Intensity-duration Thresholds Research Articles

Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment

Abstract. Debris flows triggered by rainfall are catastrophic geohazards that occur compounded during extreme events. Few early warning systems for shallow landslides and debris flows at the territorial scale use thresholds of rainfall intensity–duration (ID). ID thresholds are mostly defined using hourly rainfall. Due to instrumental and operational challenges, current early warning systems have difficulty forecasting sub-daily time series of weather for landslides in the Himalayas. Here, we present a framework that employs a spatio-temporal numerical model preceded by the Weather Research And Forecast (WRF) Model for analysing debris flows induced by rainfall. The WRF model runs at 1.8 km × 1.8 km resolution to produce hourly rainfall. The hourly rainfall is then used as an input boundary condition in the spatio-temporal numerical model for debris flows. The debris flow model is an updated version of Van Asch et al. (2014) in which sensitivity to volumetric water content, moisture-content-dependent hydraulic conductivity, and seepage routines are introduced within the governing equations. The spatio-temporal numerical model of debris flows is first calibrated for the mass movements in the Kedarnath catchment that occurred during the 2013 North India floods. Various precipitation intensities based on the glossary of the India Meteorological Department (IMD) are set, and parametric numerical simulations are run identifying ID thresholds of debris flows. Our findings suggest that the WRF model combined with the debris flow numerical model shall be used to establish ID thresholds in territorial landslide early warning systems (Te-LEWSs).

Optimization of rainfall thresholds for landslide early warning through false alarm reduction and a multi-source validation

AbstractThis study proposes an innovative approach to develop a regional-scale landslide forecasting model based on rainfall thresholds optimized for operational early warning. In particular, it addresses two main issues that usually hinder the operational implementation of this kind of models: (i) the excessive number of false alarms, resulting in civil protection system activation without any real need, and (ii) the validation procedure, usually performed over periods too short to guarantee model reliability. To overcome these limitations, several techniques for reducing the number of false alarms were applied in this study, and a multiple validation phase was conducted using data from different sources. An intensity-duration threshold system for each of the five alert zones composing the Liguria region (Italy) was identified using a semiautomatic procedure called MaCumBA, considering three levels of criticality: low, moderate, and high. The thresholds were developed using a landslide inventory collected from online newspapers by a data mining technique called SECaGN. This method was chosen to account for only those events that echo on the Internet and therefore impact society, ignoring landslides occurred in remote areas, not of interest for civil protection intervention, which would adversely affect the model performance because they would result in false alarms. A calibration phase was performed to minimize the impact of false alarms, allowing at least one false alarm per year over the moderate criticality level. In addition, an innovative approach to include antecedent rainfall as the third dimension of the intensity-duration thresholds was applied, generating a consistent reduction in false alarms. The results were validated through an independent landslide inventory and were compared with (i) the alert issued by the regional civil protection agency to observe the improvements achieved with the proposed model and to evaluate to what extent the proposed model is consistent with the assessments of the civil protection and (ii) a dataset of the national states of emergency to verify the suitability of the developed thresholds for alerting citizens. The thresholds obtained showed high predictive capabilities, confirming their suitability for implementation in an operational landslide early warning system.

Applying rainfall threshold estimates and frequency ratio model for landslide hazard assessment in the coastal mountain setting of South Asia

