{"id":5777,"date":"2013-01-16T18:21:08","date_gmt":"2013-01-16T18:21:08","guid":{"rendered":"http:\/\/blogs.agu.org\/landslideblog\/?p=5777"},"modified":"2013-01-17T08:19:07","modified_gmt":"2013-01-17T08:19:07","slug":"new-research-extreme-precipitation-and-landslides-in-2010","status":"publish","type":"post","link":"https:\/\/blogs.agu.org\/landslideblog\/2013\/01\/16\/new-research-extreme-precipitation-and-landslides-in-2010\/","title":{"rendered":"New research: extreme precipitation and landslides in 2010"},"content":{"rendered":"

\"ResearchBlogging.org\"<\/a><\/span> As regular readers will know, since 2002 I have been maintaining a database of landslides that kill people worldwide<\/a> (and this work was recently published in the Journal Geology<\/em><\/a>).\u00a0 In that dataset 2010 is the year with the highest level of losses from rainfall-induced landslides<\/a> – it truly was a remarkable year.\u00a0 In a recent paper (available online here<\/a> and published behind a pay wall in the Journal of Hydrometeorology<\/a>), Dalia Kirschbaum<\/a> from NASA and colleagues (Kirschbaum et al.<\/em> 2012) have used their own catalogue of mass movement events to examine the relationship between landslides and heavy rainfall.\u00a0 The landslide catalogue that they have used is rather different to mine because it compiles information about all reported rapidly moving landslides, irrespective of their impact.\u00a0 As such it is more comprehensive than my dataset, although it may be more subject to the vagaries of media and other types of reporting.\u00a0 In this study, the catalogue has been compared with precipitation data from the TRMM satellite.\u00a0 The TMPA dataset that they have used combines the TRMM data with rain gauge data to produce daily global rainfall dataset at a resolution on 0.25 x 0.25 degrees.\u00a0 This dataset is known to represent large rainfall events quite well.<\/p>\n

Perhaps unsurprisingly, the landslide dataset used here also show unusually high levels of landslide activity in 2010, with the increase above normal levels occurring primarily in Central America, the Himalayan Arc and Central-Eastern China.\u00a0 In each case, the authors clearly show that the elevated levels of landslide activity were associated with rainfall levels that were above normal.\u00a0 So, for example, this is the data for South Asia<\/p>\n

\"\". <\/a><\/p>\n

The top graph presents the precipitation data for this region.\u00a0 The red line is the precipitation pattern for 2010, whilst the green line is the average over 12 years.\u00a0 It is clear that the summer monsoon in this season was much wetter than the medium term average.\u00a0 The second (lower) graph presents the number of reported landslides in 2010 (in orange) and the average number of reported landslides for 2007-2009 in blue.\u00a0 Clearly the landslide occurrence level was significantly higher than in previous years; the obvious potential cause is the higher levels of precipitation.\u00a0 The other areas show similar patterns.<\/p>\n

Now, in some ways it might be obvious that years with larger rainfall totals, and in particular more extreme events, are associated with more landslides.\u00a0 Indeed, no-one is terribly surprised that the recent wet weather in the UK has been linked to a much higher occurrence of landslides across the country<\/a>.\u00a0 From that perspective, this paper is confirming what we already know, although the importance of exploring and quantifying an accepted truth can be underestimated.<\/p>\n

However, this contribution is much more important for two reasons. First, the fact that we can combine different datasets in this way to produce a useful analysis provides a basis upon which to start to better understand spatial and in particular temporal patterns of landslides.\u00a0 Kirschbaum et al.<\/em> (2012) start the process of examining the relationship between the observed landslide patterns and global weather systems, such as the El Nino cycle.\u00a0 They suggest for example that it is now established that in the year after an El Nino event, rainfall levels in the Himalayas are higher than normal, which explains the patterns in 2010.\u00a0 This is really useful information that will help improve management and mitigation of landslides in the future.\u00a0 Much more work of this type is needed, but this research opens the doors to it.<\/p>\n

Second, the analysis suggests that combining these datasets provides a much better way to understand those areas that are at long-term risk from landslides.\u00a0 This is likely to be a much more robust approach than the existing global landslide hazard and risk maps, such as those generated by the World Bank hotspots project<\/a>.\u00a0 Such approaches need more work, and this will take time, but in due course we should be able to identify those regions that are landslide-susceptble to a much better degree than at present.\u00a0 Of course we also need to do something similar for earthquake-triggered landslides, but the low-level of occurrence of earthquakes will make this rather more difficult.<\/p>\n

Reference<\/strong><\/p>\n

Kirschbaum, D., Adler, R., Adler, D., Peters-Lidard, C., & Huffman, G. (2012). Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years Journal of Hydrometeorology, 13<\/span> (5), 1536-1551 DOI: 10.1175\/JHM-D-12-02.1<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

A review of a paper examining the linkages between high levels of landslides in 2010 and large scale rainfall patterns<\/p>\n","protected":false},"author":22,"featured_media":5778,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[544,1],"tags":[259,469,18,545,979,11,220,17,72],"class_list":["post-5777","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-review-of-a-paper","category-uncategorized","tag-el-nino","tag-featured","tag-himalayas","tag-landslide-database","tag-monsoon","tag-nasa","tag-precipitation","tag-research","tag-south-asia"],"_links":{"self":[{"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/posts\/5777","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/users\/22"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/comments?post=5777"}],"version-history":[{"count":0,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/posts\/5777\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/media\/5778"}],"wp:attachment":[{"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/media?parent=5777"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/categories?post=5777"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.agu.org\/landslideblog\/wp-json\/wp\/v2\/tags?post=5777"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}