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20 June 2018, Volume 39 Issue 06

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Revision and Adaptability Evaluation of Temperature-based Methods for Reference Crop Evapotranspiration in the Three Irrigation Districts of China

YANG Yong-gang, CUI Ning-bo, HU Xiao-tao, GONG Dao-zhi, LI Chen, JIA Yue

2018, 39(06):  357-369.  doi:10.3969/j.issn.1000-6362.2018.06.001

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Dujiangyan irrigation district, Hetao irrigation district and Pishihang irrigation district are the largest irrigation districts in China. In order to improve the calculation precision of reference crop evapotranspiration(ET 0 ) based on temperature-based methods in the three irrigation districts of China, this paper used FAO-56 Penman-Monteith (PM) method and 8 temperature-based methods of Irmark-Allen (IA), Hargreaves-Samani (HS),Turc (Tur), McCloud (MC), Schendel (Sch), Trajkovic (Tra), Droogres-Allen-1 (DA-1) and Droogres-Allen-2 (DA-2) to calculate ET 0 based on the daily meteorological data of 8 representative stations from 1961 to 2014, and used the results of the PM method as the standard. Based on the equation of linear regression(y=kx+b) of daily ET 0 calculated by 8 temperature-based methods and PM method, this paper selected IA method and Tra method in Dujiangyan irrigation district, selected HS method, DA-1 method and DA-2 method in Hetao irrigation district, selected IA method,HS method, DA-1 method and DA-2 method in Pishihang irrigation district. And those methods selected in each irrigation district were revised by introducing adjustment parameter. And then root mean square error (RMSE), mean relative error (MRE) and Nash-Sutcliffe coefficient (NS) were used to evaluate the adaptability. The results showed that the calculation precision of the revised methods selected in Dujiangyan irrigation district and Pishihang irrigation district were improved significantly. While the calculation precision of the revised methods selected in Hetao irrigation district were not improved significantly. The reviseded IA method (IA -Du method) in Dujiangyan irrigation district had the highest calculation precision. The daily values of RMSE, MRE and NS of IA -Du method were 0.318mm·d-1 , 0.120 and 0.923, and the average values of ten days were 0.201mm·d-1 , 0.093 and 0.959. Meanwhile the calculation precisions of IA -Du method in all months were high. HS method in Hetao irrigation district had the highest calculation precision. The daily values of RMSE, MRE and NS of HS method were 0.898mm·d-1 , 0.326 and 0.785, and the average values of ten days were 0.547mm·d-1 , 0.223 and 0.904. And HS method has high calculation precision in Jan. to May and Oct. to Dec. The revised IA method (IA-Pi method) in Pishihang irrigation district had the highest calculation precision. The daily values of RMSE, MRE and NS of IA-Pi method were 0.534mm·d ?1 , 0.195 and 0.861, and the average values of ten days were 0.390mm·d ?1 , 0.167 and 0.896. Meanwhile the calculation precisions of IA-Pi method in all months were high. Therefore, IA -Du method, HS method and IA-Pi method were recommended as the temperature-based method for calculating ET 0 in Dujiangyan irrigation district, Hetao irrigation districtand and in Pishihang irrigation district respectively.

Evaluation of Different Agronomic Measures on Narrowing the Yield Gap and Improving Nitrogen Use Efficiency of Winter Wheat

LI Qin-ying,YAO Feng-mei,ZHANG Jia-hua,ZENG Rui-yun,SHI Si-qi

2018, 39(06):  370-379.  doi:10.3969/j.issn.1000-6362.2018.06.002

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The DSSAT model was used to simulate the effect of changing soil nutrient, sowing date, planting density and nitrogen application on narrowing yield gap and improving nitrogen use efficiency of winter wheat, and explore the technical approach of improving the yield and efficiency of winter wheat, which were based on the weather, agro-meteorological observations and soil data of 14 representative observation stations from 1990 to 2015.The results showed that there was great difference in potential yield between different winter wheat stations, and it ranged from 7617 to 14242 kg·ha-1. Diverse agronomic measures can influence the yield differently. Among them, potential ascension of yield for soil nutrient was 53?3124kg·ha-1, and its contribution rate of narrowing yield gap was below 8%, and nitrogen use efficiency was increased by 1.1-20.82kg·kg?1.The potential ascension of yield for early sowing date was -327 to 2292kg·ha-1, and its contribution rate of narrowing yield gap was 7%-17%, and nitrogen use efficiency ranged from -2.18 to 15.28kg·kg-1. The potential ascension of yield for planting density was ?255 to 699kg·ha?1, and the contribution rate of narrowing yield gap was less than 5%, and nitrogen use efficiency ranged from -1.7 to 4.66kg·kg-1.The potential ascension of yield for nitrogen fertilizer was 0-4491kg·ha-1, and the contribution rate of narrowing yield gap was 11%-33%, and nitrogen use efficiency ranged from -32.04 to 0kg·kg-1. This indicated that potential ascension of yield for increasing the nitrogen fertilizer and adjusting sowing date contributed more to narrow the yield gap, followed by soil nutrients and increased planting density. However, increasing nitrogen fertilizer obviously decreased nitrogen use efficiency.

