Geoelectric section of the lithosphere in the central part of the Middle Amur sedimentary basin (Far East) based on the magnetotelluric sounding data

Results of magnetotelluric soundings (MTS) along the profile plotted across the strike of the Middle Amur sedimentary basin are considered. The results of field studies are analyzed and different factors influencing the behavior of sounding curves are discussed. A reference curve and reference geoelectric section selected on the basis of the previous MTS works within the Middle Amur depression allowed us to compensate for the influence of different geoelectric inhomogeneities and construct a starting model for two-dimensional mathematical modeling based on the field data. As a result, a geoelectric model of the lithosphere structure in the Middle Amur sedimentary basin across its strike was compiled.     

Geological structure, composition of ores and age of the Bamsk gold deposit, Amur region, Russia

The Bamsk gold-ore deposit is located in the Amur region, the Far East of Russia. It is confined to the Early Cretaceous volcanicoplutonic uplift of central type, located in the Stanov folded-clumpy Pre-Cambrian system. The deposit is presented by a series of gold-bearing quartz and carbonate-quartz vein-stringer zones. They are confined to the super-intrusive zone of the Nevachansk subvolcanic intrusion of sienite-porphyric composition. The mineralization is being controlled by zone of fractures developed in the autochthone of the Bamsk fault. Quartz, carbonates and sericite prevail in the composition of ores. The quantity of ore minerals doesn‘t exceed 1% ～ 5%. Pyrite, chalcopyrite, galena and native gold are widely spread, Sheelite, gold and silver tellurides, sulphobismuthites, acanthite, sphalerite and cinnabar are less developed. Four stages of mineralization have been distinguished. Gold-sulphide-sulphosalt ore with tellurides of gold and silver is productive for gold. The following set of elements is typomorphic for the ores of the deposit: Au, Ag, Cu, Bi, Mo, Pb and Sb (W1, Pb1, Mo) -Cu- (Ag, Bi, Sb, Mn, W2,, Pb2) form the vertical series of zoning. Rocks, enclosing the mineralization are exposed to the processes of listvenitization-beresitization. The processes of gumbeization and argillization are less manifested. The age of the gold mineralization, determined by Rb-Sr method on ore-accompanying minerals, is 130.6 Ma.     

甘肃河西干旱区温室葡萄对地表覆盖的响应

试验了温室葡萄超氧化物气化酶（SOD）活性、过氧化氢酶（CAT）活性、游离脯氨酸（Pro）含量、丙二醛（MDA）含量和果粒生长对地表覆盖的响应。结果表明：整个生育期内,砂土覆盖、秸秆覆盖、秸秆+白地膜覆盖及秸秆+黑地膜覆盖都对0~40 cm土层土壤有显著的保水作用,其中秸秆+黑地膜保水性能最强（土壤含水量比无覆盖的提高14.53%,P<0.05）,且各覆盖方式的保水能力随着土层的加深而增强。秸秆+白地膜覆盖下葡萄细胞的抗氧化酶活性最高。砂土覆盖极显著（P<0.01）提高果粒内Pro含量（约增加42.40%）。砂土覆盖后葡萄果粒粒径最大,秸秆+地膜覆盖、秸秆覆盖下的果粒粒径均小于无覆盖的粒径。秸秆覆盖能够提高土壤水分含量,抑制果粒的增长。砂土覆盖可以作为温室葡萄适宜覆盖方式。     

山葡萄品质气象预测预报模型

山葡萄的品质决定着葡萄酒的质量,葡萄浆果糖度决定着葡萄品质。葡萄成熟过程中浆果含糖量和含酸量是相互制约的,含糖量主要呈对数略显“S”型变化,含酸量呈指数曲线型变化。将成熟期葡萄浆果含糖量作为葡萄品质的评价指标,利用通化产区19952016年成熟期山葡萄浆果含糖量的实测数据与气象条件进行相关分析,得出山葡萄品质与5月9月上旬积温、7月8月日照时数、5月9月上旬水热系数、8月9月上旬积温关系密切,相关关系均通过了α为0.05或0.01的显著性检验。利用多元回归统计方法建立了山葡萄品质气象预测预报模型,模型的判定系数R^2为0.815,通过了α=0.01的显著性检验。模型的拟合检验平均误差百分率为3.91%。利用2017年、2018年资料对模型进行试报检验,误差百分率分别为1.59%和3.79%。模型具有较高的准确率,能够满足通化产区山葡萄栽培对气象预报和服务的需求。     

