聚力“整体智治” 提升六大能力——德清县打造地质灾害防治新格局

德清县紧紧围绕“不死人、少伤人、少损失”的总目标,聚力“整体智治”,充分运用云计算、大数据、物联网、人工智能等现代科学技术,扎实推进地质灾害防御体系和智控能力建设,整体提升地质灾害综合防治水平,努力实现从单部门应对单一灾种向多部门联动应对灾害链转变,从人防为主向人防技防并重转变,从隐患点管理向风险防控转变,有效破解地质灾害治理难题,最大限度减少地质灾害给人民生命和财产造成损失,已连续14年实现了地质灾害“零伤亡”,为“平安德清”建设提供地质环境安全保障。     

PRELIMINARY STUDY ON THE FLOODING AND DROUGHT CLAMITY DURING PAST 1500 YEARS IN THE HAI′AN REGION，JIANGSU PROVINCE

Collection and arrangement of the historical records of climatic changes and environment evolution,espectial-lyin the aspect of calamities,are made on the history documents of past 1500 years about Haiˊan region,Jiangsu Province.There existed two obvious flooding-drought frequently-occurring periods:one was from 1550 AD to 1850 AD and another was 100 AD to 1200AD.The period of 1550 AD to1850 AD is interrupted by two relatively arid and cold climatic periods:one was from 1630 AD to 1700 AD and another was 1750 AD to 1820 AD.The main characteristic of the calamity periods is that they occurred by turns,and sometimes,both drought and flooding occurred in the same year.The instability of the climatic changes in the Little Ice Age may be the main reason of the frequently-occurring flooding and drought in Haiˊan region.Research results also show that the frequently-occurring periods of flooding and drought is in close relationship with the solar activity,and therefore,occurrence of the flooding and drought may be in relation with the intensity of the solar activity.This hypothesis may need further study in the future.     

一种新的振幅滤波法在化磁极中的应用

本文针对低纬度地区频率域化磁极存在的问题，在频谱分析的基础上，提出了一种新的滤波方法即振幅滤波法。该方法能将低纬度地区化极磁场的频谱恢复到垂直磁化磁场的频谱，大大提高了低纬度地区化磁极的精度。     

西宁盆地泥石流类型及其防治意见

概略地叙述了西宁地区的泥石流形成条件和形成机理,并将西宁地区泥石流划分为稀性泥石流类及泥石质泥石流种类。在此基础上提出防治泥石流灾害的意见。     

景宁县国土资源局 早准备 早部署 有效地组织抗洪

6月18日以来，景宁县普降大暴雨，洪水；中毁道路、房屋、桥梁、电力通讯设备等，造成重大经济损失。截止23日统计，这次洪灾共引发滑坡、崩塌、泥石流等各类地质灾害106起。在这次抗洪中，县国土资源局早准备、早部署，有效地组织抗洪，全局出动抗洪23次59人。县乡村各级干部战斗在抗洪一线，特别是负责地质灾害隐患点的乡镇村干部和国土资源所工作人员高度重视，紧急撤离63个隐患点中的1503人，     

The Geologic Time Scale and the Italian stratigraphic record

The construction of the Geologic Time Scale (GTS) is a titanic scientific challenge that has been under way for two centuries and will require much dedicated effort in the future. Italy preserves a paramount stratigraphic record of Mesozoic and Cenozoic marine sediments that have been significant in the development of the modern GTS. The Italian stratigraphic record has been histori-cally important in introducing and defining the standard Chronostratigraphic Units (CUs) of the Neogene and Quaternary. Pelagic successions from Northern Apen-nines and Southern Alps have been used in the seventies for integrating the late Cretaceous-Paleogene Geomag-netic Polarity Time Scale (GPTS) with planktonic microfossil biostratieraohv and standard CUs. This was a major contribution to the construction of a new gener-ation of GTS based on integrated magnetobiochronol-ogy. The middle Miocene to early Pleistocene marinerecord from Sicily and southern Italy has been funda-mental for establishing the recently developed Astro-nomical Time Scale (ATS). In prospect, there are many potentials still to be exploited in the Italian marine stratigraphic record for implementing the GTS by defin-ing GSSPs of various CUs, improving magneto-biochronology and extending downwards the ATS.     

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.     

The Lagoon of Venice： geological setting,evolution and land subsidence

The paper deals with the geological setting, history and subsidence of the Venetian Plain. Major attention is paid to the Pleistocene-Holocene stratigraphic sequence in the Lagoon of Venice, in relation to its origin that datesback to 6-7 kyr BP. Geological land subsidence, which played an important role in the origin and the evolution of the lagoon, and anthropogenic subsidence, that has recently assumed a major importance for the Venetian environment, are discussed. Considering also the sealevel rise, 23 cm loss in land elevation has occurred in the last century, leading to increased flooding events and environmental problems that require protective works.