贵州最高气温预报方法研究

最高气温预报一直以来是贵州最为棘手的问题,近年来在国家气象局预报质量通报中,成绩较为靠后。为改变这一现象,笔者基于各预报中心常规气温预报资料及地面观测资料,在贵州境内展开最高气温的多模式集合预报研究。结果表明,多模式集合预报技术有效地改进了预报的准确率,在对2013年1月1日—2014年4月30日120 h的逐24 h预报中,各预报中心的多模式集合预报结果明显降低了预报的均方根误差,效果远优于最好的单个预报中心(ECMWF)和多模式的集合平均,不仅很好地改善了贵州最高气温的预报效果,还给当地预报及决策气象服务提供更有效的参考。     

重采样方法对DEM数据质量的影响

[目的]针对在数字地形分析的实际应用问题,利用重采样方法得到的DEM数据精度,旨在分析不同的重采样方法对所获得的DEM数据质量的影响。[方法]从数据误差的角度,以陕西省绥德县窑家湾沟流域的以全数字摄影测量得到的DEM数据为基准,计算并比较利用重采样方法得到的DEM的数据误差。[结果]无论采用何种重采样方法,得到DEM数据质量均未得到提高,其高程误差的空间分布与重采样方法相关,地形变化剧烈的地方,误差较大;中误差的大小则取决于重采样方法与原始格网尺寸。[结论]最近邻法得到的重采样DEM数据的中误差最高,三次立方卷积法的最小,双线性内插法则略高于三次立方卷积法。     

Estimating N status of winter wheat using a handheld spectrometer in the North China Plain

Excessive nitrogen (N) fertilizer application is very common in the North China Plain. Diagnosis of in-season N status in crops is critical for precision N management in this area. Remote sensing, as a timely and nondestructive tool, could be an alternative to traditional plant testing for diagnosing crop N status. The objectives of this study were to determine which vegetation indices could be used to estimate N status in winter wheat (Triticum aestivum L.) under high N input conditions, develop models to predict winter wheat N uptake using spectral vegetation indices and validate the models with data from farmers’ fields. An N rate experiment and a variety-N experiment were conducted in Huimin, Shandong Province from 2005/2006 to 2006/2007 to develop the models. Positive linear relationships between simple ratio vegetation indices (red vegetation index, RVI and green vegetation index, GVI) and N uptake were observed independent of growth stages and varieties (R², 0.48–0.74). In contrast, the relationships between normalized difference vegetation indices (NDVI and GNDVI), red and green normalized difference vegetation index (RGNDI), and red and green ratio vegetation index (RGVI) were exponentially related to N uptake (R², 0.43–0.79). Subsequently, 69 farmers’ fields in four different villages were selected as datasets to validate the developed models. The results indicated that the prediction using RVI had the highest coefficient of determination (R², 0.60), the lowest root mean square error (RMSE, 39.7 kg N ha⁻¹) and relative error (RE, 30.5%) across different years, varieties and growth stages. We conclude that RVI can be used to estimate nitrogen status for winter wheat in over-fertilized farmers’ fields before heading.     

Simulation of transpiration, drainage, N uptake, nitrate leaching, and N uptake concentration in tomato grown in open substrate

