Saied Morid, Mahnosh Moghaddasi,
Volume 9, Issue 1 (3-2005)
Abstract
Tehran province experienced one of the severest drought status during 1998 to 2000. This drought can be assessed by drought indices. Drought indices are quantitative expression of this disaster that make its spatial and temporal evaluations possible. In this research work three indices including EDI, SPI and DI have been used to develop monthly drought maps for the aforementioned period, using the information of 43 meteorological stations and geographical information system (GIS). The results show that DI has very exaggerated responses to rainfall, especially to the summer rainfall. Also SPI is not responsive enough to rainfall deficiencies. Morover, it frequently detected normal situation for this period. But, EDI is able to response properly and shows good temporal and spatial consistency in drought detection.
Volume 26, Issue 6 (11-2024)
Abstract
Climate change is one of the most important challenges that influence different parts of human life. An important consequence of climate change is its effects on water resources and the occurrence of drought. Since the agricultural sector is influenced by drought, the present research aimed to evaluate the livelihood resilience of farmers to drought in Kermanshah Township, Iran. The research used both primary and secondary data. First, the drought status of Kermanshah Township was evaluated with Standardized Precipitation Index (SPI) and Percent of Normal Index (PNI) and the Drought Indices Calculator (DIC) software package for a 51-year statistical period. Based on the results, the years 1973, 1978, 1979, 1995, 1999, 2001, 2008, 2013, and 2015 were dry. It was observed that, as we approached 2020, the number of years with a negative SPI increased. Then, the dimensions of livelihood capital were studied with the focus group method in the form of three focus groups from the perspective of 19 key experts. Data in this phase were analyzed by the content analysis method. The output of this phase was the development of a questionnaire for the final phase. Finally, to check the livelihood capitals influencing the enhancement of farmers’ resilience to drought in the region, 380 farmers were selected by the multistage sampling method. The potential of the independent variables in accounting for the variance in the farmers’ livelihood resilience was checked by stepwise multivariate linear regression. Based on the results, the variables of financial capital, social capital, and human capital with beta values of, respectively, 0.378, 0.324, and 0.152 had the greatest role in capturing the variance in farmers’ resilience to drought in Kermanshah Township.
