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引用本文:王怡宁,丁佳楠,吕海深, 等..基于水面蒸发量及气温因子的潜水蒸发量计算模型研究[J].灌溉排水学报,2022,41(3):69-74.
WANG Yining,DING Jia’nan,LYU Haishen, et al.基于水面蒸发量及气温因子的潜水蒸发量计算模型研究[J].灌溉排水学报,2022,41(3):69-74.
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基于水面蒸发量及气温因子的潜水蒸发量计算模型研究
王怡宁, 丁佳楠, 吕海深, 等.
1.南京水利科学研究院,南京 210029;2.河海大学,南京 211100;3.江苏省水利勘测设计研究院有限公司,南京 210000;4.安徽省(水利部淮委)水利科学研究院 五道沟实验站,安徽 蚌埠 233000
摘要:
【目的】探究不同气象因子对潜水蒸发量的影响。【方法】利用五道沟水文试验站0.3 m2口径的蒸渗仪测定潜水蒸发量,以及气象观测场的相关仪器测定气象数据,选取2006—2015年潜水蒸发量和气象实测数据,分别构建了砂姜黑土和黄潮土基于埋深因子的裸地潜水蒸发量与水面蒸发量、气温单气象因子和双气象因子计算模型。【结果】砂姜黑土各计算模型R2在0.88左右,平均绝对误差(MAE)为1.50 mm/10 d,均方根误差(RMSE)为2.30 mm/10 d;黄潮土各计算模型R2为0.92,平均绝对误差(MAE)为1.94 mm/10 d,均方根误差(RMSE)为2.80 mm/10 d,均有较高的精度,且黄潮土各拟合模型的精度要高于砂姜黑土。单气象因子计算模型的R2为0.92,平均绝对误差(MAE)为1.80 mm/10 d,均方根误差(RMSE)为2.60 mm/10 d;双气象因子计算模型的R2为0.94,平均绝对误差(MAE)为1.40 mm/10 d,均方根误差(RMSE)为2.05 mm/10 d,双气象因子拟合效果高于单气象因子。2种土壤多气象因子复合模型,其平均绝对误差(MAE)分别为2.21 mm/10 d和2.91 mm/10 d,均方根误差(RMSE)分别为3.31 mm/10d和3.93 mm/10 d,估算精度较优。【结论】潜水埋深、水面蒸发量及气温对潜水蒸发量具有显著影响,可根据各地区获得的气象资料选择合适的计算模型。
关键词:  潜水蒸发量;水面蒸发量;气温;埋深
DOI:10.13522/j.cnki.ggps.2021105
分类号:
基金项目:
Estimating Shallow Groundwater Evaporation Based on Surface Evaporation and Ambient Air Temperature
WANG Yining, DING Jia’nan, LYU Haishen, et al
1.Nanjing Institute of Water Resources, Nanjing 210029, China; 2.Hohai University, Nanjing 210098, China; 3.Jiangsu Water Conservancy Survey and Design Research Institute Co., Ltd., Nanjing 210000, China; 4.Anhui Province (Huaiwei Committee of the Ministry of Water Resources) Wudaogou Experimental Station of Water Conservancy Research Institute, Bengbu 233000, China
Abstract:
【Objective】Evaporation loss via capillary rise is an important component of groundwater cycle but difficult to measure in situ. This paper presents an empirical formula to estimate it using surface evaporation and ambient air temperature, based on long-term experimental data obtained from a hydrological experimental station.【Method】Groundwater evaporation from phreatic surface of shallow groundwater was measured from lysimeters with cross section of 0.3 m2 at Wudaogou Hydrological Experiment Station, and the meteorological data were measured from a weather station installed at the station. There were two soils, a fluvo-aquic soil and a lime concretion black soil. For each soil, we established a regression model using temperature and surface evaporation, either separately or in combination, to estimate groundwater evaporation. 【Result】 For the lime concretion black soil, the average R2 of the models using single or two meteorological factors was 0.88, and its associated average absolute error (MAE) and root mean square error (RMSE) were 0.15 mm/d and 0.23 mm/d, respectively. For the yellow fluvo-aquic soil, the associated results were R2=0.92, MAE=0.194 mm, and RMSE=0.28 mm/d. When using a single meteorological factor, the average R2 for the two soils using all models was R2=0.92, and its associated MAE and RMSE were 0.18 mm/d and 0.26 mm/d, respectively. In contrast, in using the two meteorological factors, the average R2 for the two soils using all models was 0.94, and its associated MAE and RMSE were 0.14 mm/d and 0.205 mm/d, respectively. 【Conclusion】For a given area, the evaporation of its shallow groundwater via capillary rise depends on surface evaporation and ambient air temperature. Since air temperature and surface evaporation are closely correlated, we can use either one of the two factor or their combination to estimate the groundwater evaporation.
Key words:  shallow groundwater evaporation; surface water evaporation; air temperature; groundwater depth