Predicting vegetation phenology in response to climate change using bioclimatic indices in Iraq

Afrah Daham, Dawei Han, W. Matt Jolly, Miguel Rico-Ramirez, Anke Marsh

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)
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Abstract

Although most phenology models can analyze and predict future trends in response to climate change, these models often perform poorly in semi-arid regions where precipitation is limited. In this study, we modified an existing phenology model, the Growing Season Index (GSI), to better quantify relationships between weather and vegetation canopy dynamics across various semi-arid regions of Iraq. A modified GSI was created by adding a cumulative precipitation control to the existing GSI framework. Both unmodified and modified GSI values were calculated for three locations in Western Iraq: Sulaymaniyah in the north, Wasit in the centre and Basrah in the south as well as a country-wide mean and the running mean daily unmodified and modified GSI values for these study areas were calculated from 2001-2010 and compared to the Normalized Difference Vegetation Index (NDVI) from MODerate-resolution Imaging Spectroradiometer (MODIS) for the same time period. Country-wide median inter-annual correlations between GSI and NDVI more than doubled with the addition of the precipitation control and within-site correlations also show substantial improvements. The modified model has a huge potential be used to predict future phenological responses to changing climatic conditions, as well as to reconstruct historical vegetation conditions. This study is important to understanding not only the Iraqi region as it considers the results of climatic and environmental changes that have taken place in recent decades, but it should improve vegetation phenological predictions across Iraq and other semiarid regions of the world, particularly in the face of rapid climate change and environmental deterioration.
Original languageEnglish
Pages (from-to)835–851
JournalJournal of Water and Climate Change
Volume10
Issue number4
Early online date23 Feb 2018
DOIs
Publication statusPublished - 1 Dec 2019

Keywords

  • climate change
  • minimum temperature
  • GSI model
  • phenology
  • photoperiod
  • vapour pressure deficit
  • daylength
  • precipitation

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