ARMA order model detection using minimum of Kurtosis: application on seismic data

The objective of this study is to find the order and coefficients of non-low-phase causal filters for ARMA (auto regressive moving average) filter model, using the Kurtosis minimization criterion. This method is based on the Kurtosis calculation of the treated sample at the input level and its identification at the output of the ARMA model. For this purpose, the order and coefficients of the AR (auto regressive) part are identified using the Yule-Walker algorithm at order two and then extended to order four. To obtain the MA (moving average) part, the AR components are calculated at first from the ARMA filter by deconvolution. Then, spectrally equivalent and minimum phase (SEMP) MA filter is identified using the Durbin algorithm at second and fourth order. Finally, the correct filter is found when the Kurtosis value of the output ARMA filter reconstituted is the closest to the Kurtosis of introduced signal. The proposed method is then tested on simulated processes and applied to real seismic data to perform blind deconvolution and obtain the reflectivity coefficients of subsoil studied.     

ENSO and IOD analysis on the occurrence of floods in Pakistan

Different techniques have been used to discuss the existence of significant relation between the El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Various studies present their interaction and influence on the natural disasters (i.e. drought, flood, etc.) over large parts of the globe. This study uses a Markov chain method to investigate the relation between the ENSO and IOD for the period of 62 years (1950–2011) and aggregates their influence on the occurrence of floods in Pakistan. Both data sets show similarities in the formation of transition matrices and expected number of visits from one state to another. The strong values of 2-dimensional correlation and high self-communication of the transition states confirm the existence of a possible relation between ENSO and IOD data. Moreover, significant values of dependency and stationary test endorse the applicability of the Markov chain analyses. The independent analysis shows that strong events of both data sets are co-occurred in the same flood years. During the study period maximum number of floods was observed during summer monsoon season. However, further analysis shows that after 1970, Pakistan observed the highest percentage of floods occurred per year during El Nino, Non-ENSO and positive IOD years. These observations and results demonstrate that climate variability especially ENSO and IOD should be incorporated into disaster risk analyses and policies in Pakistan.     

A micro–macro investigation of the capillary strengthening effect in wet granular materials

Wet granular materials are three-dimensionally simulated by the discrete element method with water bridges incorporated between particles. The water bridges are simplified as toroidal shapes, and the matric suction is constantly maintained in the material. A comparison with experimental tests in the literature indicates that the toroidal shape approximation may be one of the best choices with high practicability and decent accuracy. Mechanical behaviours of wet granular materials are studied by triaxial tests. Effects of particle size distributions and void ratios are investigated systematically in this study. The hydraulic limit of the pendular state is also discussed. It gives the capillary cohesion function which is not only determined by the degree of saturation but also positively correlated to relative density and particle size polydispersity and inversely proportional to mean particle size. Furthermore, the capillary strengthening effect is also analysed microscopically in aid of the Stress–Force–Fabric relationship, mainly in fabric anisotropy, coordination number and stress transmission pattern, which revealed the micro-mechanisms of the additional effective stress induced by capillary effect.     

陕西地洞河高分辨率石笋记录的DO18季风增强事件

千年尺度事件的结构特征和区域响应是理解和认识冰期气候变化及动力机制的关键。本文基于陕西汉中宁强县地洞河一支长417 mm石笋DDH1的11个U-Th年代和417个氧同位素（δ¹⁸O）数据,重建了末次冰期（64.8~33.2 ka B.P.）亚洲季风演化历史。石笋δ¹⁸O记录在64.7±0.2 ka B.P.和59.3±0.1 ka B.P.快速负偏,分别指示了DO18事件的开始和H6事件的结束。在DO18事件结束过程,石笋δ¹⁸O记录在64.0~60.4 ka B.P.持续正偏,振幅达2.9 ‰,反应季风逐渐减弱,但未出现明显转型阶段。其总体形态与大西洋Cariaco盆地岩芯反射率、南极冰芯的记录较为一致,但是不同于格陵兰冰芯的记录。因地洞河所处青藏高原、秦岭叠加影响的区域,纬度和地形的双重影响使得其石笋δ¹⁸O记录较其他地区偏负,振荡幅度更大。因地形阻挡了高纬信号,使得低纬甚至南半球的信号突现出来,ITCZ的移动、南半球温度和水汽潜热的释放作用在这一区域尤为显著。