Application of Two-wavelength Bichromatic Correlation Method to Calculate the Average Surface Energy and Water Vapor Fluxes in Plantation North China

ZHANG Gong,ZHANG Jin-song,MENG Ping,ZHENG Ning

2018, 39(06):  380-389.  doi:10.3969/j.issn.1000-6362.2018.06.003

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A field campaign which measuring heat fluxes based on the optical-microwave scintillometer (OMS), was conducted in the plantation ecosystems in the hilly area of North China. The differences between the results of OMS and Eddy Covariance (EC) system were compared in details, the impact of OMS results on the energy balance was estimated, and affecting factors of OMS were also discussed. Results showed that, the sensible heat flux observed by OMS is in favorable consistency with the EC observations, while the latent heat flux estimated by the OMS system is overvalued by 28%. The energy balance observed by the OMS system was over-closed and with an excess of 5%, because of the overestimation of latent heat flux. Bowen ratio and wind speed have great influences on the OMS. As a new method for measuring surface energy and water vapor fluxes, OMS can simultaneously and directly measuring sensible heat flux and latent heat flux at the regional scale, shortening the sampling interval, reducing the statistical uncertainties, contributing to a more accurate measurement of the heat flux and benefit for the further research of the energy balance.

Effect of Silicate Application on Hybrid Rice Growth and Yield under Nighttime Warming

ZHENG Ze-hua, LOU Yun-sheng, ZUO Hui-ting, SHI Yi-fan, WANG Ying

2018, 39(06):  390-397.  doi:10.3969/j.issn.1000-6362.2018.06.004

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Field experiment with rice was conducted to investigate the effects of silicate (Si) supply on tiller number, leaf area index, biomass and yield at tillering stage, jointing stage, heading stage, filling stage and maturity stage under nighttime warming. The experiment was designed with two nighttime warming levels, i.e. nighttime warming (NW) and control (CK, ambient temperature), and two Si supply levels, i.e. control (Si0) and Si1 (slag fertilizer, 200kgSiO2·ha-1). The results showed that, (1) nighttime warming increased the average temperature on rice canopy and at 5cm depth soil by 1.21℃ and 0.41℃,the lowest temperature by 1.21℃ and 0.62℃, and the highest temperature by 1.20℃ and 0.28℃, respectively, at night (19：00-6：00) during entire rice growth period. (2) Nighttime warming decreased tiller number, leaf area index, above-ground biomass, below-ground biomass and yield by 10.81%, 5.65%, 8.20%, 3.29% and 4.45%, respectively. Silicate application increased the above indicators by 16.22%, 11.18%, 14.16%, 6.51% and 22.10%, respectively, and increased the above indicators by 16.67%, 11.71%, 12.56% and 20.90% under nighttime warming. (3)Nighttime warming decreased effective panicles, filled grain numbers per panicle, 1000-seedweight and maturing rate by 2.66%, 12.72%, 1.53% and 2.06%, respectively; silicate application increased the above indicators by 6.91%, 15.49%, 2.00% and 4.48%, respectively, silicate application increased the above indicators by 4.37%, 22.50%, 2.15% and 3.31%, respectively, under nighttime warming. It is suggested that silicate application had significant effects on rice growth and grain yield, mainly concerned with effective panicles and filled grain numbers per panicle.

Difference and Cause Analysis of Drought Characteristics during Growth Period between the Corn Belts of China and the United States in Past 30 Years

