Glacial lake outburst flood risk in the Bolivian Andes

The Bolivian Andes have experienced sustained and widespread glacier area reduction and volume loss in recent decades. This study finds that from 1986 to 2018 glacier areas have shrunk from 529 km2 to 281 km2 (49 %) in the Bolivian Cordillera Oriental. Glacier melting and recession has been accompanied by the development of proglacial lakes, which can pose a glacial lake outburst flood (GLOF) risk to downstream communities. Therefore, glacier bed topographies were extracted and illustrate the potential development of 68 future lakes. Eight of these lakes possess populations downstream. A simple geometric model (MC-LCP) was used to model GLOFs from these potential future lakes, illustrating that ~1100 to ~2900 people could be affected by flooding if these lakes were to appear and to burst. The rest of this work is dedicated on the estimation of the risk from current, already existing lakes. Multi- Criteria Decision Analysis (MCDA) was used to rapidly identify potentially dangerous proglacial lakes in regions around the world without existing tailored GLOF risk assessments, where a range of proglacial lake types exist, and where field data are sparse or non-existent. After testing the robustness of the MCDA model against a number of past GLOFs, it was applied to the Bolivian Cordillera Oriental. From the 25 lakes possessing populations downstream, 3 lakes were found to pose ‘medium’ or ‘high’ risk, and required further detailed investigation. Since no attempt has yet been made to model GLOF inundation downstream from these proglacial lakes, 2m resolution DEMs were generated from stereo and tri-stereo SPOT 6/7 satellite images to drive a hydrodynamic model (HEC-RAS 5.0.3) of GLOF flow. The model was tested against field observations of a 2009 GLOF from Keara, in the Cordillera Apolobamba, and was shown to reproduce realistic flood depths and inundation. The model was then used to model GLOFs from Pelechuco lake (Cordillera Apolobamba) and Laguna Arkhata and Laguna Glaciar (Cordillera Real). In total, ~1100 to ~2200 people could be directly affected by outburst flooding

Capacity management of migrant accommodation centers using approximate dynamic programming

Irregular migration has become a major macro-economic and political challenge. Due to rising political conflicts and income inequality across the world, the number of migrants is expected to increase exponentially over the coming decade. Thus, it is of critical importance to effectively use the limited resources allocated to humanitarian operations for irregular migration. In this paper we model the problem of capacity management and migrant transfers within a network of migrant accommodation centres with stochastic dynamic programming. Our study extends the literature on stochastic modelling and humanitarian operations by applying Approximate Dynamic Programming (ADP) into a new context. The model is translatable in other similar migratory routes and locations around the world where governments need to deal with uncertain numbers of irregular migrants. We test our approach on five Greek islands which have been the main migrant arrival points during the European Migrant Crisis. The results show that ADP provides a better computational performance than a simple myopic heuristic. The sensitivity analysis gives insights to the decision-makers about the impact of parameter values on the policies

Progress and challenges in glacial lake outburst flood research (2017–2021):a research community perspective

