文章摘要
常宏芳,蔡甲冰,肖春安,张宝忠,许迪.考虑降雨和气温变化对土壤热通量估算模型的修正[J].水利学报,2025,56(3):411-422
考虑降雨和气温变化对土壤热通量估算模型的修正
Enhancing soil heat flux estimation with the consideration of precipitation and air temperature influences
投稿时间:2024-06-07  
DOI:10.13243/j.cnki.slxb.20240351
中文关键词: 土壤热通量  灌区  空气温度  降雨  能量平衡
英文关键词: soil heat flux  irrigation district  air temperature  precipitation  energy balance
基金项目:国家自然科学基金项目(52130906,51979286);内蒙古科技兴蒙项目(NMKJXM202208-3,NMKJXM202301-3)
作者单位E-mail
常宏芳 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
国家节水灌溉北京工程技术研究中心, 北京 100048 
 
蔡甲冰 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
国家节水灌溉北京工程技术研究中心, 北京 100048 
caijb@iwhr.com 
肖春安 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
国家节水灌溉北京工程技术研究中心, 北京 100048 
 
张宝忠 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
国家节水灌溉北京工程技术研究中心, 北京 100048 
 
许迪 中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
国家节水灌溉北京工程技术研究中心, 北京 100048 
 
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中文摘要:
      土壤热通量是地表能量平衡中的分量之一,对于农田和区域生态水文过程水分收支的准确估算有着重要影响。土壤热通量估算中,常用的半理论半经验公式在作物生育期内日尺度计算结果恒为正值,不符合田间实际观测结果。本文设计特定参数来量化降雨和气温变化的影响,修正了考虑植被生长的土壤热通量估算模型。利用内蒙古河套灌区向日葵和北京大兴试验站冬小麦-夏玉米生育期实测数据,对修正模型关键参数进行率定和验证;结合遥感反演的植被覆盖度,利用全球通量网FLUXNET提供的美国玉米大豆轮作和韩国水稻站点实测日尺度土壤热通量数据对修正模型进行校核及应用。结果表明:(1)通过引入降雨及气温因子,修正模型考虑了田间气象变化对土壤热通量的影响,能有效估算作物生育期内日尺度土壤热通量为负值的情况;(2)模型估算各地区不同作物农田多年土壤热通量与实测值相一致,二者之间的决定系数、均方根误差、一致性系数及平均相对误差范围分别为0.54~0.63、3.30~11.70 W/m2、0.82~0.88和-13.4%~11.70%;(3)利用蒙特卡罗法得到修正模型中关键参数,α和z分别推荐为0.1和10~20;(4)指标敏感性分析表明,气温对修正模型的影响程度较大,其每变化1℃可使土壤热通量估算值变动10%~25%。研究结果为改善地表能量平衡不闭合现象提供了参考方法,并为大尺度精量遥感反演获取土壤热通量提供了技术支撑。
英文摘要:
      Soil heat flux is an important element of surface energy balance,holding a significant role in accurately estimating water budget during eco-hydrological processes in farmland and region.In estimating soil heat flux,the estimated daily-scale soil heat flux values in crop growth season by the conventional semi-theoretical and semi-empirical methods are always positive that do not align with the field observations.In this study,the soil heat flux model based on vegetation growth was revised by quantifying the influence of precipitation and air temperature changes expressed using special design factors.Utilizing the measurements from the Hetao irrigation district in Inner Mongolia for sunflower and Beijing’s Daxing district for winter wheat and summer maize,the parameters of the revised model were calibrated and validated.Then,the revised model was tested and applied using data obtained from the global flux network(FLUXNET)sites in the United States for maize-soybean rotation and in South Korea for rice,combined with the fractional vegetation cover from remote sensing satellites.Results showed that:(1)By incorporating precipitation and air temperature factors,the revised model effectively accounted for the influence of meteorological variations on soil heat flux and could accurately estimate the negative values of daily-scale soil heat flux during crop growth season.(2)Compared to observations,the revised model provided accurate estimates of soil heat flux across different regions and crop types for years,with the ranges of determination coefficient,root mean square error,the index of model agreement,and mean relative error of 0.54-0.63,3.30-11.70 W/m2,0.82-0.88,and -13.4%-11.70%,respectively.(3)Based on the Monte Carlo method,the key coefficients α and z in the revised model were determined as 0.1 and 10-20,respectively.(4)The sensitivity analysis of factors revealed that the air temperature had a more important influence on the revised model.A change of 1 ℃ in air temperature could result in a 10%-25% variation in estimating soil heat flux.These findings serve as a beneficial reference for mitigating the surface energy imbalance and provide valuable technical support for precise soil heat flux estimation in large-scale remote sensing inversions.
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