Charlotte Gisèle Weil | EPFL Graph Search

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Vegetation Drastically Reduces Wind Erosion: An Implementation of the RWEQ in the Mongolian Gobi Steppe

Charlotte Gisèle Weil

Soil loss prevention is an important ecosystem service for protecting human and environmental health. Using spatiotemporal climate and environmental data of the Eastern Gobi Steppe, a region missing from previous studies of Mongolian wind-based soil erosion, we implemented the Revised Wind Erosion Equation (RWEQ) model to estimate soil loss. A replicable pipeline was developed to perform these computations, and made available openly. Soil loss was estimated on a monthly basis to analyze seasonal variations. The results show that the annual total soil loss was 61 x 10(10) kg over an area of 69.3 x 10(3) km(2), which is about 90 tonnes per hectare. Increasing fractional vegetation coverage to a uniform 50% coverage (doubling current vegetation coverage in every 1 km(2)) could reduce soil loss by 60%, highlighting the importance of protecting and increasing vegetation coverage in ecosystem service preservation.

MDPI2022

Landscape of data repositories and platforms

Eliane Ninfa Blumer, Miriam Braskova, Francesco Varrato, Charlotte Gisèle Weil

Scholarly Communication is still shifting from papers to richer content, as for instance research data and code. Data dissemination has a crucial role and yet it is in its infancy, with visible fragmentation and too many unknowns for researchers to get onboard. With our work, we want to mitigate this situation and help researchers decide which platforms are best suited to disseminate their data and code. The table we elaborated is based on multiple feedback from EPFL researchers, and its purpose is both to capture the variety of use-cases, and to guide researchers to make their choice. This poster is principally conceived for colleagues working in university services related to Open Science and Research Data Management, to provide them with an example of collaboration that might be reproduced in their institutions, and to create awareness on the challenges that such an endeavor entails. In this publication, we also include the current version of the comparative table of data dissemination solutions.

2021