Following the impact of droughts witnessed during the last decade there is an urgent need to develop a drought management strategy, policy framework, and action plan for Jordan. This study aims to provide a historical baseline using the standardized precipitation index (SPI) and meteorological drought maps, and to investigate the spatial and temporal trends using long-term historical precipitation records. Specifically, this study is based on the statistical analysis of 38 years of monthly rainfall data, gathered from all 29 meteorological stations that cover Jordan. The Mann–Kendall test and linear regression analysis were used to uncover evidence of long-term trends in precipitation. Drought indices were used for calculating the meteorological SPI on an annual (SPI12), 6-months (SPI6), and 3-months basis (SPI3). At each level, every drought event was characterized according to its duration, interval, and intensity. Then, drought maps were generated using interpolation kriging to investigate the spatial extent of drought events, while drought patterns were temporally characterized using multilinear regression and spatial grouped using the hierarchical clustering technique. Both annual and monthly trend analyses and the Mann–Kendall test indicated significant reduction of precipitation in time for all weather stations except for Madaba. The rate of decrease is estimated at approximately 1.8 mm/year for the whole country. The spatial SPI krig maps that were generated suggest the presence of two drought types in the spatial dimension: Local and national. Local droughts reveal no actual observed trends or repeatable patterns of occurrence. However, looking at meteorological droughts across all time scales indicated that Jordan is facing an increasing number of local droughts. With a probability of occurrence of once every two years to three years. On the other hand, extreme national droughts occur once every 15 to 20 years and last for two or more consecutive years. Linear trends indicated significant increase in drought magnitude by time with a rate of 0.02 (p < 0.0001). Regression analysis indicated that draught in Jordan is time dependent (p < 0.001) rather than being spatially dependent (p > 0.99). Hierarchical clustering was able to group national draughts into three zones, namely the northern zone, the eastern zone, and the southern zone. This study highlights the urgent need for a monitoring program to investigate local and national drought impacts on all sectors, as well as the development of a set of proactive risk management measures and preparedness plans for various physiographic regions.

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.

A hierarchical fuzzy inference system (FIS) integrated with the DRASTIC model is applied in this study to enhance the assessment of shallow groundwater vulnerability in southeast Hungary, a region characterized by extensive agriculture and industrial growth. Traditional groundwater vulnerability models often struggle with parameter imprecision and uncertainty, affecting their reliability. To address these limitations, fuzzy logic was incorporated to refine the classification of vulnerability zones. The hierarchical FIS incorporates the seven DRASTIC parameters: depth to the water table, net recharge, aquifer media, soil media, topography, vadose zone impact, and hydraulic conductivity, assigning flexible ratings through fuzzy membership functions. The model classifies the fuzzy groundwater vulnerability index (FGWVI) into low, moderate, and high categories, revealing that 63.9% of the study area is highly susceptible to contamination, particularly in regions with shallow water tables and sandy soils. Validation was conducted using nitrate (NO₃⁻) concentrations and electrical conductivity (EC) measurements from 46 agricultural wells to assess the correlation between predicted vulnerability zones and actual groundwater quality indicators. The correlation analysis revealed a moderately strong positive relationship between FGWVI and both NO₃⁻ (R² = 0.4785) and EC (R² = 0.528), supporting the model’s ability to identify high-risk contamination zones. This study highlights the effectiveness of the fuzzy-enhanced DRASTIC model in evaluating aquifer vulnerability and provides crucial insights to assist policymakers in identifying pollution sources and developing strategies to mitigate groundwater contamination, thereby alleviating the stress on this critical resource.

The research investigated the process of excess water formation. Complex measurement stations were developed in order to determine the most important hydro-meteorological and soil factors contributing to the formation of excess water. The stations measure the amount of precipitation, evapotranspiration, evaporation from water surface, soil moisture in 3 different depths; soil temperature in 5 different depths; furthermore, soil water level. The study area is located in the southeastern part of Hungary, near Szeged, in the flood plain of Tisza and Maros with extremely clayey soils. The former soil data were completed by new soil survey to determine several soil parameters (e.g. bulk density, porosity, field capacity, saturated hydraulic conductivity). Infiltration was calculated from the measured parameters and water budget elements of bigger rainfall event were analyzed between March 2010 and August 2011. Genetic types of excess water can be separated based on the data.

The quality of newly constructed pavement depends mostly on compaction, which is essential for ensuring the pavement’s longevity and performance. Traditional methods of evaluating pavement compaction and density, such as core sampling and nuclear gauge measurements, are often time-consuming and invasive and provide only a limited amount of data at a low spatial resolution on the potential air void content of the asphalt layers. The present study aimed to assess the specific gravity (G_mb) of a dolomitic asphalt mixture at different degrees of compaction using GPR techniques. Relative density (RD) maps were generated to visualize the spatial homogeneity of the asphalt density. Nuclear density gauging was applied for the calibration, and cores were used to validate the results. The survey was conducted on two recently paved roads in Szeged, Hungary. After testing various approaches, it was found that applying horn antennas and the surface reflection (SR) method is the most feasible way to obtain reliable and accurate dielectric permittivity (ε) data. Based on the measurements, clear relationships were found between dielectric constants, G_mb, and aggregate size. The findings highlight that it is possible to indirectly determine the G_mb of asphalts composed of dolomite and limestone aggregates using GPR, with aggregate sizes ranging from 11 mm to 25 mm and G_mb values between 2.43 and 2.57 g/cm³. Consequently, a robust function was developed, which can be applied to other asphalts with similar compositions.