Inexact rough-interval two-stage stochastic programming for conjunctive water allocation problems

An inexact rough-interval two-stage stochastic programming (IRTSP) method is developed for conjunctive water allocation problems. Rough intervals (RIs), as a particular case of rough sets, are introduced into the modeling framework to tackle dual-layer information provided by decision makers. Through embeding upper and lower approximation intervals, rough intervals are capable of reflecting complex parameters with the most reliable and possible variation ranges being identified. An interactive solution method is also derived. A conjunctive water-allocation system is then structured for characterizing the proposed model. Solutions indicate a detailed optimal allocation scheme with a rough-interval form; a total of [[1048.83, 2078.29]:[1482.26, 2020.60]] would be obtained under the pre-regulated inputs. Comparisons of the proposed model to a conventional and an interval two-stage stochastic programming model are also conducted. The results indicate that the optimal objective function values of TSP and ITSP always fall into the range of , while they are sometimes out of the range of ; the optimal solutions of decision variables also present this feature. This implies the reliability of IRTSP in handling conjunctive water allocation problems.     

Understanding the Ecology of Blue Elderberry to Inform Landscape Restoration in Semiarid River Corridors

Societal constraints often limit full process restoration in large river systems, making local rehabilitation activities valuable for regeneration of riparian vegetation. A target of much mitigation and restoration is the federally threatened Valley elderberry longhorn beetle and its sole host plant, blue elderberry, in upper riparian floodplain environments. However, blue elderberry ecology is not well understood and restoration attempts typically have low success rates. We determined broad-scale habitat characteristics of elderberry in altered systems and examined associated plant species composition in remnant habitat. We quantified vegetation community composition in 139 remnant riparian forest patches along the Sacramento River and elderberry stem diameters along this and four adjacent rivers. The greatest proportion of plots containing elderberry was located on higher and older floodplain surfaces and in riparian woodlands dominated by black walnut. Blue elderberry saplings and shrubs with stems <5.0 cm in diameter were rare, suggesting a lack of recruitment. A complex suite of vegetation was associated with blue elderberry, including several invasive species which are potentially outcompeting seedlings for light, water, or other resources. Such lack of recruitment places increased importance on horticultural restoration for the survival of an imperiled species. These findings further indicate a need to ascertain whether intervention is necessary to maintain functional and diverse riparian woodlands, and a need to monitor vegetative species composition over time, especially in relation to flow regulation.     

An Inexact Fuzzy-robust Two-stage Programming Model for Managing Sulfur Dioxide Abatement Under Uncertainty

In this study, an inexact fuzzy-robust two-stage programming (IFRTSP) method is developed for tackling multiple forms of uncertainties that can be expressed as discrete intervals, probabilistic distributions and/or fuzzy membership functions. The model can reflect economic penalties of corrective measures against any infeasibilities arising due to a particular realization of system uncertainties. Moreover, the fuzzy decision space can be delimited into a more robust one with the uncertainties being specified through dimensional enlargement of the original fuzzy constraints. A management problem in terms of regional air pollution control has been studied to illustrate the applicability of the proposed approach. Results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers identify desired pollution-abatement strategy with minimized system cost and maximized environmental efficiency.     

GENERATION OF DAILY PRECIPITATION OVER AN AREA1

ABSTRACT: A model was developed of the periodic-stochastic structure of daily precipitation over an area. The model is based ona multivariate normal distribution. The square roots of daily precipitation at a point were found to approximate a sample from a univariate normal distribution that had been truncated at zero. The zero daily precipitation amounts were considered negative amounts of unknown quantity. The multivariate normal distribution was used to describe the variation of daily precipitation over an area. The periodic fluctuations of the model parameters were described with Fourier series. The model was tested using data from two areas of different precipitation characteristics. Data generated with the model contained many of the statistical characteristics observed in the historical data.     

空气污染对中老年人认知能力的影响

利用中国健康与养老追踪调查(CHARLS)数据,采用两阶段最小二乘法评估了空气污染对我国中老年人认知能力的影响及其传导路径,并进一步分析了不同类型污染物的影响差异性.研究发现:空气污染与中老年人的认知能力显著负相关,且通过一系列稳健性检验表明研究结果具有稳健性;机制分析与异质性分析显示,空气污染通过影响个人的情绪和状态、运动、社交活动、健康和记忆力来间接影响其认知能力,且空气污染对年长者、女性、有不良健康行为以及社会经济地位较低人群的认知能力负面影响更大;进一步研究发现,PM_2.5、PM₁₀、SO₂、CO具有显著的认知功能折旧效应.本文聚焦于我国空气污染和人口老龄化问题,识别了空气污染对我国居民认知能力的潜在健康影响,这在一定程度上为国家健康环境治理和实现健康老龄化提供了现实依据和政策借鉴.     

