|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4478883||1622952||2013||12 صفحه PDF||سفارش دهید||دانلود رایگان|
• We reported a modified dual crop coefficient (Kc) model to partition evapotranspiration.
• Daily basal Kc was dynamically calculated by introducing canopy cover coefficient.
• Leaf senescence factor was taken into consideration to modify basal Kc.
• Evaporation coefficient was modified by accounting for effect of ground-mulching.
• The good agreements were found through comparing measurements with predictions.
The accurate partitioning of crop evapotranspiration (ETc) into two components, soil evaporation (Es) and transpiration (Tr), is needed to better understand terrestrial hydrological cycles and develop precise irrigation scheduling. However, there is no easy way to distinguish between the two. Based on FAO-56 dual crop coefficient (Kc) approach, we developed a modified dual Kc model for better predicting Tr through basal crop coefficient (Kcb) and Es through evaporation coefficient (Ke). Daily Kcb was dynamically calculated by introducing a canopy cover coefficient that could be simply described as a function of leaf area index or fraction of canopy cover. Also, leaf senescence factor was taken into consideration to modify Kcb when leaf suffers functional senescence. Ke was modified through introducing the fraction of ground-mulching (fm) to account for the effect of mulching on Es. The model was parameterized by measurements in 2009, and validated using independent data for grain and seed maize with and without mulching in 2010 and 2011. The results indicate that the predicted Kc values by the modified model were obviously better than those by the original model. The good agreements were found between the predicted ETc, Tr and Es using the modified model and the measurements for grain maize in 2010 with fm = 0.6, with the slope of linear regression of 0.99 (R2 = 0.90), 1.01 (R2 = 0.92) and 0.96 (R2 = 0.78), respectively. The modified model also well reproduced the values of ETc and Es for seed maize in 2011, which had lower plant height and leaf area index compared to grain maize, under mulching (fm = 0.7) and non-mulching (fm = 0) conditions. The slopes of linear regression between predictions and measurements were 0.98 (R2 = 0.91) and 0.99 (R2 = 0.92) for ETc, and 0.98 (R2 = 0.79) and 0.97 (R2 = 0.80) for Es under fm = 0.7 and 0.0, respectively. These results suggest that the modified dual Kc model can accurately predict ETc, Es and Tr for different crop types under different mulching, thus could be a useful tool for improving irrigation water management.
Journal: Agricultural Water Management - Volume 127, September 2013, Pages 85–96