Parametrization Of Resistances For Modeling Crop Transpiration And Soil Evaporation In The Southern Jiangsu

Accurate estimation of crop evapotranspiration?ET_c?is important in the development of precise irrigation scheduling and the enhancement water-use efficiency in agricultural production.The individual components of ET_c include evaporation from the soil surface?E_g?and transpiration through the stomata of plants?T_r?.The function of E_g and T_r is distinctly different:T_r is usually associated with plant productivity,whereas E_g is undesirable and does not directly contribute to production.The E_g accounts for a large part of ET_c,and cannot be ignored in the sparse planting environment or in the early crop growth stage.Therefore,ET_c partitioning is the key to further improve water use efficiency and rationally distribute irrigation water.In this study,tea and winter wheat in the open field and cucumber in the greenhouse were used for the experiments.The meteorological data,soil moisture content and crop physiological indicators were monitored to systematically analyze the change characteristics of water and heat flux,and clarify the response mechanism of crop water consumption to the change of environmental factors under different planting environments.The Shuttleworth-Wallace?SW?model and Revised Dual Crop Coefficient?RDCC?were parameterized based on the data from the tea field,and the performances were evaluated based on the continuous measured ET_c of tea field by Bowen ratio energy balance system.To verify the applicability of the SW and RDCC models,the simulated results were compared with the measured values in the winter wheat and greenhouse by weighing system and Bowen ratio energy balanced system,respectively.At last,based on the partitioned ET_c,the supply-demand features of water resources for typical crops in the Southern Jiangsu was evaluated.The detailed results are as follow:?1?the net radiation?R_n?was mainly consumed by latent heat flux?LET?under different planting environments,but the energy distribution in open field and greenhouse has different characteristics.In the open field,the energy distribution was in the order of R_n>LET>H?sensible heat flux?>G?soil heat flux?,while in the greenhouse,the order was LET>R_n and H<0 after 3 PM,that is advection of sensible heat.The path analysis showed that the R_n was the most influential factor which directly affected LET,and the other factors mainly indirectly affected LET through R_n path.The second factor was the vapor pressure deficit?VPD?,and had the highest correlations with R_n.It is confirmed that R_n is the driving force of farmland ecosystem operation.?2?the measured LET values in tea and winter wheat fields were integrated into the Penman-Monteith?PM?model to obtain the canopy resistance values,and the nonlinear canopy resistance models with the meteorological factors and aerodynamic resistance were obtained.The correlation analysis between the measured stomatal resistance and the main meteorological factors in greenhouse cucumber showed that solar radiation was the main meteorological factor affecting stomatal resistance,and the exponential model of canopy resistance in greenhouse cucumber was obtained?R²>0.74?.Soil surface resistance in greenhouse was measured by soil surface evaporation and soil surface temperature,and the exponential soil surface resistance model with the soil moisture content and soil surface resistance was simulated?R²=0.62?.Canopy coverage coefficient was used to calculate the dynamic basal crop coefficient(K_cb)under different planting environments.The K_cb of tea were 0.85 and 0.92 at the early?2015?and the middle?2016-2018?growth stage,respectively.The average K_cb of winter wheat was 0.25 in the early growth stage,0.93 in the middle growth stage and0.78 in the later growth stage.The K_cb of cucumber in greenhouse was 0.32 in the early growth stage,stable at about 0.95 in the middle growth stage,and decreased to about0.80 in the later growth stage.?3?the RDCC model seriously overestimated ET_c in the tea field,with the Root Mean Square Error?RMSE?and Bias of 1.16 mm d^-1 and 0.41 in four years,respectively.Compared to the RDCC model,the SW model had a better performance in estimating ET_c of the tea field,with the RMSE and Bias of 0.47 mm d^-1 and 0.09.To verify the accuracy of the above results,we have compared the RDCC model and the SW model in estimating ET_c for cucumber and winter wheat.The results showed that both two models can accurately estimate ET_c of cucumber and winter wheat,but the SW model has higher estimation accuracy.For the greenhouse cucumber,the SW model estimated ET_c with RMSE and Bias of 0.45 mm d^-1 and-0.12,while the RDCC model estimated ET_c with RMSE and Bias of 0.57 mm d^-1 and-0.15.For the winter wheat,the SW model estimated ET_c with RMSE and Bias of 0.19 mm d^-1 and-0.01,while the RDCC model estimated ET_c with RMSE and Bias of 0.27 mm d^-1 and 0.04.?4?the parameterized SW model estimated that E_g/ET_c was 17.35%for the cucumber in the whole growth stage,16.69%for the tea in the early and middle growth stage,10.42%for the winter wheat in the whole growth stage.The irrigation and ET_c of greenhouse cucumber were 242 mm and 196.48 mm for spring planting season,while for the autumn planting season the values were 130 mm and 99.50 mm.The rainfall and ET_c of tea field were 1012.00 mm and 731.60 mm in the early growth stage,2040.13mm and 2092.16 mm in the middle growth stage;for the winter wheat field the values was 392.50 mm and 294.72 mm in the whole growth stage.The results showed that the irrigation of cucumber in the greenhouse was mainly consumed by ET_c,accounting for81.19%and 76.54%in the two planting seasons,respectively;during the experimental period,the precipitation can meet the ET_c of tea field and winter wheat field.