in the RGS.This study provided a comprehensive understanding of the CH_(4) flux and its drivers in the rice-wheat rotation agroecosystem in the Huai River Basin of China.In addition,our findings will be helpful for the validation and adjustment of the CH_(4) models in this region.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
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
The 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 this study,the YHRB is divided int...The 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 this study,the YHRB is divided into two core regions-the northern YHRB(nYHRB)and southern YHRB(sYHRB)-based on 29-year(1979–2007)June–July–August(JJA)temporally averaged daily rainfall rates and the standard deviation of rainfall.A spectral analysis of JJA daily rainfall data over these 29 years reveals that a 3–7-day synoptic-timescale high-frequency mode is absolutely dominant over the nYHRB,with 10–20-day and 15–40-day modes playing a secondary role.By contrast,3–7-day and 10–20-day modes are both significant over the sYHRB,with 7–14-day,15–40-day,and 20–60-day modes playing secondary roles.Based on a comparison between bandpass-filtered rainfall anomalies and original rainfall series,a total of 42,1,5,and 3 heavy rainfall events(daily rainfall amounts in the top 5%of rainy days)are detected over the nYHRB,corresponding to 3–7-day,7–14-day,10–20-day,and 15–40-day variation disturbances.Meanwhile,a total of 28,8,12,and 6 heavy rainfall events are detected over the sYHRB,corresponding to 3–7-day,7–14-day,10–20-day,and 20–60-day variation disturbances.The results have important implications for understanding the duration of summer heavy rainfall events over both regions.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 Natural Science Foundation of Jiangsu Province,China(BK20220017)the Innovation Development Project of China Meteorological Administration(CXFZ2023J073)+1 种基金the Key Research and Development Program of Anhui Province,China(2022M07020003)the Graduate Student Practice and Innovation Program of Jiangsu Province,China(SJCX22_0374)。
文摘To understand the CH_(4) flux variations and their climatic drivers in the rice-wheat agroecosystem in the Huai River Basin of China,the CH_(4) flux was observed by using open-path eddy covariance at a typical rice-wheat rotation system in Anhui Province,China from November 2019 to October 2021.The variations and their drivers were then analyzed with the Akaike information criterion method.CH_(4) flux showed distinct diurnal variations with single peaks during 9:00-13:00 local time.The highest peak was 2.15μg m^(-2)s^(-1)which occurred at 11:00 in the vegetative growth stage in the rice growing season(RGS).CH_(4) flux also showed significant seasonal variations.The average CH_(4)flux in the vegetative growth stage in the RGS(193.8±74.2 mg m^(-2)d^(-1))was the highest among all growth stages.The annual total CH_(4) flux in the non-rice growing season(3.2 g m^(-2))was relatively small compared to that in the RGS(23.9 g m^(-2)).CH_(4) flux increased significantly with increase in air temperature,soil temperature,and soil water content in both the RGS and the non-RGS,while it decreased significantly with increase in vapor pressure deficit in the RGS.This study provided a comprehensive understanding of the CH_(4) flux and its drivers in the rice-wheat rotation agroecosystem in the Huai River Basin of China.In addition,our findings will be helpful for the validation and adjustment of the CH_(4) models in this region.
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 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jointly supported by the National Basic Research Program of China [973 Program,grant number2015CB954102]the National Natural Science Foundation of China [grant number 41475043]
文摘The 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 this study,the YHRB is divided into two core regions-the northern YHRB(nYHRB)and southern YHRB(sYHRB)-based on 29-year(1979–2007)June–July–August(JJA)temporally averaged daily rainfall rates and the standard deviation of rainfall.A spectral analysis of JJA daily rainfall data over these 29 years reveals that a 3–7-day synoptic-timescale high-frequency mode is absolutely dominant over the nYHRB,with 10–20-day and 15–40-day modes playing a secondary role.By contrast,3–7-day and 10–20-day modes are both significant over the sYHRB,with 7–14-day,15–40-day,and 20–60-day modes playing secondary roles.Based on a comparison between bandpass-filtered rainfall anomalies and original rainfall series,a total of 42,1,5,and 3 heavy rainfall events(daily rainfall amounts in the top 5%of rainy days)are detected over the nYHRB,corresponding to 3–7-day,7–14-day,10–20-day,and 15–40-day variation disturbances.Meanwhile,a total of 28,8,12,and 6 heavy rainfall events are detected over the sYHRB,corresponding to 3–7-day,7–14-day,10–20-day,and 20–60-day variation disturbances.The results have important implications for understanding the duration of summer heavy rainfall events over both regions.
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.
