Abstract. We release two datasets that track the enhanced landsliding induced by the
2008 Mw 7.9 Wenchuan earthquake over a portion of the Longmen
Mountains, at the eastern margin of the Tibetan Plateau (Sichuan, China). The
first dataset is a geo-referenced multi-temporal polygon-based inventory of
pre- and coseismic landslides, post-seismic remobilisations of coseismic
landslide debris and post-seismic landslides (new failures). It covers
471 km2 in the earthquake's epicentral area, from 2005 to 2018. The
second dataset records the debris flows that occurred from 2008 to 2017 in a
larger area (∼17 000 km2), together with information on their
triggering rainfall as recorded by a network of rain gauges. For some
well-monitored events, we provide more detailed data on rainfall, discharge,
flow depth and density. The datasets can be used to analyse, on various
scales, the patterns of landsliding caused by the earthquake. They can be
compared to inventories of landslides triggered by past or new earthquakes or
by other triggers to reveal common or distinctive controlling factors. To our
knowledge, no other inventories that track the temporal evolution of
earthquake-induced mass wasting have been made freely available thus far. Our
datasets can be accessed from https://doi.org/10.5281/zenodo.1405489.
We also encourage other researchers to share their datasets to facilitate
research on post-seismic geological hazards.
Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ~10 km 2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristics of the monitoring systems is the differentiation between a continuous mode that samples at low frequency ("non-event mode") and another mode that records the measurements at high frequency ("event mode"). The event detection algorithm, used to switch into the "event mode" depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.
Based on the historical and future outputs of 17 coupled model intercomparison project phase 5 (CMIP5) models, simulation of the precipitation extremes in China was evaluated under baseline climate condition compared to a gridded daily observation dataset CN05.1. The variations in precipitation extremes for eight global warming targets were also projected. The 17 individual models and the multi-model ensemble accurately reproduced the spatial distribution of precipitation extremes, although they were limited in their ability to capture the temporal characteristics. A notable dry bias existed in Southeast China, while a wet bias was present in North and Northwest China. The precipitation extremes in China were projected to be more frequent and more intense as global temperature rise reached the 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0°C warming targets. The projected percentage changes in the annual number of days with precipitation [50 mm (R50) and total precipitation during days in which the daily precipitation exceeds the 99th percentile (R99p) are projected to increase by 25.81 and 69.14 % relative to the baseline climate for a 1.5°C warming target, and by 95.52 and 162.00 % for a 4.0°C warming target, respectively. As the global mean temperature rise increased from 1.5 to 5°C, the subregions considerably affected by the East Asian summer monsoon (e.g., Southwest China, South China, and the Yangtze-Huai River Valley) were projected to experience a more dramatic increase in extreme precipitation events, in both number of days and intensity, while North and Northwest China were projected to suffer from relatively slight increases. The model uncertainties in the projected precipitation extremes in China by 17 CMIP5 models increase as global temperature rise increases.
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