Due to the complex and multi-dimensional nature of droughts, it is not possible to assess droughtinduced damage and its consequences for various social, economic, and environmental aspects of societies by relying only on a univariate index such as precipitation-based drought indices. The present study aimed to develop a practical and scientific framework based on hazard, vulnerability (social, economic, and environmental), and coping capacity to generate a drought risk map for the hot and dry climate regions of Iran. Accordingly, the Drought Hazard Index (DHI), Drought Vulnerability Index (DVI), and Drought Coping Capacity Index (DCCI) were derived from the Standardized Precipitation Evapotranspiration Index (SPEI), 16 social, economic and environmental variables and three social, economic variables, respectively. The layers of all variables of the three indices in the GIS were provided, and they were combined in the form of an equation to produce a drought hazard map of central and southeastern Iran. The results indicate that the counties most and least vulnerable to drought were located in the southeast and west of the case study area, respectively. A number of large households, long distances from provincial centers, and soil erosion were the most important social, economic, and environmental factors making the southeast of the case study (including south of Sistan and Baluchestan and south of Kerman provinces) most vulnerable to drought. Due to their high drought coping capacity, counties located in the west of the case study (west of Kerman and south of Yazd provinces) were least vulnerable to drought. Extended support for low-income households by charitable organizations, tertiary education, and most importantly, a variety of jobs and career opportunities were the most important factors in reducing vulnerability in this part of Iran. Furthermore, our methodology by taking social, economic, and environmental dimensions into account as risk, vulnerability, and coping capacity indices can be far more efficient than the methods considering only risk and vulnerability factors.

Climate change is projected to increase the frequency and severity of droughts, possibly causing sudden and elevated tree mortality. Better understanding and predictions of boreal forest responses to climate change are needed to efficiently adapt forest management. We used tree-ring width chronologies from the Swedish National Forest Inventory, sampled between 2010 and 2018, and a random forest machine-learning algorithm to identify the tree, stand, and site variables that determine drought damage risk, and to predict their future spatial-temporal evolution. The dataset consisted of 16,455 cores of Norway spruce, Scots pine, and birch trees from all over Sweden. The risk of drought damage was calculated as the probability of growth anomaly occurrence caused by past drought events during 1960-2010. We used the block cross-validation method to compute model predictions for drought damage risk under current climate and climate predicted for 2040-2070 under the RCP.2.6, RCP.4.5, and RCP.8.5 emission scenarios. We found local climatic variables to be the most important predictors, although stand competition also affects drought damage risk. Norway spruce is currently the most susceptible species to drought in southern Sweden. This species currently faces high vulnerability in 28% of the country and future increases in spring temperatures would greatly increase this area to almost half of the total area of Sweden. Warmer annual temperatures will also increase the current forested area where birch suffers from drought, especially in northern and central Sweden. In contrast, for Scots pine, drought damage coincided with cold winter and early-spring temperatures. Consequently, the current area with high drought damage risk would decrease in a future warmer climate for Scots pine. We suggest active selection of tree species, promoting the right species mixtures and thinning to reduce tree competition as promising strategies for adapting boreal forests to future droughts.