Glacial lake outburst floods (GLOFs) are among the most concerning consequences of retreating glaciers in mountain ranges worldwide. GLOFs have attracted significant attention amongst scientists and practitioners in the past 2 decades, with particular interest in the physical drivers and mechanisms of GLOF hazard and in socioeconomic and other human-related developments that affect vulnerabilities to GLOF events. This increased research focus on GLOFs is reflected in the gradually increasing number of papers published annually. This study offers an overview of recent GLOF research by analysing 594 peer-reviewed GLOF studies published between 2017 and 2021 (Web of Science and Scopus databases), reviewing the content and geographical focus as well as other characteristics of GLOF studies. This review is complemented with perspectives from the first GLOF conference (7-9 July 2021, online) where a global GLOF research community of major mountain regions gathered to discuss the current state of the art of integrated GLOF research. Therefore, representatives from 17 countries identified and elaborated trends and challenges and proposed possible ways forward to navigate future GLOF research, in four thematic areas: (i) understanding GLOFs - timing and processes; (ii) modelling GLOFs and GLOF process chains; (iii) GLOF risk management, prevention and warning; and (iv) human dimensions of GLOFs and GLOF attribution to climate change.Fil: Emmer, Adam. University of Graz; AustriaFil: Allen, Simon K.. Universitat Zurich; Suiza. Universidad de Ginebra; SuizaFil: Carey, Mark. University of Oregon; Estados UnidosFil: Frey, Holger. Universitat Zurich; SuizaFil: Huggel, Christian. Universitat Zurich; SuizaFil: Korup, Oliver. Universitat Potsdam; AlemaniaFil: Mergili, Martin. University of Graz; AustriaFil: Sattar, Ashim. Universitat Zurich; SuizaFil: Veh, Georg. Universitat Potsdam; AlemaniaFil: Chen, Thomas Y.. Columbia University; Estados UnidosFil: Cook, Simon J.. University Of Dundee; Reino Unido. Unesco. Centre For Water Law, Policy And Science; Reino UnidoFil: Correas Gonzalez, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Das, Soumik. Jawaharlal Nehru University; IndiaFil: Diaz Moreno, Alejandro. Reynolds International Ltd; Reino UnidoFil: Drenkhan, Fabian. Pontificia Universidad Católica de Perú; PerúFil: Fischer, Melanie. Universitat Potsdam; AlemaniaFil: Immerzeel, Walter W.. Utrecht University; Países BajosFil: Izagirre, Eñaut. Universidad del País Vasco; EspañaFil: Joshi, Ramesh Chandra. Kumaun University India; IndiaFil: Kougkoulos, Ioannis. American College Of Greece; GreciaFil: Kuyakanon Knapp, Riamsara. University of Oslo; Noruega. University of Cambridge; Estados UnidosFil: Li, Dongfeng. National University Of Singapore; SingapurFil: Majeed, Ulfat. University Of Kashmir; IndiaFil: Matti, Stephanie. Haskoli Islands; IslandiaFil: Moulton, Holly. University of Oregon; Estados UnidosFil: Nick, Faezeh. Utrecht University; Países BajosFil: Piroton, Valentine. Université de Liège; BélgicaFil: Rashid, Irfan. University Of Kashmir; IndiaFil: Reza, Masoom. Kumaun University India; IndiaFil: Ribeiro De Figueiredo, Anderson. Universidade Federal do Rio Grande do Sul; BrasilFil: Riveros, Christian. Instituto Nacional de Investigación En Glaciares y Ecosistemas de Montaña; PerúFil: Shrestha, Finu. International Centre For Integrated Mountain Development Nepal; NepalFil: Shrestha, Milan. Arizona State University; Estados UnidosFil: Steiner, Jakob. International Centre For Integrated Mountain Development Nepal; NepalFil: Walker-Crawford, Noah. Colegio Universitario de Londres; Reino UnidoFil: Wood, Joanne L.. University of Exeter; Reino UnidoFil: Yde, Jacob C.. Western Norway University Of Applied Sciences; Suiz

A multi-method approach to prioritize locations of labor exploitation for ground-based interventions

Recent estimates suggest that more than 40 million people worldwide are in situations of modern slavery and other forms of labor exploitation. UN Sustainable Development Goal 8.7 addresses this problem and urges stakeholders to take effective measures to end all forms of labor exploitation by 2030. Labor exploitation is often a direct consequence of forced migration, and humanitarian operations have a key role to play in tackling this issue worldwide. Academic research can facilitate this by providing the necessary decision-making tools to support antislavery practitioners in humanitarian organizations and governments. For effective resource allocation, these practitioners need tools to help them systematically identify and assess the risks of labor exploitation in an area. In this paper, we develop a multi-method approach that combines various data sources to capture the issue’s complex and multidimensional nature. Through satellite remote sensing, we first identify 50 informal settlements hosting migrant workers in the strawberry production area of Southern Greece. We then apply a multi-criteria decision analysis (MCDA) method to a subset of six informal settlements in order to evaluate their labor exploitation risks based on eight criteria. In addition to being practically implemented by a humanitarian organization and a government agency in Greece, our paper advances research on humanitarian operations and labor exploitation by elucidating how a multi-method approach can be used for data-driven prioritization of interventions against labor exploitation. Our approach offers opportunities for other applications in the field of humanitarian operations