A NEW FINDING OF SURFACE RUPTURE ZONES ASSOCIATED WITH THE 1936 LINGSHAN M6(3/4) EARTHQUAKE,GUANGXI, CHINA

On April 1, 1936, an M6(3/4) earthquake occurred on the Fangcheng-lingshan Fault. This event is the biggest historical earthquake on the coastal seismic zone, South China ever. But so far, no any findings about the surface rupture of this event have been reported. This paper is the first to find several intact surface rupture zones associated with the 1936 Lingshan seismic event, in the areas of Gaotang, Jiaogengping etc. on the northeast segment of the Fangcheng-Lingshan Fault. According to the field work, the surface rupture stretches to 10km and distributes along NE direction in front of Luoyang Mountain, represented by earthquake scarp, extensional fracture, dextrally faulted gully and river system etc. The characteristics of surface ruptures and faulted landforms indicate that the surface rupture is of normal-dextral strike slip faulting. The trenching on this fault exposed that at least three seismic events have been recorded, including two historical earthquake events and the latest one is the 1936 Lingshan M6(3/4) earthquake. These surface rupture zones are the key to the detection of seismogenic structure and the re-estimate of magnitude of this event. The new finding of these surface rupture zones would be particularly significant for the detection of the seismogenic structure of Lingshan M6(3/4) earthquake.     

Hydro-meteorological drought assessment under climate change impact over the Vu Gia–Thu Bon river basin,Vietnam

Hydro-meteorological drought was assessed with respect to climate change over an estuary catchment Vu Gia-Thu Bon in Central Vietnam, which economy is dependent on agriculture. The fully-distributed hydrological model MIKE SHE was used to simulate river flow over the study region for the period 1991–2010. Drought were assessed using the Standardized Precipitation Index and the Standardized Runoff Index. The future climate was studied using the regional climate model Weather Research and Forecasting by downscaling an ensemble of three global climate models – CCSM3.0, ECHAM5 and MIROC-medium resolution over current (1961–1990) and future climates (2011–2040), under the A2 emissions scenario. The results suggest that, despite hotter and wetter future climate, the area is likely to suffer more from severe and extreme droughts, increasing about 100% in the median range for drought characteristics. Thus, there is a need for proper adaptation and planning for water resources management in this region.     

Flow patterns in temporary rivers: a methodological approach applied to southern Iberia

Temporary flow patterns remain understudied, despite their wide distribution and their importance for managerial practices and river conservation. This paper explores an advanced procedure for the characterization and definition of temporary flow patterns based on the frequency, duration and magnitude of non-flow (cessation) periods. A detailed analysis of flow patterns was performed on 12 rivers of the Guadiana Basin in Southern Iberia (10 in Spain and 2 in Portugal). An open methodology that can allow managers to better characterize and improve the structure and functioning of those rivers is suggested. This methodology is based on inter- and intra-annual variability analysis and its integration with river ecotypes. Within the methodology, a set of parameters related to ecological features of temporary rivers is proposed for application. This methodology may contribute to a better definition of cessation periods and an integrated understanding of the flow requirements of temporary rivers.     

M5'模型树算法和无人机航拍影像在震后崩塌滑坡分析中的应用——以鲁甸M_S6.5地震为例

利用高分辨率无人机航拍影像,结合基本地质资料,分析了影响2014年8月3日鲁甸M_S6.5地震震后崩塌滑坡分布的主要因素,使用M5'模型树算法建立了崩塌滑坡密度与其影响因子间的分段线性模型,并检验了该模型的预测性能。结果表明,地震诱发的崩塌滑坡分布受断层距、岩土体结构强度、坡度、植被条件等的影响,其中,断层距、岩土体结构强度及坡度等为主要影响因素;崩塌滑坡易发生在结构破裂区及坡度为38°~50°的区域,其分布密度随断层距的增加而减小;利用M5'模型树算法建立的模型体现出崩塌滑坡分布与其影响因子间复杂的非线性关系,模型检验结果显示,理论模型与实际关联函数间的相关系数达到0.88,因此,可利用该模型预测地震诱发的崩塌滑坡的分布。     

