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20 October 2019, Volume 40 Issue 10

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Spatial Downscaling of TRMM Precipitation Data in Areas of Complex Terrain: A Case Study in Sichuan Province

LI Hao, LEI Yuan

2019, 40(10):  607-619.  doi:10.3969/j.issn.1000-6362.2019.10.001

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Precipitation data have became an indispensable part for agriculture, hydrological, meteorological, ecological and other environmental applications. Satellites obtain the earth's precipitation data from space through on-board sensors, which is playing a more and more important role in the data collection currently. Research increasingly suggests that satellite-derived precipitation products with their advantages in the continuity of spatial scale and high degree of prediction accuracy have vast space for development. It is well-known that use of the Tropical Rainfall Measuring Mission (TRMM) has been widely employed for obtaining global precipitation data recently due to its incomparable superiority to traditional method. However, the application is subject to certain restrictions by the relatively low spatial resolution (about 20?30km) of the data. Considering various influence factors such as spatial location and terrain and their spatial non-stationary characteristics, a case study on the application of mixed geographic weighted regression combined with Kriging interpolation (MGWRK) for spatial downscaling of the TRMM annual precipitation data was undertaken at Sichuan Province, Southwest China with a significant space differentiation of precipitation. And in the meantime, assessment of the downscaling results derived by different methods were carried out based on the measured data of 41 meteorological stations. Some results in this study showed that: (1) by use of the MGWRK model for downscaling, the spatial resolution of TRMM precipitation data was increased sharply from 0.25° (about 26km) to 1km, which can describe the spatial variation of precipitation more detailly and effectively in study area. (2) The MGWRK model not only attempted to use a combination of various auxiliary information with high-resolution such as spatial location and terrain, but also explored the characteristics of spatial stationary of the relationship between TRMM precipitation and its factors. From the assessment results of various downscaling approach to the TRMM data of mean annual values (1998?2017) and the two typical years’ values (the wet year at 1998 and the dry year at 2006), it was found that the MGWRK method can prove a higher accuracy compared with the OLS-based global regression Kriging (GRK) and the Bilinear resample (Bil) method and obtain a result that is more approximate to the original status. (3) The downscaling model presented in this paper considered the improvement of spatial resolution without compromising the maintaining accuracy and therefore it is obviously an approach available for the spatial downscaling of TRMM precipitation data in study area and contribute to define a foundation for the application of the TRMM data in small scale.

Analysis on Thermal Characteristics of Trapezoidal Wall Based on Phase Change Materials in Solar Greenhouse

LI Peng, ZHANG Ya-hong, BAI Qing, HU Wei, JIANG Li, ZHAI Xue-ning

2019, 40(10):  620-629.  doi:10.3969/j.issn.1000-6362.2019.10.002

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In order to explore the effect of phase change materials on the inner temperature of the solar greenhouse, the solid-liquid phase change composite material, in which paraffin wax was a main component, was sprayed onto the inner surface of north trapezoidal wall in the solar greenhouse. Then, the heat flux, temperature near the north trapezoidal wall, and the temperature indoor and outdoor both in the sprayed greenhouse and ordinary greenhouse were measured and analyzed by performing typical weather and monthly changed. The results showed that the heat storage in day-time and heat release in night-time of the north trapezoidal wall in the phase change coated greenhouse was significantly higher than that in the ordinary greenhouse (P<0.05). There was a certain difference in the temperature of the same layer and the same typical time of the phase change coating greenhouse and the ordinary greenhouse, which decreased gradually with the depth increasing of the north wall, and the difference between 0?300mm was the most significant (P<0.05). The daily average value of accumulated heat storage in the phase change coating greenhouse was 8.1% higher than that of the ordinary greenhouse, and the daily average value of accumulated heat release was 14.8% higher than that of the ordinary greenhouse.There was a significant difference between the monthly average temperature at the surface and the various inner layers in the north wall of the phase change coating and the ordinary greenhouse (P<0.05). The monthly average temperature in the phase change coating greenhouse, ordinary greenhouse and outdoor were 9.93℃, 8.63℃ and -8.91℃, respectively. It indicated that the phase change coating north wall effectively increased the heat storage and heat release and enhanced the greenhouse air temperature, especially the night temperature.

Grain Filling Characters and Its Correlation with 1000-grain Weight in Different Winter Wheat Varieties

LIU Hong-jie, NI Yong-jing, REN De-chao, DU Ke-ming, GE Jun, ZHU Pei-pei, ZHAO Jing-ling, HUANG Jian-ying, LV Guo-hua, HU Xin

2019, 40(10):  630-636.  doi:10.3969/j.issn.1000-6362.2019.10.003

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Based on the field experimental data of winter wheat in 2017/2018, grain filling process was analyzed by logistic equation for 2 weak springiness varieties and 6 semi-winter varieties. Correlations on grain weight and grain filling characters were analyzed. The results showed that grain filling rate of semi-winter variety was generally larger than that of weak springiness variety. The 1000-grain weight was significantly increased by the higher grain filling rate at middle and late grain filling stage. The weak springiness varieties grow faster after reviving, bloomed earlier, and lasted longer in grain filling stage. However, the mean and maximum grain filling rates of weak springiness variety were significantly smaller than those of semi-winter variety. The 1000-grain weight was greatly influenced by grain filling rate, especially at middle and late grain filling stages. Although the grain filling duration of different genotype varieties was different, it had little effect on the increase of 1000-grain weight. According to the correlation analysis between grain filling parameters and 1000-grain weight, grain filling rate at quick-increase filling stage and slight-increase filling stage played the key roles. No significant correlation between grain filling duration at all stages and 1000-grain weight were found. It was concluded that the semi-winter varieties of S355, YJ5, and CM1 were more suitable for popularization in the experimental area.

