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

2021 ◽  
Vol 21 (5) ◽  
pp. 1531-1550
Author(s):  
Clàudia Abancó ◽  
Georgina L. Bennett ◽  
Adrian J. Matthews ◽  
Mark Anthony M. Matera ◽  
Fibor J. Tan
Keyword(s):  
Soil Moisture ◽  
High Intensity ◽  
The Philippines ◽  
Saturation Point ◽  
Rainfall Events ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
First Time

Abstract. In 2018 Typhoon Mangkhut (locally known as Typhoon Ompong) triggered thousands of landslides in the Itogon region of the Philippines. A landslide inventory of the affected region is compiled for the first time, comprising 1101 landslides over a 570 km2 area. The inventory is used to study the geomorphological characteristics and land cover more prone to landsliding as well as the hydrometeorological conditions that led to widespread failure. The results showed that landslides mostly occurred on grassland and wooded slopes of clay superficial geology, predominantly facing east-southeast. Rainfall (Integrated Multi-satellitE Retrievals for Global Precipitation Measurement, IMERG GPM) associated with Typhoon Mangkhut is compared with 33 high-intensity rainfall events that did not trigger regional landslide events in 2018. Results show that landslides occurred during high-intensity rainfall that coincided with the highest soil moisture values (estimated clays saturation point), according to Soil Moisture Active Passive level 4 (SMAP-L4) data. Our results demonstrate the potential of SMAP-L4 and GPM IMERG data for landslide hazard assessment and early warning where ground-based data are scarce. However, other rainfall events in the months leading up to Typhoon Mangkhut that had similar or higher rainfall intensities and also occurred when soils were saturated did not trigger widespread landsliding, highlighting the need for further research into the conditions that trigger landslides in typhoons.

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 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

Endogenous jasmonates in dry and imbibed sunflower seeds from plants grown at different soil moisture contents

2007 ◽  
Vol 17 (2) ◽  
pp. 91-98 ◽  
Author(s):  
Ana Vigliocco ◽  
Sergio Alemano ◽  
Otto Miersch ◽  
Daniel Alvarez ◽  
Guillermina Abdala
Keyword(s):  
Soil Moisture ◽  
Environmental Conditions ◽  
Differential Sensitivity ◽  
Sunflower Seeds ◽  
Seed Progeny ◽  
Hormonal Content ◽  
Tolerant Line ◽  
Sensitive Line ◽  
Moisture Conditions

AbstractIn this study, we characterized two sunflower (Helianthus annuus L.) lines with differential sensitivity to drought, the sensitive line B59 and the tolerant line B71. Using both lines, we compared the content of endogenous jasmonates (JAs) in dry and imbibed seeds from plants grown under irrigation and drought. Jasmonic acid (JA), 12-oxo-phytodienoic acid (OPDA), 11-hydroxyjasmonate (11-OH-JA) and 12-hydroxyjasmonate (12-OH-JA) were detected in dry and imbibed sunflower seeds. Seeds from plants grown under drought had a lower content of total JAs and exhibited higher germination percentages than seeds from irrigated plants, demonstrating that environmental conditions have a strong influence on the progeny. OPDA and 12-OH-JA were the main compounds found in dry seeds of both lines. Imbibed seeds showed an enhanced amount of total JAs with respect to dry seeds produced by plants grown in both soil moisture conditions. Imbibition triggered a dramatic OPDA increase in the embryo, suggesting a role of this compound in germination. We conclude that JAs patterns vary during sunflower germination and that the environmental conditions experienced by the mother plant modify the hormonal content of the seed progeny.

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.

A review of the role of excess soil moisture conditions in constraining farm practices under Atlantic conditions

2012 ◽  
Vol 28 (4) ◽  
pp. 580-589 ◽  
Author(s):  
R. P. O. Schulte ◽  
R. Fealy ◽  
R. E. Creamer ◽  
W. Towers ◽  
T. Harty ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Conditions

scholarly journals Qualitative soil moisture assessment in semi-arid Africa: the role of experience and training on inter-rater reliability

2015 ◽  
Vol 12 (3) ◽  
pp. 3029-3058
Author(s):  
M. Rinderer ◽  
H. Komakech ◽  
D. Müller ◽  
J. Seibert
Keyword(s):  
Soil Moisture ◽  
Classification Scheme ◽  
Functional Relation ◽  
Soil Surface ◽  
Arid Environment ◽  
Rater Reliability ◽  
Moisture Conditions ◽  
And Training ◽  
Semi Arid

