Scenario modelling of basin-scale, shallow landslide sediment yield, Valsassina, Italian Southern Alps

Author:

Bathurst J. C.,Moretti G.,El-Hames A.,Moaven-Hashemi A.,Burton A.

Abstract

Abstract. The SHETRAN model for determining the sediment yield arising from shallow landsliding at the scale of a river catchment was applied to the 180-km2 Valsassina basin in the Italian Southern Alps, with the aim of demonstrating that the model can simulate long term patterns of landsliding and the associated sediment yields and that it can be used to explore the sensitivity of the landslide sediment supply system to changes in catchment characteristics. The model was found to reproduce the observed spatial distribution of landslides from a 50-year record very well but probably with an overestimate of the annual rate of landsliding. Simulated sediment yields were within the range observed in a wider region of northern Italy. However, the results suggest that the supply of shallow landslide material to the channel network contributes relatively little to the overall long term sediment yield compared with other sources. The model was applied for scenarios of possible future climate (drier and warmer) and land use (fully forested hillslopes). For both scenarios, there is a modest reduction in shallow landslide occurrence and the overall sediment yield. This suggests that any current schemes for mitigating sediment yield impact in Valsassina remain valid. The application highlights the need for further research in eliminating the large number of unconditionally unsafe landslide sites typically predicted by the model and in avoiding large overestimates of landslide occurrence.

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3