scholarly journals Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds

2019 ◽  
Vol 574 ◽  
pp. 276-287 ◽  
Author(s):  
Binru Zhao ◽  
Qiang Dai ◽  
Dawei Han ◽  
Huichao Dai ◽  
Jingqiao Mao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Rainfall Thresholds ◽  
Moisture Conditions ◽  
Probabilistic Thresholds

Exploring the potential of soil moisture reanalysis data for improving the identification of regional landslide triggering thresholds

2021 ◽  
Author(s):  
Nunziarita Palazzolo ◽  
David J. Peres ◽  
Enrico Creaco ◽  
Antonino Cancelliere
Keyword(s):  
Soil Moisture ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Rainfall Duration ◽  
Soil Moisture Data ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Different Depths ◽  
Moisture Conditions ◽  
Landslide Triggering

<p>Landslide triggering thresholds provide the rainfall conditions that are likely to trigger landslides, therefore their derivation is key for prediction purposes. Different variables can be considered for the identification of thresholds, which commonly are in the form of a power-law relationship linking rainfall event duration and intensity or cumulated event rainfall. The assessment of such rainfall thresholds generally neglects initial soil moisture conditions at each rainfall event, which are indeed a predisposing factor that can be crucial for the proper definition of the triggering scenario. Thus, more studies are needed to understand whether and the extent to which the integration of the initial soil moisture conditions with rainfall thresholds could improve the conventional precipitation-based approach. Although soil moisture data availability has hindered such type of studies, yet now this information is increasingly becoming available at the large scale, for instance as an output of meteorological reanalysis initiatives. In particular, in this study, we focus on the use of the ERA5-Land reanalysis soil moisture dataset. Climate reanalysis combines past observations with models in order to generate consistent time series and the ERA5-Land data actually provides the volume of water in soil layer at different depths and at global scale. Era5-Land project is, indeed, a global dataset at 9 km horizontal resolution in which atmospheric data are at an hourly scale from 1981 to present. Volumetric soil water data are available at four depths ranging from the surface level to 289 cm, namely 0-7 cm, 7-28 cm, 28-100 cm, and 100-289 cm. After collecting the rainfall and soil moisture data at the desired spatio-temporal resolution, together with the target data discriminating landslide and no-landslide events, we develop automatic triggering/non-triggering classifiers and test their performances via confusion matrix statistics. In particular, we compare the performances associated with the following set of precursors: a) event rainfall duration and depth (traditional approach), b) initial soil moisture at several soil depths, and c) event rainfall duration and depth and initial soil moisture at different depths. The approach is applied to the Oltrepò Pavese region (northern Italy), for which the historical observed landslides have been provided by the IFFI project (Italian landslides inventory). Results show that soil moisture may allow an improvement in the performances of the classifier, but that the quality of the landslide inventory is crucial.</p>

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias, NW Spain)

Landslides ◽  
2017 ◽  
Vol 15 (2) ◽  
pp. 273-282 ◽  
Author(s):  
Pablo Valenzuela ◽  
María José Domínguez-Cuesta ◽  
Manuel Antonio Mora García ◽  
Montserrat Jiménez-Sánchez
Keyword(s):  
Soil Moisture ◽  
Nw Spain ◽  
Rainfall Thresholds ◽  
Moisture Conditions

scholarly journals Modeling Antecedent Soil Moisture to Constrain Rainfall Thresholds for Shallow Landslides Occurrence

2020 ◽  
Author(s):  
Maurizio Lazzari ◽  
Marco Piccarreta ◽  
Ram L. Ray ◽  
Salvatore Manfreda
Keyword(s):  
Soil Moisture ◽  
Rainfall Intensity ◽  
Shallow Landslide ◽  
Rainfall Thresholds ◽  
Antecedent Soil Moisture ◽  
Correct Definition ◽  
Triggering Conditions ◽  
Definition Of ◽  
Moisture Conditions ◽  
Traditional Approaches

Rainfall-triggered shallow landslide events have caused losses of human lives and millions of euros in damage to property in all parts of the world. The need to prevent such hazards combined with the difficulty of describing the geomorphological processes over regional scales led to the adoption of empirical rainfall thresholds derived from records of rainfall events triggering landslides. These rainfall intensity thresholds are generally computed, assuming that all events are not influenced by antecedent soil moisture conditions. Nevertheless, it is expected that antecedent soil moisture conditions may provide critical support for the correct definition of the triggering conditions. Therefore, we explored the role of antecedent soil moisture on critical rainfall intensity-duration thresholds to evaluate the possibility of modifying or improving traditional approaches. The study was carried out using 326 landslide events that occurred in the last 18 years in the Basilicata region (southern Italy). Besides the ordinary data (i.e., rainstorm intensity and duration), we also derived the antecedent soil moisture conditions using a parsimonious hydrological model. These data have been used to derive the rainfall intensity thresholds conditional on the antecedent saturation of soil quantifying the impact of such parameters on rainfall thresholds.

