| Water and heat flux research in the paddy rice field has great impact on the local energy balance, mass exchanging and global climate research. This paper is based on the experiments conducted in agro meteorological experiment station of NUIST in 2013 and 2014. Value the effectiveness of each method by comparing flux data, which was measured through the corrected EC data and other methods by direct measuring and indirect calculating. Taking heat storage terms, the surface resistance, soil heat flux and the stability of the atmosphere into consideration PM model was to analyze errors theoretically. Also regression analysis was conducted to analyze the surface structure, flux contribution and radiation term during EC data error analysis, which mainly focus on simulating flux out of the interest areas and contribution errors of the paddy rice field. Based on the EC data, the regression analysis, typical days’ comparisons and model simulation were used to illustrate the energy distribution by different water depths. Conclusions are identified as follows.(1)Based on the Lysimeter data, comparing with EC measuring method, EC-Bowen ratio energy balance method [BRE(EC)], gradient-Bowen energy balance method [BRE(G)] and profile theory method(PT), it showed that The latent heat of the other methods was underestimated, and EC data is similar to the Lysimeter data; Due to the energy imbalance of the paddy rice field and the difficulties of measuring the water heat flux, it made energy balance function worse than profile theory. The sensible heat flux of different method had the similar results, too.(2)PM model error analysis showed that heat storage term was more effective on the evapotranspiration simulation. Water heat storage during the transplanting-jointing stage functioned larger than maturing stage. Stability has smaller influence on the evapotranspiration simulation correction which reduced evapotranspiration less than 0.005, because each stage of the atmosphere stratifications was mostly neutral or weak stable. EC error regression analysis showed that measuring error was quite related to the radiation terms; the underling structure by larger LAI and deeper water depths would expand the errors. The flux error outside of the interest fields and contribution ratio of the footprint showed that there was a relationship between contribution ratio and the wind direction & stability of the atmosphere, with the average contribution ratio 63%. The data showed a better performance (except the correlation coefficient) after contribution ratio correction. Both of the latent heat and sensible heat were improved after the energy balance correction, and the trend of sensible heat was more clearly.(3)The energy distributions mainly focus on the influenced by different the water depths. The regression analysis among meteorological factors and water depths showed that water depths had an impact on the energy distribution by decreasing the latent heat at 7:00-13:00 and increasing the sensible heat at 6:00-14:00 with the water depth becoming deeper, the water heat flux was also increased in the daytime and on the contrary at night. Compassion among the typical days, it illustrated that the water storage heat was increased along with the water depth which increased the water heat flux, too. The decreasing of the available energy (Rn-Qs) changed the latent heat and sensible heat distribution. The latent heat flux decreased with the water depth increasing in the daytime. The sparse canopy stage was more apparently due to the actual water depth and canopy structures. And the sensible heat didn’t show great significance due to the magnitude and measuring errors. Simulating the latent heat by double-source evapotranspiration modeling, it showed that water depth was mainly decrease the latent heat from the water but influencing less to that from canopy. |
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