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20 May 2018, Volume 39 Issue 05

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Spatial and Temporal Variation of Actual Evapotranspiration in China under the 1.5℃ and 2.0℃ Global Warming Scenarios

SU Bu-da, ZHOU Jian, WANG Yan-jun, TAO Hui, GAO Chao, LIU Feng-xia, LI Xiu-cang,

2018, 39(05):  293-303.  doi:10.3969/j.issn.1000-6362.2018.05.001

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Evapotranspiration is a key process of hydrological cycle, and understanding it's changing patterns in the warming world is of great significance to the integrated water resources management. Monthly evapotranspiration outputs from 17 global climate models for 1961?2100 are used to analyze spatial and temporal changes of actual evapotranspiration over China under the 1.5℃ and 2.0℃ global warming scenarios. The results showed that: (1) In the 1.5℃ warming level, annual actual evapotranspiration in China will show a spatial pattern of decrease from the southeast coastal area to the northwest inland. Actual evapotranspiration over China is projected to 4.4% higher than in the reference period of 1986-2005, with the highest growth rate of 7.7% in the Northwest River Basin. Seasonally, increase of actual evapotranspiration will be obvious in winter, reaching at about 5.2%. (2) In the 2.0℃ warming, annual actual evapotranspiration over China will increase by 7.8% with relative to the reference period. The growth rate in the river basins in southern China is less than that in the north. Increase of actual evapotranspiration in the Pearl River Basin will be about 3.9%, but possibly approaching 10% in the Liaohe River Basin in northeast China and the central Northwest River Basin. On seasonal scale, the highest increase of actual evapotranspiration by 8.3% will be in spring and winter over China. (3) Relative to the 1.5℃ level, annual actual evapotranspiration will increase by about 3.4% for an additional 0.5℃ global warming scenario in China. Evapotranspiration is projected to increase obviously in northwest of the Southwest River Basin, southwest of the Northwest River Basin and the Liaohe River Basin, but might be slightly reduced in northeast and northwest parts of the Northwest River Basin. Seasonally, growth rate will be high in spring but comparatively less in autumn. The projected result that the actual evapotranspiration might show an upward trend in China with the increase of global mean temperature indicates aggravation of regional droughts in future, which might bring adverse impacts on agricultural production.

Effect of Air Humidity on Nutrient Content and Dry Matter Distribution of Tomato Seedlings under High Temperature

WANG Lin, YANG Zai-qiang, WANG Ming-tian, YANG Shi-qiong, CAI Xia, ZHANG Jie

2018, 39(05):  304-313.  doi:10.3969/j.issn.1000-6362.2018.05.002

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Took tomato variety of ‘Jinfen5’ as material, the experiment was conducted in Venlo greenhouse of Nanjing University of Information Science and Technology from April to September in 2016. The temperature was maintained at 41℃/18℃(day/night), the humidity (daytime) was set at 50%, 70%, and 90%（±5 percent points）, and 28℃/18℃ and 45%?55% was took as control (CK), to determine the effects of different treatments on the distribution of nutrients and dry matter in different organs of plants. The results showed that the contents of soluble sugar and free amino acids in different organs of tomato seedlings were significantly higher than those under normal temperature and humidity conditions (CK) at high temperature, but the protein content was significantly lower than CK(P<0.05) .When the humidity was increased to above 70%, the content of soluble sugar in various organs of tomato seedlings decreased, and the higher the humidity was, the lower the content of soluble sugar was in different air humidity treatments, the differences of treatments were obvious(P<0.05). The contents of free amino acids and soluble proteins in different organs of tomato seedlings were as follows, the higher the air humidity, the higher the contents of free amino acids and soluble proteins. The proportion of dry matter in tomato seedling leaves increased, the proportion of dry matter in stems and roots decreased at high temperature, and the lower the humidity, the greater the difference with CK. The proportion of dry matter in stems and roots decreased significantly(P<0.05), it was extremely unfavorable to plant growth under 50% humidity. After the high temperature stress was relieved, 70% and 90% of humidity treated tomatoes had higher recovery ability, and the ratio of nutrient and dry matter allocation of plants returned to CK level on the 12th day during recovery. The results indicated that increasing air humidity to more than 70% can effectively improve the heat resistance and resilience after the high temperature stress on tomato.

Multi-Step Rolling Prediction Model of Greenhouse Microclimate Based on R-BP Neural Network

REN Shou-gang, LIU Xin, GU Xing-jian,WANG Hao-yun, YUAN Pei-sen,XU Huan-liang

2018, 39(05):  314-324.  doi:10.3969/j.issn.1000-6362.2018.05.003

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High greenhouse efficiency depends on the proper greenhouse environment. So it is of great significance to establish an accurate multi-step greenhouse microclimate prediction model to optimize the greenhouse environment control. A rolling back propagation (R-BP) neural network group model was proposed in this paper. The R-BP model mainly includes two stages: (1) Establish an initial BP neural network model, which adopts an auto-encoder (AE) to learn initial network factors and optimize the network factors by improved particle swarm algorithm; (2) Establish a rolling prediction model to realize multi step prediction of greenhouse microclimate. It used the output of the previous network as partial input of the next network. To prove the effectiveness of the R-BP model, several experiments were implemented in the Abu Dhabi auto-controlled green house and non-controlled Suzhou greenhouse. The experiments in Abu Dhabi greenhouse proved that the R-BP model achieved an average of 69.9% error decrease in 6h temperature prediction in the greenhouse and an average of 47% error decrease in relative humidity prediction, compared with the traditional BP neural network. In Suzhou greenhouse, the average prediction error of temperature was reduced by 43.3% and the average prediction error of humidity was reduced by 55.6%. The experimental results prove that the R-BP model can accurately predict the change of the greenhouse microclimate for future 6 hours, to provide the basis for greenhouse microclimate control optimization.

