Global sensitivity analysis of yield output from the water productivity model

This study includes a global sensitivity analysis of the water productivity model AquaCrop. The study rationale consisted in a comprehensive evaluation of the model and the formulation of guidelines for model simplification and efficient calibration. The global analysis comprehended a Morris screening followed by a variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) under diverse environmental conditions for maize, winter wheat and rice. The analysis involved twenty-two different climate-crop-soil-meteorology combinations. The main objectives were to distinguish the model's influential and non-influential parameters, and to examine the yield output sensitivity. For the AquaCrop model, a number of non-influential parameters could be identified. Making these parameters fixed would be a step towards model simplification. Also, a list of influential parameters was identified. Despite the dependence of parameter ranking on environmental conditions, guiding principles for priority parameters were formulated for calibration in diverse conditions, valuable to model users. For this model that focuses on modelling yield response to water, parameters describing crop responses to water stress were not often among those showing highest sensitivity. Instead, particular root and soil parameters, relevant in the determination of water availability, were influential under various conditions and merit attention during calibration. The considerations made in this study about sensitivity analysis method (Morris vs. EFAST), prior parameter ranges, target functions and ranking variation according to environmental conditions can be extrapolated to other conditions and models, if done with the necessary precaution.     

Latitudinal gradient of floristic condition among Great Lakes coastal wetlands

Coastal wetland vegetation along the Great Lakes differs strongly with latitude, but most studies of Great Lakes wetland condition have attempted to exclude the effect of latitude to discern anthropogenic effects on condition. We developed an alternative approach that takes advantage of the strong relationship between latitude and coastal wetland floristic condition. Latitude was significantly correlated with 13 of 37 environmental variables tested, including growing degree days, agriculture, atmospheric deposition, nonpoint-source pollution, and soil texture, which suggests that latitude is a good proxy for several environmental drivers of vegetation. Using data from 64 wetlands along the U.S. coast of Lakes Huron, Michigan, Erie, and Ontario, we developed linear regressions between latitude and two measures of floristic condition, the Floristic Quality Index (FQI, adj. r² = 0.437, p < 0.001) and the first axis scores from a non-metric multidimensional scaling of wetland plant cover (MDS1, adj. r² = 0.501, p < 0.001). Departures from the central tendency of these regression models represented wetlands of better or worse condition than expected for their latitude. This approach provides a means to identify wetlands worthy of preservation, to establish vegetation targets for wetland restoration, and to forecast changes in floristic quality associated with future climate change.     

雨季生产润滑油水分不合格原因探讨

水分是润滑油的一项重要指标。润滑油在雨季生产过程中,因连续降雨和环境湿度大,容易造成润滑油水分不合格,文章从人、机、料、法、环等方面进行分析,通过分析发现,基础油储存时间长、半罐调合生产是润滑油雨季生产水分不合格的主要原因,通过控制基础油库存、满罐调合及过程防护,可以减少雨季生产润滑油水分不合格,降低质量风险。     

数据挖掘与非正常日的负荷预测

提高非正常日的负荷预测精度是当前负荷预测工作的难点。文中提出了一种基于知识库的事先判别突变并做出适当处理的预测流程,介绍了利用数据挖掘的决策树技术建立知识库的方法,并给出了几种典型的非正常日修正模型。最后,通过对长时期负荷预测数据的统计分析,说明了新方法的有效性和实用性。     

五日生化需氧量(BOD_5)测定时防止氨氮干扰的方法探讨

生化处理后的水样富含硝化细菌,当氨氮含量较高时会对五日生化需氧量(BOD5)的测定产生干扰。该文对硝化抑制剂的加入做了对比研究,旨在找出适合再生水BOD5测定的方法。     

电离层参数的相似日短期预测方法

提出了时间序列频率特征参数相似日和时间序列时频双特征参数相似日的电离层参数(F2层临界频率)短期预测方法,利用中国9个电离层观测台站一个太阳活动周(1977~1987年)的F2层临界频率数据对提前1~24h预测的精度进行了测试。结果表明:相对于现有的一些短期预测方法,相似日的预测精度有明显改善,该方法简便、有效,具有实际工程应用价值。     

大兴安岭雷暴日数的时空分布特征

利用大兴安岭地区1980--2008年的雷暴观测资料,对大兴安岭地区雷暴天气的时空分布特征及初、终雷目的变化特征等进行了分析,结果表明：大兴安岭地区年雷暴日数的分布与测站地理位置及纬度有关,近年来年平均雷暴日数以加格达奇为最多,呼玛为最少;年平均雷暴日数的多少与雷暴期的长短无关。大兴安岭地区的雷暴表现出明显的季节性特征,即雷暴多生在夏季,春秋季次之,冬季没有雷暴产生,7月份为雷暴出现的高峰月。雷暴的初、终日出现日期与候平均气温有关。     

近61年武汉市降水变化特征及趋势

武汉市是我国暴雨灾害频发的城市之一,研究其降水量变化特征及趋势,对做好区域防灾、减灾工作具有重要意义。基于武汉市1951~2011年逐日降水资料,采用线性回归法、5年滑动均值法、累积距平法、Mann-Kendall法和R/S分析法,选取最大1d降水量(P_(1d))、连续最大3d降水量(P_(3d))、中雨日降水量(P_(10))、大雨日降水量(P_(25))、暴雨日降水量(P_(50))、中雨日数(D_(10))、大雨日数(D_(25))、暴雨日数(D_(50))和降水日数(D0.1)等指标,研究了武汉市降水的年际、季节和逐日变化特征及趋势。结果表明,武汉市降水经历了"丰-枯-丰"三个阶段,春夏两季降水偏多、秋冬两季降水偏少,四季降水分别以-7.4、8.7、-2.4、3.7mm/10a的速率呈线性变化;除P_(1d)、D_(0.1)呈线性减少变化外,中雨日、大雨日和暴雨日数存在同步放大趋势,这会加剧区域内干旱、洪涝的发生,并给区域水资源规划与管理工作带来一定的压力和挑战。研究成果可为武汉市水资源优化分配、防洪抗旱提供决策依据。     

基于特征提取相似日的ELM短期负荷预测研究

为解决短期电力负荷预测中预测精度差、计算时间长等问题,提出一种基于自组织特征映射网络进行特征提取相似日的极限学习机短期电力负荷预测方法。通过自组织特征映射网络找出与预测日同类型的历史数据作为训练样本;并采用预测能力强、计算时间短的ELM网络进行预测。以某市电力负荷数据进行仿真,并将上述方法与传统神经网络进行对比。仿真算例表明,基于特征提取相似日的ELM方法具有较高的预测精度,泛化性能好,且运算时间短。     

再生混凝土的抗冻性能研究

旨在研究未掺任何外加剂的再生混凝土的抗冻性能。即再生混凝土在硬化初期受到一次冻结对其质量的影响,用抗压强度来表征它的力学性能。同时研究经过在标准条件下养护几天后再受冻的再生混凝土的早期抗冻能力,并分析影响再生混凝土抗冻性能的原因。