| 基于GEP和地理位置信息的湘鄂地区月参考作物腾发量模拟计算 |
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| 引用本文： | 王 升,付智勇,陈洪松,聂云鹏,王克林.基于GEP和地理位置信息的湘鄂地区月参考作物腾发量模拟计算[J].中国生态农业学报,2015,23(4):490-496. |
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| 作者姓名： | 王 升 付智勇 陈洪松 聂云鹏 王克林 |
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| 作者单位： | 1. 中国科学院亚热带农业生态研究所/中国科学院亚热带农业生态过程重点实验室 长沙 410125
2. 中国科学院环江喀斯特生态系统观测研究站 环江 547100 3. 中国科学院大学 北京 100049,1. 中国科学院亚热带农业生态研究所/中国科学院亚热带农业生态过程重点实验室 长沙 410125
2. 中国科学院环江喀斯特生态系统观测研究站 环江 547100,1. 中国科学院亚热带农业生态研究所/中国科学院亚热带农业生态过程重点实验室 长沙 410125
2. 中国科学院环江喀斯特生态系统观测研究站 环江 547100,1. 中国科学院亚热带农业生态研究所/中国科学院亚热带农业生态过程重点实验室 长沙 410125
2. 中国科学院环江喀斯特生态系统观测研究站 环江 547100,1. 中国科学院亚热带农业生态研究所/中国科学院亚热带农业生态过程重点实验室 长沙 410125
2. 中国科学院环江喀斯特生态系统观测研究站 环江 547100 |
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| 基金项目： | 中国科学院西部行动计划项目(KZCX2-XB3-10)、国家自然科学基金项目(41171187, 31100294)和湖南省自然科学基金项目(14JJ3144)资助 |
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| 摘 要： | 参考作物腾发量(ET0)是计算植被蒸散发的关键因子,准确估算ET0对水资源管理、灌溉制度设计等具有重要意义。本研究利用湘鄂地区46个气象站点1955—2005年的逐月气象数据,包括月最高气温、最低气温、平均风速、日照时数以及相对湿度,用FAO-56 Penman-Monteith法计算各站的逐月ET0值。然后结合基因表达式编程(GEP)算法挖掘公式的能力,以各站点的地理位置信息(纬度、经度、海拔)及月序数为输入,以多年逐月平均ET0值为输出,建立基于地理位置信息的月ET0模型,并与传统ET0模型的计算结果进行比较。结果表明,所建立的模型具有足够的精度,校正、检验阶段的决定系数(R2)和均方根误差(RMSE)分别为0.934、0.951和10.050 mm、8.628 mm;与Hargreaves和Priestley-Taylor法相比,基于地理位置信息建立的GEP模型的结果均方根误差最小,变化范围为8.628~9.967 mm。本研究所建立的月ET0模型具有明确的表达式,简单易用,在湘鄂地区仅利用地理位置信息计算逐月ET0是可行的,可以利用该模型进行月尺度的灌溉制度设计和植被蒸散发的估算。
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| 关 键 词： | 参考作物腾发量 基因表达式编程 地理位置信息 月尺度 湘鄂地区 |
| 收稿时间： | 2014/9/18 0:00:00 |
| 修稿时间： | 2014/12/11 0:00:00 |
Using Gene-Expression Programming method and geographical location information to simulate evapotranspiration in Hunan and Hubei Provinces |
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| WANG Sheng,FU Zhiyong,CHEN Hongsong,NIE Yunpeng and WANG Kelin.Using Gene-Expression Programming method and geographical location information to simulate evapotranspiration in Hunan and Hubei Provinces[J].Chinese Journal of Eco-Agriculture,2015,23(4):490-496. |
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| Authors: | WANG Sheng FU Zhiyong CHEN Hongsong NIE Yunpeng and WANG Kelin |
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| Institution: | 1. Institute of Subtropical Agriculture, Chinese Academy of Sciences / Key Laboratory of Agro-ecological Processes in Subtropical Region, Chinese Academy of Sciences, Changsha 410125, China 2. Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China 3. University of Chinese Academy of Sciences, Beijing 100049, China,1. Institute of Subtropical Agriculture, Chinese Academy of Sciences / Key Laboratory of Agro-ecological Processes in Subtropical Region, Chinese Academy of Sciences, Changsha 410125, China 2. Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China,1. Institute of Subtropical Agriculture, Chinese Academy of Sciences / Key Laboratory of Agro-ecological Processes in Subtropical Region, Chinese Academy of Sciences, Changsha 410125, China 2. Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China,1. Institute of Subtropical Agriculture, Chinese Academy of Sciences / Key Laboratory of Agro-ecological Processes in Subtropical Region, Chinese Academy of Sciences, Changsha 410125, China 2. Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China and 1. Institute of Subtropical Agriculture, Chinese Academy of Sciences / Key Laboratory of Agro-ecological Processes in Subtropical Region, Chinese Academy of Sciences, Changsha 410125, China 2. Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China |
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| Abstract: | Both Hunan and Hubei Provinces are major agricultural regions. Rice production is not only related to food security in the two provinces, but also importantly influences food security in China. Water resources in the two provinces will further decline due to the South-North Water Transfer project. Reference crop evapotranspiration (ET0) is the key factor for estimating vegetation evapotranspiration. Accurate estimation of ET0 is essential for water resources management and irrigation schedule. The adapted FAO-56 Penman Monteith (P-M) equation has been recommended as the reference equation for estimating ET0 and for calibrating other ET0 equations. The main drawback of using the P-M equation is the requirement for a range of meteorological inputs (air temperature, relative humidity, solar radiation and wind speed). However, the number of meteorological stations is limited even in developed countries, where meteorological variables are more accurately measured. As ET0 is correlated with geographical location, this study investigated the suitability of Gene-Expression Programming (GEP) technique for modeling ET0 using readily available geographical location information for Hunan and Hubei Provinces. Monthly observation data for 1955 2005 from 46 stations in Hunan and Hubei Provinces were used. The dataset, including monthly maximum temperature, minimum temperature, average wind speed, sunshine duration and relative humidity, were used to model ET0 based on the FAO-56 P-M equation as the reference equation. While the GEP was trained using latitude, longitude, altitude variables and month count as input, monthly ET0 was as output. The GEP model proved to have an adequate precision, with the coefficient of determination (R2) and root mean square error (RMSE) for the validation and test analyses of 0.934, 0.951 and 10.050 mm, 8.628 mm, respectively. Through comparison with the Hargreaves and Priestley-Taylor methods, the GEP model had the lowest RMSE values (8.628 9.967 mm). As the GEP technique could produce a simple and explicit mathematical algorithm, irrigation technicians in data-poor regions could use the GEP model to easily estimate ET0 with adequate precision. It was inferred that ET0 could be calculated using geographical location information in Hunan and Hubei Provinces. The GEP model could simplify monthly irrigation schedule and vegetation evapotranspiration estimation. |
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| Keywords: | Reference crop evapotranspiration Gene-Expression Programming model Geographical location information Month scale Hunan and Hubei Provinces |
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