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61.
秸秆焚烧对区域城市空气质量影响的模拟分析   总被引:2,自引:0,他引:2  
利用融合火点排放源、人为源和生物源的WRF-Chem(Weather Research and Forecasting Model coupled with Chemistry)模式,模拟2015年9月30日08:00(北京时间)起的72 h发生在淮河流域的一次农作物秸秆大面积露天焚烧过程,研究了农作物秸秆焚烧释放的气态污染物和颗粒物对区域城市空气质量的影响。通过有无火点两组试验分析了此次秸秆焚烧对流域内河南、山东、江苏和安徽四省83座城市CO、PM10(空气动力学当量直径小于等于10μm的颗粒物,即可吸入颗粒物)、PM2.5(空气动力学当量直径小于等于2.5μm的颗粒物,即细颗粒物)和O3浓度的定量影响,结果表明:(1)融合NCAR-FINN(Fire Inventory from NCAR)火点排放资料的WRF-Chem模式较好地再现了此次秸秆焚烧及火点烟羽扩散过程。同时结合EDGAR-HTAP(Emission Database for Global Atmospheric Research on Hemispheric Transport of Air Pollution)人为源和MEGAN(Model of Emission of Gases and Aerosols from Nature)生物源的WRF-FIRE(考虑火点排放试验)对流域内城市大气污染物的模拟效果较为理想,尤其对秸秆焚烧释放的污染物CO、PM10和PM2.5和产生的二次污染物O3浓度的模拟。(2)秸秆焚烧所释放的污染物造成流域内城市一次污染物CO、PM10和PM2.5浓度的增加,火点中心和下风向城市增幅最为明显,最大小时浓度增幅达到3倍标准差。气态污染物CO和相比PM10粒径更小的PM2.5可随风扩散至更远的地区,对城市浓度影响更大。(3)此外,秸秆焚烧也使得火点中心城市和下风向城市二次污染物O3浓度增加,但小时浓度增幅极值区分布在火点下风向烟羽末端太阳光照充足的地区,最大小时浓度增幅接近3倍标准差。秸秆焚烧对区域城市空气质量的影响存在明显的空间分布差异且对城市各大气污染成分的影响也不相同。  相似文献   
62.
63.
With the problem of shortage of water resources becoming increasingly prominent, the improvement of production efficiency of agricultural water resources in China has become an important research content of modern irrigated agriculture. The technology of activated irrigation water provides a new way to excavate the physiological production potential of irrigation water and improve the comprehensive efficacy of irrigation water in agro-ecosystems. In this study, the research progress of the variable characteristics of physicochemical properties of activated irrigation water, the transport and transformation of soil material by activated irrigation water, and the promotion of crop growth by activated irrigation water were comprehensively analyzed. On this basis, according to the basic theories of soil physics, crop physiology, and material transport dynamics, the effects of activated irrigation water on soil material transport, soil material transformation, water and nutrition uptake by root, and crop yield formation and the probable pathway were analyzed. The key problems of basic science and applied technology in the future research are put forward to provide reference for the scientific and reasonable utilization of activated irrigation water technology.  相似文献   
64.
CO2补偿点是作物生长模型中最基本的关键模型参数之一,本文利用Licor-6400便携式光合作用测定仪,对1949年以前和1949-2005年中国华北地区不同年代冬小麦主要品种的生理生态参数进行大量的系统测定,在此基础上,对华北地区不同冬小麦品种的光合作用模型进行拟合,以确定不同年代不同品种冬小麦CO2的补偿点。结果表明:中国华北地区冬小麦CO2补偿点随光强升高而降低,在800 μmol·m-2·s-1光量子通量密度条件下,野生麦种CO2补偿点最高,达123.40 μmol·mol-1。1949-2005年华北地区不同冬小麦品种中泰山1号CO2补偿点最高,达107.07 μmol·mol-1;红秃头CO2补偿点最低,为57.25 μmol·mol-1;不同品种冬小麦CO2补偿点最高值和最低值差值为49.82 μmol·mol-1,说明华北地区冬小麦随品种演化CO2补偿点变化明显。建立了中国华北地区7个典型冬小麦品种包含CO2因子的直角双曲线光合作用模型,确定了不同年代不同品种冬小麦CO2的补偿点,为进一步建立包含CO2直接作用的气候变化影响评估机理模型提供基础数据。  相似文献   
65.
