Groundwater resources are essential in Jordan that require careful planning and management in order to sustain human socio-economic development and various ecosystems. However these vital resources are under the threat of degradation by both mismanagement and over-exploitation that leads to contamination and decline of water levels. A new by-law, which specifically addresses pollution prevention and protection of water resources used for domestic purposes through appropriate land use restriction and zoning, is currently under preparation in Jordan. This law (i.e., Groundwater Management Policy) addresses the management of groundwater resources including development, protection, management, and reducing abstraction for each renewable aquifer to the sustainable rate (i.e., safe yield). Groundwater vulnerability mapping and delineation of groundwater protection zones were implemented in different areas in Jordan in cooperation between the German Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) company and Ministry of Water and Irrigation. This paper presents the status of groundwater resources in Jordan and their major issues. It attempts to discuss the groundwater vulnerability and protection strategy and the impacts of over-exploitation on the groundwater aquifers in an integrated water resources management perspective.

Understanding the causes and effects of road accidents is critical for developing road and action plans in a country. The causation hypothesis elucidates how accidents occur and may be applied to accident analysis to more precisely anticipate, prevent, and manage road safety programs. Driving behavior is a critical factor to consider when determining the causes of traffic accidents. Inappropriate driving behaviors are a set of acts taken on the roadway that can result in aberrant conditions that may result in road accidents. In this study, using Al-Ahsa city in Saudi Arabia’s Eastern Province as a case study, a Bayesian belief network (BBN) model was established by incorporating an expectation–maximization algorithm. The model examines the relationships between indicator variables with a special focus on driving behavior to measure the uncertainty associated with accident outcomes. The BBN was devised to analyze intentional and unintentional driving behaviors that cause different types of accidents and accident severities. The results showed when considering speeding alone, there is a 26% likelihood that collision will occur; this is a 63% increase over the initial estimate. When brake failure was considered in addition to speeding, the likelihood of a collision jumps from 26% to 33%, more than doubling the chance of a collision when compared to the initial value. These findings demonstrated that the BBN model was capable of efficiently investigating the complex linkages between driver behavior and the accident causes that are inherent in road accidents.

An experimental program was conducted in order to compare the engineering properties of reclaimed concrete aggregate waste from various demolition sources: lab-tested concrete waste from a commercial ready-mix company with known engineering properties, construction and demolition (C&D) concrete waste with some information about engineering properties, and regular aggregate from the market, which was used as control samples. This study explores the potential use of construction waste for the development of sustainable construction materials in order to obtain economic returns from the waste. After processing the construction debris into gravel, the amount of reclaimed material from the waste was calculated, and then aggregate tests were conducted. Lab samples were fabricated based on a 35 MPa mix-design with reclaimed aggregate from the various waste sources, along with control samples. Finally, compressive strength, tensile strength, and flexural strength, as well as some nondestructive tests (NDT), such as pulse velocity and hammer tests, were conducted. Correlation between results obtained from the various tests were analyzed in this experimental program; a linear correlation was noted between compressive strength and other mechanical properties evaluated, namely, split tensile strength, flexural strength, pulse velocity, and Schmidt Hammer.

Climate change poses a challenge to the security and long-term viability of the global food supply chain. Climate unpredictability and extreme weather events have significant impacts on Saudi Arabia’s vulnerable food system, which is already under stress. The Kingdom of Saudi Arabia faces distinct challenges in comparison to other dry locations across the world. Here, the per capita water demand is high, the population is growing, the water resources are extremely limited, and there is little information on the existing groundwater supplies. Consequently, it is anticipated that there will be formidable obstacles in the future. In order to make data-driven decisions, policymakers should be aware of causal links. The complex concerns pertaining to the Saudi Arabian food system were analyzed and rationally explained in the current study. A causality analysis examined different driving factors, including temperature, greenhouse gas (GHG) emission, population, and gross domestic product (GDP) that cause vulnerabilities in the country’s food system. The results of the long-run causality test show that GDP has a positive causal relationship with the demand for food, which implies that the demand for food will increase in the long run with an increase in GDP. The result also shows that Saudi Arabia’s GDP and population growth are contributing to the increase in their total GHG emissions. Although the Kingdom has made some efforts to combat climate change, there are still plenty of opportunities for it to implement some of the greatest strategies to guarantee the nation’s food security. This study also highlights the development of appropriate policy approaches to diversify its import sources to ensure future food security.

Considering hydro-climatic diversity, integrating dynamic dimensions of water security modeling is vital for ensuring environmental sustainability and its associated full range of climate resilience. Improving climate resiliency depends on the attributing uncertainty mechanism. In this study, a conceptual resilience model is presented with the consideration of input uncertainty. The impact of input uncertainty is analyzed through a multi-model hydrological framework. A multi-model hydrological framework is attributed to a possible scenario to help apply it in a decision-making process. This study attributes water security modeling with the considerations of sustainability and climate resilience using a high-speed computer and Internet system. Then, a subsequent key point of this investigation is accounting for water security modeling to ensure food security and model development scenarios. In this context, a four-dimensional dynamic space that maps sources, resource availability, infrastructure, and vibrant economic options is essential in ensuring a climate-resilient sustainable domain. This information can be disseminated to farmers using a central decision support system to ensure sustainable food production with the application of a digital system.