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Based on an empirical exploration, the dominant objective of the paper is to understand the impact of industrial projects, for example, National Aluminium Company Limited (NALCO) on the sustainability of tribal communities as well as the surrounding natural environment. The contemporary industrial project has devastated the natural capital through its industrial practices, such as over-extraction of natural resources, over-passage of decomposed wastes, contamination of water bodies, inordinate drilling out of groundwater, etc., without any concern for the existence of nature as well as the rich culture developed by the tribal communities. In this context, the study unearths an empirical understanding of NALCO in Koraput, Odisha, and its impact on the sustainability of the tribal village communities as well as their symbiotic relationship with the natural environment. The empirical investigation has been conducted in selected tribal villages located in and around the NALCO.

Abstract. The assessment of uncertainties in landslide susceptibility modelling in a changing environment is an important, yet often neglected, task. In an Austrian case study, we investigated the uncertainty cascade in storylines of landslide susceptibility emerging from climate change and parametric landslide model uncertainty. In June 2009, extreme events of heavy thunderstorms occurred in the Styrian Basin, triggering thousands of landslides. Using a storyline approach, we discovered a generally lower landslide susceptibility for the pre-industrial climate, while for the future climate (2071–2100) a potential increase of 35 % in highly susceptible areas (storyline of much heavier rain) may be compensated for by much drier soils (−45 % areas highly susceptible to landsliding). However, the estimated uncertainties in predictions were generally high. While uncertainties related to within-event internal climate model variability were substantially lower than parametric uncertainties in the landslide susceptibility model (ratio of around 0.25), parametric uncertainties were of the same order as the climate scenario uncertainty for the higher warming levels (+3 and +4 K). We suggest that in future uncertainty assessments, an improved availability of event-based landslide inventories and high-resolution soil and precipitation data will help to reduce parametric uncertainties in landslide susceptibility models used to assess the impacts of climate change on landslide hazard and risk.