Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds

Abstract. The Norwegian Water Resources and Energy Directorate (NVE) have run a national flood forecasting and warning service since 1989. In 2009, the directorate was given the responsibility of also initiating a national forecasting service for rainfall-induced landslides. Both services are part of a political effort to improve flood and landslide risk prevention. The Landslide Forecasting and Warning Service was officially launched in 2013 and is developed as a joint initiative across public agencies between NVE, the Norwegian Meteorological Institute (MET), the Norwegian Public Road Administration (NPRA) and the Norwegian Rail Administration (Bane NOR). The main goal of the service is to reduce economic and human losses caused by landslides. The service performs daily a national landslide hazard assessment describing the expected awareness level at a regional level (i.e. for a county and/or group of municipalities). The service is operative 7 days a week throughout the year. Assessments and updates are published at the warning portal http://www.varsom.no/ at least twice a day, for the three coming days. The service delivers continuous updates on the current situation and future development to national and regional stakeholders and to the general public. The service is run in close cooperation with the flood forecasting service. Both services are based on the five pillars: automatic hydrological and meteorological stations, landslide and flood historical database, hydro-meteorological forecasting models, thresholds or return periods, and a trained group of forecasters. The main components of the service are herein described. A recent evaluation, conducted on the 4 years of operation, shows a rate of over 95 % correct daily assessments. In addition positive feedbacks have been received from users through a questionnaire. The capability of the service to forecast landslides by following the hydro-meteorological conditions is illustrated by an example from autumn 2017. The case shows how the landslide service has developed into a well-functioning system providing useful information, effectively and on time.

Section: Thresholdsmentioning

confidence: 76%

The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides

Krøgli

Devoli

Colleuille

et al. 2018

“…However, it is widely recognized that soil moisture conditions before the triggering rainfall event can play a crucial role in the initiation of landslides, especially when deepseated landslides and terrains with complex hydrological settings are involved (Wieczorek, 1996;Zezere et al, 2005;Jemec and Komac, 2013;Peres and Cancelliere, 2016;Bogaard and Greco, 2018).…”

Section: Introductionmentioning

confidence: 99%

Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system

Segoni

Rosi

Lagomarsino

et al. 2018

Abstract. We communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because landslides are not expected to occur. Another approach deeply modifies the original RSLEWS: thresholds based on antecedent rainfall accumulated over long periods are substituted with soil moisture thresholds. A back analysis demonstrated that both approaches consistently reduced false alarms, while the second approach reduced missed alarms as well.

“…This has been valid until today since most operational landslide forecasting and early warning systems rely on the relationship between rainfall and landslide occurrence, thus representing only a simplification of the underlying physical processes. Bogaard and Greco (2018) critically analyze the role of rainfall thresholds for shallow landslides and debris flows from a hydrometeorological point of view. It is beyond the scope of this paper to provide a review of past and present landslide early warning systems, which can be found elsewhere (e.g., Alfieri et al, 2012a;Thiebes, 2012;Thiebes and Glade, 2016;Piciullo et al, 2018).…”

Section: Probabilistic Forecasting In Hydrology and Ties To Landslidementioning

confidence: 99%

“…Guzzetti et al (2007) and Segoni et al (2018a) give an overview of rainfall and climate variables used in the literature for the definition of rainfall thresholds for the initiation of landslides; however, such empiricalstatistical approaches disregard the physical relationship between rainfall occurrence and the mechanisms leading to landslides, neglecting local environmental conditions and the role of the hydrological processes occurring along slopes (Reichenbach et al, 1998;Bogaard and Greco, 2018). Attempts to relate landslide-triggering thresholds to weather and other physically based characteristics can be very challenging given the quality of currently available data (Peres et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology

Canli

Mergili

Thiebes

et al. 2018

Abstract. Landslide forecasting and early warning has a long tradition in landslide research and is primarily carried out based on empirical and statistical approaches, e.g., landslidetriggering rainfall thresholds. In the last decade, flood forecasting started the operational mode of so-called ensemble prediction systems following the success of the use of ensembles for weather forecasting. These probabilistic approaches acknowledge the presence of unavoidable variability and uncertainty when larger areas are considered and explicitly introduce them into the model results. Now that highly detailed numerical weather predictions and high-performance computing are becoming more common, physically based landslide forecasting for larger areas is becoming feasible, and the landslide research community could benefit from the experiences that have been reported from flood forecasting using ensemble predictions. This paper reviews and summarizes concepts of ensemble prediction in hydrology and discusses how these could facilitate improved landslide forecasting. In addition, a prototype landslide forecasting system utilizing the physically based TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) model is presented to highlight how such forecasting systems could be implemented. The paper concludes with a discussion of challenges related to parameter variability and uncertainty, calibration and validation, and computational concerns.