基于随机前沿分析的中国城镇建设用地利用效率研究

建设用地高效利用是促进城镇高质量增长的有效方式之一。借助2009—2016年30个省级单元面板数据,构建了用于城镇建设用地效率测度的“一步法”随机前沿模型,并对效率水平与建设用地投入、污染水平等展开关联比较。结果表明:（1）非期望产出会导致城镇建设用地利用效率损失,研究期内其分别造成东、中、西部效率损失3.77%、7.74%、8.77%。（2）效率分布具有明显的区域非均衡性,东部总体水平最高,而西部最低;且在考虑非期望产出后,不同地区效率值会因污染排放程度的差异而呈现更大分异。（3）高投入、高产出并不一定带来高土地利用效率,较高的污染排放也会造成效率损失。研究结果有助于揭示未来建设用地效率改进的重点与方向。     

南昌市湖泊丰水期浮游细菌群落结构及影响因素

浮游细菌群落对城市湖泊中的营养元素循环及有机质分解发挥着重要作用.基于高通量测序技术,对南昌市湖泊浮游细菌群落结构的时间(4、6和8月)和城郊差异及其影响因素进行了研究.结果表明：(1)南昌湖泊浮游细菌优势类群为放线菌门(Actinobacteria, 41.60%)、变形菌门(Proteobacteria, 22.29%)、蓝藻菌门(Cyanobacteria, 16.21%)和拟杆菌门(Bacteroidota, 10.17%).(2)南昌湖泊细菌群落结构在4、6和8月间存在显著差异,但在城区湖泊与郊区湖泊间不存在显著差异;以Proteobacteria(4月>6月>8月)和Cyanobacteria(6月>8月>4月)为主的10种菌门的丰度在3个月份间存在显著差异;6月菌群结构的相似性会随地理距离的增加产生明显的减小趋势,4月和8月的减小趋势不明显.(3)在降水偏多的6月,湖泊非淡水细菌的占比显著高于4月和8月,城区湖泊与郊区湖泊的非淡水细菌占比没有显著差异.(4)确定性过程主导了湖泊细菌群落的构建,随机过程对湖泊菌群构建的贡献较低;水温是影响南昌湖泊细菌...     

基于wavelet-SVM的PM10浓度时序数据预测

太原是以煤炭为主要能源的重工业城市,PM_(10)(particulate matter)是太原市的主要大气污染物,因此研究其变化趋势,并给出污染物浓度预测结果,为相关部门进行大气污染防治,为突发污染事件应急提供理论支持是一项非常重要的工作.支持向量机(support vector machine,SVM)应用于PM_(10)污染物浓度时序数据预测时,表现出良好的泛化能力.在预测模型建立过程中通常选择历史数据作为学习模型的输入特征,然而这样的数据表示形式,结构单一,信息表达不完备,在很大程度上将影响预测模型的泛化能力.本文以山西省太原市城区4个监测站点的PM_(10)日浓度数据为研究数据,通过小波变换(wavelet transform)将一维输入数据转化为由低频信息和高频信息构成的高维数据,并以该数据为输入数据建立wavelet-SVM预测模型.结果表明,相较于传统SVM模型预测,wavelet-SVM模型预测结果具有更高的精度,尤其能更加准确捕捉到PM_(10)浓度突变点,为大气污染预警提供有效信息支持,并且wavelet-SVM模型对于PM_(10)浓度时序数据变化趋势的预测精度有明显提升,能更好地预测PM_(10)浓度变化趋势,揭示PM_(10)浓度时序数据内在规律.     

Human Adaptation to Work in Two Different Climates

The processes of acclimation to hot-dry and to warm-humid climates were studied using two approaches: a quantitative analysis of literature data and an experimental study in the laboratory concerning the physiological parameters of heart rate, rectal temperature, sweat loss, and subjective assessment.

Analysis o f literature data: Data from 62 experiments with a total of 813 participants were pooled and recalculated. The experiments ranged from 6 to 24 days, air temperatures from 30.4 to 50.0°C, water vapor pressures from 1.5 to 6.5 kPa, and wet bulb globe temperatures (WBGT) from 27.4 to 38.6°C.

Laboratory studies: In the laboratory, 8 participants were acclimated during 15 consecutive days to a hot-dry climate and to a warm-humid climate, which were equivalent in terms of the WBGT (33.5 and 33.6°C, respectively). The participants walked four times for 25 min on a treadmill at a speed of 4 km/h. The hot-dry climate caused somewhat greater strain than the warm-humid condition. In the course of acclimation to the hot-dry climate, heart rate and rectal temperature started at higher levels, decreased slightly steeper but remained on a higher level throughout. Nevertheless, the differences between both thermal conditions were small, and both physiologic functions reached the point of acclimation almost at the same time under warm-humid and under hot-dry exposure. Sweat loss, which is not regarded as a valid predictor for acclimation, was considerably higher but increased less in the hot-dry than in the warm-humid climate.     

Estimation of Daily Streamflow of Southeastern Coastal Plain Watersheds by Combining Estimated Magnitude and Sequence

Commonly used methods to predict streamflow at ungauged watersheds implicitly predict streamflow magnitude and temporal sequence concurrently. An alternative approach that has not been fully explored is the conceptualization of streamflow as a composite of two separable components of magnitude and sequence, where each component is estimated separately and then combined. Magnitude is modeled using the flow duration curve (FDC), whereas sequence is modeled by transferring streamflow sequence of gauged watershed(s). This study tests the applicability of the approach on watersheds ranging in size from about 25‐7,226 km² in Southeastern Coastal Plain (U.S.) with substantial surface storage of wetlands. A 19‐point regionalized FDC is developed to estimate streamflow magnitude using the three most selected variables (drainage area, hydrologic soil index, and maximum 24‐h precipitation with a recurrence interval of 100 years) by a greedy‐heuristic search process. The results of validation on four watersheds (Trent River, North Carolina: 02092500; Satilla River, Georgia: 02226500; Black River, South Carolina: 02136000; and Coosawhatchie River, South Carolina: 02176500) yielded Nash‐Sutcliffe efficiency values of 0.86‐0.98 for the predicted magnitude and 0.09‐0.84 for the predicted daily streamflow over a simulation period of 1960‐2010. The prediction accuracy of the method on two headwater watersheds at Santee Experimental Forest in coastal South Carolina was weak, but comparable to simulations by MIKE‐SHE.