Can long-term landscape change predict the impact of extreme events? A test from the flashfloods of the upper Indus Valley, Ladakh, 6th August 2010.

长期景观变化能否预测极端事件的影响？

• 批准号: NE/I017747/1
• 负责人: Hugh Sinclair
• 金额: $ 6.25万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI017747%2F1
• 关键词: long; term; landscape; change; predict

Communities based in mountainous regions of the world are always susceptible to debris flows, mudflows and landslides. Such events are commonly triggered by intense rainfall as has been the case for this summer's Indian monsoons which has caused huge surges of mud and debris down the valleys of the usually arid landscapes that border Tibet. In the town of Leh in the Ladakh region of NW India, more than half of their annual rainfall fell in one hour on the 6th August, and the mud and debris killed 185 people and left 500 missing. Climate model predictions suggest that these types of events in this region are likely to double over the next 60 years. Therefore, it is vital that we consider ways to mitigate and adapt for future scenarios, and that this must involve improved understanding of the processes, and the likelihood of a similar event happening in the near future. Fortunately, researchers at the University of Edinburgh have been surveying the exact river catchments that have been responsible for this summer's devastation. Based on these surveys, they have built sophisticated models of the evolution of the landscape over the last 100,000 years. Using these models they can predict the long-term distribution of river downcutting and the accumulation of mud and rock; the question is 'can models that are based on the time-averaged trajectory of landscape change be used to predict the impact of extreme events?' This question can be answered by re-surveying the exact sections of the river valley that had been measured three years ago, and recording where rivers have downcut, where hillslopes have collapsed and where mud and rocky debris have accumulated. If the landscape change following this summer's events is similar to the pattern of long-term change, then the impact of this event is predictable from the current models, and further analyses will be able to estimate the likelihood of a similar event happening again. If the re-surveys show that the signal of landscape change is different to the long-term pattern, then it will highlight the dangers of follow-on events linked to the reorganisation of the landscape back to its more stable form. For example, if the rivers have incised deeply, forming steep gorges, then the probability of collapse of the gorge walls will be increased. In contrast, if the river channels have accumulated lots of sediment, then the likelihood of flooding is increased as water is displaced onto the floodplains. This post-event legacy of landscape change is vital for the communities dependent on the rivers for their drinking water and irrigation in this arid environment. Clearly, if the rates of long-term landscape change are known, then the significance of this summer's event can be assessed. Once again, the researchers at Edinburgh have been fortunate in that the age of many of the geomorphological landforms such as moraines has been dated at around 100,000 years ago. For this project, the team intend to improve the measurement of this age in order to get better resolution on the time averaged rates of landscape change in the region. Having done this, the relative significance of this event can be assessed. Having better understood the redistribution of sediment and rock generated by this event, and the likelihood of it being repeated in the near future, the Edinburgh team aim to hold local workshops in the town of Leh with help from their colleague Dr Shakil Romshoo at the University of Jammu and kashmir. Their hopes are that by discussing their findings with government and non-government bodies, they will help local communities develop policies for mitigation and adaptation against future events.

位于世界山区的社区总是容易受到泥石流、泥石流和山体滑坡的影响。在印度西北部拉达克地区的列城，8月6日一个小时内的降雨量超过了全年降雨量的一半，泥石流和瓦砾造成185人死亡，500人失踪。气候模式预测表明，这一地区的这类事件在未来60年可能会增加一倍。因此，至关重要的是，我们要考虑减轻和适应未来情景的方法，这必须包括提高对过程的理解，以及在不久的将来发生类似事件的可能性。幸运的是，爱丁堡大学的研究人员一直在调查导致今年夏天这场灾难的确切河流集水区。在这些调查的基础上，他们建立了过去10万年景观演变的复杂模型。利用这些模型，他们可以预测河流下游的长期分布和泥岩的堆积；问题是，基于景观变化时间平均轨迹的模型能否用于预测极端事件的影响这个问题可以通过重新测量三年前测量的河谷的确切部分来回答，并记录河流的下降，山坡的倒塌以及泥土和岩石碎片的积聚。如果今年夏季气候事件之后的景观变化与长期变化的模式相似，那么这一事件的影响就可以从目前的模型中预测出来，进一步的分析将能够估计类似事件再次发生的可能性。如果重新调查显示景观变化的信号与长期模式不同，那么它将突出与景观重组相关的后续事件的危险，使其恢复到更稳定的形式。例如，如果河流切割得很深，形成陡峭的峡谷，那么峡谷壁坍塌的可能性就会增加。相反，如果河道积聚了大量的沉积物，那么洪水的可能性就会增加，因为水被排入洪泛区。在干旱的环境中，这种景观变化对依赖河流提供饮用水和灌溉的社区至关重要。显然，如果知道长期景观变化的速度，那么就可以评估今年夏天这一事件的重要性。再一次，爱丁堡的研究人员很幸运，因为许多地貌地貌（如冰碛）的年龄可以追溯到大约10万年前。在这个项目中，团队打算改进这个年龄的测量，以便更好地解决该地区景观变化的时间平均速率。这样做之后，就可以评估这一事件的相对重要性。在更好地了解了这次事件所产生的沉积物和岩石的再分配，以及在不久的将来这种情况再次发生的可能性之后，爱丁堡团队计划在查谟和克什米尔大学的同事Shakil Romshoo博士的帮助下，在列城举行当地研讨会。他们的希望是，通过与政府和非政府机构讨论他们的发现，他们将帮助当地社区制定缓解和适应未来事件的政策。

项目成果

Reconstruction of a major storm event from its geomorphic signature: The Ladakh floods, 6 August 2010

• DOI: 10.1130/g32935.1
• 发表时间: 2012-06
• 期刊: Geology
• 影响因子: 5.8
• 作者: D. Hobley;H. Sinclair;S. Mudd