WANG Fang, WANG Chun-yi, WU Ding-rong, YAO Shu-ran, BAI Yue-ming, ZHANG Ji-quan

2018, 39(06):  398-410.  doi:10.3969/j.issn.1000-6362.2018.06.005

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Corn growth in China and the United States(US) has been seriously affected by the drought disaster under climate change. In order to effectively reference the advanced experiences on drought mitigation of the US, the standardized precipitation evapotranspiration index(SPEI) was calculated for two corn belts located in Northeast of China(NEC) and the US based on the observed meteorological data during 1986-2015. The observed differences in drought characteristics were compared and their causes were further analyzed by conducting the linear fitting analysis, correlation test and other statistical methods. The results showed that, compared with the US, corn growth period in the corn belt of NEC has higher solar radiation, lower average air temperature, and less but concentrated precipitation during late growth stage, and precipitation in the corn belt of the US was relatively evenly distributed during the whole growth period. Time variation of annual SPEI, drought frequency, drought severity and drought extent during different growth stages were significant different in two areas, with respective characteristics in the spatial distribution. Drought frequency and severity in the corn belt of NEC was higher than that of the US during the whole growth period because of the higher frequency of high air temperature, rainless and high radiation weather, especially the differences of drought characteristics between two areas became more significant during late growth stage due to the lower frequency of abnormal weather happened in the corn belt of the US. Consistency of temporal changes of radiation, air temperature and precipitation in two areas led to the similar trends of dry-wet variations, i.e., wetter during early and drier during late growth stage. However, significant wetter trend was only happened in the corn belt of the US during early growth stage due to its significant increase in precipitation and decrease in radiation. The US may pay more attention to the drought management during early growth stage of the corn belt in respond to drought threats, but for NEC, in addition to the drought management during early growth stage, additional attention should be paid to the late growth stage. Therefore, in referencing the experience of drought mitigation from foreign countries, enough attention should be paid to the differences of drought-resistant measures resulted from the differences in the characteristics and disaster-leading factors of drought disaster in the different regions.

Irrigation Simulation of Spring Maize in Central and Western of Jilin Province Based on WOFOST Model

ZHANG Yang, WANG Lian-xi, LI Qi, HU Zheng-hua,GUO Chun-ming,REN Jing-quan

2018, 39(06):  411-420.  doi:10.3969/j.issn.1000-6362.2018.06.006

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Based on meteorological data from 1961 to 2015 of midwestern stations in Jilin Province, the Peman-Monteith formula was utilized to calculate the evapotranspiration of spring maize’s growing season in the main growing areas and confirm the effective precipitation in the growing periods. The net irrigation amount of maize and the irrigation requirement index determined the critical irrigation periods; then the WOFOST crop model was used to simulate the yield of irrigation schemes for different precipitation years of the site, and the critical irrigation periods which were verified through the simulation yielded results to get a better irrigation plan. The results showed that the effective precipitation in the midwest of Jilin Province accounted for about 69% of the water demand, and the irrigation requirement index was higher in the sowing?seedling stage, seedling?jointing stage and milk?maturing stage. The three growth periods were the critical periods of spring maize to irrigate. When the spring maize was irrigated, the most efficient irrigation stage was the milking?maturing stage, followed by the sowing?emergence stage, multiply the irrigation time during the critical growth periods.

Collection Model for Maturity Forecasting of Juicy Peach in Zhejiang Province

YANG Dong, DING Ye-yi, JIN Zhi-fen, HUANG He-lou, ZHEN Jian, LI Qing-bin

2018, 39(06):  421-430.  doi:10.3969/j.issn.1000-6362.2018.06.007

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The phenological forecast is mostly based on the single model which is with poor accuracy and stability. It is difficult to realize the business application. Taking the mature stage of peach as an example, the feasibility of the collection model in the refined prediction of phenological period was explored. By using the phenological data and meteorological data collected from major peach producing areas in Ningbo from 2005 to 2017, the maturity prediction models of peach with different time scale (hours, days, 5-days, 10-days and month) and multiple starting point (phenological period, fixed date) were built. The weighted sum method was employed to construct the collection models with different forecast aging for maturity forecasting. The weights of ensemble forecasting members were determined by using arithmetic mean method, regression coefficient method, correlation coefficient method and absolute error method based on the accuracy and stability of the model prediction results. The results showed that: the collection models, constructed with four kinds of weight coefficient determination methods, were with high accuracy and stability. The AE (absolute error) of the collection models’ regression test was only 0.69 (0.56-0.87) days, RMSE (root mean square error) was 0.90 (0.69-1.14) days, R (correlation coefficient) was 0.95 (0.92-0.98). Compared with the single model, the AE and RMSE of the collection model were 0.5 days and 0.6 days lower, and R was 0.12 higher. The collection model based on the absolute error method was the best, the average value of AE and RMSE by back-generation test were 0.66 and 0.88 days, respectively. The AE of maturity forecasting for main peach producing area in Ningbo was less than 2 days. The prediction error could be reduced by 0.2-0.3 days by the fusion of stone hardening observation in the collection model. We suggest that collection model provide a good proxy for fine phenological prediction and can meet the needs of business applications.