基于SEBAL模型的土默特右旗腾发量研究

苏婷婷; 魏占民; 白燕英

引用本文:	苏婷婷,魏占民,白燕英.基于SEBAL模型的土默特右旗腾发量研究[J].灌溉排水学报,2019,38(2):70-75.
	SU Tingting,WEI Zhanmin,BAI Yanying.基于SEBAL模型的土默特右旗腾发量研究[J].灌溉排水学报,2019,38(2):70-75.

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基于SEBAL模型的土默特右旗腾发量研究
苏婷婷，魏占民*，白燕英
内蒙古农业大学水利与土木建筑工程学院，呼和浩特 010018

摘要:

【目的】评价SEBAL模型在估算内蒙古包头市土默特右旗腾发量时的适用性。【方法】基于2015年作物生育期内的Landsat8遥感影像，建立SEBAL模型，估算腾发量，利用FAO Penman-Monteith公式与水量平衡法估算得到腾发量进行了验证及评价，并采用多元逐步回归方法对其影响因素进行了分析。【结果】日腾发量的分布具有明显的空间差异性，呈现出“山峰型”变化趋势。SEBAL模型腾发量估算值与水量平衡法估算值相比，相对误差的平均值为6.053%； Penman-Monteith公式计算得到的日腾发量与水量平衡法估算值相差7.682%，都在10%以内，达到了精度要求，且SEBAL模型估算腾发量的精度高于Penman-Monteith公式。日腾发量与NDVI和地表温度相关性显著，由二者建立了最优的多元逐步回归方程。【结论】在缺乏数据的情况下，利用SEBAL模型可以较为准确地估算出土右旗的腾发量，且NDVI和地表温度对其的影响较大。

关键词: 遥感； SEBAL模型；腾发量；空间差异性；多元逐步回归

DOI：10.13522/j.cnki.ggps.20180119

分类号:

基金项目:

Using the SEBAL Model to Calculate Evapotranspiration in Tumoteyouqi

SU Tingting, WEI Zhanmin*, BAI Yanying

College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China

Abstract:

【Objective】Evapotranspiration is one of the most important processes in hydrological cycle and this paper evaluates the feasibility and accuracy of the SEBAL model to estimate it in Tumoteyouqi of Baotou, Inner Mongolia. 【Method】 Using the Landsat8 remote sensing images taken during the crop growth season in 2015, the SEBAL model was established to estimate the evapotranspiration. The result was validated against that estimated using the FAO-recommended Penman-Monteith formula and water balance method respectively, based on the multivariate stepwise regression of the factors believed to affect evapotranspiration. 【Result】 The daily evapotranspiration varied spatially, peaking in the mountainous areas. Compared with that calculated from the water balance, the average relative errors of the estimated evapotranspiration from the SEBAL model and the Penman-Monteith formula was 6.053% and 7.682% respectively. Daily evapotranspiration was significantly correlated to NDVI and surface temperature, and we derived an optimal multivariate stepwise regression model to estimate the evapotranspiration. 【Conclusion】 In the absence of ground-truth data, the SEBAL model can provide an accurate estimation of the evapotranspiration which was affected greatly by NDVI and surface temperature.

Key words: remote sensing; SEBAL model; evapotranspiration; spatial variability; multiple stepwise regression