There is a clear need to improve and update landslide susceptibility models across the Philippines. This is challenging, as landslides in this region are frequently triggered by temporally and spatially disparate typhoon events, and it remains unclear whether such spatially and/or temporally distinct typhoon events cause similar landslide responses, i.e. whether the landslide susceptibility for one typhoon event is similar for another. Here, we use logistic regression to develop four landslide susceptibility models based on three typhoon-triggered landslide inventories for the 2009 Typhoon Parma (local name Typhoon Pepeng), the 2018 Typhoon Mangkhut (local name Typhoon Ompong), and the 2019 Typhoon Kammuri (local name Typhoon Tisoy). The 2009 and 2018 inventories were mapped across the same 150 km2 region of Itogon in Benguet Province, whilst the 2019 event was mapped across a 490 km2 region of Abuan in Isabela Province. The four susceptibility models produced are for the 2009, 2018, and 2019 inventories separately, as well as for the 2009 and 2018 inventories combined. Using the area under the receiver operator curve (AUROC) validation, the accuracy of the models is found to be 78 %-82 % for the Itogon models and 65 % for the Abuan model. To assess landslide time dependency, we use the AUROC validation and the Itogon models to quantify the degree to which susceptibility models derived from one event(s) in time can forecast/hindcast the landslides triggered by another. We find that using a susceptibility model for a typhoon event in one year to forecast/hindcast a typhoon in another leads to a 6%-10 % reduction in model accuracy compared to the accuracy obtained when modelling and validating each event separately. This suggests some degree of time dependency in typhoon-triggered landslides in the Philippines. However, using a susceptibility model for two combined typhoon events (2018 + 2009) to forecast/hindcast each typhoon event separately led to just a 1%-3 % reduction in model accuracy. This suggests that combined multi-event typhoon-triggered landslide susceptibility models will be more accurate and reliable for the forecasting of future typhoon-triggered landslides. Finally, by undertaking a high-level comparison of the Abuan and Itogon susceptibility models through space, we preliminarily suggest that there may be spatial dependency in typhoon-triggered landslides in the Philippines but that further work into issues of spatial dependency in this region is required. Copyright:

In mountainous environments, quantifying the drivers of mass-wasting is fundamental for understanding landscape evolution and improving hazard management. Here, we quantify the magnitudes of mass-wasting caused by the Asia Summer Monsoon, extreme rainfall, and earthquakes in the Nepal Himalaya. Using a newly compiled 30-year mass-wasting inventory, we establish empirical relationships between monsoon-triggered mass-wasting and monsoon precipitation, before quantifying how other mass-wasting drivers perturb this relationship. We find that perturbations up to 5 times greater than that expected from the monsoon alone are caused by rainfall events with 5-to-30-year return periods and short-term (< 2 year) earthquake-induced landscape preconditioning. In 2015, the landscape preconditioning is strongly controlled by the topographic signature of the Gorkha earthquake, whereby high Peak Ground Accelerations coincident with high excess topography (rock volume above a landscape threshold angle) amplifies landscape damage. Furthermore, earlier earthquakes in 1934, 1988 and 2011 are not found to influence 2015 mass-wasting.

Climate change impacts on sediment production and transfer processes on hillslopes and through channels are governed by possible changes in precipitation, runoff, and air temperature. These hydrological and geomorphological impacts are difficult to predict in temperature-sensitive Alpine environments. In this study, we combined a stochastic weather generator model with the most current climate change projections to feed a hillslope-channel sediment cascade model for a major debris-flow system in the Swiss Alps (the Illgraben). This allowed us to quantify climate change impacts and their uncertainties on sediment yield and the number of debris flows at hourly temporal resolution. We show that projected changes in precipitation and air temperature lead to a reduction in both sediment yield (−48%) and debris-flow occurrence (−23%). This change is caused by a decrease in sediment supply from hillslopes, which is driven by frost-weathering. Additionally, we conduct model experiments that show the sensitivity of projected changes in sediment yield and debris-flow hazard to basin elevation, with important implications for assessing natural hazards and risks in mountain environments. Future changes in hydrological and sediment fluxes are characterized by high uncertainty, mainly due to irreducible internal climate variability. Therefore, this stochastic uncertainty needs to be considered in climate change impact assessments for geomorphic systems.