Landslides pose a serious risk to life and property in the mountainous regions around the globe. Understanding the interplay of landslide conditioning and triggering factors is essential for lessening the impacts caused by the hazard. Cox's Bazar — a coastal mountainous district in Bangladesh is recurrently affected by rainfall-triggered landslides. Based on analysis of 14 experiential landslides and combination of gauged and satellite rainfall estimates for the period from 2003 to 2019, the present study determines three landslide-triggering rainfall thresholds for the Cox's Bazar District (CBD): 1. Intensity-Duration (ID) threshold derived in this study revealed that any rainfall event with an intensity of ≥4.04 ​mm/h if prolonging for ≥12h can cause slope failures; 2. Event-Duration (ED) threshold suggested that a normalized cumulative event rainfall (EMAP) of 0.15 for one day is expected to trigger landslides; and 3. threshold calculated using randomly chosen antecedent rainfall expressed best distinction on 30-day rainfall and the equation of the threshold came out as Rth ​= ​64–0.02 Ra30. The recurrence probability of the derived antecedent rainfall threshold and likely landslides was determined through the Poisson distribution. Moreover, we assess the landslide susceptibility of the district with a coupled use of Frequency Ratio (FR) statistical measure and Geographic Information System (GIS). Considering the combined role of selected conditioning factors, the landslide susceptibility status of the CBD was quantified and classified into probability intervals. The accuracy of the susceptibility maps was assessed through the Relative Landslide Density Index (R-Index) that used a field landslide inventory, comprising well distributed 891 events. Moreover, gridded population data was superimposed on the derived susceptibility maps to understand the risk levels of people. The derivation of landslide-triggering rainfall thresholds and spatial susceptibility assessment has been useful to propose a low-cost Landslide Early Warning System (LEWS) which can contribute in alleviating the adverse effects of landslide hazard in the CBD.

I–D Threshold Analysis of Rainfall-Triggered Landslides Based on TRMM Precipitation Data in Wudu, China

This study explored the applicability of TRMM, TRMM nonlinear downscaling, and ANUSPLIN (ANU) interpolation of three different types of precipitation data to define regional-scale rainfall-triggered landslide thresholds. The spatial resolution of TRMM precipitation data was downscaled from 0.25° to 500 m by the downscaling model considering the relationship between humidity, NDVI, and numerous topographic factors and precipitation. The rainfall threshold was calculated using the rainfall intensity–duration threshold model. The calculation showed that TRMM downscaled precipitation data have better detection capability for extreme precipitation events than the other two, the TRMM downscaling threshold was better than the ANU interpolation, and the cumulative effective rainfall of TRMM downscaling was preferred as the macroscopic critical rainfall-triggered landslide threshold for the early warning of the Wudu. The predictive performance of the rainfall threshold of 50% was better than the other two (10% and 90%). When the probability of landslide occurrence was 50%, the TRMM downscaled threshold curve was given by I50=21.03×D−1.004. The authors also analyzed the influence of factors such as topography landform and soil type on the rainfall threshold of landslides in the study area. The rainfall intensity of small undulating mountains was higher than that of medium and large undulating mountains, and the rainfall intensity of landslides peaks at high altitude mountains of 3500–5000 m.

Hydro–Mechanical Behaviour of a Rainfall-Induced Landslide by Instrumental Monitoring: Landslide–Rainfall Threshold of the Western Black Sea Bartin Region of Türkiye

Bartin City is located in the Western Black Sea Region of Türkiye, where rainfall-induced landslides are more frequently observed. Although it is known that many landslides are induced by rainfall, there is limited knowledge regarding how rainfall triggers these landslides in the city. To clarify the triggering mechanisms of rainfall-induced landslides, a detailed field monitoring program was performed on a chosen area to represent landslides in Bartin. The instrumentation included the measurements of site suction, volumetric water content, groundwater level, and rainfall amount over a period of two years. Various stability analyses were performed regarding pore pressures after both transient flow infiltration analysis and site-measured suction values. The rainfall intensity–duration thresholds were obtained for both dry and wet periods as a result of the numerical analyses performed by means of parameters obtained from field monitoring. The results show that the wet period conditions create more critical conditions before failure compared to the dry period conditions, so landslides occur more easily in wet periods. According to the landslide–rainfall threshold relations, landslide-risk limits are reached if the rainfall intensity is over 10 mm/h for the dry periods and lasts between 0.85 h and 17 h depending on the saturated hydraulic conductivity of the soil. When the rainfall intensities are less than 10 mm/h, longer rainfall durations are needed for a landslide to occur. For the wet periods, landslide-risk situations are encountered if the rainfall intensity over 1 mm/h continues for 0.36 h–3.67 h, depending on the saturated hydraulic conductivities.