     

Hydraulic Conductivity Tests for Evaluating Compatibility of Lateritic Soil—Fly Ash Mixtures with Municipal Waste Leachate

Long term competent performance of liner systems is a critical issue in the design and construction of waste repositories due to adverse interactions associated with leachate generated by wastes. This study was conducted to verify the efficacy of fly ash stabilization in enhancing compatibility between lateritic soil and municipal waste leachate. Applications investigated include soil mixtures containing 0, 5, 10, 15, and 20% fly ash compacted at approximately 2% wet of optimum moisture content with modified proctor energy. Baseline hydraulic conductivity was first established at every level of fly ash content by permeating soil mixtures with tap water before permeation with leachate in a compaction mould permeameter using the falling head test method. Results show that the trend in hydraulic conductivity of specimen containing 0% fly ash was characterized by a gradual but erratic decrease which may suggests partial entry of the leachate cations into the double layer. Conversely, specimens containing fly ash showed a general trend consisting of an initial drop in k (up to an order of magnitude) that was followed by slight decrease sustained until k stabilized and later terminated. Above 10% fly ash content, the relatively high values of k observed was not connected with the reactivity of the soil mixtures with leachate, rather it may be attributed to excessive fly ash content that altered their textural and hydraulic properties. The result of this study is potentially significant in the assessment of fly ash as a compatibility enhancing agent which can be admixed in barrier materials that are susceptible to adverse reactions with the liquid to be contained.     

Long-Term Changes in the Extreme Significant Wave Heights on the Western North Pacific: Impacts of Tropical Cyclone Activity and ENSO

Seasonal extreme wave statistics were reproduced by using the 25-km-grid global wave model of WAVEWATCH-III. The results showed that the simulated wave dataset for the present climate (1979-2009) was similar to Climate Forecast System Reanalysis (CFSR) wave data. Statistics such as the root mean squared error (RMSE) and correlation coefficient (CC) over the western North Pacific (WNP) basin were 0.5 m and 0.69 over the analysis domain. The largest trends and standard deviation were around the southern coast of Japan and western edge of the WNP. Linear regression analysis was employed to identify the relationship between the leading principal components (PCs) of significant wave heights (SWHs) in the peak season of July to September and sea surface temperature (SST) anomalies in the equatorial Pacific. The results indicated that the inter-annual variability of SWH can be associated with the El Niño-Southern Oscillation in the peak season. The CC between the first PC of the SWH and anomalies in the Nino 3.4 SST index was also significant at a 99% confidence level. Significant variations in the SWH are affected by tropical cyclones (TCs) caused by increased SST anomalies. The genesis and development of simulated TCs can be important to the variation in SWHs for the WNP in the peak season. Therefore, we can project the variability of SWHs through TC activity based on changes in SST conditions for the equatorial Pacific in the future.     

The formation of wind curl in the marine atmosphere boundary layer over the East China Sea Kuroshio in spring

Various data are used to investigate the characteristics of the surface wind field and rainfall on the East China Sea Kuroshio (ESK) in March and April, 2011. In March, the wind speed maximum shows over the ESK front (ESKF) in the 10 meter wind field, which agrees with the thermal wind effect. A wind curl center is generated on the warm flank of the ESKF. The winds are much weaker in April, so is the wind curl. A rainband exists over the ESKF in both the months. The Weather Research and Forecasting (WRF) model is used for further researches. The winds on the top of the marine atmosphere boundary layer (MABL) indicate that in March, a positive wind curl is generated in the whole MABL over the warm flank of the ESKF. The thermal wind effect forced by the strong SST gradient overlying the background wind leads to strong surface northeasterly winds on the ESKF, and a positive shearing vorticity is created over the warm flank of the ESKF to generate wind curl. In the smoothed sea surface temperature experiment, the presence of the ESKF is responsible for the strong northeast winds in the ESKF, and essential for the distribution of the rainfall centers in March, which confirms the mechanism above. The same simulation is made for April, 2011, and the responses from the MABL become weak. The low background wind speed weakens the effect of the thermal wind, thus no strong Ekman pumping is helpful for precipitation. There is no big difference in rainfall between the control run and the smooth SST run. Decomposition of the wind vector shows that local wind acceleration induced by the thermal wind effect along with the variations in wind direction is responsible for the pronounced wind curl/divergence over the ESKF.     