Boulder movement can be observed not only in rockfall activity, but also in association with other landslide types such as rockslides, soil slides in colluvium originating from previous rockslides, and debris flows. Large boulders pose a direct threat to life and key infrastructure in terms of amplifying landslide and flood hazards as they move from the slopes to the river network. Despite the hazard they pose, boulders have not been directly targeted as a mean to detect landslide movement or used in dedicated early warning systems. We use an innovative monitoring system to observe boulder movement occurring in different geomorphological settings before reaching the river system. Our study focuses on an area in the upper Bhote Koshi catchment northeast of Kathmandu, where the Araniko highway is subjected to periodic landsliding and floods during the monsoons and was heavily affected by coseismic landslides during the 2015 Gorkha earthquake. In the area, damage by boulders to properties, roads, and other key infrastructure, such as hydropower plants, is observed every year. We embedded trackers in 23 boulders spread between a landslide body and two debris flow channels before the monsoon season of 2019. The trackers, equipped with accelerometers, can detect small angular changes in the orientation of boulders and large forces acting on them. The data can be transmitted in real time via a long-range wide-area network (LoRaWAN®) gateway to a server. Nine of the tagged boulders registered patterns in the accelerometer data compatible with downslope movements. of these, six lying within the landslide body show small angular changes, indicating a reactivation during the rainfall period and a movement of the landslide mass. Three boulders located in a debris flow channel show sharp changes in orientation, likely corresponding to larger free movements and sudden rotations. This study highlights the fact that this innovative, cost-effective technology can be used to monitor boulders in hazard-prone sites by identifying the onset of potentially hazardous movement in real time and may thus establish the basis for early warning systems, particularly in developing countries where expensive hazard mitigation strategies may be unfeasible.

Landslide susceptibility models are fundamental components of landslide risk management strategies. These models typically assume that landslide occurrence is time-independent, even though processes including earthquake preconditioning and landslide path dependency transiently impact landslide occurrence. Understanding the temporal characteristics of landslide occurrence remains limited by a lack of systematic investigation into how landslide distributions vary through time, and how this impacts landslide susceptibility. Here, we apply Kolmogorov-Smirnoff and chi-square statistics to a 30-yr inventory of monsoon-triggered landslides from Nepal to systematically quantify how landslide spatial distributions vary through time in “normal” years and years impacted by extreme events. We then develop binary logistic regression (BLR) susceptibility models for 12 yrs in our inventory with >400 landslides and use area under receiver operator curve validation to assess how well these models can hindcast landslide occurrence in other years. Landslide distributions are found to vary through time, particularly in years impacted by storms (1993 and 2002), earthquakes (2015), and floods (2017). Notably, Gorkha earthquake landscape preconditioning shifted 2015 monsoon-triggered landslides to higher slopes, reliefs, and excess topographies. These variations significantly impact BLR susceptibility modeling, with models trained on extreme years unable to consistently hindcast landslide occurrence in other years. However, developing BLR models using increasingly long historical inventories shows that susceptibility models developed using >6–8 yrs of landslide data provide consistently good hindcasting accuracy. Overall, our results challenge time-independent assumptions of landslide susceptibility approaches, highlighting the need for time-dependent modeling techniques or historical inventories for landslide susceptibility modeling.

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 eastsoutheast. Rainfall (Integrated Multi-satellitE Retrievals for Global Precipitation Measurement, IMERG GPM) associated with Typhoon Mangkhut is compared with 33 highintensity 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.

A landscape's sediment grain size distribution is the product of, and an important influence on, earth surface processes and landscape evolution. Grains can be large enough that the motion of a single grain, infrequently mobile in size-selective transport systems, constitutes or triggers significant geomorphic change. We define these grains as boulders. Boulders affect landscape evolution; their dynamics and effects on landscape form have been the focus of substantial recent community effort. We review progress on five key questions related to how boulders influence the evolution of unglaciated, eroding landscapes: 1) What factors control boulder production on eroding hillslopes and the subsequent downslope evolution of the boulder size distribution? 2) How do boulders influence hillslope processes and long-term hillslope evolution? 3) How do boulders influence fluvial processes and river channel shape? 4) How do boulder-mantled channels and hillslopes interact to set the long-term form and evolution of boulder-influenced landscapes? 5) How do boulders contribute to geomorphic hazards, and how might improved understanding of boulder dynamics be used for geohazard mitigation? Boulders are produced on eroding hillslopes by landsliding, rockfall, and/or exhumation through the critical zone. On hillslopes dominated by local sediment transport, boulders affect hillslope soil production and transport processes such that the downslope boulder size distribution sets the form of steady-state hillslopes. Hillslopes dominated by nonlocal sediment transport are less likely to exhibit boulder controls on hillslope morphology as boulders are rapidly transported to the hillslope toe. Downslope transport delivers boulders to eroding rivers where the boulders act as large roughness elements that change flow hydraulics and the efficiency of erosion and sediment transport. Over longer timescales, river channels adjust their geometry to accommodate the boulders supplied from adjacent hillslopes such that rivers can erode at the baselevel fall rate given their boulder size distribution. The delivery of boulders from hillslopes to channels, paired with the channel response to boulder delivery, drives channel-hillslope feedbacks that affect the transient evolution and steady-state form of boulder-influenced landscapes. At the event scale, boulder dynamics in eroding landscapes represent a component of geomorphic hazards that can be mitigated with an improved understanding of the rates and processes associated with boulder production and mobility. Opportunities for future work primarily entail field-focused data collection across gradients in landscape boundary conditions (tectonics, climate, and lithology) with the goal of understanding boulder dynamics as one component of landscape self-organization.