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This paper provides an example for regional scale analysis of climate vulnerability incorporating environmental as well as socio-economic indicators. Researches have focused on different aspects of climate vulnerability so far, but usually there is little connection between the physical and social dimensions. Our study provides a more complex analysis, which builds on the application of international indices which have been used on the local and regional levels very rarely. In our research we combined physical and human geographical approaches and research techniques. The physical geographical assessment is based on indicators referring to ground water levels and vegetation production, while the human geographical side of the analysis focuses on economic and social sensitivity, adaptation and exposure indices, combined in the so-called socio-economic climate vulnerability index. In the analysis we tried to figure out the most sensitive areas in the Hungarian Southern Great Plain region. The main findings of the study are "hot spots" which coincide on both analyses, therefore, the most sensitive areas under current climate change conditions could be delimited. This study also demonstrates that the resolution of global climate change vulnerability indices is not suitable for regional scale analysis because of the significant territorial differences. Therefore, local or regional scale assessments are needed for the preparation of strategies for the elaboration of mitigation and adaptation policies.

Water scarcity is one of the largest global risks in terms of potential impact over the next decade as it affects every continent is manifested by partial or no satisfaction of expressed demand, economic competition for water quantity or quality, disputes between users, irreversible depletion of groundwater, and negative impacts on the environment. Jordanian water crises are exacerbating all of the time due to increased water demands derived from high population growth, sudden fluxes of refugees, economic development, and increased frequency of drought events. These forces stress the urgent need to develop drought adaptation planning based on vulnerability mapping correlated to prolonged weather events. The objective of this research is thus to generate a drought vulnerability map with an emphasis on the severity and probability of drought occurrence, and to propose adaption measures based on groundwater sector impact chain analysis by incorporating numerical scorings for exposure, sensitivity, and adaptive capacities at groundwater basin and Jordanian district levels. Drought impacts on groundwater basins were investigated based on measurements of severity and probability of drought occurrence, and drought exposure over the whole country computed by means of a combined drought index (CDI) that included the precipitation drought index, temperature drought index, and vegetation drought index from 1980 to 2017. Results indicated that drought in Jordan is characterised by a temporal and spatial variability regarding probability and severity. The most prolonged drought events range from mild to moderate, with long periods of exposure that may extend for up to 13 consecutive years. Due to high groundwater basin sensitivity and low adaptive capacity, the groundwater systems in Jordan are fragile and highly vulnerable to drought impacts, being subject to either reduction in quantity and/or deterioration in quality over time. The most vulnerable groundwater basins are the Azraq and Dead Sea regions, while Disi and Yarmouk are also highly vulnerable groundwater basins based on the weak enforcement of transboundary agreements. The proposed drought risk management system based on this research includes proactive and contingency plans enabled by policies and legal frameworks at the national level to ensure sustainable water resilience and governance.

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One of the undoubtedly recognizable consequences of the ongoing climate change in Hungary is the permanent change of groundwater depth, and consequently the sustainably reachable local water resources. These processes trigger remarkable changes in soil and vegetation. Thus, in research of sensitivity of any specific landscape to the varying climatic factors, monitoring and continuous evaluation of the water resources is inevitable. The presented spatiotemporal geostatistical cosimulation framework is capable to identify rearrangements of the subsurface water resources through water resource observations. Application of the Markov 2-type coregionalization model is based on the assumption, that presumably only slight changes have to be handled between two consecutive time instants, hence current parameter set can be estimated based on the spatial structures of prior and current dataset and previously identified parameters. Moreover, the algorithm is capable to take into consideration the significance of the geomorphologic settings on the subsurface water flow. Trends in water resource changes are appropriate indicators of certain areas climate sensitivity. The method is also suitable in determination of the main cause of the extraordinary groundwater discharges, like the one, observed from the beginning of the 1980’s in the Danube–Tisza Interfluve in Hungary.