Without power? Landslide inventories in the face of climate change
Without power? Landslide inventories in the face of climate change
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DOI：
10.1002/esp.2248
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发表时间：
2012-01
影响因子：
3.3
通讯作者：
O. Korup;Tolga Görüm;Y. Hayakawa
中科院分区：
文献类型：
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作者：
O. Korup;Tolga Görüm;Y. Hayakawa
气候变化的预测情景涉及对山体滑坡的规模和频率可能发生变化的一般预测，特别是由于降水和温度制度变化的结果。这种滑坡对当代或过去气候变化的响应是否可以用不同的尺度统计来反映滑坡的大小分布和由此得出的侵蚀率，仍然存在争议。我们用简单的蒙特卡罗和Bootstrap模拟来测试这一概念，这些统计模型通常用来描述经验滑坡大小分布。我们的结果表明，这类清单中包含的总容量的重大变化可能被统计上无法区分的比例参数所掩盖，这些参数关键取决于记录的最大滑坡的规模等。相反，可比较的模型参数值可能掩盖了滑坡发生的重大变化，即超过两倍的变化，从而推断出山坡剥蚀和向排水网络输送泥沙的速率。地球上一些最大的物质运动的时间序列揭示了在最后一次冰川-间冰期转变之前的聚集，以及从白噪声到这一时期周围的时间聚集的明显跨越。然而，阐明这是一阶气候变化对斜坡稳定性影响的明显信号，还是仅仅与从短期统计噪声向长期稳定状态条件的转变重合，仍然是一个重要的研究挑战。版权所有©2011 John Wiley&Sons，Ltd.
Projected scenarios of climate change involve general predictions about the likely changes to the magnitude and frequency of landslides, particularly as a consequence of altered precipitation and temperature regimes. Whether such landslide response to contemporary or past climate change may be captured in differing scaling statistics of landslide size distributions and the erosion rates derived thereof remains debated. We test this notion with simple Monte Carlo and bootstrap simulations of statistical models commonly used to characterize empirical landslide size distributions. Our results show that significant changes to total volumes contained in such inventories may be masked by statistically indistinguishable scaling parameters, critically depending on, among others, the size of the largest of landslides recorded. Conversely, comparable model parameter values may obscure significant, i.e. more than twofold, changes to landslide occurrence, and thus inferred rates of hillslope denudation and sediment delivery to drainage networks. A time series of some of Earth's largest mass movements reveals clustering near and partly before the last glacial‐interglacial transition and a distinct step‐over from white noise to temporal clustering around this period. However, elucidating whether this is a distinct signal of first‐order climate‐change impact on slope stability or simply coincides with a transition from short‐term statistical noise to long‐term steady‐state conditions remains an important research challenge. Copyright © 2011 John Wiley & Sons, Ltd.