J.M. Mankelow

The El Salvador earthquakes of January and February 2001: context, characteristics and implications for seismic risk

The small Central American republic of El Salvador has experienced, on average, one destructive earthquake per decade during the last hundred years. The latest events occurred on 13 January and 13 February 2001, with magnitudes Mw 7.7 and 6.6, respectively. The two events, which were of different tectonic origin, follow the patterns of the seismicity of the region although neither event has a known precedent in the earthquake catalogue in terms of size and location. The earthquakes caused damage to thousands of traditionally built houses and triggered hundreds of landslides, which were the main causes of fatalities. The earthquakes have clearly demonstrated trends of increasing seismic risk in El Salvador due to rapid population expansion in areas of high shaking and landslide hazard, exacerbated by deforestation and uncontrolled urbanisation. The institutional mechanisms required for the control of land use and building practice are very weak and present a major obstacle to risk mitigation. q 2002 Elsevier Science Ltd. All rights reserved.

Evaluating Earthquake-Triggered Landslide Hazard at the Basin Scale Through Gis in the Upper Sele River Valley

To evaluate techniques for assessing earthquake-triggeredlandslide hazard in the Southern Apennines (Italy), a GIS-based analysis was used to modelseismically induced slope deformations. Geological, geotechnical, geomorphological and seismologicaldata were integrated into a standard earthquake slope stability model. The model assessed thelandslide potential that existed during the 1980 Irpinian earthquake in the Upper Sele river Valley.The standard Newmark displacement analysis, widely used for predicting the location of shallowunstable slopes, does not take into account errors and/or uncertainties in the input parameters.Therefore, a probabilistic Newmark displacement analysis technique has been used. Probabilistictechniques allow, e.g., an estimation of the probability that a slope will exceed a certain criticalvalue of Newmark displacement. In our probabilistic method, a Monte-Carlo based simulation modelis used in conjunction with a GIS. The random variability of geotechnical data is modelled by probabilitydensity functions (pdfs), while for the seismic input three different regression laws wereconsidered. Input probability distributions are sampled and the resulting values input into empiricalrelations for estimating Newmark displacement. The outcome is a map in which to each siteis related a spatial probability distribution for the expected displacement in response to seismic loading.Results of the experiments show a high grade of uncertainty in the application of the Newmarkanalysis both for the deterministic and probabilistic approach in a complex geological setting suchas the high Sele valley, quite common in the Southern Apennines. They show a strong dependence onthe reliability of the spatial data used in input, so that, when the model is used at basin scale,results are strongly influenced by local environmental condition (e.g., topography, lithology, groundwatercondition) and decrease the model performance.

Uncertainty in ground motion estimates for the evaluation of slope stability during earthquakes

Three examples of landslides triggered by earthquakes have been examined to consider the natural variability of the slope forming materials, and the uncertainties surrounding input ground motions. These were the landslides at Villa Del Monte, California, Tachia Gorge, Taiwan and Las Colinas, El Salvador which were triggered by the Loma Prieta, (MW=7.0, 1989), Chi Chi, (MW=7.6, 1999) and El Salvador (MW=7.6, 2001) earthquakes respectively. The results of these analyses show a large scatter in the calculated factors of safety for earthquake conditions, some of which indicated stability when failure actually occurred. The models used in the calculation of seismic slope stability yield acceptable results. However, it is clear that the natural variability of slope forming materials has a strong influence on the range of results reported for the analysis of slopes subjected to strong shaking. This variability is exacerbated by limited knowledge about the interaction with seismic waves and slopes resulting in topographic amplification. Such problems are often further complicated by uncertainty and error associated with attenuation relationships.

OBTAINING PROBABILISTIC ESTIMATES OF DISPLACEMENT ON A LANDSLIDE DURING FUTURE EARTHQUAKES

The assessment of earthquake triggered landslide hazard may be undertaken using both deterministic and probabilistic techniques. Probabilistic methods have been developed because much of the data can be considered as random variables where parameters such as the angle of internal friction and moisture content do not have a single fixed value but may assume any number of values across a range. This random variability can be modelled by a probability density function (PDF) which describes the relative likeli-hood that a random variable will assume a particular value. Instead of using just the average or expected value of an input parameter, the complete range of possible values can be used to estimate a range of possible outcomes. Thus the probability of a slope being unstable can be obtained rather than a single indicator of stability. Such proba-bilistic analyses allow for the incorporation of the likely variability of each parameter and therefore allow a more intimate assessment of slope stability to be derived. Utilising empirical relationships for calculating earthquake ground motions and associated slope displacement, an investigation was undertaken to identify the contribution that modern simulation techniques could make to the assessment of earthquake-triggered landslides. To achieve this, geotechnical and earthquake data obtained from a deep-seated landslide triggered during the M w 7.0 Loma Prieta earthquake was used. By incorporating the variability of the geotechnical parameters and the uncertainty in earthquake location the model derived the probabilities associated with increasing amounts of slope displacement during future probable earthquakes. Analysis was undertaken for four of the principal fault segments in the San Francisco Bay area. These estimates were then combined with the occurrence probabilities of the earthquakes to provide temporal estimates of dis-placement for a 30 year period. Results indicated that a M w 7.0 earthquake located on the Peninsula Segment of the San Andreas fault was most hazardous with a 11% chance of minor slope displacement (≥0.10 m) and a 6% chance of moderate slope displacement (≥0.30 m) within the next 30 years.