冬小麦生长模式及其在干旱影响评估中的应用   总被引:11,自引:3,他引:8       下载免费PDF全文
在前人理论研究和田间试验的基础上,考虑水分胁迫影响的后效性及作物不同发育阶段对水分胁迫的敏感性,研制出实际水分条件下的冬小麦生长模拟模式。经与不同水分处理的实测资料对比,模拟效果基本令人满意,平均误差为10%左右。利用生长模式得到实际水分条件下的干物重减少率,进行了干旱影响实时评估的尝试。并分别在返青后、拔节后和成熟前展望了干旱对最终生物量的可能影响。  相似文献   
66.
The development of cost-effective, reliable and easy to implement crop condition monitoring methods is urgently required for perennial tree crops such as coffee (Coffea arabica), as they are grown over large areas and represent long term and higher levels of investment. These monitoring methods are useful in identifying farm areas that experience poor crop growth, pest infestation, diseases outbreaks and/or to monitor response to management interventions. This study compares field level coffee mean NDVI and LSWI anomalies and age-adjusted coffee mean NDVI and LSWI anomalies in identifying and mapping incongruous patches across perennial coffee plantations. To achieve this objective, we first derived deviation of coffee pixels from the global coffee mean NDVI and LSWI values of nine sequential Landsat 8 OLI image scenes. We then evaluated the influence of coffee age class (young, mature and old) on Landsat-scale NDVI and LSWI values using a one-way ANOVA and since results showed significant differences, we adjusted NDVI and LSWI anomalies for age-class. We then used the cumulative inverse distribution function (α  0.05) to identify fields and within field areas with excessive deviation of NDVI and LSWI from the global and the age-expected mean for each of the Landsat 8 OLI scene dates spanning three seasons. Results from accuracy assessment indicated that it was possible to separate incongruous and healthy patches using these anomalies and that using NDVI performed better than using LSWI for both global and age-adjusted mean anomalies. Using the age-adjusted anomalies performed better in separating incongruous and healthy patches than using the global mean for both NDVI (Overall accuracy = 80.9% and 68.1% respectively) and for LSWI (Overall accuracy = 68.1% and 48.9% respectively). When applied to other Landsat 8 OLI scenes, the results showed that the proportions of coffee fields that were modelled incongruent decreased with time for the young age category and while it increased for the mature and old age classes with time. We concluded that the method could be useful for the identification of anomalous patches using Landsat scale time series data to monitor large coffee plantations and provide an indication of areas requiring particular field attention.  相似文献   
67.
In this study, hyperspectral reflectance (HySR) data derived from a handheld spectroradiometer were used to assess the water status of three grapevine cultivars in two sub-regions of Douro wine region during two consecutive years. A large set of potential predictors derived from the HySR data were considered for modelling/predicting the predawn leaf water potential (Ψpd) through different statistical and machine learning techniques. Three HySR vegetation indices were selected as final predictors for the computation of the models and the in-season time trend was removed from data by using a time predictor. The vegetation indices selected were the Normalized Reflectance Index for the wavelengths 554 nm and 561 nm (NRI554;561), the water index (WI) for the wavelengths 900 nm and 970 nm, and the D1 index which is associated with the rate of reflectance increase in the wavelengths of 706 nm and 730 nm. These vegetation indices covered the green, red edge and the near infrared domains of the electromagnetic spectrum. A large set of state-of-the-art analysis and statistical and machine-learning modelling techniques were tested. Predictive modelling techniques based on generalized boosted model (GBM), bagged multivariate adaptive regression splines (B-MARS), generalized additive model (GAM), and Bayesian regularized neural networks (BRNN) showed the best performance for predicting Ψpd, with an average determination coefficient (R2) ranging between 0.78 and 0.80 and RMSE varying between 0.11 and 0.12 MPa. When cultivar Touriga Nacional was used for training the models and the cultivars Touriga Franca and Tinta Barroca for testing (independent validation), the models performance was good, particularly for GBM (R2 = 0.85; RMSE = 0.09 MPa). Additionally, the comparison of Ψpd observed and predicted showed an equitable dispersion of data from the various cultivars. The results achieved show a good potential of these predictive models based on vegetation indices to support irrigation scheduling in vineyard.  相似文献   
68.
