Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study of the Torgiovannetto Landslide in Central Italy

Abstract

Predicting the spatial and temporal occurrence of rainfall triggered landslides represents an important scientific and operational issue due to the high threat that they pose to human life and property. This study investigates the relationship between rainfall, soil moisture conditions and landslide movement by using recorded movements of a rock slope located in central Italy, the Torgiovannetto landslide. This landslide is a very large rock slide, threatening county and state roads. Data acquired by a network of extensometers and a meteorological station clearly indicate that the movements of the unstable wedge, first detected in 2003, are still proceeding and the alternate phases of quiescence and reactivation are associated with rainfall patterns. By using a multiple linear regression approach, the opening of the tension cracks (as recorded by the extensometers) as a function of rainfall and soil moisture conditions prior the occurrence of rainfall, are 1233 correlation coefficient, r) significantly enhances if an indicator of the soil moisture conditions is included. Specifically, r is equal to 0.40 when only rainfall is used as a predictor variable and increases to r = 0.68 and r = 0.85 if the API and the SWI are used respectively. Therefore, the coarse spatial resolution (25 km) of satellite data notwithstanding, the ASCAT SWI is found to be very useful for the prediction of landslide movements on a local scale. These findings, although valid for a specific area, present new opportunities for the effective use of satellite-derived soil moisture estimates to improve landslide forecasting.

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

“…Specifically, in Brocca et al (2013) the model was validated exactly in the same study area by obtaining reliable and satisfactory results. Based on previous studies, the accuracy (RMSE) of SWBM was found to range between 0.02 and 0.04 m 3 m −3 when compared with in situ measurements.…”

Soil Moisture for Hydrological Applications: Open Questions and New Opportunities

“…Similarly, a limited number of stations can be used for the validation of coarse scale satellite soil moisture products, as indirectly demonstrated by the high correlations that are frequently obtained between coarse scale (~20 km) and point scale (~5 cm) measurements (e.g., [57][58][59]). Vice versa, coarse scale measurements, as obtained by remote sensing, can be used for regional or local studies (e.g., [11,86]). In summary, the temporal stability concept allows to mitigate the spatial discrepancies between point measurements and the scale needed in the applications.…”

“…Soil moisture governs the partitioning of the mass and energy fluxes between the land and the atmosphere, thus playing a key role in the assessment of the different components of the water and energy balance. Soil moisture is an important variable for flood and landslide modelling and prediction [9][10][11][12], for drought assessment and forecasting [13][14][15], and for numerical weather prediction [16][17][18][19], to cite a few. Soil moisture is also the water source for plants and, hence, its knowledge is required for irrigation management and agricultural studies [20].…”

Evaluation of satellite soil moisture products over Norway using ground-based observations

“…The use of observations from satellites has become a powerful tool to enhance our understanding of the role of soil moisture in the hydrological cycle in a number of areas, e.g., land-atmosphere processes (Miralles et al, 2012;Taylor et al, 2012); weather and runoff forecasts (Brocca et al, 2010;Bisselink et al, 2011); landslides (Brocca et al, 2012b); and rainfall products (Chen et al, 2012). Since 2000 several satellite missions measuring soil moisture have been launched: e.g., the Advanced Microwave Sounding Radiometer for EOS (AMSR-E) (Njoku and Chan, 2006), the Advanced SCATterometer (ASCAT) (Bartalis et al, 2007b), and the Soil Moisture Ocean Salinity (SMOS) .…”