Causes of Landslide and its Socio-economic Effects: a study on Chattogram City and Surrounding Areas, Bangladesh

Landslide is a regular hazard in Bangladesh especially in Chattogram, the South-Eastern part of the Country. In 2007 and 2008 there happened two massive landslides in Chattogram. As a result, a huge number of people (130 and 11 respectively) died with heavy loss of properties affecting thousands of people in the region. Most of the landslides happened after torrential rain. Combined effect of rainfall and hill cutting induced slope instability adding Earthquake-triggered landslide in Chattogram. Some influential people are involved in hill cutting and developing hilly settlements in Chattogram. In some places, Government and non-Government authorities are developing settlements by razing hills there. A detailed area planning, landslide vulnerability zoning, landslide database development, geophysical analysis, and strictly implementation of Government’s existing rules are recommended to ensure avoiding further tragedy in Chattogram like 2007 and 2008.

CHILDA – Czech Historical Landslide Database

National and regional historical landslide databases are increasingly viewed as providing empirical evidence for the geomorphic effects of ongoing environmental change and for supporting adaptive territorial planning. In this work, we present the design and current content of the Czech Historical Landslide Database (CHILDA), the first of its kind for the territory of Czechia (the Czech Republic). We outline the CHILDA system, its functionality, and technical solution. The database was established by merging and extending the fragmented regional datasets for highly landslide-prone areas in Czechia. Currently, the database includes 699 records (619 landslides, 75 rockfalls, and 5 other movement types) encompassing the period from the oldest determined records (1132) up to 1989, which represents an important cultural, political, and socioeconomic divide.

CHILDA − Czech Historical Landslide Database

National and regional historical landslide databases are increasingly viewed as providing empirical evidence for the geomorphic effects of ongoing environmental change and for supporting adaptive territorial planning. In this work, we present the design and current content of the Czech Historical Landslide Database (CHILDA), the first of its kind for the territory of Czechia (the Czech Republic). We outline the CHILDA system, its functionality and technical solution. The database was established by merging and extending the fragmented regional datasets for highly landslide prone areas in Czechia. Currently, the database includes 699 records (619 landslides, 75 rockfalls, and 5 other movement types) encompassing the period from the oldest determined records (1132) up to 1989 which represents an important cultural, political and socioeconomic divide. Along with characterizing the content of the database, we discuss its further developments and applications.

Meteorological and hydrological conditions triggering rockfall events in Germany

<p>In this study we present the results of a logistic regression model aimed at describing changes in probabilities for rockfall events in Germany in response to changes in meteorological and hydrological conditions.</p><p>The rockfall events for this study are taken from the landslide database for Germany (Damm and Klose, 2015). The meteorological variables we tested as predictors for the logistic regression model are daily precipitation from the REGNIE data set (Rauthe et al. 2013), hourly precipitation from the RADKLIM radar climatology (Winterrath et al., 2018) and temperature from the E-OBS data set (Cornes et al., 2018). As there is no observational soil moisture data set covering the entire country, we used soil moisture modelled with the state-of-the-art hydrological model mHM (Samaniego et al. 2010), which was calibrated using gauge measurements.</p><p>In order to select the best statistical model we tested a large number of physically plausible combinations of meteorological and hydrological predictors. Each model was checked using cross-validation. The decision on the final model was based on the value of the logarithmic skill score and on expert judgement.</p><p>The final statistical model includes the local percentile of daily precipitation, total relative soil moisture and freeze-thawing cycles in the previous weeks as predictors. It was found that daily precipitation is the most important parameter in the model. An increase of daily precipitation from its median to its 80th percentile approximately doubles the probability for a rockfall event. Higher soil moisture and the occurrence of freeze-thaw cycles also increase the probability for rockfall events. </p><p><br>Cornes, R. C. et al., 2018: An ensemble version of the E‐OBS temperature and precipitation data sets. Journal of Geophysical Research: Atmospheres, 123, 9391– 9409.</p><p>Damm, B., Klose, M., 2015. The landslide database for Germany: Closing the gap at national level. Geomorphology 249, 82–93</p><p>Rauthe, M. et al., 2013: A Central European precipitation climatology – Part I: Generation and validation of a high-reso-lution gridded daily data set (HYRAS), Vol. 22(3), p 235–256.</p><p>Samaniego, L. et al., 2010: Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523</p><p>Winterrath, T. et al., 2018: RADKLIM Version 2017.002: Reprocessed gauge-adjusted radar data, one-hour precipitation sums (RW), DOI: 10.5676/DWD/RADKLIM_RW_V2017.002.</p>