Rainfall early warning threshold and its spatial distribution of rainfall-induced landslides in China

In order to investigate the spatial distribution of early warning threshold for landslide induced by rainfall in China, the literatures about rainfall thresholds of landslides in China in recent 20 years are selected. Statistical analysis and visualization methods were employed to systematically analyze the research progress of rainfall early warning thresholds at various scales. Taking the typical rainfall intensity-duration (I-D) threshold model as the research object, combined with the geographical characteristics of China and the average annual rainfall of 20 years, the spatial distribution of early warning thresholds for rainfall-induced landslide in China is depicted. The results show that the inspired rain intensity coefficient α of the rainfall threshold (I-D curve) in China roughly increases gradually with the decrease of topography. Moreover, under consistent annual rainfall conditions, the scalar index β exhibits regular changes corresponding to variations in terrain. Topography and rainfall are the two main factors strongly associated with the rainfall threshold. This research establishes a clear framework for studying the early warning thresholds for rainfall-induced landslides in China and holds significant scientific implications for developing more effective rainfall threshold models.

Implementation of hydrometeorological thresholds for regional landslide warning in Catalonia (NE Spain)

Soil moisture plays a vital role in slope stability. As water infiltrates into the soil, shear strength decreases eventually leading to failure. However, most of the existing regional-scale landslide early warning systems (LEWS) rely solely on rainfall information and use rainfall thresholds to determine if the landslide triggering conditions are met. The original version of the Catalonia region LEWS combines real-time rainfall observations and susceptibility to compute warnings. The LEWS applies a set of rainfall intensity-duration thresholds to determine if the rainfall conditions have the potential to trigger a landslide. This work explores the potential of using modelled soil moisture data in the Catalonia region LEWS. Volumetric water content (VWC) from the LISFLOOD hydrological simulations of the European Flood Awareness System and rainfall estimates have been analysed at the location of recent landslide events. Based on this data, a set of empirical hydrometeorological thresholds combining rainfall and soil moisture information has been obtained for their application into the Catalonia region LEWS. The LEWS has been run for nine months (April–December 2020) using two approaches: (i) combining susceptibility and rainfall intensity-duration (I-D) thresholds and (ii) combining susceptibility and the new hydrometeorological thresholds including soil moisture information. Generally, both LEWS approaches issued moderate or high warnings in the areas where significant rainfall accumulations were recorded. The outputs have been compared at specific locations where landslides were reported during the analysed period. Results show that at the analysed locations false positives are generally reduced when employing the hydrometeorological thresholds in the LEWS. Therefore, this approach is promising and could help improve regional scale LEWS in Catalonia.

Quantify the effect of antecedent effective precipitation on rainfall intensity-duration threshold of debris flow

Quantify the effect of antecedent effective precipitation on rainfall intensity-duration threshold of debris flow

Feasibility of satellite-based rainfall and soil moisture data in determining the triggering conditions of debris flow: The Jiangjia Gully (China) case study

Heavy precipitation is the main trigger for debris-flow hazards. The antecedent moisture condition, which is usually represented by antecedent precipitation, is another hydrometeorological contributing factor to debris flows that originate from shallow landslides. Satellite techniques are an economical and effective way to access rainfall and soil wetness information to determine the triggering conditions of debris flow. However, satellite-based thresholds need to be compared with ground-based thresholds and adjusted to the data source prior to their application. In this study, rainfall intensity-duration (I-D) thresholds were derived from the early and final run products of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG-E and IMERG-F) and gauge measurements using logistic regression for debris flows in the Jiangjia Gully, Yunnan Province, southern China, which has a dense rain gauge network. Data from both the IMERG-E and IMERG-F covered the entire study period. Our evaluation revealed that the I-D threshold derived from the IMERG-E deviated from the gauge-based thresholds. Although the threshold determined by the IMERG-F was comparable to the ground-based ones, the presence of substantial false positives and false negatives indicated that its performance was weaker than that of the gauge-based ones. Furthermore, the IMERG-F was suitable if the nearest available gauge was farther than 10 km from the debris-flow initiation zone. We evaluated the feasibility of the surface soil moisture product provided by the Climate Change Initiative program of the European Space Agency (CCI-SM), root-zone soil moisture derived from the CCI-SM using an exponential filter (SM-RZ), and antecedent precipitation for improving the performance of the thresholds by separately using them as the third explanatory variable in addition to rainfall intensity and duration in logistic regression. Satellite soil moisture data were available for 54% of the study period. The results suggested that including antecedent precipitation effectively improved the performance of the thresholds. In contrast, the performance of the thresholds increased only slightly when the CCI-SM or SM-RZ was included. Although these findings are valid only for this study area and need to be assessed for other regions, they present new insights for using satellite rainfall and soil moisture estimates to define thresholds for debris flow.

