Characteristics and interpretation of the seismic signal of a field-scale landslide dam failure experiment

Outburst floods caused by breaches of landslide dams may cause serious damages and loss of lives in downstream areas; for this reason the study of the dynamic of the process is of particular interest for hazard and risk assessment. In this paper we report a field-scale landslide dam failure experiment conducted in Nantou County, in the central of Taiwan.The seismic signal generated during the dam failure was monitored using a broadband seismometer and the signal was used to study the dam failure process.We used the short-time Fourier transform(STFT) to obtain the time–frequency characteristics of the signal and analyzed the correlation between the power spectrum density(PSD) of the signal and the water level. The results indicate that the seismic signal generated during the process consisted of three components: a low-frequency band(0–1.5 Hz), an intermediate-frequency band(1.5–10 Hz) and a highfrequency band(10–45 Hz). We obtained the characteristics of each frequency band and the variations of the signal in various stages of the landslide dam failure process. We determined the cause for the signal changes in each frequency band and its relationship with the dam failure process. The PSD sediment flux estimation model was used to interpret the causes of variations in the signal energy before the dam failure and the clockwise hysteresis during the failure. Our results show that the seismic signal reflects the physical characteristics of the landslide dam failure process. The method and equipment used in this study may be used to monitor landslide dams and providing early warnings for dam failures.     

Spatial patterns and storage composition of woody debris in a natural secondary forest dominated by <Emphasis Type="Italic">Pinus tabulaeformis</Emphasis> on Loess Plateau,China

Woody debris (WD) is an important part of natural Pinus tabulaeformis mixed stands, and it affects the forest ecosystem stability and development. The WD spatial patterns are especially important structural characteristics that can provide insights into forest dynamics. In this paper, the WD storage, WD spatial patterns and WD associations among the main species were examined in the natural secondary forest on Loess Plateau in northwest China. Data were collected in a 1 ha (100 m × 100 m) permanent plot, and all the trees with a diameter at breast height of more than 3 cm were measured and stem-mapped. Ripley’s K functions from the spatial-point-pattern-analysis method were used to analyze the spatial distribution and associations. The results showed that: (1) The total storage of WD was 10.73 t/ha, fallen wood was the main source of WD, and the majority diameters were greater than 20 cm, and in intermediate levels of decay; (2) The overall spatial pattern was closely related to the spatial scale, which exhibited an aggregated pattern on a small scale, and a random pattern on a large scale. The spatial patterns of coarse woody debris also gradually transitioned from an aggregated pattern in fine scales to a random pattern in broader spatial scales, which matched the overall spatial pattern. The spatial intensity was gradually decreased with the increasing diameters, and increased with the decomposition classes; (3) The WD of Pinus tabulaeformis species was negatively associated with Betula platyphylla and Populus davidiana on a small scale but positively associated with these species on a large scale. The spatial pattern and interspecies relations were the results of long-term interactions between the natural secondary forest community and the surrounding natural environment. These findings would provide a scientific basis for the sustainable management and protection of natural secondary forest ecosystems on Loess Plateau.     

A novel model to assess soil productivity in the dry-hot valleys of China

Accurate evaluation of soil productivity has been a long-standing challenge. Although numerous models for productivity assessment exist, most are cumbersome to use and require substantial parameter inputs. We developed a new empirical soil productivity model based on field investigations of soil erosion, soil physicochemical properties, and crop yields in the dry-hot valleys (DHVs) in China. We found that soil pH, and organic matter and available potassium contents significantly affected crop yields under eroded conditions of the DHVs. Moreover, available potassium content was the key factor affecting soil productivity. We then modified an existing soil productivity model by adding the following parameters: contents of effective water, potassium, organic matter, and clay, soil pH, and root weighting factor. The modified soil productivity model explained 63.5% of the crop yield. We concluded that the new model was simple, realistic, and exhibited strong predictability. In addition to providing an accurate assessment of soil productivity, our model could potentially be applied as a soil module in comprehensive crop models.     

A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China

Xigeda formation is a type of hundred-meter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design, and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua (FLAC^3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loading-test pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neural-network-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides.     

Geomorphologic map of the 1<Superscript>st</Superscript> Mutnaya River,Southeastern Kamchatka,Russia

The Kamchatka Peninsula–situated in the Pacific “Ring of Fire”–has 29 active and over 400 extinct volcanoes. Since it is situated in the northeastern extremity of Russia, in subarctic climate, the volcanic landforms are overprinted by the 446 glaciers. This research focuses on the 1^stMutnaya catchment which drains the southern slopes of two active volcanoes: Avachinsky and Koryaksky. Those volcanoes are a permanent threat for the cities of Petropavlovsk and Elizovo, which are the 2 of 3 cities of the peninsula. Hence, most of the studies carried out in the area dealt with the natural hazards and only few focus on landscape evolution. Thus, the purpose of this study was to elaborate a cartographic approach which integrates classic geomorphology with state of the art GIS and remote sensing techniques. As result, different landforms and related processes have been analysed and included in the first general geomorphologic map of the 1^stMutnaya catchment.     