气象条件与酿酒葡萄糖分积累的关系

气象条件是影响葡萄糖分积累的主要环境因素之一.利用酿酒葡萄(赤霞珠)糖分观测数据和相应气象数据研究气象因子对酿酒葡萄糖分积累的影响发现,在酿酒葡萄着色至成熟期,对酿酒葡萄糖分积累影响较大的气象因子是日平均气温、最高气温、日照时数和温湿比.最适于糖分积累的平均气温、最高气温、日照时数和温湿比分别是24.0℃、29.3℃、6.4 h和0.35左右,在小于上述极值点的范围内,糖分日积累量随各因子(值)的增加而增加}在大于上述极值点的范围内,糖分日积累量随各因子(值)的增加而减少.     

Spatial-temporal variability of snow cover over the Amur River Basin inferred from MODIS daily snow products in recent decades

MODIS snow products MOD10A1\MYD10A1 provided us a unique chance to investigate snow cover as well as its spatial-temporal variability in response to global changes from regional and global perspectives. By means of MODIS snow products MOD10A1\MYD10A1 derived from an extensive area of the Amur River Basin, mainly located in the Northeast part of China, some part in far east area of the former USSR and a minor part in Republic of Mongolia, the reproduced snow datasets after removal of cloud effects covering the whole watershed of the Amur River Basin were generated by using 6 different cloud-effect-removing algorithms. The accuracy of the reproduced snow products was evaluated with the time series of snow depth data observed from 2002 to 2010 within the Chinese part of the basin, and the results suggested that the accuracies for the reproduced monthly mean snow depth datasets derived from 6 different cloud-effect-removing algorithms varied from 82% to 96%, the snow classification accuracies (the harmonic mean of Recall and Precision) was higher than 80%, close to the accuracy of the original snow product under clear sky conditions when snow cover was stably accumulated. By using the reproduced snow product dataset with the best validated cloud-effect-removing algorithm newly proposed, spatial-temporal variability of snow coverage fraction (SCF), the date when snow cover started to accumulate (SCS) as well as the date when being melted off (SCM) in the Amur River Basin from 2002 to 2016 were investigated. The results indicated that the SCF characterized the significant spatial heterogeneity tended to be higher towards East and North but lower toward West and South over the Amur River Basin. The inter-annual variations of SCF showed an insignificant increase in general with slight fluctuations in majority part of the basin. Both SCS and SCM tended to be slightly linear varied and the inter-annual differences were obvious. In addition, a clear decreasing trend in snow cover is observed in the region. Trend analysis (at 10% significance level) showed that 71% of areas between 2,000 and 2,380 m a.s.l. experienced a reduction in duration and coverage of annual snow cover. Moreover, a severe snow cover reduction during recent years with sharp fluctuations was investigated. Overall spatial-temporal variability of Both SCS and SCM tended to coincide with that of SCF over the basin in general.     

Influences of forest on MODIS snow cover mapping and snow variations in the Amur River basin in Northeast Asia during 2000–2014