Using principal component analysis to incorporate multi-layer soil moisture information in hydrometeorological thresholds for landslide prediction: an investigation based on ERA5-Land reanalysis data

Abstract. A key component for landslide early warning systems (LEWSs) is constituted by thresholds providing the conditions above which a landslide can be triggered. Traditionally, thresholds based on rainfall characteristics have been proposed, but recently, the hydrometeorological approach, combining rainfall with soil moisture or catchment storage information, is becoming widespread. Most of the hydrometeorological thresholds proposed in the literature use the soil moisture from a single layer (i.e., depth or depth range). On the other hand, multi-layered soil moisture information can be measured or can be available from reanalysis projects as well as from hydrological models. Approaches using this multi-layered information are lacking, perhaps because of the need to keep the thresholds simple and two-dimensional. In this paper, we propose principal component analysis (PCA) as an approach for deriving two-dimensional hydrometeorological thresholds that use multi-layered soil moisture information. To perform a more objective assessment we also propose a piecewise linear equation for the identification of the threshold's shape, which is more flexible than traditional choices (e.g., power law or bilinear). Comparison of the receiver operating characteristic (ROC) (true skill statistic, TSS) of thresholds based on single- and multi-layered soil moisture information also provides a novel tool for identifying the significance of multi-layered information on landslide triggering in a given region. Results for Sicily island, considering the ERA5-Land reanalysis soil moisture data (available at four different depth layers), corroborate the advantages of the hydrometeorological approach gained in spite of the coarse spatial resolution and the limited accuracy of reanalysis data. Specifically, the TSS of traditional precipitation intensity–duration thresholds is equal to 0.5, while those of the proposed hydrometeorological thresholds is significantly higher (TSS=0.71). For the analyzed region, however, multi-layered information seems not to be relevant, as performances in terms of TSS are similar to those obtained with single-layer soil moisture at the upper depths, namely 0–7 and 7–28 cm, which can imply that in Sicily landslide phenomena are mainly influenced by soil moisture in most shallow soil layers.

Triggering rainfall intensities for post-wildfire debris flows in the Sonoran Desertscrub plant community

Wildfire makes landscapes more vulnerable to debris flows by reducing soil infiltration capacity and decreasing vegetation cover. The extent to which fire affects debris-flow processes depends on the severity of the fire, the climatology of intense rainfall, the pre-fire plant community, and sediment supply, among other factors. As fire expands into new plant communities and geographic regions, there is a corresponding need to expand efforts to document fire-induced changes and their impacts on debris-flow processes. In recent years, several large wildfires have impacted portions of the Sonoran Desertscrub plant community in Arizona, USA, a plant community where fire has been historically infrequent. Following two of these fires, we monitored debris-flow activity at the watershed scale and quantified wildfire-driven changes in soil hydraulic properties using in-situ measurements with mini disk tension infiltrometers. Results indicate that rainfall intensity-duration thresholds for the initiation of post-fire debris flows in recently burned watersheds within the Sonoran Desertscrub plant community are substantially greater than those in nearby areas dominated by other plant communities, such as chaparral. Results provide insight into the impact of fire on debris-flow processes in a plant community where it is likely to be more impactful in the future and help expand existing post-fire debris flow databases into a plant community where there is a paucity of observations.

