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

Segoni, Samuele; Rosi, Ascanio; Lagomarsino, Daniela; Fanti, Riccardo; Casagli, Nicola

doi:10.5194/nhess-18-807-2018

Cited by 93 publications

(68 citation statements)

References 25 publications

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“…This result is not unexpected and is in line with the findings of some recent works on landslide rainfall thresholds (Capra et al, 2018;Segoni et al, 2018b). The relative water supply is derived from simulated rain or snowmelt from the snowpack (in which rain may percolate), as a percentage of an annual average value for a 30-year period.…”

Section: Thresholdssupporting

confidence: 72%

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

Krøgli

Devoli

Colleuille

et al. 2018

Nat. Hazards Earth Syst. Sci.

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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.

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Section: Thresholdssupporting

confidence: 72%

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

Krøgli

Devoli

Colleuille

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…The study of antecedent rainfall for landslide incidences is important as it may lead to an increase in soil moisture content leading to slope instability. The impact of antecedent rainfall should be a site-specific study and may not always hold good for other regions with similar geological and rainfall conditions [34]. The variation in soil moisture content across an area is difficult to accurately determine as it depends on various factors like the variation in soil type, depth, climatic variation, etc.…”

Section: Methodsmentioning

confidence: 99%

Estimating Rainfall Thresholds for Landslide Occurrence in the Bhutan Himalayas

Dikshit

Sarkar

Pradhan

et al. 2019

Water

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Consistently over the years, particularly during monsoon seasons, landslides and related geohazards in Bhutan are causing enormous damage to human lives, property, and road networks. The determination of thresholds for rainfall triggered landslides is one of the most effective methods to develop an early warning system. Such thresholds are determined using a variety of rainfall parameters and have been successfully calculated for various regions of the world at different scales. Such thresholds can be used to forecast landslide events which could help in issuing an alert to civic authorities. A comprehensive study on the determination of rainfall thresholds characterizing landslide events for Bhutan is lacking. This paper focuses on defining event rainfall-duration thresholds for Chukha Dzongkhag, situated in south-west Bhutan. The study area is chosen due to the increase in frequency of landslides during monsoon along Phuentsholing-Thimphu highway, which passes through it and this highway is a major trade route of the country with the rest of the world. The present threshold method revolves around the use of a power law equation to determine event rainfall-duration thresholds. The thresholds have been established using available rainfall and landslide data for 2004-2014. The calculated threshold relationship is fitted to the lower boundary of the rainfall conditions leading to landslides and plotted in logarithmic coordinates. The results show that a rainfall event of 24 h with a cumulated rainfall of 53 mm can cause landslides. Later on, the outcome of antecedent rainfall varying from 3-30 days was also analysed to understand its effect on landslide incidences based on cumulative event rainfall. It is also observed that a minimum 10-day antecedent rainfall of 88 mm and a 20-day antecedent rainfall of 142 mm is required for landslide occurrence in the area. The thresholds presented can be improved with the availability of hourly rainfall data and the addition of more landslide data. These can also be used as an early warning system especially along the Phuentsholing-Thimphu Highway to prevent any disruptions of trade. initiated due to heavy monsoon precipitation and aggravated due to the increase in human activities. The increasing number of landslide events in Bhutan can be attributed to complex geological conditions, steep slopes, climate change, type of soil, and tectonic activity. Landslides in Bhutan mostly occur during the monsoons during which the torrential rainfall leads to several flash floods and landslide triggering, cutting off many parts of south Bhutan from the rest.The relationship between the amount of rainfall associated with landslide occurrences is generally studied using either an empirical or physical based approach [4][5][6][7]. Physical process models are based on numerical models which study the relationship between rainfall, pore water pressure, soil type, and volumetric water content that can lead to slope instability. Such a study is usually site specific due to variation in soil prop...

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“…At a landslide-prone slope in Cervinanra (Campania, Italy), a significant improvement of the threshold performance was reported after rainfall characteristics were normalized by the measured soil moisture state from suction and soil water content sensors (Comegna et al 2016;Greco and Bogaard 2016). Segoni et al (2018b) reported a significant improvement of the forecast quality of a rainfall-based LEWS in Emilia Romagna (Italy) by replacing the antecedent rainfall component with a modelled soil moisture value averaged over specific territorial units. Satellite-derived soil moisture estimates were used for landslide early warning in the Italian regions of Umbria (Brocca et al 2016) and Emilia Romagna (Zhuo et al 2019), as well as the San Francisco Bay Area (CA, USA; Thomas et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessing the potential of soil moisture measurements for regional landslide early warning

et al. 2020

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In mountainous terrain, rainfall-induced landslides pose a serious risk to people and infrastructure. Regional landslide early warning systems (LEWS) have proven to be a cost-efficient tool to inform the public about the imminent landslide danger. While most operational LEWS are based on rainfall exceedance thresholds only, recent studies have demonstrated an improvement of the forecast quality after the inclusion of soil hydrological information. In this study, the potential of in situ soil moisture measurements for regional landslide early warning is assessed. For the first time, a comprehensive soil moisture measurement database was compiled for Switzerland and compared with a national landslide database (Swiss flood and landslide damage database, WSL). The time series were homogenized and normalized to represent saturation values. From ensembles of sensors, the mean and standard deviation saturation were calculated and infiltration events were delimited, characterized, and classified as landslidetriggering or non-triggering based on the occurrence of landslides within a specified forecast distance. A logistic regression function was applied to model the landslide activity based on the infiltration event characteristics and several models were analysed and compared with receiver operating characteristics (ROC). A strong distance dependence becomes apparent showing a forecast goodness decrease with increasing distance between water content measurement site and landslide, and a better forecast goodness for long-lasting as opposed to short-duration precipitation events. While most variability can be explained by the two event properties antecedent saturation and change of saturation during an infiltration event, event properties that describe antecedent conditions are more important for long-lasting as opposed to shortduration precipitation events that can be better explained by properties describing event dynamics. Overall, the analysis demonstrated that in situ soil moisture data effectively contains specific information useful for landslide early warning.

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

Cited by 93 publications

References 25 publications

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

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

Estimating Rainfall Thresholds for Landslide Occurrence in the Bhutan Himalayas

Assessing the potential of soil moisture measurements for regional landslide early warning

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