Publication detailsPereira, Ryan, Bovolo, C. Isabella, Forsythe, Nathan, Pedentchouk, Nikolai, Parkin, Geoff & Wagner, Thomas (2014). Seasonal patterns of rainfall and river isotopic chemistry in northern Amazonia (Guyana): From the headwater to the regional scale. Journal of South American Earth Sciences 52: 108-118.
- Publication type: Journal Article
- ISSN/ISBN: 0895-9811
- DOI: 10.1016/j.jsames.2014.02.005
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
We use first field-based observations of precipitation and river isotopic chemistry from a three-year study (2009–2011) in rainforest and nearby savannah in central Guyana at the northern rim of the Amazon rainforest to establish the quality of modelled or remotely-sensed datasets. Our 3 years of data capture a reduced rainfall regime in 2009 and an extended wet season in 2010, in contrast to the widely documented Amazonian floods in 2009 and droughts in 2010. Comparisons of observed precipitation with satellite derived TRMM and ECMWF ERA-Interim reanalysis precipitation show that both of these data sets capture the general pattern of seasonality, but substantially underestimate rainfall amounts in the primary wet season (by up to 50% and 72% respectively). The TRMM dataset is generally better at characterising the main dry season from September to December but the ERA-Interim model can overestimate precipitation in the dry season by up to 175%. Our new data on isotopic chemistry of river waters show that δ2H/δ18O values in this region are broadly consistent with interpolated global datasets of modelled precipitation isotopic signatures. The dominance of isotopically lighter water derived from the rains of the ITCZ during the wet season provides evidence of the close coupling of water chemistry of headwater rivers on the northern rim of Amazonia to the positioning of the ITCZ over the region. Our results highlight the challenge in understanding and representing local scale hydrological and biogeochemical characteristics using regional scale model data. We argue that combining point and local scale field data with larger scale model data is necessary to progress towards a comprehensive understanding of climate–hydrology interactions in Amazonia.