A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

A study of coral reef resilience and implications of adaptive management and rehabilitation in Khanh Hoa Province, Vietnam

The Province of Khanh Hoa, Vietnam, is located in the western South China Sea and boasts a shoreline of 385 km and many islands. Previous studies have indicated the extreme diversity and abundance of coral reefs in its waters as compared with other coastal provinces of Vietnam. A study on the resilience of coral reefs against increased surface water temperature and anthropogenic impact is conducted at 19 reef sites in 2015. At each site, a series of parameters (e.g., coral covers, genus diversity, and coral recruitment, substratum heterogeneity, depth, water exchange level, and sediment deposit and water temperature) are measured quantitatively or semi-quantitatively. The measured data are rated based on the relationship between the parameter values and coral susceptibility; the consideration that reef health reflects the biological capability to adapt to environmental changes and the recruitment potential if bleached; and positive or negative influences of physical factors in the mitigation of thermal stress and protecting corals from bleaching. A cumulative analysis enables researchers to divide the studied reefs into four categories based on varying levels of reef health to support resilience, recovery, and vulnerability in the case of increased water temperature. Relevant management interventions for each category and other supporting activities are suggested to enhance management effectiveness and to plan the rehabilitation of coral reefs for biodiversity conservation and touristic development, taking into account the involvement of related stakeholders.     

Spread-F during the magnetic storm of 22 January 2004 at low latitudes: Effect of IMF-Bz in relation to local sunset time

The paper describes the results of spread-F at low latitude stations around the world during the magnetic storm starting at 0130 UT on 22 January 2004. The storm can be divided into two phases, first phase up to 1000 UT when interplanetary magnetic field IMF-Bz was highly fluctuating around a small positive value and the second phase after a sudden large southward turning of IMF-Bz at 1030 UT. The first phase produced strong spread-F at Jicamarca, Sao Luis, and Ascension Island and caused complete inhibition of spread-F at Thumba and Waltair in India. It generated weak spread-F at Ho Chi Minh City in Vietnam and strong spread-F at Hainan and Chung Li. The strong spread-F at Hainan and Chung Li were caused by the positive IMF-Bz during the first phase of the storm and not by the negative pulse of IMF-Bz at 1000 UT.     

An analysis of coastal erosion in the tropical rapid accretion delta of the Red River, Vietnam

The largest plain in the North Vietnam has formed by the redundant sediment of the Red River system. Sediment supply is not equally distributed, causing erosion in some places. The paper analyzes the evolvement and physical mechanism of the erosion. The overlay of five recent topographical maps (1930, 1965, 1985, 1995, and 2001) shows that sediment redundantly deposits at some big river mouths (Ba Lat, Lach, and Day), leading to rapid accretion (up to 100 m/y). Typical mechanism of delta propagation is forming and connecting sand bars in front of the mouths. Erosion coasts are distributed either between the river mouths (Hai Hau) or nearby them (Giao Long, Giao Phong, and Nghia Phuc). The evolvement of erosion is caused by wave-induced longshore southwestward sediment transport. Meanwhile sediment from the river mouths is not directed to deposit nearshore. The development of sand bars can intensively reduce the erosion rate nearby river mouths. Erosion in Hai Hau is accelerated by sea level rise and upstream dams. Sea dike stability is seriously threatened by erosion-induced lowering of beach profiles, sea level rise, typhoon, and storm surge.     

Features in REE and Methane Anomalies Distribution in the East China Sea Water Column: a Comparison with the South China Sea

Water Resources - This paper presents review of dissolved Rare Earth Elements (REE) and methane anomalies distribution in the East China Sea water column. In general, the REE concentrations of the...     

中越红河断裂带考察与研究（一）

基于对越南境内红河断裂带的野外考察,结合中国境内红河断裂带已有考察研究成果,从断裂几何结构、构造演化与地层发育、新生代地质地貌特征等多个方面,初步探讨了红河断裂带现今活动的基本特征.认为:(1)红河断裂带在断裂几何结构、断裂长期的发育演化过程、断裂活动的地质地貌表现等诸多方面都表现出异常突出的时空不均匀性和分段性;(2)红河断裂新构造运动以来的夷平面发育与解体、新生代盆地发育与堆积、水系及河流阶地发育与变形等方面的特征表明,中国境内红河断裂带第四纪以来总体活动水平由北向南逐渐减弱的趋势一直延续到了越南境内;(3)青藏高原侧向挤出作用的影响范围足有限的,这一认识对于探索川滇地区地壳运动与强震活动的动力学机制具有重要意义.     

Multifractal behaviour of long‐term karstic discharge fluctuations

Karstic watersheds are highly complex hydrogeological systems that are characterized by a multiscale behaviour corresponding to the different pathways of water in these systems. The main issue of karstic spring discharge fluctuations consists in the presence and the identification of characteristic time scales in the discharge time series. To identify and characterize these dynamics, we acquired, for many years at the outlet of two karstic watersheds in South of France, discharge data at 3‐mn, 30‐mn and daily sampling rate. These hydrological records constitute to our knowledge the longest uninterrupted discharge time series available at these sampling rates. The analysis of the hydrological records at different levels of detail leads to a natural scale analysis of these time series in a multifractal framework. From a universal class of multifractal models based on cascade multiplicative processes, the time series first highlights two cut‐off scales around 1 and 16 h that correspond to distinct responses of the aquifer drainage system. Then we provide estimates of the multifractal parameters α and C₁ and the moment of divergence q_D corresponding to the behaviour of karstic systems. These results constitute the first estimates of the multifractal characteristics of karstic spingflows based on 10 years of high‐resolution discharge time series and should lead to several improvements in rainfall‐karstic springflow simulation models. Copyright © 2012 John Wiley & Sons, Ltd.     

3-D inversion of borehole-to-surface electrical data using a back-propagation neural network

The “fluid-flow tomography”, an advanced technique for geoelectrical survey based on the conventional mise-à-la-masse measurement, has been developed by Exploration Geophysics Laboratory at the Kyushu University. This technique is proposed to monitor fluid-flow behavior during water injection and production in a geothermal field. However data processing of this technique is very costly. In this light, this paper will discuss the solution to cost reduction by applying a neural network in the data processing. A case study in the Takigami geothermal field in Japan will be used to illustrate this. The achieved neural network in this case study is three-layered and feed-forward. The most successful learning algorithm in this network is the Resilient Propagation (RPROP). Consequently, the study advances the pragmatism of the “fluid-flow tomography” technique which can be widely used for geothermal fields. Accuracy of the solution is then verified by using root mean square (RMS) misfit error as an indicator.     

The sediment load and deposition by river discharge and their relation to organochlorine pesticides pollutants in the sediment bottom of Nha Trang Bay,Vietnam

Ocean Science Journal - Based on previous results from the “River reef impact studies project that was carried out as a co-operation programme between ZMT (Germany) and NIO (Vietnam) from...