Precipitation forecasting by large-scale climate indices and machine learning techniques

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.     

青土湖干涸湖底2种典型固沙植物群落土壤粒径分布分形特征与养分关系研究

以石羊河流域下游青土湖干涸湖底人工梭梭林和白刺灌丛沙包土壤为研究对象，通过分析2种植物群落5种立地条件土壤粒径分布和分形特征及其与土壤养分的关系，揭示了湖底2种典型植物群落土壤粒度的分布特征。结果表明:1）研究区固沙植被0~10 cm土壤颗粒以细砂粒为主，没有粗砂粒，其中白刺灌丛沙包表层极细砂含量、土壤颗粒物分形维数较梭梭林和对照区高。2）土壤颗粒分形维数与各粒级颗粒百分含量的关系差异较大，分形维数与黏粒、极细砂含量呈显著正相关，与细砂、中砂含量呈显著负相关，但是与粉粒含量关系不显著。土壤颗粒分形维数越大，土壤所含的细粒物质越多。3）土壤分形维数D值、黏粒、粉粒含量与有机质（SOM）、全N（TN）呈正相关性，土壤颗粒物的分形维数越大、土壤黏粒、粉粒含量越高，则土壤有机质、全N含量越高。综合分析，固定白刺灌丛表层土壤沙化程度相对较低，其他类型风蚀严重，因此，应积极采取生物措施和工程措施开展生态修复防治风蚀和盐尘暴的发生。     

单叶刺槐半同胞子代叶片的滞尘能力及叶表SEM特征分析

以单叶刺槐母本(A1-1)及6个叶形产生明显变异的半同胞子代无性系(A20-5、B24-3、C24-2、B23-1、C24-1、C23-1)新鲜叶片为材料,测定各样本的单位叶面积总颗粒物滞留量、颗粒物粒径分析及叶表微观结构SEM特征,通过相关性分析,筛选与滞尘能力相关的叶形及SEM指标,运用隶属函数法,依据各样本滞尘指标的隶属度均值对滞尘能力进行综合评价。结果表明:子代B23-1对空气中总颗粒物的滞留能力最强,C24-1对PM2.5的滞留能力最强,A20-5对PM2.5-10及PM>10的滞留能力最强;部分叶形及SEM特征指标与滞尘指标之间存在显著相关性;综合评价滞尘能力,全部样本可分为4类,第Ⅰ类为B23-1,滞尘能力强;第Ⅱ类为C24-1,滞尘能力较强;第Ⅲ类包括母本、A20-5、C23-1、C24-2,滞尘能力中等;第Ⅳ类为B24-3,滞尘能力相对较差。     

不同粒度猫尾草对羔羊体外发酵特性和微生物数量的影响

通过Rusitec-s体外发酵系统研究不同粒度猫尾草对羔羊体外发酵参数与微生物数量的影响,选取6种不同粒度(1.00、2.36、3.35、4.75、8.00和12.50 mm)的猫尾草作为试验饲粮的纤维来源,按照猫尾草的粒度将试验分为6个处理组,每个处理4个重复,利用Rusitec-s型人工瘤胃模拟装置进行48 h体外发酵,测定养分降解率、发酵参数及发酵液中6种微生物菌群的拷贝数。结果表明：与其他处理组相比,2.36 mm组显著提高了体外中性洗涤纤维降解率(IVNDFD)、丁酸、异丁酸、戊酸、异戊酸摩尔比和溶纤维丁酸弧菌(B. f)数量(P<0.05),且显著降低总产甲烷菌(TMe)数量(P<0.05)。总菌(TB)与氨态氮(NH3-N)浓度、乙酸摩尔比呈正相关(R²=0.84,P=0.038;R²=0.88,P=0.021);B. f数量与丙酸摩尔比呈正相关(R²=0.82,P=0.045),且与pH呈负相关(R²=-0.98,P=0.001);TMe数量与体外粗蛋白质降解率(IVCP...     

沙漠藻固沙结皮的研究与问题探讨

本文综合分析了沙漠藻结皮研究的现状,并结合自己的研究,探讨了沙漠藻固沙结皮的形成与植被发育的关系、沙漠藻结皮人工接种效果,提出了藻沙粒结皮是沙漠藻结皮的早期形式,探讨了进一步研究沙漠藻固沙结皮的关键技术问题。     

小叶锦鸡儿灌丛土壤肥力变化的研究

研究了内蒙古风蚀沙化区退化草原植被恢复或重建过程中灌丛对养分的聚集和土壤肥力的保护作用,结果表明灌丛大小和灌丛不同土层养分含量没有明显的变化趋势,灌丛内0~5 cm土层的养分含量高于相应的对照样地,5~20 cm土层有机质和速效氮含量高于相应的对照,灌丛土壤颗粒含量和本地区土壤本底颗粒组成有密切的关系,和对照区相比,短期内没有显著增加土壤的细粒成分,但灌丛在减少风蚀方面具有一定的作用。     

原料表面碱液处理对稻草碎料板力学性能的影响

在实验室条件下探索了稻草原料表面碱液处理对稻草碎料板力学性能的影响.试验表明,处理后的稻草碎料板的内结合强度比处理前有大幅度提高,弯曲弹性模量和静曲强度比处理前则有所下降,但都达到了相关的国家标准;2h吸水厚度膨胀率升高,超过国家标准.因此稻草表面碱液处理提高了稻草原料表面润湿性和胶合强度,但对稻草碎料板的力学性能有影响.     

提高刨花板尺寸稳定性的研究——刨花预处理和刨花板的后期热处理

以速生意大利杨为材料,对刨花进行预处理后制成脲醛胶刨花板,用未处理刨花制成酚醛胶刨花扳,并进行后期热处理,分别测试它们的尺寸稳定性,结果表明,两种方法都能较为有效地提高刨花板的尺寸稳定性,具可行性,通过合理选择适宜的预处理和后期处理的时间,可以使刨花板的性能达到预期要求。