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Spatio-Temporal Variation of Climate Change and its Impacts on Agriculture in Iran

Malaekeh, Morteza | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54996 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Safaie, Ammar; Shiva, Layla
  7. Abstract:
  8. The relative lack of research concerning the potential impacts of climate change on different sectors in developing countries, especially the Middle Eastern countries, as the essential prerequisite of climate policy actions has made these countries the frontline against climate impacts. To fill this gap, in the first phase, we first analyzed spatial distributions and trends in thirty-seven hydro-climatic mean and extreme indices across Iran based on the state-of-the-art reanalysis datasets (ERA5-Land and AgERA5) at the county level from 1986 to 2015 using several nonparametric approaches such as multiple modified Mann-Kendall statistical tests and Sen’s Slope estimator. Their interannual oscillations were also examined using continuous wavelet transform to portray a complete picture of the temporal variability of the variables. Thereafter, we used a non-market valuation model to assess the future impacts of climate change on agriculture in Iran. In this phase, the relationship between farmland net revenue, as a proxy for land values, and climate change was investigated using a long-spanning Ricardian framework. For farm variables, we took into account novel hydro-climatic variables and climate extreme indices by taking advantage of the high-resolution meteorological dataset to tackle the sparse distribution of weather stations in Iran. For non-farm variables, we considered the pressure of rapid urbanization and migrations from rural areas in addition to socio-economic variables. This study also contributed to the body of literature through methodological improvement by taking advantage of spatial panel econometrics to develop a more robust and consistent model against spatial dependency, spatial heterogeneity, and omitted factors extraneous to the agriculture sector. The estimated coefficients were then employed in projecting long-run welfare impacts on the agricultural sector under several climate change scenarios based on the sixth phase of the Coupled Model Intercomparison Project (CMIP6) in 2050 and 2080. The results show that although climate change probably could have deleterious impacts on agriculture when we see the whole picture, its impacts would highly depend on climate zones and geographical locations
  9. Keywords:
  10. Climate Change ; Continuous Wavelet Transform ; Climate Impacts ; Long Term Trend Analysis ; Spatial Panel Econometrics ; Spatio-Temporal Analysis ; Rural Economy

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