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
Drought is the most widespread and insidious natural hazard, presenting serious challenges to ecosystems and human society. The daily Standardized Precipitation Evapotranspiration Index(SPEI) has been developed to ide...Drought is the most widespread and insidious natural hazard, presenting serious challenges to ecosystems and human society. The daily Standardized Precipitation Evapotranspiration Index(SPEI) has been developed to identify the regional spatiotemporal characteristics of drought conditions from 1960 to 2016, revealing the variability in drought characteristics across Southwest China. Daily data from142 meteorological stations across the region were used to calculate the daily SPEI at the annual and seasonal time scale. The Mann-Kendall test and the trend statistics were then applied to quantify the significance of drought trends, with the following results. 1) The regionally averaged intensity and duration of all-drought and severe drought showed increasing trends, while the intensity and duration of extreme drought exhibited decreasing trends. 2) Mixed(increasing/decreasing) trends were detected, in terms of intensity and duration, in the three types of drought events. In general, no evidence of significant trends(P < 0.05) was detected in the drought intensity and duration over the last 55 years at the annual timescale. Seasonally, spring was characterized by a severe drought trend for all drought and severe drought conditions, while extreme drought events in spring and summer were very severe. All drought intensities and durations showed an increasing trend across most regions, except in the northwestern parts of Sichuan Province. However, the areal extent of regions suffering increasing trends in severe and extreme drought became relatively smaller. 3) We identified the following drought hotspots: Guangxi Zhuang Autonomous Region from the 1960 s to the 1990 s, respectively. Guangxi Zhuang Autonomous Region and Guizhou Province in the 1970 s and 1980 s, and Yunnan Province in the 2000 s. Finally, this paper can benefit operational drought characterization with a day-to-day drought monitoring index, enabling a more risk-based drought management strategy in the context of global warming.展开更多
Exact prediction of evapotranspiration is necessary for study, design and management of irrigation systems. In this research, the suitability of soft computing approaches namely, fuzzy rule base, fuzzy regression and ...Exact prediction of evapotranspiration is necessary for study, design and management of irrigation systems. In this research, the suitability of soft computing approaches namely, fuzzy rule base, fuzzy regression and artificial neural networks for estimation of daily evapotranspiration has been examined and the results are compared to real data measured by lysimeter on the basis of reference crop (grass). Using daily climatic data from Haji Abad station in Hormozgan, west of Iran, including maximum and minimum temperatures, maximum and minimum relative humidities, wind speed and sunny hours, evapotranspiration was predicted by soft computing methods. The predicted evapotranspiration values from fuzzy rule base, fuzzy linear regression and artificial neural networks show root mean square error (RMSE) of 0.75, 0.79 and 0.81 mm/day and coefficient of determination of (R2) of 0.90, 0.87 and 0.85, respectively. Therefore, fuzzy rule base approach was found to be the most appropriate method employed for estimating evapotranspiration.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Under the auspices of National Natural Science Foundation of China(No.41561024)Philosophy Social Science Foundation of Shanxi Province of China(No.2015265)
文摘Drought is the most widespread and insidious natural hazard, presenting serious challenges to ecosystems and human society. The daily Standardized Precipitation Evapotranspiration Index(SPEI) has been developed to identify the regional spatiotemporal characteristics of drought conditions from 1960 to 2016, revealing the variability in drought characteristics across Southwest China. Daily data from142 meteorological stations across the region were used to calculate the daily SPEI at the annual and seasonal time scale. The Mann-Kendall test and the trend statistics were then applied to quantify the significance of drought trends, with the following results. 1) The regionally averaged intensity and duration of all-drought and severe drought showed increasing trends, while the intensity and duration of extreme drought exhibited decreasing trends. 2) Mixed(increasing/decreasing) trends were detected, in terms of intensity and duration, in the three types of drought events. In general, no evidence of significant trends(P < 0.05) was detected in the drought intensity and duration over the last 55 years at the annual timescale. Seasonally, spring was characterized by a severe drought trend for all drought and severe drought conditions, while extreme drought events in spring and summer were very severe. All drought intensities and durations showed an increasing trend across most regions, except in the northwestern parts of Sichuan Province. However, the areal extent of regions suffering increasing trends in severe and extreme drought became relatively smaller. 3) We identified the following drought hotspots: Guangxi Zhuang Autonomous Region from the 1960 s to the 1990 s, respectively. Guangxi Zhuang Autonomous Region and Guizhou Province in the 1970 s and 1980 s, and Yunnan Province in the 2000 s. Finally, this paper can benefit operational drought characterization with a day-to-day drought monitoring index, enabling a more risk-based drought management strategy in the context of global warming.
文摘Exact prediction of evapotranspiration is necessary for study, design and management of irrigation systems. In this research, the suitability of soft computing approaches namely, fuzzy rule base, fuzzy regression and artificial neural networks for estimation of daily evapotranspiration has been examined and the results are compared to real data measured by lysimeter on the basis of reference crop (grass). Using daily climatic data from Haji Abad station in Hormozgan, west of Iran, including maximum and minimum temperatures, maximum and minimum relative humidities, wind speed and sunny hours, evapotranspiration was predicted by soft computing methods. The predicted evapotranspiration values from fuzzy rule base, fuzzy linear regression and artificial neural networks show root mean square error (RMSE) of 0.75, 0.79 and 0.81 mm/day and coefficient of determination of (R2) of 0.90, 0.87 and 0.85, respectively. Therefore, fuzzy rule base approach was found to be the most appropriate method employed for estimating evapotranspiration.
文摘基于陆面能量平衡原理,通过对搭载在欧洲空间局环境卫星(Environmental Satellite,ENVI-SAT)上中分辨率影像光谱仪(Medium Resolution Imaging Spectrometer,MERIS)2005年6月7,11和27日的遥感观测资料进行大气纠正等预处理后,得到估算瞬时蒸散发量所需要的地表反照率和植被覆盖度等值,并利用分裂窗法和ENVISAT上搭载的先进的沿轨迹扫描辐射计(Advanced Along-TrackScanning Radiometer,AATSR)的观测资料进行了地表温度的反演,进一步估算出黄土高原塬区午间瞬时净辐射、感热通量和土壤热通量。结合与卫星遥感观测资料同期研究区域气象站的太阳辐射、气温、日照时数和风速等气象要素资料,充分考虑到植被冠层和陆地表面对蒸散发量的不同影响,发展了一个可以估算陆面潜热的简化模型,并将瞬时蒸散发量转化为日蒸散发量。对卫星遥感估算的潜热通量,利用黄土高原塬区陆面过程野外观测试验(Loess Plateau land surface process field Experiments,LOPEXs)的地面通量观测资料进行验证,结果表明:二者最大相对差异为10.9%,最小相对差异为4.8%,并对差异误差产生的原因进行了分析和探讨。
