جستجوی مقالات مرتبط با کلیدواژه « Climate disasters » در نشریات گروه « جغرافیا »

The impact of climate change on societies depends on their resilience. The economic resilience approach, due to its dynamic and foresight nature, can be more effective in increasing the economic adaptability of farmers against disasters. This study was conducted with the aim of obtaining suitable indicators for evaluating the economic resilience of farmers in dealing with climate disasters. The current research was conducted in two stages using systematic review and Delphi techniques. In the first stage of the study, based on a systematic review of the theoretical literature on resilience, a model of resilience that is adapted from Jantao's economic resilience model was selected as a suitable model for farmers' economic resilience studies, which consists of three main dimensions of stability, adaptation and change. THEN 44 primary indicators were extracted based on a systematic review of the theoretical literature of resilience studies. The second stage was done using the Delphi technique. According to the results, out of the 44 investigated indicators, 19 indicators were selected as suitable indicators for evaluation, and based on the opinions of experts and elites, 6 indicators in the dimension of stability, 9 indicators in adaptability and 4 indicators in change were the most frequent, and the indicators of the ability to adapt Relative economic conditions of the family at the time of crisis, having diverse job and livelihood capacity, ability to create and develop business through diversification of non-agricultural activities were of the greatest importance and emphasis.

The increase in greenhouse gases in the last few decades has caused a disturbance in the global climate balance and climate changes (Aalst, 2006). Climate change and the increase in extreme conditions have caused disasters (Helmer & Hilhorst, 2006), increasing floods, and tropical storms (Haqtalab et al., 2012). Other consequences of climate change are changes in erosion and soil loss (Akbarian & Khoorani, 2022). Soil loss and sediment transport have always been one of the most critical problems of land management. Climate change and, consequently, changes in precipitation affect soil erosion and loss from various aspects such as the amount, intensity-duration, and distribution of rainfall (Gabris et al., 2003). As a result of climate change, the erosive power of rain is expected to increase (Sun et al., 2002). In order to predict the effects of climate change on the erosivity of rainfall, it is necessary to predict rainfall with climate models and then estimate the erosive power of rainfall with suitable erosion estimation models. Rainfall is the most crucial active driver of soil loss that displaces soil particles (Talchabhadel, 2020). It is difficult to accurately evaluate raindrops' characteristics with soil displacement and detachment. Therefore, the empirical methods are used based on rainfall. Some of these empirical models can be used with future climate data. The Revised Universal Soil Loss Equation (RUSLE) is one of the models used to predict soil erosion. Since precipitation is one of the main factors in this model, many researchers have used it to reflect upon the role of climate change on erosion changes. According to Goldies et al. (2022), using the RUSLE-GIS approach can estimate the current and future annual soil erosion rates in watersheds by reflecting climate change to the R factor based on the latest CMIP6 phase 6 climate forecasts.
Soil loss and sediment transport have always been one of the most critical problems of land management. According to the mentioned materials, the use of different models to estimate erosion is essential in the basins that are faced with a lack of data and statistics. The area studied in this research is the Minab watershed, which is vital from various economic and social aspects, especially the drinking water supply of Bandar Abbas in Hormozgan province. Accordingly, this research tried to determine the changes of erosion in these periods by examining the climate condition in the past, present, and future periods so that this information becomes available to decision-makers and managers for better planning. The Minab watershed is located in the range of 48°56° to 57°59° east and 27° to 28°32° north latitude. This basin is one of the sub-basins of Bandar Abbas-Sedich, located in the northeast of Hormozgan province and the south of Kerman province. The area of the basin is 10613 square kilometers. The Minab River, which is the result of the connection of the Jaghin and Rodan rivers, is considered the most important river in this basin. With the construction of the Minab Dam, its water resources are used to provide drinking water to Bandar Abbas.

This research used monthly data from meteorological stations, precipitation data extracted from different climate models and scenarios, soil data, and satellite images. The climate data are in different periods (base period 2020-2002 and future period 2020-2050). The RUSLE model was used to study erosion changes due to climate change. First, by preparing the RUSLE model invoices, the model was implemented for the 2010 and 2020 time periods. Next, two climate models, BCC-CSM2-MR and CanESM5, based on the sixth report and under scenarios 2.6, 4.5, and 8.5, were used to predict precipitation. After evaluating the models, the precipitation erosion layer in 2040 was prepared by the two models.

The results showed that the average rain erosivity layer has increased from 41.57 in 2010 to 52.01 in 2020. There is not much difference between the prediction results of the BCC-CSM2-MR model and the observed value, so it can be said that the model performed well in different scenarios. Among the used scenarios, the 8.5 scenario has the slightest error, and the 4.5 scenario is placed at the end. In the case of the CanESM5 model, there is no significant difference between the observed and the predicted values. Although the difference increases for more distant years, such as 2040, the results of different scenarios are similar. The output of the two BCC-CSM2-MR and CanESM5 models also indicate an increase in the rate of precipitation erosion in 2040. The average erosion in 2010 was 13.8 t/ha/y, which increased to 17 t/ha/y in 2020 and was predicted to increase to 17.3 t/ha/y in 2040.

The average rain erosion layer in 2010 was 41.57; in 2019, this value reached 52.01. According to the results, the analysis of precipitation data obtained from climate scenarios and models shows an increase in the erosivity factor of rain in the near future (2040). Considering the importance of the rainfall erosivity layer in water erosion, if other factors affecting erosion remain constant, in the near future, we will see an increase in erosion and soil loss in the Minab basin. The results of the RUSLE model in the three periods also indicate an increase in erosion over time. The spatial changes of basin erosion are a function of LS (topographic factor), and the rainfall erosivity factor (P) causing temporal changes in erosion.