Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Klose, Martin

doi:10.1007/978-3-319-20403-1

Cited by 16 publications

(15 citation statements)

References 148 publications

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“…Landslides belong to one of the most impacting natural hazards in alpine landscapes with a high frequency of occurrence and significant economic losses. In Switzerland landslide‐related damages were estimated to exceed 0.5 billion USD in the period 1972–2007 [ Hilker et al ., ] and similar levels of economic losses were reported for other alpine countries [ Kjekstad and Highland , ; Salvati et al ., ; Trezzini et al ., ; Klose , ]. In the U.S. landslides are estimated to lead to about 2 billion USD damage on average every year [ Schuster , ].…”

Section: Introductionmentioning

confidence: 99%

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

Leonarduzzi

Molnár

McArdell

2017

Water Resources Research

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A high‐resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972–2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity‐duration ID curves and validated their performance. The best predictive performance was obtained by the intensity‐duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country‐wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high‐quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack‐knife and cross‐validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

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Section: Introductionmentioning

confidence: 99%

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

Leonarduzzi

Molnár

McArdell

2017

Water Resources Research

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“…The landslides affect mostly the houses, churches, cemeteries, roads, railways (in 1992 the railway sector between Dîngeni and Săveni was affected by landslides on a sector of 100 m, which finally because of the lack of investments generated the closure of this 53.4 km railway sector), industrial infrastructure (Zemeș, Bacău County landslide with a surface of 42 ha and a volume of 3 million m 3 , which affected 47 oil pumps and one house, triggered by the oil drilling activities) and other public infrastructure form the study area. …”

Section: Resultsmentioning

confidence: 99%

“…The landslide hazard and risk assessment requires spatial and temporal data of landslide events [1,2,3]. This information is given by historical sources, since the use of aerial and satellite imagery is limited to the last 60 to 80 years.…”

Section: Introductionmentioning

confidence: 99%

“…While the use of remote sensing images allow us to elaborate complete landslide inventories for a limited amount of time, which in most cases is overlaid with the last climatic cycle, the historical information can be used to cover several climatic cycles, but the obtained inventory will not be complete. The historical information on landslides, in the past and today is related to events that happened in areas where society and landslides meet [3,4]. Although not complete this type of landslide inventories are actually needed for assessing scenarios of vulnerability in order to objectively create risk scenarios [5,6,7].…”

Section: Introductionmentioning

confidence: 99%

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The landslide database of North-Eastern Romania

Niculiţă¹,

Adrian²,

Lupu³

2017

Proceedings of the 33rd Romanian Geomorphology Symposium

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Abstract-Landslide databases are key elements used for assessing the vulnerability and the risk associated with landslide hazard. Also these databases show us to what extent the landslides produce damages to the society, which are the most vulnerable parts and also add an important component to hazard analysis, by showing the temporal distribution of the phenomenon. Recently, this type of databases is used also for landslide rainfall initiation threshold analysis, being the base of landslide early warning systems at national and regional level. The main source for the landslide events information were the local, regional and national news publications, and scientific publications and the time span of the identified landslide events is from 1900 to 2015. Every landslide event was geolocated at least at commune level and located in time at least with the month and year. Beside the spatial and temporal localization, all the information related to the magnitude of the event (surface, volume, speed), the type of the landslide, the triggering causes, the damages that were induced to infrastructure and houses and any other information that has a meaning for landslide research.The majority of the landslide events are reactivations, which occur from February to August, the biggest frequency periods being June-July, when heavy rainfall occurs and March-April when snowmelt and rainfall overlay. The speed of the events is small enough to allow evacuation of the population, so there was no human loess found. Beside natural causes (snowmelt and intense rainfall), there are landslides related to human activities: deforestation, road cutting, oil and gas mining. The main types of damages are related to houses and road infrastructure.While the database is not complete, because of the different density of the sources, it is showing the general pattern of landslide reactivation and damages scenarios caused by landslides in the north-east region of Romania.

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“…At the same time, daily rainfall thresholds or ID curves may also exhibit good predictive power for landsliding, e.g. as shown in a comprehensive analysis in Switzerland (Leonarduzzi et al, 2017). So the following question arises: how does the temporal resolution of the rainfall data actually affect landslide prediction?…”

Section: Introductionmentioning

confidence: 99%

Deriving rainfall thresholds for landsliding at the regional scale: daily and hourly resolutions, normalisation, and antecedent rainfall

Leonarduzzi

Molnár

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Rainfall thresholds are a simple and widely used method to forecast landslide occurrence. We provide a comprehensive data-driven assessment of the effects of rainfall temporal resolution (hourly versus daily) on rainfall threshold performance in Switzerland, with sensitivity to two other important aspects which appear in many landslide studies – the normalisation of rainfall, which accounts for local climatology, and the inclusion of antecedent rainfall as a proxy of soil water state prior to landsliding. We use an extensive landslide inventory with over 3800 events and several daily and hourly, station, and gridded rainfall datasets to explore different scenarios of rainfall threshold estimation. Our results show that although hourly rainfall did show the best predictive performance for landslides, daily data were not far behind, and the benefits of hourly resolutions can be masked by the higher uncertainties in threshold estimation connected to using short records. We tested the impact of several typical actions of users, like assigning the nearest rain gauge to a landslide location and filling in unknown timing, and we report their effects on predictive performance. We find that localisation of rainfall thresholds through normalisation compensates for the spatial heterogeneity in rainfall regimes and landslide erosion process rates and is a good alternative to regionalisation. On top of normalisation by mean annual precipitation or a high rainfall quantile, we recommend that non-triggering rainfall be included in rainfall threshold estimation if possible. Finally, while antecedent rainfall threshold approaches used at the local scale are not successful at the regional scale, we demonstrate that there is predictive skill in antecedent rain as a proxy of soil wetness state, despite the large heterogeneity of the study domain.

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Landslide Databases as Tools for Integrated Assessment of Landslide Risk

Cited by 16 publications

References 148 publications

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

The landslide database of North-Eastern Romania

Deriving rainfall thresholds for landsliding at the regional scale: daily and hourly resolutions, normalisation, and antecedent rainfall

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