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The 2008 Wenchuan earthquake lead to various complex multi-hazard chains that included seismically triggered landslide initiation, landslide runout, river damming, dam breaching, and flooding. The modeling of the interactions between such hazardous processes is challenging due to the complexity and uncertainty. Here we present an event-based physically based model that is able to simulate multi-hazard land surface process chains within a single unified simulation. The final model is used to simulate a multi-hazard chain event in the Hongchun watershed, where co-seismic landslides led to a landslide dam and, 2 years later, a debris flow that breached the landslide dam. While most aspects of the multi-hazard chain are predicted well, the correct prediction of slope failures remains the biggest challenge. Although the results should be treated carefully, the development of such a model provides a significant progress in the applicability of multi-hazard chain simulations.

A quantitative procedure for estimating landslide risk to life and property is presented and applied in a mountainous area in the Nilgiri hills of southern India. Risk is estimated for elements at risk located in both initiation zones and run-out paths of potential landslides. Loss of life is expressed as individual risk and as societal risk using F-N curves, whereas the direct loss of properties is expressed in monetary terms. An inventory of 1084 landslides was prepared from historical records available for the period between 1987 and 2009. A substantially complete inventory was obtained for landslides on cut slopes (1042 landslides), while for natural slopes information on only 42 landslides was available. Most landslides were shallow translational debris slides and debris flowslides triggered by rainfall. On natural slopes most landslides occurred as first-time failures. For landslide hazard assessment the following information was derived: (1) landslides on natural slopes grouped into three landslide magnitude classes, based on landslide volumes, (2) the number of future landslides on natural slopes, obtained by establishing a relationship between the number of landslides on natural slopes and cut slopes for different return periods using a Gumbel distribution model, (3) landslide susceptible zones, obtained using a logistic regression model, and (4) distribution of landslides in the susceptible zones, obtained from the model fitting performance (success rate curve). The run-out distance of landslides was assessed empirically using landslide volumes, and the vulnerability of elements at risk was subjectively assessed based on limited historic incidents. Direct specific risk was estimated individually for tea/coffee and horticulture plantations, transport infrastructures, buildings, and people both in initiation and run-out areas. Risks were calculated by considering the minimum, average, and maximum landslide volumes in each magnitude class and the corresponding minimum, average, and maximum run-out distances and vulnerability values, thus obtaining a range of risk values per return period. The results indicate that the total annual minimum, average, and maximum losses are about US$ 44 000, US$ 136 000 and US$ 268 000, respectively. The maximum risk to population varies from 2.1 × 10−1 for one or more lives lost to 6.0 × 10−2 yr−1 for 100 or more lives lost. The obtained results will provide a basis for planning risk reduction strategies in the Nilgiri area.

In the present study, spatial and temporal patterns of rain event properties are analysed. These event properties are rain event depth, event duration, mean event rain rate, peak rain rate and the time span between two consecutive rain events which is referred to as inter-event time (IET). In addition, we assessed how rain event properties change when the period over which rainfall data is aggregated changes from 1 to 6 min and when the minimum inter-event time (MIT) changes from 30 min to 8 h. Rainfall data is obtained from a field campaign in two wet seasons of June–August (JJA) of 2007 and 2008 in Gilgel Abbay watershed that is situated at the source basin of the Upper Blue Nile River in Ethiopia. The rainfall data was automatically recorded at eight stations. The results revealed that rain event depth is more related to peak rain rate than to event duration. At the start and towards the end of the wet season, the rain events have larger depth with longer duration and longer IET than those in mid-season. Event rain rate and IET are strongly related to terrain elevation. Sekela which is on a mountain area has the shortest IET while Bahir Dar which is at the south shore of Lake Tana has the longest IET. The period over which rainfall data is aggregated significantly affected the values of rain event properties that are estimated using relatively small value (30 min) of MIT but its effect diminished when the MIT is increased to 8 h. It is shown that increasing the value of MIT has the largest effect on rain event properties of mountain stations that are characterised by high rainfall intermittency.

A quantitative approach for landslide risk assessment along transportation lines is presented and applied to a road and a railway alignment in the Nilgiri hills in southern India. The method allows estimating direct risk affecting the alignments, vehicles and people, and indirect risk resulting from the disruption of economic activities. The data required for the risk estimation were obtained from historical records. A total of 901 landslides were catalogued initiating from cut slopes along the railway and road alignment. The landslides were grouped into three magnitude classes based on the landslide type, volume, scar depth, run-out distance, etc and their probability of occurrence was obtained using frequency-volume distribution. Hazard, for a given return period, expressed as the number of landslides of a given magnitude class per kilometre of cut slopes, was obtained using Gumbel distribution and probability of landslide magnitude. In total 18 specific hazard scenarios were generated using the three magnitude classes and six return periods (1, 3, 5, 15, 25, and 50 years). The assessment of the vulnerability of the road and railway line was based on damage records whereas the vulnerability of different types of vehicles and people was subjectively assessed based on limited historic incidents. Direct specific loss for the alignments (railway line and road), vehicles (train, bus, lorry, car and motorbike) was expressed in monetary value (US$), and direct specific loss of life of commuters was expressed in annual probability of death. Indirect specific loss (US$) derived from the traffic interruption was evaluated considering alternative driving routes, and includes losses resulting from additional fuel consumption, additional travel cost, loss of income to the local business, and loss of revenue to the railway department. The results indicate that the total loss, including both direct and indirect loss, from 1 to 50 years return period, varies from US$ 90 840 to US$ 779 500 and the average annual total loss was estimated as US$ 35 000. The annual probability of a person most at risk travelling in a bus, lorry, car, motorbike and train is less than 10-4/annum in all the time periods considered. The detailed estimation of direct and indirect risk will facilitate developing landslide risk mitigation and management strategies for transportation lines in the study area.