A simple approach to modeling microbial biomass in the rhizosphere

Microorganisms make an important contribution to the degradation of contaminants in bioremediation as well as in phytoremediation. An accurate estimation of microbial concentrations in the soil would be valuable in predicting contaminant dissipation during various bioremediation processes. A simple modeling approach to quantify the microbial biomass in the rhizosphere was developed in this study. Experiments were conducted using field column lysimeters planted with Eastern gamagrass. The microbial biomass concentrations from the rhizosphere soil, bulk soil, and unplanted soil were monitored for six months using an incubation–fumigation method. The proposed model was applied to the field microbial biomass data and good correlation between simulated and experimental data was achieved. The results indicate that plants increase microbial concentrations in the soil by providing root exudates as growth substrates for microorganisms. Since plant roots are initially small and do not produce large quantities of exudates when first seeded, the addition of exogenous substrates may be needed to increase initial microbial concentrations at the start of phytoremediation projects.     

Assessing the relative impacts of the factors affecting MIS adoption process

Micro-irrigation systems (MIS) have been at the forefront of policy-making and social research in exploring determinants that could potentially impact the adoption of MIS technologies in the field to fulfil the basic aim of enhanced agricultural productivity and enriched nutritional quality of the produce with optimal adoption of natural resources. Therefore, this study was undertaken to determine why MIS technologies have not been adopted to the extent anticipated, so that suitable policy schemes, promotional schemes and socio-technical frameworks could be formulated for their enhanced adoption to enhance the socio-economic status of the farming community in the Dahod district of Gujarat State, India. A study of 350 non-MIS (NMIS) and 350 MIS farmers was conducted to identify factors affecting the MIS adoption process. The logit model was fitted using XLSTAT software (XLSTAT 2014.1.04) to the explanatory variables (determinants) of the MIS adoption process. Type III analysis and ANOVA were conducted to test the relative significance of the explanatory variables adopted. It was found that total income had the highest weight (or beta coefficient, i.e. 0.625) followed by total land area (0.546), motor horsepower (0.499), dependency ratio (0.397), and education (0.295) and age of household head (0.207). Furthermore, to assess the efficacy of the logit model, the ROC curve was also developed and the AUC was found to be 0.881, and therefore the model was considered to discriminate well in identifying the factors affecting the MIS adoption process. The study found that higher total income and education level increase the likelihood of MIS adoption and agricultural water management, and therefore special training programmes on installation, as well as repair and maintenance, of MIS systems and agricultural water management can be planned at the institutional/organisation level. The total cultivable area is also one of the important determinants in MIS adoption, and therefore the adoption of MIS schemes should not be restricted to large farmers only, but rather should be extended to both small and marginal farmers.     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

宁波市大气可吸入颗粒物PM1o和PM2.5的源解析研究

在宁波市布设4个代表性点位,于2010年春季、夏季和冬季进行大气PM10和PM2.s的采样,同时采集了多种颗粒物源样品,建立了PM10、PM2.5和源样品的化学成分谱.采用化学质量平衡模型(CMB)对宁波市PM10、PM2.5进行源解析.结果表明,城市扬尘、煤烟尘、机动车尾气尘是宁波市PM10、PM2.5的3大污染源,...     

暴雨泥石流预报程式

论述了暴雨泥石流预报的４个基本原理,即现象可预报性原理、成困分类组合原理、判别因素简化原理和预报决策依据原理。对泥石流时间预报模型作了分类,提出了通过泥石流活动周期与降水量周期叠加,建立泥石流活动性的长期趋势预测模型;通过泥石流活动年数频次与降水量丰欠等级频次组合,建立泥石流活动年份频次的态势预测模型;根据月或旬雨量确定泥石流发生的阈值关系,建立年内月或旬泥石流发生频次的中期预报模型;由短期天气预     

阵性泥石流运动与堆积的欧拉─拉格朗日模型──Ⅰ.理论

自然界中的泥石流具有突发性和非恒定性的特点。为了模拟典型泥石流现象,在流团模型的 基础上,进一步完善了基于欧拉─拉格朗日（Ｅ—Ｌ）观点的ＰＩＣ（Ｐａｒｃｅｌ　Ｉｎ　Ｃｅｌｌ）算法,细化了流元结 构,建立了能够模拟典型阵性泥石流发生、运动和堆积的准结构两相流模型。求解该模型不仅可以 模拟泥石流运动过程,而且可以对泥石流的堆积过程、停积形态、冲刷特征及泥石流中多组分颗粒 的分选特征进行定量描述。     

MR阻尼器的简化参数模型及其应用

MR阻尼器应用于控制风振、地震等引起的随机振动时需用参数化表达式来描述MR阻尼器简化的力学模型 ,从而更好地揭示MR阻尼器的减振机理。本文采用偏最小二乘法误差估计、Chebyshev多项式拟合建立了MR阻尼器简化模型的参数化表达式 ,并应用于斜拉索振动控制中 ,为合理选择MR阻尼器提供了便捷、可靠的手段     

陕西省农业旱灾系统及农业旱灾灾情模型研究

为试图解决当前有关干旱（旱灾）指标的片面性,本文提出了农业旱灾系统（ＡＤＳ）,并设计了描述农业旱灾灾情的模型：Ｅ＝ｋ＊Ｍ＊Ｈ＊Ａ。农业旱灾系统由气象干旱（Ｍ）、水利抗旱（Ｈ）、农业承旱（Ａ）及农业旱灾灾情（Ｅ）等四个要素组成。每一要素均由若干区域性指标进行刻划。在分析陕西省农业旱灾特点的同时,建立了陕西省农业旱灾系统的框架,并利用各种资料分析了陕西省农业旱灾灾情。分析结果表明,由该模型计算的陕西省各县级单位的农业旱灾灾情和几十年来的实际资料是相吻合的,模型是可靠的。而且,通过模型和实际情况的对比,能够为研究农业旱灾灾情形成机制提供更好的佐证。     

滑坡变形趋势分析

将自回归滑动平均模型引入滑坡变形分析,同时考虑了坡体变形趋势性和波动性对未来变形的影响,使得所建模型能更全面地反映坡体变形的动态。