湘江中下游农田土壤和蔬菜的重金属污染

A total of 219 agricultural soil and 48 vegetable samples were collected from the midstream and downstream of the Xiangjiang River（the Hengyang-Changsha section）in Hunan Province.The accumulation characteristics,spatial distribution and potential risk of heavy metals in the agricultural soils and vegetables were depicted.There are higher accumulations of heavy metals such as As,Cd,Cu,Ni,Pb and Zn in agricultural soils,and the contents of Cd（2.44 mg kg^-1 ）,Pb（65.00 mg kg^-1 ）and Zn（144.13 mg kg^-1 ）are 7.97,3.69 and 1.63 times the corresponding background contents in soils of Hunan Province,respectively. 13.2%of As,68.5%of Cd,2.7%of Cu,2.7%of Ni,8.7%of Pb and 15.1%of Zn in soil samples from the investigated sites exceeded the maximum allowable heavy metal contents in the China Environmental Quality Standard for Soils（GB15618-1995,Grade Ⅱ）.The pollution characteristics of multi-metals in soils are mainly due to Cd.The contents of As,Cd,Cu,Pb and Zn in vegetable soils are significantly higher than the contents in paddy soils.95.8%, 68.8%,10.4%and 95.8%of vegetable samples exceeded the Maximum Levels of Contaminants in Foods（GB2762-2005）for As,Cd,Ni and Pb concentrations,respectively.There are significantly positive correlations between the concentrations of Cd,Pb and Zn in vegetables and the concentrations in the corresponding vegetable soils（p〈0.01）.It is very necessary to focus on the potential risk of heavy metals for food safety and human health in agricultural soils and vegetables in the midstream and downstream of the Xiangjiang River,Hunan Province of China.     

The assessment of landslide susceptibility mapping using random forest and decision tree methods in the Three Gorges Reservoir area,China

Landslide susceptibility mapping is an indispensable prerequisite for landslide prevention and reduction. At present, research into landslide susceptibility mapping has begun to combine machine learning with remote sensing and geographic information system (GIS) techniques. The random forest model is a new integrated classification method, but its application to landslide susceptibility mapping remains limited. Landslides represent a serious threat to the lives and property of people living in the Zigui–Badong area in the Three Gorges region of China, as well as to the operation of the Three Gorges Reservoir. However, the geological structure of this region is complex, involving steep mountains and deep valleys. The purpose of the current study is to produce a landslide susceptibility map of the Zigui–Badong area using a random forest model, multisource data, GIS, and remote sensing data. In total, 300 pre-existing landslide locations were obtained from a landslide inventory map. These landslides were identified using visual interpretation of high-resolution remote sensing images, topographic and geologic data, and extensive field surveys. The occurrence of landslides is closely related to a series of environmental parameters. Topographic, geologic, Landsat-8 image, raining data, and seismic data were used as the primary data sources to extract the geo-environmental factors influencing landslides. Thirty-four layers of causative factors were prepared as predictor variables, which can mainly be categorized as topographic, geological, hydrological, land cover, and environmental trigger parameters. The random forest method is an ensemble classification technique that extends diversity among the classification trees by resampling the data with replacement and randomly changing the predictive variable sets during the different tree induction processes. A random forest model was adopted to calculate the quantitative relationships between the landslide-conditioning factors and the landslide inventory map and then generate a landslide susceptibility map. The analytical results were compared with known landslide locations in terms of area under the receiver operating characteristic curve. The random forest model has an area ratio of 86.10%. In contrast to the random forest (whole factors, WF), random forest (12 major factors, 12F), decision tree (WF), decision tree (12F), the final result shows that random forest (12F) has a higher prediction accuracy. Meanwhile, the random forest models have higher prediction accuracy than the decision tree model. Subsequently, the landslide susceptibility map was classified into five classes (very low, low, moderate, high, and very high). The results demonstrate that the random forest model achieved a reasonable accuracy in landslide susceptibility mapping. The landslide hazard zone information will be useful for general development planning and landslide risk management.