Objective definition of discharge thresholds for post-fire debris flows

Runoff-generated debris flows are a common post-fire hazard in the western United States and a growing number of regions around the world. As wildfire continues to emerge across a broader range of geographic regions and plant communities, there is an increasing need for generalizable methods to predict post-fire debris-flow initiation. The prediction of post-fire debris flow during intense rainstorms has traditionally relied upon empirical rainfall thresholds. Rainfall intensity-duration thresholds are often developed based on rainfall data and the hydrologic response to those rainstorms. They are most applicable to the specific regions where data are collected. Here, we present a new predictive approach that utilises processes-based models with fundamental physics and machine learning methods to estimate discharge thresholds for runoff-generated debris-flow initiation in four recently burned areas in the western United States. We assess the performance of the objectively defined discharge threshold-based predictions for post-fire debris-flow initiation from our hybrid framework, which utilises debris-flow timing within rainstorms, physically based numerical simulations of runoff, and the support vector machines method. The proposed thresholds have a good balance between true and false predictions for debris flow and floods. Importantly, our method permits the direct estimation of rainfall intensity-duration thresholds for areas where post-fire debris flow observations are limited.

Analysis of Ocean Parameters as Sources of Coastal Storm Damage: Regional Empirical Thresholds in Northern Spain

This contribution aims to explore the role of oceanographic parameters on the damage caused by storms at the eastern Cantabrian coast (1996–2016). All wave storms affecting the study area were characterized in terms of several oceanographic parameters; among them, damaging storms (responsible for direct and tangible loss) were identified. Cross-referencing both databases makes it possible to find some thresholds that explain storm conditions associated with property damage. Particularly relevant are those responsible for significant and widespread damage: maximum significant offshore wave height >6.5 m, maximum total water level >6 m, SPI > 1700 m2h, and a storm duration >48 h. These values are exceptionally high, mostly exceeding the 95th percentile. A comparison has been made with other thresholds described in the literature. The concurrence of high wave height and high tidal level is crucial as the greatest damage is caused by the combination of wave impact and over-wash, so a long duration of the storm is necessary to coincide with high tide. An empirical Intensity-Duration threshold has also been obtained with the following function I = 248.7 D−0.45. Damage can occur with moderate storms, but with severe effects only with exceptional wave and sea-level values, during long-lasting storms.

Critical Rainfall Thresholds as a Tool for Urban Flood Identification in Attica Region, Greece

Rainfall intensity–duration thresholds are commonly used to assess flood potential in both urban and rural environments. Derivation of these thresholds is one of the approaches commonly used for the development of flash flood warning systems that are mainly based on rainfall predictions. This research work presents a detailed analysis on these threshold estimations, implemented for the Attica region, Greece, as prior work in parts of the study area is limited and previous estimations regarding rainfall intensity–duration thresholds are based on a short period of available data. The analysis considers a large number of stations and takes into account all flood events occurred during the period between 2005 and 2017 in order to define two maximum intensity limits for various durations that denote three areas; conditions of flood occurrence, mixed conditions, and conditions linked to solely flood occurrence, respectively. Finally, limitations regarding the determination of specific spatiotemporal thresholds as observed through this analysis are also discussed. The application of this methodology as a tool to assess flood occurrence may contribute to minimize possible situations of pre-crisis or immediate crisis by reducing the flood consequences and the resources involved in emergency response to flood events.

