Journal
AGRICULTURAL WATER MANAGEMENT
Volume 235, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.agwat.2020.106154
Keywords
Drip irrigation; Path analysis; Single crop coefficient; Soil water stress coefficient
Categories
Funding
- National Natural Science Foundation of China [51809094, 51509130, 51579102, 51779093]
- Key Technologies R&D and Promotion Program of Henan Province [192102110090]
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Information of crop evapotranspiration (ETc) and crop coefficient (K-c) is essential for improving water use and optimizing irrigation scheduling. Here, a three-year (2015, 2016 and 2019) experiment was conducted for tomato grown in a solar greenhouse under full and deficit drip irrigation to investigate the variation of ETc measured by sap flow system plus micro-lysimeter in 2015 and by weighing lysimeter in 2016 and 2019. The controlling meteorological factors on ETc in two irrigation treatments were analyzed by using path analysis method. A single crop coefficient model considering leaf senescence, soil water stress and fraction of canopy cover was proposed under two irrigation levels. The results showed that total seasonal ETc over the whole growth stage under full irrigation was 310 - 350 mm, which was 16-23 % higher than that under deficit irrigation. The maximum hourly ETc rate in each month during the three-years experiment varied from 0.15 to 0.89, and from 0.15 to 1.88 mm h(-1), respectively, under deficit and full irrigation. Path analysis showed that the net radiation was the dominant meteorological factor aff ;ecting ETc through the direct eff ;ect, followed by the vapor pressure deficit, mainly through an indirect action on ETc. The K-c values at different growth stages estimated by the proposed single crop coefficient model under full and deficit irrigation agreed well with the measured ones, and the water stress coefficient, K-s under deficit irrigation varied from 0.5 to 1.0. The proposed single crop coefficient model also estimate daily ETc of drip irrigated tomato reasonably in the solar greenhouse with regression coefficient of 0.93 - 0.99, determination of coefficient of 0.78 - 0.95 and root mean square root of 0.35 - 0.52 mm d(-1).
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