Seasonal trends in Tibetan lake level changes as observed by icesat laser altimetry

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Abstract

The Tibetan plateau is covered by hundreds of larger and smaller lakes. Until recently there was no method to monitor their water level variations due to lack of in-situ measurements or unfitness of available remote sensing methods. However the ICESat/GLA14 laser altimetry data provide global surface elevations for land during 18 one-month campaigns between 2003 and 2009. This product could be used to accurately monitor water level variations and to estimate annual water level trends of about 150 Tibetan lakes. Based on the ICESat campaign schedule, lake levels derived from the GLA14 data are classified into three groups referenced to the Tibetan seasons: late dry, early wet, and early dry. For each lake sampled by sufficient ICESat campaigns, seasonal water level trends could be estimated and inter-seasonal lake level variations could be determined. The results indicate that most of the southern Tibetan lakes have a downward seasonal trend while most lakes elsewhere in Tibet have a positive seasonal trend. This means that these seasonal trends are similar to the annual trends. Moreover, lake level variations between seasons are much larger in the south than in the north and the west of Tibet. Based on the spatial pattern of the lakes, the Tibetan plateau is divided into four sub-areas corresponding to seasonal lake level trends and inter-seasonal lake level variations. The results confirm climatic trends as discussed in meteorological literature. Therefore, this analysis is expected to improve the understanding of the limnological processes on the Tibetan plateau and their impacts on the surrounding regions.

Original languageEnglish
Pages (from-to)237-242
Number of pages6
JournalISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Volume1
DOIs
Publication statusPublished - 16 Jul 2012
EventXXII ISPRS Congress, Melbourne, Australia - s.l.
Duration: 28 Aug 20121 Sep 2012

Keywords

  • change detection
  • climate
  • hydrology
  • LIDAR
  • satellite
  • understanding

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