HOW WILL CLIMATE CHANGE IMPACT THE STORM MAGNITUDE AND THROUFALL IN SEVERAL FOREST AREAS IN IRAN?

• Main Authors: P. Attarod, Q. Tang, J. T. Van Stan II, T. G. Pypker, X. Liu
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-10-01
• Series: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Online Access: https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W18/117/2019/isprs-archives-XLII-4-W18-117-2019.pdf

Across all forest systems, the primary driver of throughfall (TF) amount is rainfall amount (P_g) though no work has addressed the sensitivity of the TF response to projected shifts in P_g due to climate change. We assessed how climate change may impact TF sensitivity to variability in P_g for eleven typical forest sites across the main climate types of Iran using a nondimensional relative sensitivity coefficient. The Coupled Model Intercomparison Project phase 5 (CMIP5) HadGEM2-ES product was used under two emission scenarios (Representative Concentration Pathway (RCP) 2.6 and 8.5) to project yearly precipitation and P_g for the measurement sites during 2020–50. There was a strong linear relationship between TF and P_g at all sites [TF = 0.66 (P_g) – 0.30; R² = 0.91; n = 639]. The sensitivity coefficient ranged from 0.96–5.3 across the eleven forest sites. Large sensitivity coefficient differences were found between small (< mean annual P_g) and large (> mean annual P_g) storms for arid plantations. To buffer expected shifts in storm size due to climate change, it may be suitable to incorporate TF sensitivity when choosing landscaping and urban greening. Shifts in P_g and increased small storm frequency are predicted for 2020–50 per CMIP5 HadGEM2-ES low and high emission scenarios.