Free-drainage or “open” substrate system used for vegetable production in greenhouses is associated with appreciable NO₃⁻ leaching losses and drainage volumes. Simulation models of crop N uptake, N leaching, water use and drainage of crops in these systems will be useful for crop and water resource management, and environmental assessment. This work (i) modified the TOMGRO model to simulate N uptake for tomato grown in greenhouses in SE Spain, (ii) modified the PrHo model to simulate transpiration of tomato grown in substrate and (iii) developed an aggregated model combining TOMGRO and PrHo to calculate N uptake concentrations and drainage NO₃⁻ concentration. The component models simulate NO₃⁻-N leached by subtracting simulated N uptake from measured applied N, and drainage by subtracting simulated transpiration from measured irrigation. Three tomato crops grown sequentially in free-draining rock wool in a plastic greenhouse were used for calibration and validation. Measured daily transpiration was determined by the water balance method from daily measurements of irrigation and drainage. Measured N uptake was determined by N balance, using data of volumes and of concentrations of NO₃⁻ and NH₄⁺ in applied nutrient solution and drainage. Accuracy of the two modified component models and aggregated model was assessed by comparing simulated to measured values using linear regression analysis, comparison of slope and intercept values of regression equations, and root mean squared error (RMSE) values. For the three crops, the modified TOMGRO provided accurate simulations of cumulative crop N uptake, (RMSE = 6.4, 1.9 and 2.6% of total N uptake) and NO₃⁻-N leached (RMSE = 11.0, 10.3, and 6.1% of total NO₃⁻-N leached). The modified PrHo provided accurate simulation of cumulative transpiration (RMSE = 4.3, 1.7 and 2.4% of total transpiration) and cumulative drainage (RMSE = 13.8, 6.9, 7.4% of total drainage). For the four cumulative parameters, slopes and intercepts of the linear regressions were mostly not statistically significant (P < 0.05) from one and zero, respectively, and coefficient of determination (r²) values were 0.96-0.98. Simulated values of total drainage volumes for the three crops were +21, +1 and −13% of measured total drainage volumes. The aggregated TOMGRO-PrHo model generally provided accurate simulation of crop N uptake concentration after 30-40 days of transplanting, with an average RMSE of approximately 2 mmol L⁻¹. Simulated values of average NO₃⁻ concentration in drainage, obtained with the aggregated model, were −7, +18 and +31% of measured values.     

Soil aggregate formation and stability induced by starch and cellulose

Soil aggregate (SA) can be formed and stabilized when soil organic matter (SOM) is decomposed in the soil. However, the relationships between the SA dynamics and SOM with different decomposition rates have not been clarified. Therefore, this study examined the effects of the addition of polysaccharides to soil on SA formation and stability. A Japanese tropical soil was incubated for 99 d at 30 °C in a dark environment following the addition of 0.5% (w/w) starch or cellulose. The decomposition rates of the amendments, and SA formation and stability were evaluated by measuring soil respiration rates, and distribution fractions of soil aggregate sizes and mean weight diameter (MWD) of SA, respectively. The cumulative soil respirations with all treatments rapidly increased until Day 12 of the incubation. The initial slope of the cumulative soil respiration in the soil with starch was significantly higher than that in the soil with cellulose. In either soil with starch or cellulose, the fractions of macro-aggregates (>1000 μm in diameter) significantly increased, respectively, compared with control soil. However, the fractions of meso-aggregates (250–1000 μm) and nano-aggregate (<20 μm) in the soil with starch significantly decreased, while those fractions in the soil with cellulose fluctuated until Day 6. The MWDs reached the maximum on Day 6, indicating the SA formation in the soils with starch or cellulose. The increasing rate of the SA formation in the starch-amended soil was greatly higher than that in the cellulose-amended soil. After Day 6, the MWDs in the soils with either polysaccharide decreased with similar trends with no significant differences between treatments, indicating similar stability of the SA in both treatments. This study showed that the different decomposability of the organic amendments might influence the SA formation differently, but not the SA stability.     

Effect of quinoa flour on gluten-free bread batter rheology and bread quality

A new gluten-free bread formulations composed of quinoa, buckwheat, rice flour and potato starch were developed in the present study. Rheological characteristics of the bread batter with increasing amount of quinoa were determined; storage (G′) and loss modulus (G″) values were also measured for investigation of viscoelastic properties. To evaluate the quality of breads; technological and physical (bake loss %, specific volume, texture, microstructure, color), chemical (protein, moisture, ash) and sensory properties were determined. All batter formulations independent of the quinoa amount exhibited pseudoplastic behavior, and G′ values were found to be higher than G″ values in expressing the solid like characteristics of the batter. Amount of quinoa flour addition did not present significant difference on bake loss%, specific volume and protein content (p>0.05); however, 25% quinoa flour bread displayed better results with its higher sensory scores and softer texture. Quinoa and buckwheat flour mixture therefore will be a good alternative for conventional gluten-free bread formulations.     

