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Impact of Climate Variables Change on the Yield of Wheat and Rice Crops in Iran (Application of Stochastic Model Based on Monte Carlo Simulation).

Akram JavadiMohammad GhahremanzadehMaria SassiOzra JavanbakhtBoballah Hayati
Published in: Computational economics (2023)
This study aims to predict the yield of two strategic crops in Iran; wheat and rice, under climate scenarios that indicate probable changes in climate variables. It implemented by a stochastic model based on the Monte Carlo method. This model were estimated based on historical data from 1988 to 2019 for precipitation and temperature provided possible changes in the pattern of and their probability of occurrence. The results show that rain-fed wheat, irrigated wheat and rice yields decrease by 42%, 29% and 21% respectively in the average scenario. Therefore, policy makers should try to make the right decisions to increase the production of the country's strategic crops. R&D management to introduce drought-tolerant varieties, use of modern irrigation systems and use of low-volume irrigation methods are some of the proposed solutions to mitigate the effects of climate change.
Keyphrases
  • climate change
  • monte carlo
  • human health
  • public health
  • risk assessment
  • machine learning
  • artificial intelligence
  • deep learning
  • water quality