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利用改进的MOD16模型估算区域蒸散发

Estimating regional evapotranspiration by the improved MOD16 model

  • 摘要: 蒸散发(Evapotranspiration,ET)是地表水循环和能量循环的关键纽带,准确、定量地估算区域ET对于理解陆-气相互作用、全球气候变化等至关重要。MOD16模型基于Penman-Monteith(P-M)方程,是一种获取区域ET的重要遥感模型。然而,MOD16模型没有直接利用土壤水分信息,而是通过相对湿度(Relative Humidity,RH)、饱和水汽压差(Vapor Pressure Deficit,VPD)、叶面积指数(Leaf Area Index,LAI)等间接表达土壤水分信息的作用,这可能会给区域ET的估算带来一些不确定性。该研究将归一化水指数(Normalized Difference Water Index,NDWI)作为土壤水分信息的补充项,对MOD16模型的地表阻抗进行修正,以改进MOD16模型(改进后的模型为MOD16-sm),并将改进后的模型在中国西北干旱区绿洲进行验证和应用。模型验证包括模拟值与观测值的对比及误差分析。模拟值与观测值的对比分析结果表明,MOD16-sm模型获取的ET精度较高,决定系数(Coefficient of Determination,R2)为0.77,均方根误差(Root Mean Square Error,RMSE)为0.8 mm/d,平均绝对误差(Mean Absolute Deviation,MAE)为0.46 mm/d;误差分析结果显示,MOD16-sm模型估算结果的误差控制优于MOD16模型,结合模拟值与观测值的对比分析可知,MOD16-sm模型改善了MOD16模型的部分高估现象,MOD16-sm模型能更好地反映土壤水分对ET的影响。模型应用包括ET估算值的空间分布分析及ET估算值的频率分布统计。对MOD16-sm模型的估算结果进行空间分析发现,高植被覆盖区的ET值较高,低植被覆盖区的ET值较低,说明MOD16-sm模型的ET估算结果与土地利用类型密切相关;研究区ET估算值的频率分布结果表明,MOD16-sm模型能较好地反映和表达出不同植被覆盖区的ET通量异质性。因此,利用NDWI对MOD16模型进行改进是可行的和合理的,该研究可为提高区域ET的估算精度提供参考和思路。

     

    Abstract: Abstract: Evapotranspiration (ET) is a key link in the hydrological and energy cycle in agricultural irrigation and water resource management. An accurate and quantitative estimation of regional ET is crucial to clarify the land-air interaction and global climate change. MOD16 model has been one of the most commonly-used remote sensing models to obtain the regional ET using the Penman-Monteith (P-M) equation. However, the MOD16 model cannot directly consider the soil moisture using the Relative Humidity (RH), Vapor Pressure Deficit (VPD), and Leaf Area Index (LAI), leading to some uncertainties in the ET estimation. In this study, an attempt was made to improve the MOD16 model using the normalized water index (NDWI) as an additional item of soil moisture. As such, the modified surface impedance of the MOD16 model (the improved model named MOD16-sm) was achieved to verify and apply in the arid oasis located in northwest China. Model validation included the comparative (between ET estimates and measurements) and error analyses. The comparative analyses between ET estimates and measurements showed that the scatter distribution of ET observations and estimates by the MOD16-sm model was very close to the 1:1 straight line. The accuracy of ET estimates acquired by the MOD16-sm model increased, with a higher Coefficient of Determination (R2) of 0.77, a lower Root Mean Square Error (RMSE) of 0.8 mm/d, and a lower Mean Absolute Deviation (MAE) of 0.46 mm/d, while the accuracy of ET estimates obtained by the MOD16 model was low, with a lower R2 of 0.64, a higher RMSE of 0.93 mm/d, and a higher MAE of 0.7 mm/d, indicating the convincible MOD16-sm model. Error analyses showed that the percentage error ranges of ET estimates by the two models were significantly different, and the maximum percentage error of ET estimates by the MOD16 model was higher than that by the MOD16-sm model, indicating the better performance of the MOD16-sm model on the ET estimates. The comparative analyses between ET estimates and measurements indicated that the MOD16-sm model corrected some overestimations of the MOD16 model, particularly with the better performance for the influence of soil moisture on ET estimations. The model application was conducted to analyze the spatial distribution of ET estimates, and the frequency distribution histograms on ET estimates. Correspondingly, the spatial distribution of ET estimates was closely related to the land use types, with the high vegetation cover regions (such as farmland, and woodland) in the high ET values, while the sparse vegetation cover areas (such as villages) showing the low ET values, which was in line with the objective facts. The ET frequency distribution demonstrated that the MOD16-sm model can be expected to serve as the heterogeneity of ET flux in the different vegetation cover areas. Therefore, it is feasible and reasonable for the improved MOD16 model by the Normalized Difference Water Index (NDWI) as an additional item of soil moisture. The finding can also provide a strong reference for the higher accuracy of regional ET estimations.

     

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