scholarly journals The role of geomorphology, rainfall and soil moisture in the occurrence of landslides triggered by 2018 Typhoon Mangkhut in the Philippines

2020 ◽  
Author(s):  
Clàudia Abancó ◽  
Georgina L. Bennett ◽  
Adrian J. Matthews ◽  
Mark A. Matera ◽  
Fibor J. Tan
Keyword(s):  
Soil Moisture ◽  
The Philippines ◽  
Intense Rainfall ◽  
Triggering Mechanism ◽  
Rainfall Thresholds ◽  
Rainfall Events ◽  
Satellite Rainfall ◽  
Moisture Conditions ◽  
Triggering Rainfall

Abstract. In 2018, Typhoon Mangkhut (locally known as Typhoon Ompong) triggered thousands of landslides in the area of Itogon (Philippines). A landslide inventory of 1101 landslides over a 570 km2 area is used to study the geomorphological characteristics and land cover more prone to landsliding as well as the rainfall and soil moisture conditions that led to widespread failure. Landslides mostly occurred in slopes covered by wooded grassland in clayey materials, predominantly facing East–Southeast. The analysis of both satellite rainfall (GPM IMERG) and soil moisture (SMAP-L4) finds that, in addition to rainfall from the typhoon, soil water content plays an important role in the triggering mechanism. Rainfall associated with Typhoon Mangkhut is compared with 33 high intensity rainfall events that did not trigger regional landslide events in 2018 and with previously published rainfall thresholds. Results show that: (a) it was one of the most intense rainfall events in the year but not the highest, and (b) despite satellite data tending to underestimate intense rainfall, previous published regional and global thresholds are to be too low to discriminate between landslide triggering and non-triggering rainfall events. This work highlights the potential of satellite products for hazard assessment and early warning in areas of high landslide activity where ground-based data is scarce.

scholarly journals Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

2017 ◽  
Vol 44 ◽  
pp. 79-88 ◽  
Author(s):  
Giuseppina Brigandì ◽  
Giuseppe Tito Aronica ◽  
Brunella Bonaccorso ◽  
Roberto Gueli ◽  
Giuseppe Basile
Keyword(s):  
Soil Moisture ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Rainfall Runoff ◽  
Rainfall Thresholds ◽  
Rainfall Runoff Model ◽  
Moisture Conditions ◽  
Runoff Model ◽  
Scs Cn

Abstract. The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall–streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall–runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall–runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002–2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

Flash flood warning based on rainfall thresholds and soil moisture conditions: An assessment for gauged and ungauged basins

2008 ◽  
Vol 362 (3-4) ◽  
pp. 274-290 ◽  
Author(s):  
Daniele Norbiato ◽  
Marco Borga ◽  
Silvia Degli Esposti ◽  
Eric Gaume ◽  
Sandrine Anquetin
Keyword(s):  
Soil Moisture ◽  
Flash Flood ◽  
Ungauged Basins ◽  
Rainfall Thresholds ◽  
Flood Warning ◽  
Moisture Conditions

Evaluation of Presswheels and Seed Coverers for Direct Seeding of Brassica

HortScience ◽  
1997 ◽  
Vol 32 (4) ◽  
pp. 599E-600
Author(s):  
Regina P. Bracy ◽  
Richard L. Parish
Keyword(s):  
Soil Moisture ◽  
Sandy Loam ◽  
Visual Observation ◽  
Mustard Seed ◽  
High Soil Moisture ◽  
Loam Soil ◽  
Direct Seeded ◽  
Plant Emergence ◽  
Moisture Conditions ◽  
Determine Effect

Improved stand establishment of direct-seeded crops has usually involved seed treatment and/or seed covers. Planters have been evaluated for seed/plant spacing uniformity, singulation, furrow openers, and presswheel design; however, effects of presswheels and seed coverers on plant establishment have not been widely investigated. Five experiments were conducted in a fine sandy loam soil to determine effect of presswheels and seed coverers on emergence of direct-seeded cabbage and mustard. Seed were planted with Stanhay 870 seeder equipped with one of four presswheels and seed coverers. Presswheels included smooth, mesh, concave split, and flat split types. Seed coverers included standard drag, light drag, paired knives, and no coverer. Soil moisture at planting ranged from 8% to 19% in the top 5 cm of bed. Differences in plant counts taken 2 weeks after planting were minimal with any presswheel or seed coverer. Visual observation indicated the seed furrow was more completely closed with the knife coverer in high soil moisture conditions. All tests received at least 14 mm of precipitation within 6 days from planting, which may account for lack of differences in plant emergence.

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