LANDSLIDE INCIDENCE ANALYSIS BY MEANS OF A-DInSAR OPEN ACCESS SERVICE AND LANDSLIDE DATABASE

<p>Landslides are one of the most common and dangerous threats in the world that generate considerable damage and economic losses. The aim of this study is to analyse the suitability of using the ESA G-POD (European Space Agency Grid Processing On Demand) environment to detect landslide incidence.</p><p>This free service allows to gain Mean Deformation Maps (mm/year and cm/year) by means of P-SBAS (Parallel-Small Baseline Subset) method, which is a kind of A-DInSAR (Advanced-Differential SAR Interferometry) technique.</p><p>The study area is in the Northwest of Spain, where there are and have been some significant well-known active landslides. ENVISAT ASAR satellite data collected from 2003 to 2010, have been contrasted with the slope instabilities inventory of Asturias (BAPA: <em>Base de datos de Argayos del Principado de Asturias</em> - Principality of Asturias Landslide Database), from 2003 to 2010. Afterwards, a new check with instability data registered in BAPA dataset from 2010 to 2017 has been done.</p><p>A-DInSAR and BAPA data have been jointly integrated and examined in a GIS. The results obtained indicate that there is consistency between both types of data. In addition, this research has been useful to highlight the G-POD free service as a reliable, economic and adequate tool to analyse movements of terrain during time periods of several years in the North of Spain.</p>

Schützt der Wald vor Rutschungen? Hinweise aus der WSL-Rutschungsdatenbank

Does the forest provide protection from landslides? Evidence from the WSL Shallow Landslide Database During strong rainfall events, shallow landslides and debris avalanches (hillslope debris flows, or open-slope debris flows) are triggered and sometimes lead to considerable damage. Analysis of damage-causing events show that there are fewer landslides in forested areas compared to non-forested areas, which indicates the generally positive influence of forest vegetation on slope stability. However, these effects depend on the condition of the forest stand and quantification of the effects is difficult. Event documentation contributes to a better understanding of the relevant processes. The information obtained is not only important for the preparation of hazard maps, but also provides valuable insight for assessing the hazard protection provided by the forest. Data from the landslide database of the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) were used to evaluate the influence of the forest on slope stability. Currently, the database contains information on 734 landslides. Of these, 661 were included in the evaluation – 356 landslides in non-forested areas and 305 in forested areas. In areas with slope angles up to 38°, more landslides per unit area are observed in non-forested areas than in forested areas. In areas with steeper slope angles a stabilizing effect of the forest is no longer recognizable. Statistical analyses show that landslides in forested areas are smaller than in non-forested areas and are more frequent on steeper slopes. In general, the landslides become smaller with increasing slope. Multivariate analyses indicate a positive influence of the forest and also somewhat smaller landslides in well-developed forests. Negative effects are evident in non-forested areas and in areas with overly dense forests. In addition to illustrating the importance of the forest condition for slope stability, the paper also discusses how the forest condition can be described.

NATIONAL DATABASE OF LANDSLIDE PROCESSES: PRINCIPLES OF DEVELOPMENT, IMPLEMENTATION AND APPLICATION FOR LANDSLIDE HAZARD ASSESSMENT ON REGIONAL AND LOCAL LEVELS

The main approaches and principles of the development and formation of the database of lanslide processes within the territory of Ukraine are described. Among natural risks one of the most common are landslide phenomena, which lead to significant social and economic losses. Ukraine is characterized by active landslide processes within different structural-tectonic and landscape-climatic zones, which requires a unified approach to the development of a system of their assessment, inventory and monitoring with the subsequent forecasting, and assessment of the impact on manmade objects. The national landslide database is the most comprehensive source of information on the distribution of landslides in different regions of the country, and the main task is the input, processing, analysis and updating of information on landslides. The national landslide database consists of a series of tables stored and maintained in the relational database Oracle or PostgreSQL (open-source database). Use of ArcGIS10 provides the ability to display spatial information, store positional and non-positional attributive landslide data, and perform spatial analysis and modelling operations with the purpose of further prediction of landslide hazard at the regional and local levels.