With rapid economic development in China, crops have undergone remarkable changes in both their type and spatial pattern. Timely and accurate information of crop type distribution will help government and agricultural producers quickly understand regional agricultural production conditions to better facilitate appropriate adjustments in planting patterns and policies. Another benefit of acquiring such knowledge of crops is that it should enhance regional agricultural competitiveness, optimize resource allocations, and further guarantee national food security. Towards this end, and using the Zhangye City in the Heihe River Basin as a study area, the present research elaborated upon a methodology to classify crop type distribution based on multi-temporal Thematic Mapper and Enhanced Thematic Mapper Plus (TM/ETM+) images. Using this methodology we achieved the spatial distributions of crop types in Zhangye City in 2007 and 2012, and analyzed changes in their distributions over this period. In addition, some landscape indices were calculated to clarify the landscape pattern of crops. The crop conversion potentials in 2017 were modeled using four conversion sub-models of the Multi-Layer Perceptron (MLP) neural network. Generally, the overall accuracy of crop classification in Zhangye was high, at 89.38%. From 2007 to 2012, the cultivated land area in Zhangye increased from 463.81 × 103 ha to 493.89 × 103 ha. The sowing area of corn and oilseed rape increased by 39.21 × 103 ha and 5.99 × 103 ha, respectively, while for wheat and barley the sowing area decreased by 3.61 × 103 ha and 9.14 × 103 ha, respectively. Considering other crop types as a group, their sowing area decreased by only 2.37 × 103 ha. The increase in corn sowing area mainly came from the conversion of other crops to corn, which accounted for 43.09% of its total sowing area in 2012. Furthermore, corn and oilseed rape showed a tendency of intensive sowing, whereas for wheat and barley the tendency was towards scattered sowing. For the future, corn has high conversion potential in Linze and Gaotai counties of Zhangye, while wheat, barley and oilseed rape have high conversion potentials in Minle and Shandan counties.  相似文献   
69.
阿克苏河灌区是中纬度干旱区典型的绿洲灌溉系统,同时也是新疆第二大灌区,了解灌区作物需水量可为灌区种植结构调整、水资源优化配置提供科学依据。本研究基于联合国粮农组织(FAO)的Penman-Monteith蒸散发模型,结合作物系数法估算了阿克苏灌区作物需水量的时空变化及其对气候因子和作物种植结构的敏感性。结果表明,1960—2015年阿克苏灌区多年平均作物需水量为586 mm,且呈显著上升趋势,上升速率为38.43 mm/10 a。随着气候变化和作物种植结构的改变,1990—2015年间作物需水量急剧增加,增加速率高达99.37 mm/10 a。对于不同作物类型,果林的需水量最大,高达829.8 mm,其次是棉花、水稻和玉米,小麦需水量最低。阿克苏灌区的作物需水量对日最高气温和日照时数较为敏感,而对最低气温、风速和水汽压的敏感度较低。当日最高气温升高2℃时,作物需水量增加4%,当日照时数增加10%时,作物需水量将增加3.2%。另外,作物需水量对作物种植结构非常敏感,当果林的种植面积比例增加10%时,作物需水量增加了12.1%。  相似文献   
70.
Quantification of crop residue biomass on cultivated lands is essential for studies of carbon cycling of agroecosystems, soil-atmospheric carbon exchange and Earth systems modeling. Previous studies focus on estimating crop residue cover (CRC) while limited research exists on quantifying crop residue biomass. This study takes advantage of the high temporal resolution of the China Environmental Satellite (HJ-1) data and utilizes the band configuration features of HJ-1B data to establish spectral angle indices to estimate crop residue biomass. Angles formed at the NIRIRS vertex by the three vertices at R, NIRIRS, and SWIR (ANIRIRS) of HJ-1B can effectively indicate winter wheat residue biomass. A coefficient of determination (R2) of 0.811 was obtained between measured winter wheat residue biomass and ANIRIRS derived from simulated HJ-1B reflectance data. The ability of ANIRIRS for quantifying winter wheat residue biomass using HJ-1B satellite data was also validated and evaluated. Results indicate that ANIRIRS performed well in estimating winter wheat residue biomass with different residue treatments; the root mean square error (RMSE) between measured and estimated residue biomass was 0.038 kg/m2. ANIRIRS is a potential method for quantifying winter wheat residue biomass at a large scale due to wide swath width (350 km) and four-day revisit rate of the HJ-1 satellite. While ANIRIRS can adequately estimate winter wheat residue biomass at different residue moisture conditions, the feasibility of ANIRIRS for winter wheat residue biomass estimation at different fractional coverage of green vegetation and different environmental conditions (soil type, soil moisture content, and crop residue type) needs to be further explored.  相似文献   
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