Estimating aboveground biomass in forest and oil palm plantation in Sabah, Malaysian Borneo using ALOS PALSAR data

Conversion of tropical forests to oil palm plantations in Malaysia and Indonesia has resulted in large-scale environmental degradation, loss of biodiversity and significant carbon emissions. For both countries to participate in the United Nation’s REDD (Reduced Emission from Deforestation and Degradation) mechanism, assessment of forest carbon stocks, including the estimated loss in carbon from conversion to plantation, is needed. In this study, we use a combination of field and remote sensing data to quantify both the magnitude and the geographical distribution of carbon stock in forests and timber plantations, in Sabah, Malaysia, which has been the site of significant expansion of oil palm cultivation over the last two decades. Forest structure data from 129 ha of research and inventory plots were used at different spatial scales to discriminate forest biomass across degradation levels. Field data was integrated with ALOS PALSAR (Advanced Land-Observing Satellite Phased Array L-band Synthetic Aperture Radar) imagery to both discriminate oil palm plantation from forest stands, with an accuracy of 97.0% (κ = 0.64) and predict AGB using regression analysis of HV-polarized PALSAR data (R² = 0.63, p < .001). Direct estimation of AGB from simple regression models was sensitive to both environmental conditions and forest structure. Precipitation effect on the backscatter data changed the HV prediction of AGB significantly (R² = 0.21, p < .001), and scattering from large leaves of mature palm trees significantly impeded the use of a single HV-based model for predicting AGB in palm oil plantations. Multi-temporal SAR data and algorithms based on forest types are suggested to improve the ability of a sensor similar to ALOS PALSAR for accurately mapping and monitoring forest biomass, now that the ALOS PALSAR sensor is no longer operational.     

Early development and enlargement of wheat floret primordia suggest a role of partitioning within spike to grain set

Spike grain number, a major component in the yield of wheat, is suspected of being determined by the sudden death of most of the initiated floret primordia, which occurs at around booting. By counting twice weekly the number of floret primordia in the middle and top spikelets, the onset time for the death of floret primordia (T_d) was assessed in six genotypes of differing earliness and fertility subjected to three treatments that were applied during stem elongation. The variation in T_d was positively correlated with overall earliness, as well as with spike fertility. Ovary development and enlargement were quantified in eight specified positions within the spikes, but T_d could not be assigned to a developmental stage attained by any ovary. Development and enlargement were very strongly correlated with each other throughout the floret lifetime, yet with significant effects of genotype, treatment and position within spikes. In each position within a spike, the proportion of florets that set a grain correlated to the initial delay of development as compared to the most advanced floret (r² = 0.64), but this correlation was severely biased by genotype and the floret position effect. Better correlations were obtained with either the development or width of each ovary at T_d, thus highlighting the role of the preceding phase. The best prediction (r² = 0.93) was obtained from the ratio of ovary width to that of the most advanced floret at T_d. The importance of this width ratio emphasized the role of partitioning in grain set: only florets able to divert nutrients survived after T_d and eventually set a grain. This relationship was no longer biased by floret position, while some remaining variability due to genotype suggested potential for plant breeding: width ratios at T_d were generally related to the growth duration of various primordia, as well as to their relative growth rate.     

使用积分法估算原状土van Genuchten模型参数

The van Genuchten model is the most widely used soil water retention curve (SWRC) model. Two undisturbed soils (clay and loam) were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error (RMSE), normalized root mean square error (NRMSE) and Willmott’s index of agreement (l). The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs (4.61 × 10-5 for Eum-Orthic Anthrosol and 2.74 × 10-4 for Los-Orthic Entisol) and NRMSEs (1.56 × 10-4 for Eum-Orthic Anthrosol and 1.45 × 10-3 for Los-Orthic Entisol) were relatively small. The l values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.     

消除偏差集合平均在黄海渤海大风预报中的应用

基于日本气象厅预报模式（JMA）、美国国家环境预报中心预报模式（NCEP GFS）及美国海军全球大气预报谱模式（NOGAPS）3个模式2009年6月28日~8月10日每日20：00预报的海面风场预报资料,利用消除偏差集合平均对海面风场进行预报试验,并采用均方根误差对预报结果进行检验评估。结果表明,对于24、48 h海面风场预报,消除偏差集合平均有效地减小了预报的均方根误差,预报效果优于单个模式的预报;其中,渤海中部偏南地区及黄海中部误差减小最为明显。此外,消除偏差集合平均预报明显改善了2009年7月13~14日和8月7日大风过程的预报效果,提高了风速值和大风区位置的预报准确率。