Investigating the spatial distribution of future precipitation in Nahavand plain, Hamedan province

Authors

1 Dept of water Engineering

2 Dept. water Engineering, college of Agriculture BASU, Hamedan, Iran

3 Dept. of water Engineering, Hamedan

Abstract

The increase in the temperature of the earth causes the climates to change and transform on a wide scale and causes changes in the time and place of precipitation. In this research, the precipitation of seven meteorological stations of Barzool, Faresban, Firoozan, Giyan, Gooshesadevaghas, Synoptic and Varayaneh, Nahavand Plain, Hamadan Province in the west of Iran during the period of 1994-2020 was prepared on a daily basis from the relevant organization. Then, using the LARS-WG6.0 climate change model, precipitation was predicted under two scenarios RC4.5 and RCP8.5 during four time periods: 2021-2040, 2041-2060, 2061-2080, and 2081-2100. And the results of the spatial distribution were drawn as the annual average of the investigated period by Arc GIS 10.3 software. The calibration results of the LARS-WG6.0 model for forecasting precipitation in the region showed a high correlation coefficient of 0.94 and an nRMSE error of less than 10%. which proves the high accuracy of this model in predicting precipitation in the region. The results of the spatial distribution of precipitation under two scenarios and 4 time periods using Arc GIS10.3 software show that the RCP4.5 scenario has predicted less precipitation for the period 2041-2060 than the RCP8.5 scenario. And in the other three investigated periods, the amount of precipitation under the RCP4.5 scenario is higher than the RCP8.5 scenario. Under the two scenarios and four time periods studied, among the seven studied stations, Barzool station has the highest percentage of increase in precipitation compared to the base period. Under the RCP8.5 scenario, in the period of 2061-2080, the average precipitation of the period will decrease (3.13%), the highest percentage of decrease belongs to Gooshesadevaghas station with the amount of 7.99%.

Keywords



Articles in Press, Accepted Manuscript
Available Online from 13 January 2024
  • Receive Date: 05 December 2023
  • Revise Date: 08 January 2024
  • Accept Date: 13 January 2024