Sugarcane Leaf Photosynthetic CO2 Responses Parameters and Their Difference among Varieties

LIU Yang-yang, LI Jun, YU Qiang, LIU Shao-chun, TONG Xiao-juan, YU Ling-xiang

2019, 40(10):  637-646.  doi:10.3969/j.issn.1000-6362.2019.10.004

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Sugarcane (Saccharum officinarum L.)photosynthetic CO2 response represents an important physiological characteristic for sugarcane growth. Sugarcane is the major sugar crop, exhibiting the characteristic of higher photosynthetic efficiency as a C4 plant. This study was conducted to compare performance of different models of photosynthetic CO2 response, and to investigate the photosynthetic CO2 response characteristics of different sugarcane varieties. Field measurements were carried out in Kaiyuan, Yunnan Province, using a portable LI-6400XT photosynthesis system to explore the correlation between the photosynthetic CO2 response parameters. The non-rectangular hyperbola model (NRH), rectangular hyperbola model (RH) and Ye model were used to fit the sugarcane photosynthetic CO2 response curve of six varieties, and the photosynthetic CO2 response parameters were analyzed. The results showed that the photosynthetic CO2 response curve fitted by NRH and RH model do not determine CO2 saturation point (CSP), and overestimate the maximum net photosynthetic rate (Amax). The initial carboxylation rate (η) fitted by NRH model were almost the same as the measured values, but the respiration rate (Rp) and CO2 compensation point (CCP) fitted by NRH model were both negative. In general, the Ye model was the best in simulating the photosynthetic CO2 response curves. In the photosynthetic CO2 response parameters fitted by Ye model, η was significantly correlated (positively) with Rp/CCP (P<0.001), Rp was significantly correlated (positively) with η and CCP (P<0.05), η and Rp were significantly correlated (negatively) with CSP (P<0.05). The varieties with higher photosynthetic rate under low CO2 concentration tended to have higher respiration rate, meanwhile, they have lower photosynthesis capacity under high CO2 concentration, which are easier to reach CO2 saturation point. The average Amax value of six sugarcane varieties fitted by Ye model was 32.44.5mol·m-2·s-1, η was 0.1280.060, CSP was 115277mol·m-2·s-1 and CCP was 8.55.5045mol·m-2·s-1. ROC22 had lower Rp, and CCP and the highest Amax, indicating the most realistic to represent photosynthetic characteristics. All the five sugarcane varieties except YZ99-91 have large CSP, and could adapt to the increasing CO2 concentration in the atmosphere.

Mapping the Cultivation Areas of Summer Maize Using Spatial Variations of Crop Phenology over Huanghuaihai Plain

WANG Xue-ting, ZHANG Sha, DENG Fan, ZHANG Jia-hua

2019, 40(10):  647-659.  doi:10.3969/j.issn.1000-6362.2019.10.005

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Considering the phenological differences of maize along with latitude over a large area, the planting area of summer maize was extracted by MODIS EVI time series curve over Huanghuaihai Plain in this paper. Based on Landsat images and MOD13Q1 dataset, the MODIS EVI time series curve of summer maize was obtained in a reference area. The phenology observation data from the agro-meteorological stations were collected to build the relationship between various summer maize growth stages and latitude. The latitude was used to correct the MODIS EVI time series curve of summer maize in the reference area, and then the standard EVI time series curve of summer maize was obtained. Using the mean absolute distance (MAD) method and p-tile algorithm, the summer maize planting area was estimated in the study area. The results showed that the areas of summer maize extracted from remote sensing images in Beijing, Tianjin, Hebei, Henan and Shandong were 125.3×103, 162.6×103, 2231.8×103, 2963.6×103 and 2731.9×103ha, respectively. Meanwhile, the accuracy of extraction result in each province was above 80%. The determinant coefficient (R2) is 0.82 and the root mean square error (RMSE) is 147.8×103ha at city level, and 0.62 and 17.7×103ha at county level, respectively. It indicated that the method in present study has the ability of extracting the summer maize planting area effectively and provides a new idea for estimating the planting area of other crops in a large region.

Applicability Evaluation of CLDAS Merged Soil Relative Moisture in Northeast of China and Its Correction Research

CUI Yuan-yuan，ZHANG Qiang, QIN Jun，JING Wen-qi

2019, 40(10):  660-668.  doi:10.3969/j.issn.1000-6362.2019.10.006

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Using observed soil relative moisture data at 10cm layer, the applicability of CLDAS（CMA Land Data Assimilation System）merged soil relative moisture at 0-20cm layer was tested and verified by calculating the correlation coefficient and bias between the CLDAS product and in-situ soil moisture observation in Northeast of China during 2008-2017. The results showed that CLDAS merged soil relative moisture data could reasonably reflect the actual spatial distribution of soil moisture at a depth of 10cm in Northeast of China, however, it was not very excellent at the extreme values’ performance. CLDAS merged soil relative moisture data was obviously higher than actual site observations in western of Liaoning province and southwestern of Heilongjiang province, while the simulation was lower than the actual soil relative moisture in northeastern of Heilongjiang province. The applicability of CLDAS product in Northeast of China decreases from southwest to northeast and was better in Jilin and Liaoning provinces. Furthermore, further analysis found that the poor applicability was mainly caused by the low correlation between CLDAS and site observation in Heilongjiang province. Finally, the error of CLDAS product was corrected by regression correction method and 7 ten-day sliding average correction method. The result greatly improves the accuracy of CLDAS product, and the revised products could be applied to soil moisture drought monitoring business.