深部盐岩蠕变特性研究

通过对湖北云应的盐岩和泥岩,以及江苏金坛盐岩的单轴、三轴蠕变试验结果的分析,研究了包括应力、围压等外在条件以及内部组成结构对盐岩蠕变特性的影响。发现盐岩无论在何种围压下,稳态蠕变率都随偏应力的增加而显著地增大;围压起到限制变形的作用,而随着围压增高,围压对稳态蠕变率的影响越来越小;晶粒越大和杂质含量越多,盐岩的蠕变属性越弱。盐岩的蠕变变形是应变硬化和回复效应等内部变形机制共同作用的结果,选用内应力作为内变量可用来描述这种内部微观结构的演化过程。对云应盐岩的多级加载蠕变试验数据进行拟合,确定了非线性蠕变本构方程中的参数,理论与试验结果的比较表明,两者吻合性较好。     

Land-Parcel Land-Use History as a Key to Site Selection for Documenting Soil Contamination Risk： a Case Study from Australian Suburbia

In that orcharding in early-to-mid twentieth century southeastern Australia involved use of certain heavy metal and As compounds in regular pest-control spray procedures, some interest attaches to the possibility that these landparcels are underlain by soils with above-background Cu, Pb and As levels. Interpreta- tion of Land-cover changes allowed land parcels previously occupied by orchards to be identified in the 1950s through time-series air-photos. A comparison of soil analysis results referring to soil samples from control sites, and from land parcels formerly occupied by orchardists, shows that contamination （above-background） levels of cations in the pesticides can be found in the top 6 cm of former orchard soils. It is clear that digital spatial data handling and culturally-informed air photo interpretation has a place in soil contamination studies, land-use planning （with particular reference to re-development） and in administration of public health.     

Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer

The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.     

中国大陆科学钻探主孔声发射法现今地应力状态的确定

对中国大陆科学钻探主孔的岩心进行了声发射测量,确定了301～1531m深度的最大主应力。并与钻孔崩落法(深度1269～1655m)测量结果进行了对比,结果表明,声发射测量所得测值基本上落在钻孔崩落法测值的趋势线上,两种方法所得结果一致,说明测量结果可信。测量结果表明科学钻探主孔地应力大小随深度增加,在浅部301m最大主应力为13.4MPa,在深部1655m为55.2MPa。随深度的增加率为0.0279MPa/m。最大主应力方向为N54°±3.3°E,且方向不随深度变化。     

Wave steepness retrieved from scatterometer data in a genetic algorithm

Wave steepness is an important characteristic of a high sea state, and is widely applied on wave propagations at ports, ships, offshore platforms, and CO2 circulation in the ocean. Obtaining wave steepness is a difficult task that depends heavily on theoretical research on wavelength distribution and direct observations. Development of remote-sensing techniques provides new opportunities to study wave steepness. At present, two formulas are proposed to estimate wave steepness from QuikSCAT and ERS-1/2 scatterometer data. We found that wave steepness retrieving is not affected by radar band, and polarization method, and that relationship of wave steepness with radar backscattering cross section is similar to that with wind. Therefore, we adopted and modified a genetic algorithm for relating wave steepness with radar backscattering cross section. Results show that the root-mean-square error of the wave steepness retrieved is 0.005 in two cases from ERS-1/2 scatterometer data and from QuikSCAT scatterometer data.     

江苏盐城滨海湿地净生态系统碳交换量模拟参数选择

滨海湿地净生态系统碳交换量受到多种环境因素的影响,在进行滨海湿地净碳交换量估算建模时,参数的选择至关重要,如何合理地选择输入参数不仅对于估算结果的精度有影响,同时也会影响预测模型的适用性。本研究使用了Pearson、Spearman、距离相关系数、最大互信息相关系数4种相关系数来计算各个环境因素与净碳交换量之间的相关性,基于相关系数来选择最佳的输入参数组合。利用实际测得的江苏盐城盐沼湿地数据,依次选择各个相关性中最高的8个参数组合,基于卷积神经网络对江苏盐城滨海湿地NEE进行建模,得到了4个预测模型,并使用均方根误差和平均绝对值误差来进行模型精度的验证。研究表明,使用基于最大互信息系数得到的参数组合进行滨海湿地NEE建模时模型的精度最好,误差最小;净光合有效辐射,净辐射,地表辐射与NEE在4个相关系数中都属于强相关,表明这一类辐射类参数对滨海湿地NEE的影响要大于其他参数;各参数与NEE之间的关系既包含线性关系也包含非线性关系,传统的单一线性分析手段无法完整准确地反应各个环境参数与NEE之间的响应关系;基于卷积神经网络的滨海湿地NEE预测模型在精度上要优于其它同类型模型,这表明使用该模型在进行NEE预测建模时具有很好的适用性。     

卤水浸泡后盐岩声发射特征试验研究

为了研究盐穴能源地下储库建造过程中,腔体围岩处在地温、卤水和地应力地质环境中盐岩的损伤演化特点,利用声发射技术分析盐岩受不同温度的饱和卤水作用后的单轴压缩损伤破坏过程。试验发现：在一定温度的饱和卤水中浸泡30 d后盐岩的单轴抗压强度和弹性模量有所降低,但降低的平均幅度很小;卤水对盐岩主要表现为溶蚀作用,而浸泡弱化作用非常小;单轴压缩过程中盐岩的应力-应变曲线与声发射-应变曲线具有较好的一致性,卤水浸泡后盐岩的累计声发射数随卤水的温度升高略有增加;卤水作用后盐岩试件的声发射率和累计数要小于无卤水作用盐岩;盐穴建造期盐岩受一定温度的卤水作用后盐岩的强度将出现一定弱化,但卤水也会促进损伤盐岩体的重结晶恢复,盐岩的这种特性有利于盐穴建造期安全和稳定。     

基于LBGK方法的粘性流体晃动问题大涡模拟

LBGK结合大涡紊流模型方法应用于粘性流体运动的数值模拟,并在LBGK方法中引入VOF概念,用于跟踪自由表面的运动.利用这种方法计算了贮液容器中粘性流体的自由晃动以及非线性激励下的一阶模态晃动,得到了侧壁上压强分布,并拟合了压力和弯距的估算公式.分析和实践表明,该方法对带自由表面不可压缩流体的数值模拟具有较高的精度.     

A comparative study of extensive machine learning models for predicting long-term monthly rainfall with an ensemble of climatic and meteorological predictors

Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions.     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.