Hybrid stochastic-mechanical modeling of precipitation thresholds of shallow landslide initiation

Numerous early warning systems based on rainfall measurements have been designed to forecast the onset of rainfall-induced shallow landslides. However, their use over large areas poses challenges due to uncertainties related to the interaction among various controlling factors. We propose a hybrid stochastic-mechanical approach to quantify the role of the hydro-mechanical factors influencing slope stability and rank their importance. The proposed methodology relies on a physically based model of landslide triggering and a stochastic approach treating selected model parameters as correlated aleatory variables. The features of the methodology are illustrated by referencing data for Campania, an Italian region characterized by landslide-prone volcanic deposits. Synthetic regional intensity-duration (ID) thresholds are computed through Monte Carlo simulations. Several key variables are treated as aleatoric, constraining their statistical properties through available measurements. The variabilities of topographic features (e.g., slope angle), physical and hydrological properties (e.g., porosity, dry unit weight γd, and saturated hydraulic conductivity, Ks), and pre-rainstorm suction are evaluated to inspect its role on the resulting scatter of ID thresholds. We find that: (1) Ks is most significant for high-intensity storms; (2) in steep slopes, changes in pressure head greatly reduce the timescale of landslide triggering, making the system heavily reliant on initial conditions; (3) for events occurring at long failure times (gentle slopes and/or low-intensity storms), the significance of the evolving stress level (through γd) is highest. The proposed approach can be translated to other regions, expanded to encompass new aleatory variables, and combined with other hydro-mechanical triggering models.

Detection and forecasting of shallow landslides: lessons from a natural laboratory

Rapid shallow landslides are a significant hillslope erosion mechanism and limited understanding of their initiation and development results in persistent risk to infrastructure. Here, we analyse the slope above the strategic A83 Rest and be Thankful road in the west of Scotland. An inventory of 70 landslides (2003–2020) shows three types of shallow landslide, debris flows, creep deformation, and debris falls. Debris flows dominate and account for 5,350 m3 (98%) of shallow-landslide source volume across the site. We use novel time-lapse vector tracking to detect and quantify slope instabilities, whilst seismometers demonstrate the potential for live detection and location of debris flows. Using on-slope rainfall data, we show that shallow-landslides are typically triggered by abrupt changes in the rainfall trend, characterised by high-intensity, long duration rainstorms, sometimes part of larger seasonal rainfall changes. We derive empirical antecedent precipitation (>62 mm) and intensity-duration (>10 h) thresholds over which shallow-landslides occur. Analysis shows the new thresholds are more effective at raising hazard alerts than the current management plan. The low-cost sensors provide vital notification of increasing hazard, the initiation of movement, and final failure. This approach offers considerable advances to support operational decision-making for infrastructure threatened by complex slope hazards.

Temporal changes in rainfall intensity–duration thresholds for post-wildfire flash floods in southern California

Abstract. Rainfall intensity–duration (ID) thresholds are commonly used to assess flash flood potential downstream of burned watersheds. High-intensity and/or long-duration rainfall is required to generate flash floods as landscapes recover from fire, but there is little guidance on how thresholds change as a function of time since fire. Here, we force a hydrological model with radar-derived precipitation to estimate ID thresholds for post-fire flash floods in a 41.5 km2 watershed in southern California, USA. Prior work in this study area constrains temporal changes in hydrological model parameters, allowing us to estimate temporal changes in ID thresholds. The results indicate that ID thresholds increase by more than a factor of 2 from post-fire year 1 to post-fire year 5. Thresholds based on averaging rainfall intensity over durations of 15–60 min perform better than those that average rainfall intensity over shorter time intervals. Moreover, thresholds based on the 75th percentile of radar-derived rainfall intensity over the watershed perform better than thresholds based on the 25th or 50th percentile of rainfall intensity. Results demonstrate how hydrological models can be used to estimate changes in ID thresholds following disturbance and provide guidance on the rainfall metrics that are best suited for predicting post-fire flash floods.