唐山M 4.8地震地磁谐波振幅比变化

针对2012年5月28日河北唐山M 4.8地震,采用地磁谐波振幅比方法,分析昌黎、静海、红山及承德地磁台2007年1月至2015年12月地磁观测数据,结果显示：各台站10 min周期的计算结果波动性明显,其他周期形态较为一致;距震中最近的昌黎地磁台Y_ZHx（NS）测向的10-40 min周期地磁谐波在下降至极低值后,开始转折时发生地震,而Y_ZHy（EW）测向未出现明显转折现象;位于河北平原地震带中部的静海地磁台对此次地震反应显著,2个测向在震前均出现下降-转折-上升的变化特征。通过对比位于不同地区的4个地磁台站地磁谐波振幅比变化,发现受大范围整体构造应力场作用的影响,计算结果具有相似的趋势性变化特征,具体到局部地区或断裂带内部,各台站之间显示出一定差异。     

湛江近海M2分潮的数值模拟

利用潮汐模型,在高分辨率的自适应曲线网格下,采用潮汐调和常数作为控制模拟精度的方法,模拟了洪江附近海域M2分潮的运动特征。模拟所得的潮汐调和常数同实测值相比,误差较小。根据模拟结果绘制的M2分潮的同潮图,揭示了湛江附近海域M2分潮振幅和迟角的分布特征以及M2分潮的传播和发展规律。模拟得到的M2分潮分别在涨憩、落憩、涨急和落急几个典型时刻的流场,揭示了湛江附近海域M2分潮潮流的分布特征及其运动规律。     

2020年1月19日新疆伽师MS6.4地震InSAR同震形变场特征及发震构造初步探讨

基于Sentinel-1 SAR升、降影像,利用D-InSAR技术获取新疆伽师M S6.4地震的同震形变场,结果表明,本次地震引起的同震形变场整体呈近椭圆状分布,形变区东西长约66 km,南北宽约40 km,整个形变场由南部隆升区和北部沉降区组成,南部最大隆升量约7 cm,北部最大沉降量约3 cm。本次地震发生在块体俯冲界面处的低倾角逆冲推覆构造带上,隆升和沉降两个中心均位于逆冲推覆体的上盘,形变主要以隆升形变为主,符合低倾角逆断层中强震的变形特征。在沉降区与隆升区之间干涉条纹连续分布,未出现表征地表破裂位置的空间失相关带,表明地震未引起明显的地表破裂。结合震源机制、余震精定位及区域构造特征,初步推断认为伽师地震的发震构造可能为柯坪塔格推覆构造前缘的N倾的柯坪断裂。     

2020年1月19日新疆伽师MS6.4地震序列特征及后续趋势分析

介绍2020年1月18日新疆伽师M S5.4和1月19日M S6.4两次地震的基本参数、震源机制解、精定位等资料,分析伽师M S6.4地震序列类型、序列衰减特征和余震序列各项数字地震学资料,并就该序列与历史地震序列进行对比,提出震后趋势判定意见。分析认为,该序列为前—主—余型,余震序列衰减较为迅速。     

2020年1月19日伽师MS6.4地震灾害损失评估及震害特点分析

2020年1月19日新疆伽师发生M S6.4地震,造成1人死亡、2人受伤,各类建(构)筑物、公共服务设施、生命线工程等都遭受不同程度的破坏。按照国家相关标准的原则和方法,通过对本次地震现场震害调查,评估出本次地震造成的总直接经济损失为15.26亿元,灾后恢复重建经费约需20.78亿元,并且分析了本次地震震害特点。这为今后的抗震救灾和灾后重建提供了科学依据。     

Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET₀). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET₀. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET₀. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET₀, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively.