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On 14th and 15th July 2021 heavy rainfall in western Germany, Belgium and the Netherlands caused severe floodings. The most affected area in Germany was the 86 km long Ahr river valley, which suffered from severe damage to buildings and infrastructure and where more than 130 people died. The Ahr flood exceeded a return period of at minimum 500 years. The river Ahr drains around 900 km2 of the Rhenish Massif with a dendritic catchment from west to east causing differences in slope properties and covering different land uses. The flood water carried large woody debris that caused clogging in bridges of the main valley and some tributaries, some of which collapsed. This extreme event thus offers the opportunity to explore the spatial impact and characteristics of large wood on channel dynamics. This study aims to find thresholds for the initiation of large wood recruitment, dependent on catchment size, valley slopes, water quantity and land use.The study focuses on the whole catchment area of the Ahr river. Using general vegetation data obtained from the German national forest inventory, we quantified the type and amount of flood-affected vegetation. We adopted an NDVI (normalized differential vegetation index) based change detection approach using Landsat/Sentinel satellite data (Google Earth Engine based Hazmapper) to identify recruited live vegetation and deadwood transport during the flood. We validated this remotely obtained data with field surveys along selected valley sections.Large wood was predominantly recruited from the fluvial corridor in the main Ahr valley and not from the tributaries, even if those experienced heavy precipitation and surface runoff (up to few meters high discharge on the flood plains). Although we have observed transported tree trunks in those tributaries, there was no large pattern. We aspire to identify deposition areas using ortho photos to investigate a wood balance.Including large wood in flood modelling would improve flood hazard assessments. Remote sensing analyses offer an interim solution in this regard by helping to identify potential large wood recruitment areas and inform designing flood hazard prevention measures.

Within the extensive periglacial belt of the dry Andean high mountain range (17°30’S to 35°S), the most visible expression of creeping mountain permafrost is the occurrence of rock glaciers, which have been studied systematically in the last decades (e.g. Schrott, 1996; Trombotto et al., 1999; Halla et al. 2021). Active, inactive and relict rock glaciers are included in regional and national inventories (e.g. IANIGLA-CONICET 2018), whereas the spatial distribution, internal structure and ice content within block- and talus slopes have not been explored. Thus, there is a lack of explanatory approaches and analytical data on their local and regional distribution patterns and formative controls, despite these landforms being widespread and characteristic elements in the Upper Agua Negra catchment (ca. 30°S 69°W, Province San Juan, Argentina) and covering more than 70 % of its area. We hypothesize that the permafrost bodies and the seasonally frozen active layer of these periglacial landforms store significant amounts of ice and contribute to runoff during summer months, rendering them important water reservoirs and decisive components of the water balance in the high-Andean desert landscape. Especially in light of global climate change, understanding the spatial distribution of potentially ice-rich permafrost landforms is imperative to assess available water resources, water quality and their evolution.A holistic inventory of key cryogenic landforms with focus on block- and talus slopes will be compiled for the Agua Negra catchment. Using field and remote sensing-based geomorphological mapping (based on e.g. 12 m resolution TanDEM-X and 1 m Pléiades data), published data and statistical modeling techniques, the spatial heterogeneity of cryospheric landforms and their formation controls will be analyzed. Our regional inventory will complement the existing “Inventario Nacional de Glaciares y Ambiente Periglacial” (IANIGLA-CONICET 2018) and will further provide the basis for a first assessment of the hydrological importance of these cryogenic landforms.Halla, C., Blöthe, J.H., Tapia Baldis, C., Trombotto Liaudat, D., Hilbich, C., Hauck, C., Schrott, L., 2021. Ice content and interannual water storage changes of an active rock glacier in the dry Andes of Argentina. The Cryosphere, 15, 1187-1213.IANIGLA-CONICET, Ministerio de Ambiente y Desarrollo Sustentable de la Nación (2018). IANIGLA-Inventario Nacional de Glaciares y Ambiente Periglacial. Informe de la subcuenca del río Blanco. Cuenca del río San Juan, p. 62.Trombotto, D., Buk, E., Hernández, J., 1999. Rock glaciers in the Southern Central Andes (appr. 33° S.L.), Mendoza, Argentina: a review. Bamberger Geographische Schriften, Selbstverlag des Faches Geographie an der Universität Bamberg, Germany, 19, 145-173.Schrott, L., 1996. Some geomorphological-hydrological aspects of rock glaciers in the Andes (San Juan, Argentina). Zeitung für Geomorphologie, Supplementband 104, 161-173.

Glacial and periglacial landforms in the semi-arid Andes represent an essential water storage and feed regional river runoff. Glacial and periglacial systems are undergoing change; with signs of permafrost degradation such as thermokarst being visible in the study area of the Agua Negra catchment in the Desert Andes of Argentina. Surface changes are often indicators of thawing and freezing processes and/or permafrost degradation. The analysis of surficial changes provides local patterns and indicates potential meltwater contribution to runoff. It is important to understand such changing processes to assess their future input to the hydrological system. Analyses that exceed landform scale are, however, rare due to limited accessibility and high demand on fieldwork and resources.Glaciers and permafrost in the Agua Negra catchment exist within close proximity, suggesting (de)coupling effects. Glaciers and permafrost features can act as thermal and mechanical entity with water functioning as agent of transient glacier-permafrost interaction. Investigating (de)coupling is essential to better understand landscape (in)stability and changing water storages within the system. We hypothesize that periglacial systems directly interacting with glacial landscapes display diverging surface processes compared to non-glacially impacted periglacial systems. They differ in terms of magnitude and pattern, e.g. due to meltwater (re)routing.We derive high-resolution digital elevation models (DEMs) for one talus-derived and one glacially impacted rock glacier and assess surface change based on repeated UAV flights in 2017, 2018, 2022 and 2023 for the talus-derived, and 2022 and 2023 for the glacially impacted rock glacier; both georeferenced by DGPS measurements. We increase the spatial scale of the analysis and use tristereo Pléiades data for Pléiades-based surface change detection of two glacially impacted rock glaciers between 2014 and 2022. Here, we use the UAV-based DEMs as validation datasets. We envision that combining the two data sources allows us to investigate change signals over larger spatial areas which might provide new insight in our process-response understanding of the high Andean (peri)glacial landscape and its hydrological significance.First results from UAV based DEM comparison indicate net negative surface changes of the talus-derived rock glacier. Preliminary analysis of the Pléiades data shows a net negative mass balance of Agua Negra glacier and highlights the need for improved co-registering of the Pléiades data for rock glacier surface change detection.

The Seti River originates from the Annapurna Massif in the Higher Himalaya of Nepal and flows through the Pokhara valley in the Lesser Himalaya. The Seti River witnessed a disastrous flash flood on May 5th, 2012 causing the death of 72 people, obliterating dozens of homes and damaging infrastructures worth millions of dollars. Despite the 2012 flood event and several warnings by scientists for more yet bigger scale future floods in the Seti valley, fluvial risk is being aggravated by anthropogenic activities such as unplanned human settlement, encroachment of riverbanks, haphazard construction of road, drinking water, and hydropower projects in potential flood hazard areas in addition to the increased impacts of climate change on geological and hydro-metrological hazards as in other parts of Hindu Kush Himalayan Range. Covering some 40-km distance from the Seti headwater (Sabche Cirque) down to Pokhara city, the study is carried out based on hydro-geomorphological mapping, analysis of land-use and land-cover change, hydrological analysis including HEC-RAS modelling, historical archives, and interviews with local people. The study shows a significant change on the land use and land cover of the Seti catchment, mainly the urban/built-up area, which is increased by 405% in 24 years period (1996 to 2020) and by 47% in 7 years period (2013 to 2020). Further the study reveals that anthropogenic activities along the Seti valley have increased fluvial risk and are likely to invite more disasters. From the HEC-RAS analysis, two motor bridges built over Seti River were found to have insufficient freeboard to safely pass the highest flood discharge for 100 years return-period. Instead of relocating people to safer places, the government and local authorities rather seem to have encouraged people to live in the floodplain by providing basic amenities such as drinking water, electricity and access road. Given the context of climate change and Pokhara valley and the Seti catchment being in a high-seismic gap zone, there is a strong possibility of similar flood to the scale of 2012 or even greater in Seti River. Though the fluvial risk can be managed in a sustainable way through the application of functional space concept, i.e., by allowing more space (freedom) for rivers, this economic and environment friendly approach of the fluvial risk management has not been implemented yet in the Seti valley nor in Nepal. Rather the encroachment of floodplains by anthropogenic activities along the Seti valley is on an increasing trend. Many settlements and infrastructures along the valley have been identified vulnerable to hydro-torrential hazards, therefore it is utmost necessity to implement functional space river concept, land use and land plan policy, early warning system and public awareness education in order to mitigate and manage the future impact of fluvial hazards along the Seti valley.

In the past 20 years, motor road and bridge construction works have increased significantly in Nepal, in most cases with poor consideration of geo-hazards (rockfalls, landslides, debris flows) and river-flow dynamics. The National Road Construction (NRC) is further fostered by China’s Belt and Road Initiative (BRI). Currently, the Kali Gandaki (KG) road corridor is being upgraded to a 2-way black-top road as a project under BRI. The river dynamics of the KG sub-catchments is rarely considered by engineers despite it represents a common threat to the KG road, road bridges, and human lives. Here we study the Ghatte Khola (GK) sub-catchment that is located along the KG corridor in Dana, Myagdi district, West Nepal. From hydro-geomorphological mapping, hydrological and HEC–RAS analysis, historical archives and interviews, several questions have arisen regarding to the size of the under-construction GK motor bridge. The water way and freeboard of this bridge were found to be insufficient to safely pass the highest flood discharge for 100 years return-period, hence the bridge was found to be vulnerable to extreme floods. Actually, the nearly completed GK bridge was destroyed by a severe hyper-concentred flood on May 25, 2019. Active geo-hazards (rock falls, landslides) in the upper GK catchment appear as persistent drivers susceptible to aggravate sporadically the GK flows, and may pose serious threat to the future GK road bridge and to nearby infrastructure and settlements. We discuss these issues and eventually propose new technical, more sustainable solutions (e.g., fords). Au cours des vingt dernières années, les travaux de construction de routes et de ponts se sont considérablement accélérés au Népal, la plupart du temps sans tenir compte des instabilités de versant (chutes de pierres, glissements de terrain, coulées de débris) ni des changements de régime et de morphologie des rivières. Le développement de routes nationales au Népal (NRC) s’inscrit dans le projet chinois « Belt and Road Initiative » (BRI) : dans ce cadre, le « corridor » routier de la rivière Kali Gandaki (KG) est en train d’être aménagé en une route goudronnée à deux voies. Cependant, les ingénieurs routiers prennent rarement en considération la dynamique hydromorphologique des bassins versants affluents de la KG, bien que cela représente une menace fréquente tant pour la route que pour les ponts routiers et les riverains. Nous étudions ici le bassin-versant de la Ghatte Khola (GK), rivière torrentielle affluente de rive droite de la KG confluant au niveau de Dana (district de Myagdi, ouest du Népal). À partir de la cartographie hydro-géomorphologique, de modélisations hydrologiques (méthodes « Rational » et HEC–RAS) et de la consultation d’archives historiques et d’interviews sur place, nous évoquons plusieurs questions, en particulier celle de la taille du pont routier de la GK en cours de construction. La voie d'eau et le franc-bord de ce pont se sont avérés insuffisants pour résister en toute sécurité au débit de crue le plus élevé pour une période de retour de 100 ans, d'où une vulnérabilité du pont aux crues extrêmes. En fait, ce pont, presque achevé, a été détruit le 25 mai 2019 par une crue d’écoulement hyper-concentré. La dynamique de versant (chutes de pierres, glissements de terrain) dans la partie supérieure du bassin-versant de la GK apparaît comme un facteur permanent susceptible d'aggraver sporadiquement (notamment pendant les orages de pré-mousson) les modalités d’écoulement de la GK, constituant ainsi une menace sérieuse pour le futur pont routier de la GK et pour les infrastructures et sites d’habitat voisins. Nous discutons de ces enjeux et proposons en conclusion de nouvelles solutions techniques comme les gués, morphologiquement et économiquement plus durables.

Exceptional rainfalls (up to 200 mm in 72 h) in W-Germany, the Netherlands and Belgium led to severe flooding on 14-15 July 2021. In Germany the Ahr valley (Eifel mountains) was hit heavily, leading to 134 fatalities and substantial loss of property and infrastructure. Besides the damage in the floodplains, multiple shallow landslides were triggered along the Ahr embankments. Furthermore, the flood caused undercutting of several old landslide bodies. One such landslide in Devonian Schist bedrock is located at a narrow, bended stretch of the Ahr, near the town of Müsch. A complete failure has the potential to dam the river posing a considerable hazard.The main objectives of this study are to gain an in-depth understanding of the landslide causes and its transient activity. These objectives are tackled by a multi-method approach: landslide mapping, analysis of pre- and post-event airborne laser scanning (ALS) and terrestrial laser scanning (TLS) data, electrical resistivity tomography (ERT), seismic refraction tomography (SRT), passive seismic monitoring, geotechnical analysis and interviews with local inhabitants.The old landslide is 100 m wide and 200 m long. Preliminary analysis of ERT and SRT indicate a landslide depth of 20-30 m, leading to an overall landslide volume of 400,000 - 600,000 m³. ERT further shows underlying bedrock properties and water saturated zones. An old dumpsite as well as an ancient railway, now used as forest trail, cutting through the landslide horizontally are clearly shown as resistive zones. Analysis of ALS data shows that so far only the frontal part at the Ahr banks has been active and has lost about 6300 m³ due to fluvial erosion and landsliding. Field mapping shows clear signs of retrogressive landsliding. From October 2021 onwards the landslide body has been equipped with five geophones to record both subtle changes in ground rheology and discrete events of rock bridge failure due to incremental mass movement. Currently most seismic signals at the slope can be allocated to daily traffic and road construction in the area.The combination of geophysical and remote sensing methods enables a profound insight into the mechanisms and present processes of the Müsch landslide. Based on this, we will be able to assess the probability for a reactivation of the whole landslide body, which could trigger cascading hazards affecting a much larger region. An improved monitoring concept will be developed which can be adopted to similar structures in the Ahr valley and beyond.

Valley confined floods are a major hazard. In contrast to large river floods with day long warning time, they can evolve within minutes to hours, exhibit higher flow velocities and drive large amounts of debris into populated places. While many Alpine communities have developed mitigation, early warning and rapid response schemes for this natural hazard type, these measures are virtually unknown in Central European upland regions. Beyond flood protection, lacking measurement infrastructure also prevents retrospective collection of event anatomy data, which would be key to understand the evolution of an event and, hence to improve our response to future hazards.The 14–15 July 2021 flood that hit the Ahr valley in the Eifel mountains, west Germany, was a drastic example of the potential of such valley confined floods. A wall of water flushed through the deeply incised valley, flooding more than 15 towns and affecting 42,000 people, resulting in the highest number of casualties in Germany since 1962. All gauges along the main channel were destroyed while the flood hydrograph was still on the rising limb and grid power loss interrupted collection and transmission of data from other potential sensors.Here, we use data from a single seismic station near the town of Ahrweiler, originally deployed for earthquake seismology. Despite grid power cutoff around 23:19 CEST, the station recorded the arrival of the fast rising limb of the flood. We show how even an incomplete record of a single station not set up for flood early warning can be used to infer crucial and timely information about the flood: propagation velocity, water level and debris transport rate. We argue that installing a network of a few distributed low cost seismic sensors could have improved flood early warning and near real time provision of kinetic flood data. More importantly, such a network would be the key for improved response actions for future floods, deemed more likely in Central Europe under the currently changing climate conditions.

Highest geomorphic activity in central Nepal is mostly driven by monsoon rainfall, yet the recent development of infrastructure has increased this activity and the risks for the locals and travelers. Our aim is to illustrate recent cascading hazards and their interactions with, and impacts on, socio-economic development along an important road corridor. We focus on the middle Kali Gandaki valley reach, within the High Himalayan Crystalline Series HHC where the river deeply incised and the topography is characterized by steep hillslopes and high relief. This 20-25 km long reach experiences strong monsoon rainfall enhanced by orographic effects, with rainfall rates >2000 mm/a. In the last years between 2018 to 2021 the monsoon season was very strong and experienced several strong and long lasting rainstorm events with amplified catastrophic events such as debris flows, landsliding and river activities. On the basis of repeated field surveys, satellite images (Pléiades, Sentinel and Planet) analysis, Global Precipitation Measurement (GPM) data, UAV, river flow seismic noise records, we observed that once destabilized, hillslopes and steep, small tributary catchments evolved very rapidly during the years, all the more since road constructions for the upgrading to a 2-lane road contributed to destabilization of the hillslopes. This rapid disequilibrium has several consequences. (1) First it reworked old colluvium deposits, including old landslide material, old glacial and/or fluvial alluvium and related lacustrine deposits, hence revealing a former, complex paleo-topography of this deep valley (as observed north of Ghasa, along the Kahiku khola and Kali Gandaki). (2) Second, in providing looser material, it has accelerated the cascading system and transfer of sediments into the main Kali Gandaki River, as shown in the Rupse site, famous for its waterfall, and that was destroyed by a debris flood (July 20, 2020) generated by intense rainfall that triggered landslides in the upper catchment, with impacts at the junction with Kali Gandaki (destruction of road, bridge, settlements). Similarly, the Thaplyang site, active since 2014, was repeatedly affected by strong rainfall since 2018, with progressive erosion of an old landslide material – the active area increased from 9100 m² (March 2018) to 9600 m² (Oct. 2018) and 32300 m² (Nov 2021) – hence threatening small settlements upstream. (3) Third, the repeated disasters (river bank collapses and settlements destruction; traffic obstruction) affect the tourism economy and development along this major link between south China and north India. Further work, including SAR analyses, is ongoing to better quantify the overall sediment exported volumes and the impacts of this changing geomorphology on future infrastructure development and settlements.

Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape’s subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14–15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding.

Rain driven flash floods have severe impacts on society and landscape functions. The July 2021 flood in the Eifel region, west Germany, was one drastic example of such impact. While media and scientists rightfully highlighted the meteorological and hydrological aspects of this flood, it was the concurrent reorganisation of important landscape conditions and the debris carried by the fast flowing water that made this flood so devastating and unpredictable.Here, we take a process-based impact perspective and systematically ask, which were the specific roles of non-hydraulic but geomorphic dynamics that implemented the damage, caused flood non-linearities and amplified the landscape deterioration. We combine insights from field mapping campaigns during, right after and within the relaxation phase of the flood with high resolution geophysical and LiDAR surveys to discuss the role of hillslopes, vegetation, fluvial sediment mobilisation and the legacy of anthropogenic landscape reorganisation. We conclude that some of these elements emerged as the flood event evolved, causing either transient effects or persistent landscape features, thus modifying the response of the landscape to future events, also to less intense precipitation events.Our findings not only support more tailored recovery efforts for the flood affected Eifel catchments, but should also inform landscape development trajectories and potentially crucial factors in other Central European regions.

Multiple hazards (e.g. floods, landslides, earthquakes, glacial and landslide lake outburst floods) are threatening people, their goods and infrastructures in the high mountains of Nepal Himalaya. Floods and landslides are mainly driven by monsoonal precipitation. However, human impact often increases natural risks, like in the Kali Gandaki (KG) valley, the deepest valley (>5500 m) on earth, where the new two-lane road construction (since 2017) has caused many undercut and instable slopes.In the light of previous events, we intend to assess the cascading multi-hazard events of 2020 in three tributary catchments of KG.We adopted a pluri-disciplinary approach: interpretation of Sentinel-2 satellite images (March and November 2020), analysis of precipitation (stations of Lete and Tatopani, GPM satellite precipitation measurements), hydrologic and seismic data (Beni), geomorphological mapping, hydrological modelling in HEC-RAS, and field visits in July and November 2020, including interviews with locals.On 20 July 2020 major hyper-concentrated flood events and landslides occurred in the Rupse, Thaplyang and Kahiku catchments (between Tatopani and Lete) destroying parts of the KG road, road bridges and a hotel (Rupse site). We focus on the Rupse River entering the KG valley at Rupse waterfall (height 108 m; kyanitic gneisses) then flowing down to the KG road and to KG River 200 m below. The major flood event lasted two hours and reached a max. flood level of 35 m at the edge of the waterfall. Upstream of the waterfall, four landslides (each about 250m wide, 200 m high) were triggered. Due to cloud coverage satellite scenes are missing to unravel whether the landslides caused the damming of the river and a landslide lake outburst flood or if the landslides were mainly triggered by the flood and increased sediment input to it.Floods from these tributary catchments caused a major KG flood especially south of the Rupse catchment, which led to severe erosion and sedimentation in the channel; i.e. destruction of a pole of the national electricity grid, reactivation of the Kham Bhitta deep-seated landslide, destruction of the KG road (the construction of which probably contributed to this reactivation). Seismic data from Beni, approximately 27 km downstream of the affected catchments, provide constraints on the timing and relative magnitude of the flood in the KG. The data show that a short duration high magnitude flood with a very rapid rise and recession passed through Beni on the afternoon of 20 July. In addition, station data of Lete and Tatopani shows that yearly rainfall totals of 1839.5 and 2140.2 mm, respectively, were the highest since 1970. March and April were already very wet, followed by extremely monthly rainfall totals of 499.7 mm and 551.5 mm at Lete and Tatopani, respectively.Assessing the 2020 events demonstrates how important localized events in relatively small areas are to understand cascading multi-hazard processes in Himalayan mountain regions. In addition, such hydro-geomorphic functioning and related hazards should be carefully considered when planning road design and bridge sites together with landslide and water level monitoring, for a better traffic maintenance and safety.

Highest geomorphic activity in the central Nepal Himalayas is mainly driven by monsoonal precipitation. In contrast, the northern flanks of the Nepal Himalaya lay in the relative dry rain shadow of the mountain range. During the monsoon 2018, major floods and geomorphic events occurred in the Kali Gandaki (KG) valley impacting both the monsoon-affected and the dry parts of the catchments. We analyze the events and its triggers based on field observations, multiple satellite image interpretation, climatological analysis using Global Precipitation Measurement and MODIS snow cover data, hydrological analysis and media analysis. The hydro-meteorological triggers are complex. Exceptional precipitation in April and May 2018 occurred in the entire study area, followed by a rather dry period. Precipitation in August was exceptional in the northern part whereas below average in the South. We argue that dynamics of snow accumulation and delayed melting contributed significantly to flooding and increased geomorphic activity in the southern part in August whereas flooding in the northern part was mainly triggered by rainfalls. We thus define 2018 as an abnormal (pre-)monsoon year with less rainfall than average but being more catastrophic. Sediment dynamics in the study area are still controlled by the Dhampu rock avalanche dam and the braided river floodplain north of this knickpoint, where sediment pulses delivered from tributaries are rarely connected from the main river. During the monsoon floods 2018 sediment connectivity was given for most tributaries due to the steepness of the catchments. The study area is subject to major human impact. Mostly in the south, numerous hillslopes have been undercut by road construction, leading to higher geomorphic sensitivity. Severe landslides might thus be triggered in future even by less intense rainfall events. Magnitude and frequency of such abnormal (pre-)monsoon precipitation are highly relevant for sediment flux and natural hazards studies.

Based on empirical work from Nepal, we introduce an actor-oriented, agency-based model of Agency Toward Resilience (ATR). Our approach recognizes individuals as active agents who have the ability and willingness to take actions for building resilience in the context of disaster risk. While the ability to act is influenced by structural conditions and the access to assets, the willingness to act is shaped by individual goals and tradeoffs rooted in personal values, beliefs, and worldviews. Relating this ability and willingness with intentional actions to persist, adapt, and transform, we hope to provide with the ATR model an ontological foundation for gaining a deeper understanding of disaster risk and all its dimensions (Priority 1 of the Sendai Framework) such as people’s agency toward resilience building.

The Nepalese Himalaya is affected by a major rift valley, the Thakkhola half graben (THG). Along this fault-bounded basin, the Kali Gandaki (KG) flows from the Tibetan plateau southwards to the Dhaulagiri and Annapurna massifs, where it forms the deepest gorge on earth. The THG has been filled with up to 1 km thick Plio- and Pleistocene sediments, underlain by clay shales of the Jurassic Spiti Formation that are strongly water swellable and prone to landslides. These pre-conditions led to a series of large and complex landslides, particularly along the eastern flank of the THG, with strong effects on infrastructure and the local population. One of these landslide systems (c. 15 km²) is located in the semi-arid Muktinath Valley, a tributary basin of the KG (c. 92.5 km²). Water as most important driver of the system is provided by precipitation mainly during the summer monsoon (annual rainfall: ~ 350 mm), snowmelt and irrigation.Against this background, we aim i) to better understand regional-scale landslide systems (spatial pattern, drivers/controls), ii) to establish a long-term monitoring of local-scale landsliding in the Muktinath Valley, and iii) to share our findings with local communities to support the development of mitigation strategies.Reconstruction of landslide dynamics over the past 30 years is based on local information (interviews), field observations (damaged buildings and walls), geomorphological mapping and multi-temporal (ortho-) photo analyses (WorldView, Pleiades). Since 2018, annual UAV surveying is applied.Results include a geomorphological map of the area focusing on landslide related processes and landforms, indicators of recent landslide activity, hydrologic characteristics and irrigation infrastructure, as well as the distribution of Spiti shale outcrops. Surrounding the presently most active landslide, we observed an average displacement of c. 20 cm/a since 1988 with an increasing trend towards present (30 - 50 cm/a since 2011). In the center of the most active landslide significantly higher displacements of up to 15 m have been detected since 2011, which corresponds to an average of about 2 m/a. The landslide monitoring based on UAV surveying, structure-from-motion processing and different approaches of high-resolution topographic change and error modelling (DEM resolution: 2.6 - 4.3 cm) shows massive change between April 2018 and March 2019 (gain: 33395 ± 5489 m³; loss: 50276 ± 10781 m³), accompanied by a total sediment export of 16881 ± 12098 m³ to the Jhong River. Detailed orthophotos (resolution: 1.29 - 2.15 cm) provide valuable supplementary information not only on recent landslide propagation and dynamics but also with regard to future threatened areas (opening cracks). Boosted landslide activity in 2018 is associated to the strong monsoon that heavily impacted in the larger region as well (debris flows, flash floods, multiple bank collapses): In August 2018 Muktinath recorded the highest monthly rainfall since 1978 (172 mm, DHM Nepal). The research is located at the interface between humans and the environment. The "symbiosis" of the local population and the landslide system is unique - and enables to deconstruct various interacting landslide processes driven and modified by climate (change) and human impact.

Complete landslide inventories are rarely available. The objectives of this study were to (i) elaborate the influence of incomplete landslide inventories on statistical landslide susceptibility models and to (ii) propose suitable modelling strategies that can reduce the effects of inventory-based incompleteness. In this context, we examined whether the application of a novel statistical approach, namely mixed-effects models, enables predictions that are less influenced by such inventory-based errors. The study was conducted for (i) an area located in eastern Austria and (ii) a synthetically generated data set. The applied methodology consisted of a simulation of two different inventory-based biases and an in-depth evaluation of subsequent modelling results. Inventory-based errors were simulated by gradually removing landslide data within forests and selected municipalities. The resulting differently biased inventories were introduced into logistic regression models while we considered the effects of including or excluding predictors that are directly related to the respective inventory-based bias. Mixed-effects logistic regression was used to account for variation that was due to an inventory-based incompleteness. The results show that most erroneous predictions, but highest predictive performances, were obtained from models generated with highly incomplete inventories and predictors that were able to directly describe the respective incompleteness. An exclusion of such bias-describing predictors led to systematically confounded relationships. The application of mixed-effects models proved valuable to produce predictions that were least affected by inventory-based errors. This paper highlights that the degree of inventory-based incompleteness is only one of several aspects that determine how an inventory-based bias may propagate into the final results. We propose a four-step procedure to deal with incomplete inventories in the context of statistical landslide susceptibility modelling.

Tourism is an important source of income for many mountain communities in Nepal. However, the tourism industry is highly vulnerable to a variety of natural hazards. The ability of local people to proactively prepare, protect, and support prevention activities against natural hazards drives a mountain community's resilience. Research on whether and to what extent people have adopted such proactive behaviors has shown that human action is determined not only by sociodemographic and socioeconomic conditions—such as age, gender, or income—but also by values and worldviews. In this paper, we present data from a 2-phased survey of 160 lodge owners conducted in 2017 and 2018 in Mustang, Nepal, focusing on lodge owners' activities in disaster risk reduction (DRR) and their values and worldviews. Classifying the preparedness and support for prevention (PSP) activities of lodge owners, we found 3 different PSP types. In a second step, these PSP types were contrasted with values and worldviews held by the lodge owners, as well as sociodemographic and socioeconomic factors. This revealed strong correlations between the lodge owners' values and their PSP type. These results indicate that when trying to explain an actor's DRR activities, his or her values might be as important as commonly used sociodemographic and socioeconomic indicators. We argue that a holistic concept of resilience—combining actors' values and worldviews as well as their sociodemographic and socioeconomic status—can strengthen efforts to build resilience.

There is unanimous agreement that a precise spatial representation of past landslide occurrences is a prerequisite to produce high quality statistical landslide susceptibility models. Even though perfectly accurate landslide inventories rarely exist, investigations of how landslide inventory-based errors propagate into subsequent statistical landslide susceptibility models are scarce. The main objective of this research was to systematically examine whether and how inventory-based positional inaccuracies of different magnitudes influence modelled relationships, validation results, variable importance and the visual appearance of landslide susceptibility maps. The study was conducted for a landslide-prone site located in the districts of Amstetten and Waidhofen/Ybbs, Eastern Austria, where an earth-slide point inventory (n = 591) was available. The methodological approach comprised an artificial introduction of inventory-based positional errors into the present landslide data set and an in-depth evaluation of subsequent modelling results. Positional errors were introduced by artificially changing the original landslide position by a mean distance of 5, 10, 20, 50 and 120 m. The resulting differently precise response variables were separately used to train logistic regression models. Odds ratios of predictor variables provided insights into modelled relationships. Cross-validation and spatial cross-validation enabled an assessment of predictive performances and permutation-based variable importance. All analyses were additionally carried out with synthetically generated data sets to further verify the findings under rather controlled conditions. The results revealed that an increasing positional inventory-based error was generally related to increasing distortions of modelling and validation results. However, the findings also highlighted that interdependencies between inventory-based spatial inaccuracies and statistical landslide susceptibility models are complex. The systematic comparisons of 12 models provided valuable evidence that the respective error-propagation was not only determined by the degree of positional inaccuracy inherent in the landslide data, but also by the spatial representation of landslides and the environment, landslide magnitude, the characteristics of the study area, the selected classification method and an interplay of predictors within multiple variable models. Based on the results, we deduced that a direct propagation of minor to moderate inventory-based positional errors into modelling results can be partly counteracted by adapting the modelling design (e.g. generalization of input data, opting for strongly generalizing classifiers). Since positional errors within landslide inventories are common and subsequent modelling and validation results are likely to be distorted, the potential existence of inventory-based positional inaccuracies should always be considered when assessing landslide susceptibility by means of empirical models.

Landslides are an important means of conveying sediment from slopes to channels in steepland environments, but landsliding is a discontinuous process. This means that any single assessment in time of their contribution to the sediment cascade is of limited value. To better understand landscape dynamics and the contribution of landslides to slope–channel coupling over time, this paper quantifies connectivity over a time span of 65 years in small, steep headwater catchments in the southern Ruahine Range, New Zealand. Temporal variability in landsliding and slope–channel coupling was assessed using six sets of aerial photography flown between 1946 and 2011, from which over 6900 landslides were mapped in ArcGIS, of which up to 78% connected with the stream network. Estimates of the volume of material delivered by landslide erosion to headwater channels were based on ground survey measurements of selected landslide scars and suggest that between 1946 and 2011 over 5 million m 3 of sediment was delivered from slopes to channels in the 221 km 2 study area. Forest cover is not sufficient to prevent this erosion. These catchment systems are particularly vulnerable to high magnitude storm events, which significantly elevate landslide intensity and enhance sediment delivery, as occurred in the mid-1970s. The legacy of these events remains in these headwater channels, with ongoing consequences for stream and hazard management in and adjacent to the ranges.

Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1,354 km 2 ) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve ( AUROC ) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory. Furthermore, we observed that random forest-based maps displayed spatial artifacts. The most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias. However, none of the presented models was found to be completely unbiased. This study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps. We suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories. A joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability.

Pseudomonas aeruginosais capable of long-term survival in water, which may serve as a reservoir for infection. Although viable cell counts of PAO1 incubated in water remain stable throughout 8 weeks, LIVE/DEAD® staining indicated a high proportion of cells stained with propidium iodide (PI). The proportion of PI-stained cells increased by 4 weeks, then decreased again by 8 weeks, suggesting an adaptive response. This was also evident in an observed shift in cell morphology from a rod to a coccoid shape after 8 weeks. Fluorescence-activated cell sorting (FACS) was used to recover PI-stained cells, which were plated and shown to be viable, indicating that PI-stained cells were membrane-compromised but still cultivable. PAO1 mid-log cells in water were labeled with the dsDNA-binding dye PicoGreen® to monitor viability as well as DNA integrity, which demonstrated that the population remains viable and transitions towards increased dsDNA staining. Metabolic activity was found to decrease significantly in water by 4 weeks. The PAO1 outer membrane became less permeable and more resistant to polymyxin B damage in water, and the profile of total membrane lipids changed over time. None of the individual mutants within a library of ~2500 mapped, mini-Tn5-luxtransposon mutants were found to have decreased survival in water. Among the ~1400 transcriptionalluxfusions, gene expression in water revealed that the majority of genes were repressed, but subsets of genes were induced at particular time points. In summary, these results indicate thatP. aeruginosais dormant in water and this adaptation involves a complex pattern of gene regulation and changes to the cell to promote long-term survival and antibiotic tolerance. The approach ofP. aeruginosaincubated in water may be useful to study antibiotic tolerance and the mechanisms of dormancy and survival in nutrient limiting conditions.

Landslides occur frequently all over the world, causing at times considerable economic damage, injuries and even death. In order to improve hazard assessment, common landslide types of a given region need to be investigated in detail. While traditional techniques of subsurface investigation are expensive and only provide point information, geophysical methods are suitable tools for gathering 2D and 3D information on the subsurface quickly, reliably and cost-effectively. In this study, the suitability and limitations of 2D resistivity for the determination of landslide extent, structure and soil moisture conditions are presented. For this purpose, two identical profiles were taken during a two-month period. Significant differences in electrical resistivity (>1000 Ωm) due to varying soil moisture conditions were observed. Using various inversion parameters, it was possible to model two distinct subsurface images. Regrettably, the sliding plane could not be detected reliably, possibly due to the homogeniety of the landslide material and underlying bedrock.

Landslide inventories are the most important data source for landslide process, susceptibility, hazard, and risk analyses. The objective of this study was to identify an effective method for mapping a landslide inventory for a large study area (19,186 km2) from Light Detection and Ranging (LiDAR) digital terrain model (DTM) derivatives. This inventory should in particular be optimized for statistical susceptibility modeling of earth and debris slides. We compared the mapping of a representative set of landslide bodies with polygons (earth and debris slides, earth flows, complex landslides, and areas with slides) and a substantially complete set of earth and debris slide main scarps with points by visual interpretation of LiDAR DTM derivatives. The effectiveness of the two mapping methods was estimated by evaluating the requirements on an inventory used for statistical susceptibility modeling and their fulfillment by our mapped inventories. The resulting landslide inventories improved the knowledge on landslide events in the study area and outlined the heterogeneity of the study area with respect to landslide susceptibility. The obtained effectiveness estimate demonstrated that none of our mapped inventories are perfect for statistical landslide susceptibility modeling. However, opposed to mapping polygons, mapping earth and debris slides with a point in the main scarp were most effective for statistical susceptibility modeling within large study areas. Therefore, earth and debris slides were mapped with points in the main scarp in entire Lower Austria. The advantages, drawbacks, and effectiveness of landslide mapping on the basis of LiDAR DTM derivatives compared to other imagery and techniques were discussed.

Landslides are a significant hazard in many parts of the world and exhibit a high, and often underestimated, damage potential. Deploying landslide early warning systems is one risk management strategy that, amongst others, can be used to protect local communities. In geotechnical applications, slope stability models play an important role in predicting slope behaviour as a result of external influences; however, they are only rarely incorporated into landslide early warning systems. In this study, the physically based slope stability model CHASM (Combined Hydrology and Stability Model) was initially applied to a reactivated landslide in the Swabian Alb to assess stability conditions and was subsequently integrated into a prototype of a semi-automated landslide early warning system. The results of the CHASM application demonstrate that for several potential shear surfaces the Factor of Safety is relatively low, and subsequent rainfall events could cause instability. To integrate and automate CHASM within an early warning system, international geospatial standards were employed to ensure the interoperability of system components and the transferability of the implemented system as a whole. The CHASM algorithm is automatically run as a web processing service, utilising fixed, predetermined input data, and variable input data including hydrological monitoring data and quantitative rainfall forecasts. Once pre-defined modelling or monitoring thresholds are exceeded, a web notification service distributes SMS and email messages to relevant experts, who then determine whether to issue an early warning to local and regional stakeholders, as well as providing appropriate action advice. This study successfully demonstrated the potential of this new approach to landslide early warning. To move from demonstration to active issuance of early warnings demands the future acquisition of high-quality data on mechanical properties and distributed pore water pressure regimes.

article i nfo Physically-based models are frequently applied for local landslide analyses and predictions in order to pre- vent the potentially disastrous consequences of slope failures. Limit-equilibrium modelling approaches are very common. However, the application of such models can be very time-consuming, and due to its two- dimensional nature, it generally has to be repeated for each profile that is investigated. In this study, the physically-based two-dimensional landslide model CHASM (Combined Hydrology and Stability Model) was implemented within a web-based GIS (Geographical Information System) environment for a study area in the Swabian Alb, Germany. The required input data for CHASM modelling were derived from a variety of data sources including geological maps, drillings, geophysical investigations, hydrological monitoring, labora- tory analyses and literature sources. The implemented CHASM decision-support system is based on open- source software and utilises the WPS (web processing service) standard to execute the model algorithms on a server. The presented system allows the user to select from a variety of input data and model parameters to quickly perform limit-equilibrium analyses of slope stability. Simulation results are automatically stored to a database and can be visualised for interpretation. The implemented CHASM decision-support system rep- resents an innovative prototype which demonstrates a promising approach to engage landslide modelling. © 2013 Elsevier B.V. All rights reserved.

Many regions worldwide are threatened by multiple natural hazards with the potential to cause high damages and losses. However, the modeling of multiple hazards in a joint analysis scheme is still in the early stages of development as a range of serious challenges emerges in the multihazard context such as differing modeling approaches in use for contrasting hazards; the time- and data-demanding conduct of each single preparative, intermediate and analysis step; and the clear visualization of the modeling outcome. Under consideration of these difficulties, a regional multihazard exposure analysis concept is developed for five natural hazards: debris flows, rock falls, shallow landslides, avalanches, and river floods, complemented by a visualization scheme to present the modeling outcome. An automation of the two schemes resulted in a beta version of the MultiRISK modeling and the MultiRISK visualization software tool forming together the MultiRISK platform. To test the analysis scheme and the software implementation of MultiRISK a case study is performed in the Barcelonnette basin in France with a worst-case parameterization of the models on the basis of extensive literature reviews. Experiences from this case study offered many insights into the multihazard topic and even more questions, e.g. with respect to coherent multihazard model parameterization, validation or the comparability and interpretation of single-hazard modeling results, respectively. Although analysis schemes can be proposed and software tools can be provided to facilitate many steps, a well-conceived and reflective approach to multihazard settings is essential. The worst-case analysis based on literature values apparently leads to an overestimation of the susceptible areas and the number of exposed elements. Nevertheless, depending on the data situation of an area, especially in areas without any information on past events, this approach may offer the determination of general hazard distributions, overlaps, and areas of potential risk without data-demanding calibration.

Bell, R., Petschko, H., Rohrs, M. and Dix, A. Assessment of landslide age, landslide persistence and human impact using airborne laser scanning digital terrain models. Geografiska Annaler: Series A, Physical Geography, 94, 135–156. doi:10.1111/j.1468‐0459.2012.00454.xABSTRACTLandslides occur worldwide and contribute significantly to sediment budgets as well as to landform evolution. Furthermore, they pose hazards and risks to people and their goods. To assess the role of landslides, information on their age or persistence (i.e. the length of time the morphological characteristics of a landslide remain recognizable in the terrain) is essential. In this study, the potential of airborne laser scanning digital terrain models (ALS DTMs) is analysed for estimating landslide age, landslide persistence and human impact. Therefore, landslides in two study areas, Swabian Alb in Germany and Lower Austria in Austria, are mapped from hillshades of ALS DTMs and combined with historical information on landslide occurren...

Landslide susceptibility maps can be elaborated using a variety of methodological approaches. This study investigates quantitative and qualitative differences between two statistical modelling methods, taking into account the impact of two different response variables (landslide inventories) for the Rhenodanubian Flysch zone of Lower Austria. Quantitative validation of the four generated susceptibility maps is conducted by calculating conventional accuracy statistics for an independent random landslide subsample. Qualitative geomorphic plausibility is estimated by comparing the final susceptibility maps with hillshades of a high resolution Airborne Laser Scan Digital Terrain Model (ALS-DTM). Spatial variations between the final susceptibility maps are displayed by difference maps and their densities. Although statistical quality criterions reveal similar qualities for all maps, difference maps and geomorphic plausibility expose considerable differences between the maps. Given that, this conclusion could only be drawn by evaluating additionally the geomorphic plausibility and difference maps. Therefore, we indicate that conventional statistical quality assessment should be combined with qualitative validation of the maps.

The potential of surface roughness to quantify geomorphological landforms and processes has been enhanced with the availability of high-resolution digital terrain models (DTM). Recent studies that attempt to identify landslide features with surface roughness have suggested that this measure of topographic heterogeneity may also be applied to estimate the relative age of landslides. This is a provisional study that explores the potential of this relationship by assessing the ability of surface roughness to act as a proxy for relative landslide age. The surface roughness for a set of 12 dated landslides in the Swabian Alb that occurred between 1789 and 1985 was calculated from a 1 m2 spatial resolution LiDAR DTM with three algorithms: root-mean-square-height (RMSH), standard deviation of slope (SDS), and direction cosine eigenvalue ratios (DCE). Scale-dependence was analysed by calculating surface roughness for a range of moving window sizes (3 × 3, 5 × 5, 9 × 9 and 15 × 15), and surface roughness for each landslide was summarized by the median and upper quartile. Only weak correlations (best Spearman's rho 0.58) were present between landslide age and surface roughness. This correlation becomes weaker with increasing moving window size. Given weak observed associations and discussed challenges pertaining to the complexities of landslide morphology change over time, we currently find that surface roughness alone may not be justifiable to act as a proxy for landslide age for our study region. Furthermore, we recommend future studies should focus on addressing possible natural and anthropogenic factors such as land use change that may alter surface roughness. These studies may focus on one of the three roughness measures used here as they are strongly correlated. Copyright © 2014 John Wiley & Sons, Ltd.

In statistical landslide susceptibility modelling the identification of appropriate explanatory variables describing the predisposing and preparatory factors for the landslides of a given inventory is important. In this context information on the age and the respective land cover at the time of occurrence is beneficiary. The potential of mapping very old (or prehistoric) landslides using LiDAR derivatives has not been analysed yet. Additionally, performing a visual interpretation of derivatives of a single LiDAR DTM it is not possible to assign the accurate age or date of the occurrence of the event to each mapped landslide. Therefore, commonly no information on the land cover at the time of landslide occurrence for these very old landslides (but also for younger ones) is available. The objective of this study is, to estimate the relative age of landslides during the mapping and to explore differences of the recent land cover distribution in the relative ages of the landslides. This is performed to evaluate the sustainability of including recent land cover data into susceptibility modelling. The relative age of the landslides is estimated for each landslide according to its morphological footprint on the LiDAR DTM derivatives and to its appearance on the orthophoto. The different relative ages assigned are “very old”, “old”, “young” and “very young”. The study area is located in three districts of Lower Austria, namely Amstetten, Baden and Waidhofen/Ybbs. The resulting inventory includes 1834 landslides and shows that the “very old” and “old” landslides (60 % of all mapped landslides) are mainly covered by forest (~60 % of all land cover types). We conclude that using this inventory including recent land cover data in the susceptibility model is not appropriate for Lower Austria. There is a potential of mapping “old” or “very old” landslides on the LiDAR derivatives. The absolute age remains unknown.

Landslide susceptibility maps are helpful tools to identify areas potentially prone to future landslide occurrence. As more and more national and provincial authorities demand for these maps to be computed and implemented in spatial planning strategies, several aspects of the quality of the landslide susceptibility model and the resulting classified map are of high interest. In this study of landslides in Lower Austria, we focus on the model form uncertainty to assess the quality of a flexible statistical modelling technique, the generalized additive model (GAM). The study area (15 850 km2) is divided into 16 modelling domains based on lithology classes. A model representing the entire study area is constructed by combining these models. The performances of the models are assessed using repeated k-fold cross-validation with spatial and random subsampling. This reflects the variability of performance estimates arising from sampling variation. Measures of spatial transferability and thematic consistency are applied to empirically assess model quality. We also analyse and visualize the implications of spatially varying prediction uncertainties regarding the susceptibility map classes by taking into account the confidence intervals of model predictions. The 95% confidence limits fall within the same susceptibility class in 85% of the study area. Overall, this study contributes to advancing open communication and assessment of model quality related to statistical landslide susceptibility models.