Abstract. Soil and water management is particularly relevant in semi-arid regions to enhance agricultural productivity. During periods of water scarcity soil moisture differences are important indicators of the soil water deficit and are traditionally used for allocating water resources among farmers of a village community. Here we present a simple, inexpensive soil wetness classification scheme based on qualitative indicators which one can see or touch on the soil surface. It incorporates the local farmers' knowledge on the best soil moisture conditions for seeding and brick making in the semi-arid environment of the study site near Arusha, Tanzania. The scheme was tested twice in 2014 with farmers, students and experts (April: 40 persons, June: 25 persons) for inter-rater reliability, bias of individuals and functional relation between qualitative and quantitative soil moisture values. During the test in April farmers assigned the same wetness class in 46% of all cases while students and experts agreed in about 60% of all cases. Students who had been trained in how to apply the method gained higher inter-rater reliability than their colleagues with only a basic introduction. When repeating the test in June, participants were given improved instructions, organized in small sub-groups, which resulted in a higher inter-rater reliability among farmers. In 66% of all classifications farmers assigned the same wetness class and the spread of class assignments was smaller. This study demonstrates that a wetness classification scheme based on qualitative indicators is a robust tool and can be applied successfully regardless of experience in crop growing and education level when an in-depth introduction and training is provided. The use of a simple and clear layout of the assessment form is important for reliable wetness class assignments.

scholarly journals Qualitative soil moisture assessment in semi-arid Africa – the role of experience and training on inter-rater reliability

2015 ◽  
Vol 19 (8) ◽  
pp. 3505-3516 ◽  
Author(s):  
M. Rinderer ◽  
H. C. Komakech ◽  
D. Müller ◽  
G. L. B. Wiesenberg ◽  
J. Seibert
Keyword(s):  
Soil Moisture ◽  
Classification Scheme ◽  
Functional Relation ◽  
Soil Surface ◽  
Arid Environment ◽  
Rater Reliability ◽  
Moisture Conditions ◽  
And Training ◽  
Semi Arid

Abstract. Soil and water management is particularly relevant in semi-arid regions to enhance agricultural productivity. During periods of water scarcity, soil moisture differences are important indicators of the soil water deficit and are traditionally used for allocating water resources among farmers of a village community. Here we present a simple, inexpensive soil wetness classification scheme based on qualitative indicators which one can see or touch on the soil surface. It incorporates the local farmers' knowledge on the best soil moisture conditions for seeding and brick making in the semi-arid environment of the study site near Arusha, Tanzania. The scheme was tested twice in 2014 with farmers, students and experts (April: 40 persons, June: 25 persons) for inter-rater reliability, bias of individuals and functional relation between qualitative and quantitative soil moisture values. During the test in April farmers assigned the same wetness class in 46 % of all cases, while students and experts agreed on about 60 % of all cases. Students who had been trained in how to apply the method gained higher inter-rater reliability than their colleagues with only a basic introduction. When repeating the test in June, participants were given improved instructions, organized in small subgroups, which resulted in a higher inter-rater reliability among farmers. In 66 % of all classifications, farmers assigned the same wetness class and the spread of class assignments was smaller. This study demonstrates that a wetness classification scheme based on qualitative indicators is a robust tool and can be applied successfully regardless of experience in crop growing and education level when an in-depth introduction and training is provided. The use of a simple and clear layout of the assessment form is important for reliable wetness class assignments.

scholarly journals Soil moisture as determinant of the seasonal soil co2 emission: evidence from central siberia

2021 ◽  
Author(s):  
Anastasia Vladimirovna Makhnykina ◽  
Ivan Ivanovich Tychkov ◽  
Anatoly Stanislavovich Prokushkin ◽  
Anton Igorevich Pyzhev ◽  
Eugene Alexandrovich Vaganov
Keyword(s):  
Soil Moisture ◽  
Forest Ecosystems ◽  
Exponential Model ◽  
Additional Parameter ◽  
Direct Measurements ◽  
Different Types ◽  
Microclimatic Conditions ◽  
Moisture Conditions ◽  
Soil Emission

Abstract Background The soils of the boreal zone contain significant reserves of carbon, therefore, their response to current climate changes will significantly affect the sustainability of forest ecosystems and the future concentration of CO 2 in the atmosphere. When modeling soil emission, it is necessary to focus on the main soil environment factors. In this paper, a simple exponential model of the soil CO 2 emissions growth was modified by introducing an additional parameter - the threshold soil moisture in different types of ecosystems based on the direct measurements. Results The developed model adequately reflects the dynamic changes in soil emission for different types of ecosystems. This result was achieved by including moisture as a second environmental factor besides temperature, describing changes in soil CO 2 emissions during the summer period. The error of direct measurements for all measuring seasons was about 20% of the values of direct measurements of the CO 2 flux. Note that such a high error was observed once per season in early and mid-June, reaching 60-80% on some days. Our models demonstrate in the season with the highest amount of precipitation the smallest differences in modeled fluxes about 15-20%, which indirectly indicates that the emission flux is not inhibited by insufficient moisture in this season. Conclusions The final model application depends on the characteristics of the microclimatic conditions of a particular ecosystem, namely, a factor that has a limiting effect on the biological processes. When studying the functional role of boreal forest ecosystems the moisture conditions consideration is crucial to explain the atmospheric CO 2 emission processes.

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