The study applies the improved cloud‐free moderate resolution imaging spectral radiometer daily snow cover product (MODMYD_MC) to investigate the snow cover variations from snow hydrologic year (HY) HY2000 to HY2013 in the Amur River basin (ARB), Northeast Asia. The fractions of forest cover were 38%, 63%, and 47% in 2009 in China (the southern ARB), Russia (the northern ARB), and ARB, respectively. Validation results show that MODMYD_MC has a snow agreement of 88% against in situ snow depth (SD) observations (SD ≥ 4 cm). The agreement is about 10% lower at the forested stations than at the nonforested stations. Snow cover durations (SCDs) from MODMYD_MC are 20 days shorter than ground observations (SD ≥ 1 cm) at the forested stations, whereas they are just 8 days shorter than ground observations (SD ≥ 1 cm) at the nonforested stations. Annual mean SCDs from MODMYD_MC in the forested areas are 21 days shorter than those in the nearby farmland in the Sanjiang Plain. This indicates forest has a complex influence on the snow accumulation and melting processes and even on optical satellite snow cover mapping. Meanwhile, SCD and mean snow cover are negatively correlated with air temperature in ARB, especially in the snow melting season, when mean air temperature in March and April can explain 86% and 74% of the mean snow cover variations in China ARB and Russia ARB, respectively. From 1961 to 2015, the annual mean air temperature presented an increased trend by 0.33 °C/decade in both China ARB and Russia ARB, whereas it had a decrease trend from HY2000 to HY2013. The decrease of air temperature led to an increase of snow cover, which is different from the global decrease trend of snow cover variations. SCD and snow cover had larger increase rates in China ARB than in Russia ARB, and they were larger in the forested areas than in the nearby farmland in the Sanjiang Plain.     

影响芜湖葡萄商品果率关键气候因子特征及预测

基于1994—2014年研究区葡萄的逐年商品果率数据,1965—2014年芜湖市逐月的气象数据和1981年7月至2014年6月国家气候中心的逐月88项新大气环流指数、26项海温指数,使用相关性分析、线性趋势、MannKendall和多元逐步回归分析,对影响葡萄商品果率的关键气候因子进行遴选,并在此基础上对遴选因子的近50年变化特征和短期气候预测进行了分析与研究。结果表明:影响葡萄商品果率的关键气候因子有7、8月的平均气温(T_7,T_8)、最高气温(T_(max7),T_(max8))、最低气温(T_(min7),T_(min8))、相对湿度(R_(H7),R_(H8))、日照时数(S_7,S_8),以及8月的平均气温日较差(ΔT_8),近50年T7、T_(max7)和T_(min7)显著升高,RH7、ΔT8和S8显著下降,其中T7、T_(max7)、ΔT_8的变化以渐变为主,而T_(min7)、R_(H7)、ΔT_8则发生过突变。这些关键气候因子与前期1年内的多项大气环流指数和海温指数显著相关,并遴选其中关键指数作为预测芜湖市7、8月葡萄商品果率关键气候因子的短期气候预测指标,计算出气候因子的预测方程,以期为葡萄种植能够有效应对气候影响、保证商品果率提供帮助。     

河西酿酒葡萄生育模型及气象条件分析

分析了河西走廊酿酒葡萄果径生长和含糖量累积规律。结果发现：果粒生长动态呈抛物线型，有两个明显的生长高峰期。生长关键期出现在7月上旬～8月上旬，生长率占总生长率的64％～78％；含糖量累积遵循“S”型生长函数。糖份积累关键期出现在8月中旬中期至下旬，这一时期含糖量累积最快，日累积糖量在0．48％～0．84％，净累积量占累积总量的73％～77％；影响糖份累积的关键气象因子主要是光温积和气温日较差。日照时间长，气温高，温差大，糖份积累快，含糖量高。建立了葡萄糖份累积气候模型，以此为依据，计算了河西不同气候区含糖量地理分布，为葡萄基地建设和选择不同葡萄品种提供了依据。     

葡萄微肥"双增灵"优质丰产试验

在砀山酥梨微肥"酥梨宝"优质增产试验的基础上,通过对"酥梨宝"微肥配方的适当调整,重新配制出葡萄微肥"双增灵",在我省著名的葡萄产地萧县龙山和淮北市大庄两地,同时进行酿酒和鲜食品种的优质丰产试验.叶面肥试验表明:鲜食品种巨峰可溶性固形物平均增加1.97%,增幅达15%,总糖平均增加0.78%,增幅6%,维生素C平均增加1.259mg/100g,增幅达18%;酿酒品种白羽总糖平均增加0.59%,增幅5%,维生素C平均增加0.33mg/100g,增幅5%,产量平均提高5.07kg/株,增幅高达26.5%.同时,试验的葡萄果实中,对人体十分有益的硒(4～24倍)、锌(约1倍)元素含量也有了大幅度的提高.