Flood Disaster Index Construction of Single Cropping Rice Based on Process Rainfall in Middle and Lower Yangtze River

ZHANG Gui-xiang，HUO Zhi-guo，YANG Jian-ying，WU Li，YANG Hong-yi

2018, 39(05):  325-336.  doi:10.3969/j.issn.1000-6362.2018.05.004

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The single cropping rice is mainly distributed in the north of Yangtze River. Affected by climate, topography and landforms, Middle and Lower Yangtze River is one of the areas where floods occur most frequently. Therefore, it is very important to study the spatiotemporal variation law and risk distribution of single cropping rice flood in this area. In this study, daily precipitation data of 297 meteorological stations from 1961 to 2014, rice phenophase and flood disaster data in Middle and Lower Yangtze River were integrated to count process rainfall sequences at different stages of single cropping rice growth and different disaster levels. The lower limit of 95% confidence interval for sample sequences was calculated by t-distribution interval estimation method. Flood disaster index for each province in different single cropping rice growth stage was validated by the reserved independent samples of rice flood disaster. Afterwards, spatiotemporal and risk distribution of flood disaster for single cropping rice were analyzed in the area from 1961 to 2010. The results showed that tasselling-maturity stage’s index threshold was the highest in the same flood grade, followed by the jointing-booting stage’s and transplanting-tillering stage’s. In the same growth stage and same flood grade, index threshold of 5 provinces from low to high was Jiangsu, Anhui, Hubei, Hunan, Zhejiang. Single cropping rice flood occurred annually in each province, and without obvious tendency. With flood disaster level increasing, times of rice flood decreased. The high incidence areas of flood disaster for single cropping rice were mainly located in Poyang Lake, Zhejiang coast, Enshi and Zhangjiajie. Transplanting-tillering stage was faced with highest flood risk, with risk index >0.6. Except the coastal areas of Zhejiang, risk index in most areas decreased significantly with < 0.3 during the period from jointing to maturity.

Analysis of Pre-spraying Foliage Fertilizer on Fanqiu Late Rice Enhance the Ability of Resisting Cold Dew Wind

LI Chao，XIAO Xiao-ping，TANG Wen-guang，TANG Hai-ming，WANG Ke，CHENG Kai-kai，GUO Li-jun，YANG Guang-li

2018, 39(05):  337-343.  doi:10.3969/j.issn.1000-6362.2018.05.005

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In recent years, Fanqiu-late rice(early rice varieties for late rice direct seeding cultivation) planting is developing rapidly with the advantages of low-cost and high-economic benefits, relieve of the season contradictions during double-cropping rice production. However, the grain yield of Fanqiu late rice was lower than that of late rice for that it was affected by cold dew wind at heading stage. Therefore, to provide technical support and theoretical basis for improving the disaster avoidance and reduction ability of Fanqiu-late rice responded on cold dew wind. Three treatments including clear water (CK) and foliage fertilizer Penshibao(T1) were pre-sprayed at 2 days before cold dew wind, and Penshibao(T2) at the cold dew wind coming day in initial heading stage were used to studied the mechanism of disaster avoidance and reduction about Fanqiu-late rice resisting cold dew wind in the present paper. The results showed that, compared with CK and T2, pre-spraying foliage fertilizer(T1) could promote Fanqiu-late rice for full heading safely, the growth period reduced three to four days; T1 was good for increasing the net photosynthetic rate at grain filling stage, facilitated the value of SPAD to decline, and thus promoting net photosynthetic rate to attenuate normally, so that the carbon nutrition of the plant was more coordinated with nitrogen nutrition, dry matter run more smoothly. Therefore, the grain filling rate of T1 were increased significantly (P<0.05), seed-setting rate of T1 were increased 9.5 to 13.9 percent point, and the grain yield of T1 were increased 15.8% to 23.7%. And the appearance quality and processing quality of rice were improved by apply with pre-spraying foliage fertilizer practice. As a result, it was a better way to increase the capacity of disaster avoidance and reduction to resist the cold dew wind of Fanqiu-late rice by application of pre-spraying foliage fertilizer practice.

Optimal Scale Screening of Paddy Rice in Remote Sensing Imagery Based on High Pass Filter Fusion

ZHANG Xiao-yi，JING Yuan-shu,LI Wei-guo

2018, 39(05):  344-353.  doi:10.3969/j.issn.1000-6362.2018.05.006

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In order to confirm optimal scale of paddy rice extraction in Jiangsu, the experiment was first set up four fusion images with different scales using HPF algorithm, based on HJ1A/CCD2 image (30m×30m) and GF1/WFV4 near-infrared image (16m×16m). To screen optimal scale, it was then conducted the four images on quantitative index assessment and vegetation index inversion assessment. At last, the superiority of optimal scale in fusion images was verified with testing data from extraction of paddy rice area with decision tree method composed of multi-spectral indexes and inversion of paddy rice LAI with PROSAIL model. The results showed that: (1)it was 20m×20m and 15m×15m that both had spectral inheritance and spectral optimization to meet the use requirements, based on quantitative index assessment and vegetation index inversion assessment. Optimal scale was chose 15m×15m because of scale advantage. (2)Compared with original image scales, 15m×15m was verified higher spatial resolution, best area extraction, and improved LAI inversion, which area accuracy 93.33%, quadrat accuracy 94.71%, RMSE 0.25 ha, and LAI inversion accuracy 94.69%, RMSE 0.893. In conclusion, the optimal scale which could inverse paddy rice in research area was 15m×15m.