This study focuses on the comparison of different approaches for landslide susceptibility modelling and is part of the research project “MoNOE” (Method development for landslide susceptibility modelling in Lower Austria). The main objective of the project is to design a method for landslide susceptibility modelling for a large study area. For other objectives of the project we refer to Bell et al. (Proceedings of the 2nd world landslide forum, Rome, 3–7 Oct 2011, this volume). To reach the main objective, the two different statistical models “Weights of Evidence” and “Logistic Regression” are applied and compared. By using nearly the same input data in test areas it is possible to compare the capabilities of both methods. First results of the comparison indicate that in valleys and on south facing slopes the results are quite similar. In contrast, the analysis on north facing slopes shows differences. In the ongoing work the reasons for these differences will be analysed. Furthermore, attention will be paid to finding adequate validation methods for the two modelling approaches.

Landslide inventories, their accuracy and the stored information are of major importance for landslide susceptibility modelling. Working on the scale of a province (Lower Austria with about 10,000 km2) challenges arise due to data availability and its spatial representation. Furthermore, previous studies on existing landslide inventories showed that only few inventories can be used for statistical susceptibility modelling. In this study two landslide inventories and their resulting susceptibility maps are compared: the Building Ground Register (BGR) of the Geological Survey of Lower Austria and an inventory that was mapped on the basis of a high resolution LiDAR DTM. This analysis was performed to estimate minimum requirements on landslide inventories to allow for deriving reliable susceptibility maps while minimizing mapping efforts. Therefore a consistent landslide inventory once from the BGR and once from the mapping was compiled. Furthermore, a logistic regression model was fitted with randomly selected points of each landslide inventory to compare the resulting maps and validation rates. The resulting landslide susceptibility maps show significant differences regarding their visual and statistical quality. We conclude that the application of randomly selected points in the main scarp of the mapped landslides gives satisfactory results.

Landslides threaten most parts of the provincial state of Lower Austria and cause damage to agricultural land, forests, infrastructure, settlements and people. Thus, the project “MoNOE” (Method development for landslide susceptibility modelling in Lower Austria) was initiated by the provincial government to tackle these problems and to reduce further damage by landslides. The main aim is to prepare landslide susceptibility maps for slides and rock falls and to implement these maps into the spatial planning strategies of the provincial state.

The main purpose of this study is the analysis of rainfall thresholds and landslide susceptibility mapping in order to assist the prediction, mitigation and management of slope instability in the Wudu county in China. Firstly, the rainfall thresholds were assessed using the Antecedent soil water status (ASWS) model based on landslides induced by multi-temporal rainfall events in the Wudu county. Secondly, three separate susceptibility maps were produced using historic landslide inventories, and inventories reflecting single landslide triggering events, i.e. the 2008 Wenchuan earthquake and heavy rain storms. The separate maps were combined to illustrate the maximum landslide probability of all three landslide susceptibility maps. The results show that rainfall thresholds could be applied to forecast rainfall-induced landslides, and the integrated landslide susceptibility map could be used for planning of spatial development as well as emergency response actions.

It is important to calculate these areas prone for future landsiding through landslide susceptibility maps. A landslide causative factor database both before and after datasets was constructed. Data are stored in a resolution of 30×30m and include digital orthophoto maps (DOM), digital elevation model (DEM) and derived topographical parameters (e.g. altitude, slope, aspect, profile curvature, plan curvature), geology, land use, average annual rainfall, peak ground acceleration and further different environmental layers including road network and rivers. The 1334 post WenChuan earthquake landslide inventory is build up by field investigation and by interpretation of remote-sensing imagery (SPOT 5 and ALOS) and by monoscopic manual interpretation. The quality of susceptibility mapping was validated by splitting the study area into a training and validation set. The prediction capability analysis showed that the landslide susceptibility map has the potential to be used for land planning in this region as well as for precautionary emergency planning by local authorities.

Sagarmatha National Park and Buffer Zone (SNPBZ) in the Everest region in Nepal is among the most popular destinations for trekking tourism in Nepal. The dramatic growth of the tourism industry has increased pressures on the environment and the National Park is heavily affected by the rapidly growing waste issue. Besides, major mass movements play an important role in the Himalaya and have been observed in SNPBZ. Also, seasonal monsoon floods, debris flows, rock falls, landslides and the creation of glacial lake outburst floods are frequently occurring in the region. This paper explores the reciprocal interactions between the geo-environment and solid waste management in Everest’s SNPBZ. Therefore, geological characteristics and geomorphological processes, especially the two large rockslides in Lukla and Khumjung, as well as their consequences for rock quality, climatic and hydrologic conditions, are analyzed and simultaneously connected to the rapidly growing tourism-induced waste issue. Rockslide material shows high porosity and permeability. Thus, we argue that rockslide facies are particularly vulnerable to contamination by waste water and washed out agricultural fertilizers, which pose threats to the population especially in Namche Bazaar but probably also in Lukla. Also, the landfill sites are often affected by geomorphological processes and may consequently contaminate surface and ground water. Results highlight that regional infrastructure planning of landfill sites often collides with the natural features of the geo-environment and often causes harm to human health and the environment. The implications of the results can be applied to similar areas (such as Marsyandi Valley, Kali Gandaki Valley) with special geological characteristics and rapidly growing waste issues.

Increasing demand for carrying out not only natural hazard assessments but natural risk assessments are obvious. Within risk assessments, the definition of specific risk levels is crucial, and generally dependent on either law requirements or expert judgements.

Landslides play a key role in landscape evolution in the Eastern Alps. These geomorphic phenomena are influenced by multiple interdependent and interacting natural and anthropogenic factors. An in-depth evaluation of the spatial distribution of existing landslides enables to gain first insights into potentially hazardous areas. Morphometric analysis techniques of mapped landslides as well as their date of occurrence allow to infer their activity and also potential impacts on affected areas. The prevalent slow moving landslides and inactive slipping areas were mapped and analysed via digital terrain models (DTM), shaded relief images of highly resolved airborne laserscanning (ALS) data and in-field observations. Orthophotos from aerial surveys and ALS data allowed a deferred-time analyses of past landslide occurrences including a record of recent slope movements. All mapped landslides were classified and analysed with geomorphometric indices. Pedological processes, the lithological setting and anthropogenic landscape transformationwere taken into account when interpreting the results. The geomorphometrical evaluation of the sliding areas determine the creation of a multitemporal landslide inventory in the Northern Walgau.