Limit equilibrium method (LEM) of slope stability and calculation of comprehensive factor of safety with double strength-reduction technique

When the slope is in critical limit equilibrium(LE) state, the strength parameters have different contribution to each other on maintaining slope stability. That is to say that the strength parameters are not simultaneously reduced. Hence, the LE stress method is established to analyze the slope stability by employing the double strengthreduction(DSR) technique in this work. For calculation model of slope stability under the DSR technique, the general nonlinear Mohr–Coulomb(M–C) criterion is used to describe the shear failure of slope. Meanwhile, the average and polar diameter methods via the DSR technique are both adopted to calculate the comprehensive factor of safety(FOS) of slope. To extend the application of the polar diameter method, the original method is improved in the proposed method. After comparison and analysis on some slope examples, the proposed method's feasibility is verified. Thereafter, the stability charts of slope suitable for engineering application are drawn. Moreover, the studies show that:(1) the average method yields similar results as that of the polardiameter method;(2) compared with the traditional uniform strength-reduction(USR) technique, the slope stability obtained using the DSR techniquetends to be more unsafe; and(3) for a slope in the critical LE state, the strength parameter φ, i.e., internal friction angle, has greater contribution on the slope stability than the strength parameters c, i.e., cohesion.     

利用SLR数据检核GLONASS卫星最终轨道

采用由EDC提供的2015-01-01～2015-12-31的SLR标准点观测数据进行GLONASS卫星最终轨道（CODE提供）检核,分别按照卫星PRN号和不同测站对检核结果进行统计分析。结果表明,不同卫星的检核效果参差不齐,跟卫星的服役年限有关,较新的卫星检核结果较好,第一轨道面的卫星检核结果最好;检核结果中存在一定的系统误差,且大部分的激光测距比最终轨道反算的站星距要短;利用SLR检核2015年全年GLONASS轨道精度总体优于3.3 cm,激光观测精度总体优于1.2 cm。     

A NEW BIOGENIC SULFIDE CHEMICAL SENSOR FOR MARINE ENVIRONMENTAL MONITORING AND SURVEY

ＩＮＴＲＯＤＵＣＴＩＯＮＢｉｏｇｅｎｉｃｓｕｌｆｉｄｅｐｒｏｄｕｃｅｄｂｙｂａｃｔｅｒｉａｌｓｕｌｆａｔｅｒｅｄｕｃｔｉｏｎｉｓｏｎｅｏｆｔｈｅｍｏｓｔｉｍｐｏｒｔａｎｔｉｎｄｉｃａｔｏｒｓｉｎａｎｏｘｉｃｍａｒｉｎｅｅｎｖｉｒｏｎｍｅｎｔｓ,ｐａｒｔｉｃｕｌａｒｌｙｉｎｃｏｎｆｉｎｉｎｇｂａｙｓ,ｐｏｌｌｕｔｅｄｅｓｔｕａｒｉｅｓａｎｄａｑｕａｃｕｌｔｕｒｅａｒ ｅａｓ.Ｔｈｅｉｎｃｒｅａｓｅｏｆｉｔｓｃｏｎｃｅｎｔｒａｔｉｏｎｕｓｕａｌｌｙｉｎｄｉｃａｔｅｓｗｏｒｓｅｎｅｄｃｏｎｄｉｔｉｏｎｓ.…     

Long-term statistics of extreme tsunami height at Crescent City

Historically, Crescent City is one of the most vulnerable communities impacted by tsunamis along the west coast of the United States, largely attributed to its offshore geography. Trans-ocean tsunamis usually produce large wave runup at Crescent Harbor resulting in catastrophic damages, property loss and human death. How to determine the return values of tsunami height using relatively short-term observation data is of great significance to assess the tsunami hazards and improve engineering design along the coast of Crescent City. In the present study, the extreme tsunami heights observed along the coast of Crescent City from 1938 to 2015 are fitted using six different probabilistic distributions, namely, the Gumbel distribution, the Weibull distribution, the maximum entropy distribution, the lognormal distribution, the generalized extreme value distribution and the generalized Pareto distribution. The maximum likelihood method is applied to estimate the parameters of all above distributions. Both Kolmogorov-Smirnov test and root mean square error method are utilized for goodness-of-fit test and the better fitting distribution is selected. Assuming that the occurrence frequency of tsunami in each year follows the Poisson distribution, the Poisson compound extreme value distribution can be used to fit the annual maximum tsunami amplitude, and then the point and interval estimations of return tsunami heights are calculated for structural design. The results show that the Poisson compound extreme value distribution fits tsunami heights very well and is suitable to determine the return tsunami heights for coastal disaster prevention.     

A dinoflagellate <Emphasis Type="Italic">Cochlodinium geminatum</Emphasis> bloom in the Zhujiang (Pearl) River estuary in autumn 2009

A severe Cochlodinium geminatum red tide (>300 km2) was observed in the Zhujiang (Pearl) River estuary, South China Sea in autumn 2009. We evaluated the environmental conditions and phytoplankton community structure during the outbreak. The red tide water mass had significantly higher dissolved inorganic phosphate (DIP), ammonia, and temperature, but significantly lower nitrite, nitrate, dissolved inorganic nitrogen (DIN), and DIN/DIP relative to the non-red-tide zones. The phytoplankton assemblage was dominated by dinoflagellates and diatoms during the red tide. C. geminatum was the most abundant species, with a peak density of 4.13×107 cell/L, accounting for >65% of the total phytoplankton density. The DIN/DIP ratio was the most important predictor of species, accounting for 12.45% of the total variation in the phytoplankton community. Heavy phosphorus loading, low precipitation, and severe saline intrusion were likely responsible for the bloom of C. geminatum.