Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Snowmelt influence in shallow landslides

View through CrossRef
<p>Mass wasting is a major landform shaping process in mountainous and steep terrains, and Italy is among the most affected countries in Europe. Lombardia region has 130.450 landslides mapped, covering an area of 3.300 km<sup>2</sup> (i.e. 7.2% of the regional area). The 41% of landslides in Lombardia are rapid mass movements involving shallow soils, occurring mainly in the Alps and Fore-Alps. Many shallow landslides (SLs) result from infrequent meteorological events, inducing unstable conditions, or accelerate movements on otherwise stable slopes. In mountainous areas such as the Alps of Lombardia region, snowmelt concurs with rainfall intensity, and duration in setting the hydrologic conditions favorable to the occurrence of SLs. However, snowmelt contribution to SLs triggering is little investigated hitherto.  In regions experiencing seasonal snowmelt in spring and summer, melting water thereby could decrease the intensity and duration of rainfall needed for SL initiation, or even lead to LSs in dry weather conditions.  </p><p>Under the umbrella of the project MHYCONOS, a project founded by Fondazione CARIPLO, we developed a robust, and parameter wise parsimonious model, that mimics the triggering mechanism of shallow landslides by accounting for the combined effect of precipitation duration and intensity in, and snowmelt at thaw. The model is applied to the case study of Tartano basin, paradigmatic of SLs in the Alps of Lombardia, where in July 1987 a SL event produced 30 fatalities.</p><p>Our results show that about 37% of the Tartano Basin slopes display unstable condition, and more than 50% therein is influenced by soil moisture variation. Using a traditional (i.e. rainfall based) approach, occurrence of shallow landslides is predicted only during rainy periods, mainly October and November. In contrast, when including snow melt, the model mimics failures potentially also during April and May, when melting rate is the highest, and may increase triggering potential of rainfall. Currently, our efforts are aimed to conduct interviews and construct temporally based datasets, where occurrences of snow melt driven failures can be evidenced.</p><p>Risk perception by population may change, and public authority may be prepared to implement emergency plans in order to prevent injuries, causalities and damages to infrastructures also during spring time, when shallow landslides may occur in response to fast snow melt, even during clear sky days, in lack of precipitation.</p><p> </p>
Title: Snowmelt influence in shallow landslides
Description:
<p>Mass wasting is a major landform shaping process in mountainous and steep terrains, and Italy is among the most affected countries in Europe.
Lombardia region has 130.
450 landslides mapped, covering an area of 3.
300 km<sup>2</sup> (i.
e.
7.
2% of the regional area).
The 41% of landslides in Lombardia are rapid mass movements involving shallow soils, occurring mainly in the Alps and Fore-Alps.
Many shallow landslides (SLs) result from infrequent meteorological events, inducing unstable conditions, or accelerate movements on otherwise stable slopes.
In mountainous areas such as the Alps of Lombardia region, snowmelt concurs with rainfall intensity, and duration in setting the hydrologic conditions favorable to the occurrence of SLs.
However, snowmelt contribution to SLs triggering is little investigated hitherto.
 In regions experiencing seasonal snowmelt in spring and summer, melting water thereby could decrease the intensity and duration of rainfall needed for SL initiation, or even lead to LSs in dry weather conditions.
 </p><p>Under the umbrella of the project MHYCONOS, a project founded by Fondazione CARIPLO, we developed a robust, and parameter wise parsimonious model, that mimics the triggering mechanism of shallow landslides by accounting for the combined effect of precipitation duration and intensity in, and snowmelt at thaw.
The model is applied to the case study of Tartano basin, paradigmatic of SLs in the Alps of Lombardia, where in July 1987 a SL event produced 30 fatalities.
</p><p>Our results show that about 37% of the Tartano Basin slopes display unstable condition, and more than 50% therein is influenced by soil moisture variation.
Using a traditional (i.
e.
rainfall based) approach, occurrence of shallow landslides is predicted only during rainy periods, mainly October and November.
In contrast, when including snow melt, the model mimics failures potentially also during April and May, when melting rate is the highest, and may increase triggering potential of rainfall.
Currently, our efforts are aimed to conduct interviews and construct temporally based datasets, where occurrences of snow melt driven failures can be evidenced.
</p><p>Risk perception by population may change, and public authority may be prepared to implement emergency plans in order to prevent injuries, causalities and damages to infrastructures also during spring time, when shallow landslides may occur in response to fast snow melt, even during clear sky days, in lack of precipitation.
</p><p> </p>.

Related Results

Influence of Cumulative Rainfall on the Occurrence of Landslides in Korea
Influence of Cumulative Rainfall on the Occurrence of Landslides in Korea
This study presents the impact of cumulative rainfall on landslides, following the analysis of cumulative rainfall for 20 days before the landslide. For the 1520 landslides analyze...
Spatial correlation between landslides and geotechnical factors using Random Forest and SHAP
Spatial correlation between landslides and geotechnical factors using Random Forest and SHAP
The activation as well as the consequences of landslides are difficult to predict, as they depend on factors characterized by large variability and uncertainties. The aim of this s...
Detection and Characterization of Active Landslides with Multisource SAR Data and Remote Sensing in Western Guizhou, China
Detection and Characterization of Active Landslides with Multisource SAR Data and Remote Sensing in Western Guizhou, China
Abstract The western part of Guizhou is located in the second step of East Asia. Although the area is stratigraphically continuous and the surface is dominated by hard lime...
Rapid Hazard Assessment Model for the Extreme Rainfall-induced Regional Clustered Shallow Landslides
Rapid Hazard Assessment Model for the Extreme Rainfall-induced Regional Clustered Shallow Landslides
The undertaking of stability analysis and impact range prediction of rainfall-induced shallow landslides at the regional scale is of great significance for landslides' early warnin...
Landslide Hazard Zonation and Evaluation around Debre Werk Town, North West Ethiopia
Landslide Hazard Zonation and Evaluation around Debre Werk Town, North West Ethiopia
Abstract The present research was conducted in the town of Debre Werk, East Gojjam, North West Ethiopia, with the ultimate aim of conducting a Landslide Hazard Zonation and...
Automatic regional identification of active and inactive landslides using satellite image analysis
Automatic regional identification of active and inactive landslides using satellite image analysis
Over the past decades, landslides have significantly affected extensive areas worldwide due to changing environmental conditions and human activities, causing major problems in the...
Accounting for interannual variability in dust accelerated snowmelt in process-based hydrologic prediction, Rocky Mountains, USA
Accounting for interannual variability in dust accelerated snowmelt in process-based hydrologic prediction, Rocky Mountains, USA
Seasonal mountain snowmelt is an important contributor to surface water resources and groundwater recharge in the midlatitudes, making forecasting of snowmelt timing and duration c...
Forest impacts on snow accumulation and melt in a semi-arid mountain environment
Forest impacts on snow accumulation and melt in a semi-arid mountain environment
Snowmelt is complex under heterogeneous forest cover due to spatially variable snow surface energy and mass balances and snow accumulation. Forest canopies influence the under-cano...

Back to Top