Investigating the leaf area index changes in response to climate change (case study: Kasilian catchment, Iran)

Vegetation cover plays an important role in the hydrologic cycle of Kasilian catchment in Iran. This study aimed to estimate leaf area index (LAI), as an important vegetation factor in hydrologic loses, in response to climate change in the future period (2020–2039) over Kasilian catchment located in the north of Iran. For this purpose, LAI was simulated by gridded BIOME-BGC in 319 pixels within the case study domain over the study period (2004–2013) for three dominant land covers of the Kasilian catchment including deciduous broadleaf forest (DBF), shrubs, and C3 grasses, and BIOME-BGC accuracy has been assessed using MODIS-derived LAI. Then, monthly projections of climate variables obtained from the average of 9 AOGCMs-AR5 in the future period (2020–2039) and annual projection of CO2 level from 2004 to 2039 under RCP2.6 and RCP8.5 scenarios were used to assess the impact of climate change on LAI. Results show that LAI will increase in response to the overall predicted rise in temperature, precipitation, and CO2 level under both scenarios in all pixels. This increase under the RCP8.5 scenario is predicted to be more than RCP2.6 scenario so that the mean LAI in Kasilian catchment will increase by 3.1% and 2.2% under RCP8.5 and RCP2.6 scenarios, respectively. In addition, our analysis showed that DBF land cover will be more sensitive to climate change in this catchment.