Rainfall Triggering of Post-Fire Debris Flows over a 28-Year Period near El Portal, California, USA

ABSTRACT Wildfires frequently affect the steep hillslopes near El Portal, California (United States), a small community established during the California Gold Rush in the mid-1800s. In addition to the historical significance of El Portal, State Route 140 (SR 140) is a major transportation and economic corridor connecting the San Joaquin Valley to Yosemite National Park (YNP). In 2019, an estimated 4.5 million tourists visited and accessed YNP via SR 140. In the years after wildfires, the burned watersheds produced debris flows during intense rainfall, impacting the El Portal community and motorists traveling on SR 140 and local roads. The steepness of the hillslopes and confinement of the valley limit options for mitigating debris-flow risk. As such, emergency managers are left with evacuation orders or temporary road closures as the best options for risk reduction. The effectiveness of these options is highly dependent on establishing an accurate local rainfall intensity-duration threshold that officials can use to guide emergency response actions and timing. We present an overview of the rainfall conditions that initiated 12 post-fire debris-flow events near El Portal from 1991 to 2018 and objectively define rainfall intensity-duration thresholds from triggering rainfall rates. Our results highlight the modest rainfall rates that triggered debris flows in these steep watersheds, while radar data from more recent events (2012–2018) portray the spatial variability of intense rainfall in the area. Additional rainfall monitoring is needed to provide a robust rainfall threshold that will effectively mitigate risk for residents and motorists while minimizing the impact of road closures and evacuations.

Hydrogeomorphic Recovery and Temporal Changes in Rainfall Thresholds for Debris Flows Following Wildfire

AbstractWildfire‐induced changes to soil and vegetation promote runoff‐generated debris flows in steep watersheds. Postfire debris flows are most commonly observed in steep watersheds during the first wet season following a wildfire, but it is unclear how long the elevated threat of debris flow persists and why debris‐flow potential changes in recovering burned areas. This work quantifies how rainfall intensity‐duration (ID) thresholds for debris‐flow initiation change with time since burning and provides a mechanistic explanation for these changes. We constrained a hydrologic model using field and remotely sensed measurements of soil‐infiltration capacity, vegetation cover, runoff, and debris‐flow activity. We applied this model to estimate rainfall ID thresholds for debris‐flow initiation within three burned areas in the southwestern United States over a postfire recovery period of three to four years. Modeling suggests ID thresholds are lowest immediately following the fire (below a one‐year recurrence interval [RI] storm) and increase with time, such that a 10‐ to 25‐year RI storm would be required to generate a debris flow after three years of recovery. Modeled changes in rainfall ID thresholds result from increases in soil infiltration capacity, canopy interception, hydraulic roughness, and median grain size of sediment entrained in an incipient debris flow. The relative importance of each of these factors varied among our three sites. Results improve our ability to assess temporal changes in postfire debris‐flow potential, highlight how site‐specific factors may alter the persistence of postfire debris‐flow hazards, and provide additional constraints on the timescale of recovery following wildfire.

Temporal changes in the debris flow threshold under the effects of ground freezing and sediment storage on Mt. Fuji

Abstract. Debris flows are one of the most destructive sediment transport processes in mountainous areas because of their large volume, high velocity, and kinematic energy. Debris flow activity varies over time and is affected by changes in hydrogeomorphic processes in the initiation zone. To clarify temporal changes in debris flow activities in cold regions, the rainfall threshold for the debris flow occurrence was evaluated in Osawa failure at a high elevation on Mt. Fuji, Japan. We conducted field monitoring of the ground temperature near a debris flow initiation zone to estimate the presence or absence of seasonally frozen ground during historical rainfall events. The effects of ground freezing and the accumulation of channel deposits on the rainfall threshold for debris flow occurrence were analyzed using rainfall records and annual changes in the volume of channel deposits since 1969. Statistical analyses showed that the intensity–duration threshold during frozen periods was clearly lower than that during unfrozen periods. A comparison of maximum hourly rainfall intensity and total rainfall also showed that debris flows during frozen periods were triggered by a smaller magnitude of rainfall than during unfrozen periods. Decreases in the infiltration rate due to the formation of frozen ground likely facilitated the generation of overland flow, triggering debris flows. The results suggest that the occurrence of frozen ground and the sediment storage volume need to be monitored and estimated for better debris flow disaster mitigation in cold regions.