改进Hargreaves模型估算川中丘陵区参考作物蒸散量

为提高 Hargreaves-Samani(HS)模型参考作物蒸散量(ET0)计算精度,该文基于贝叶斯原理利用川中丘陵区1954-2002年逐日资料对其温度指数、温度系数和温度常数进行改进,并使用2003-2013年资料以Penman-Monteith(PM)模型为标准评价HS改进模型计算精度与适应性。结果表明:HS改进模型参数在川中丘陵区各区均小于联合国粮农组织推荐值,并呈现出随纬度上升而增大的趋势;与PM模型计算结果相比,HS改进模型计算的ET0相对误差在川中丘陵区北部从14.2%~60.9%降至?1.1%~33.4%、中部从40.6%~92.6%降至16.9%~61.1%、南部从31.3...

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Published in农业工程学报 Vol. 31; no. 11; pp. 129 - 135
Main Author 李晨 崔宁博 魏新平 胡笑涛 龚道枝
Format Journal Article
LanguageChinese
Published 四川大学水力学与山区河流开发保护国家重点实验室水利水电学院,成都,610065%四川大学水力学与山区河流开发保护国家重点实验室水利水电学院,成都 610065 2015
南方丘区节水农业研究四川省重点实验室,成都610066%西北农林科技大学旱区农业水土工程教育部重点实验室,杨凌,712100%中国农业科学院农业环境与可持续发展研究所作物高效用水与抗灾减损国家工程实验室,北京,100081
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ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2015.11.019

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Summary:为提高 Hargreaves-Samani(HS)模型参考作物蒸散量(ET0)计算精度,该文基于贝叶斯原理利用川中丘陵区1954-2002年逐日资料对其温度指数、温度系数和温度常数进行改进,并使用2003-2013年资料以Penman-Monteith(PM)模型为标准评价HS改进模型计算精度与适应性。结果表明:HS改进模型参数在川中丘陵区各区均小于联合国粮农组织推荐值,并呈现出随纬度上升而增大的趋势;与PM模型计算结果相比,HS改进模型计算的ET0相对误差在川中丘陵区北部从14.2%~60.9%降至?1.1%~33.4%、中部从40.6%~92.6%降至16.9%~61.1%、南部从31.3%~96.0%降至8.5%~64.4%、整个川中丘陵区从32.1%~82.7%降至9.5%~52.6%;相关性分析表明, HS改进模型和PM模型计算的ET0回归曲线的斜率更接近于1(北部1.16、中部1.02、南部0.99、全区1.13),决定系数均达到0.85(P<0.01)以上;趋势分析表明,HS改进模型和PM模型计算的ET0变化一致,年内均呈开口向下的抛物线状,年际均呈微小上升趋势。因此,基于贝叶斯原理改进的 HS 模型在川中丘陵区不同区域变异性较小,适应性较强,具有较高的计算精度,可作为川中丘陵区参考作物蒸散量简化计算的推荐模型。
Bibliography:11-2047/S
Hargreaves-Samani;Penman-Monteith;evapotranspiration;models;estimation;Hargreaves-Samani;Penman-Monteith;Bayesian Theory;Hilly area of central Sichuan Basin
Reference crop evapotranspiration (ET0) is an important part of water cycle and water balance. Accurate estimation of ET0 becomes vital in planning and optimizing irrigation schedules and irrigation systems management. Numerous methods have been proposed for estimating ET0, among which Penman–Monteith (P-M) model recommended by Food and Agriculture Organization of the United Nations (FAO) in 1998 since it provids the highest accurate results across the world wherever in an arid or humid environment. But the main problems computing ET0 by P-M model are its complicated nonlinear process and requirements of many climatic variables. Thus, there is an urgent need to develop a much simpler and more appropriate model in areas with limited data, such as the Hargreaves-Samani (HS) method, which is modified in this paper. In order to obtain more accurate HS
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2015.11.019