Moayyad Shawaqfah

Jordan experienced flash floods that resulted in numerous fatalities and injuries. This research focuses on identifying the Wadi Mujib’s flash flood potential zones and evaluating their potential magnitude. In this work, hydrological models were developed by integrating GIS settings with HEC-HMS software (V. 4.11). The hydrological model for Wadi Mujib is simulated in this research by means of the Soil Conservation Service (curve number method) while using rainfall data from 1970 to 2022. The results show that the optimum curve number values (CN) were 78.5 at normal antecedent moisture content. Additionally, in order to aid in the decision-making process for flash flood warnings, a flash flood potential index (FFPI) was also introduced based on four main physiographic parameters (slope, land use, plant cover, and soil texture) ranging from 1 to 10. The accumulative chart’s FFPI threshold, which indicates the areas with the highest potential for flash floods, was set at 95% or above. The FFPI threshold was chosen using the accumulative chart of FFPI, which shows that the FFPM threshold value is 7 and covers 13.39% of the study area.

This study employs adaptive deep learning (utilizing DNN and CNN approaches) to accurately predict soil erosion, a crucial aspect of sustainable soil resource management. The goal is to develop fuzzy logic models for erosion forecasting in a large watershed with limited in-puts, comparing them to predictions from the Revised Universal Soil Loss Equation (RUSLE). Integration of GIS enables analysis of satellite data, providing crucial details like land use, slope, rainfall distribution, and flow direction. This synergistic approach enhances erosion prediction capabilities and yields spatial erosion distributions. Producing precise erosion risk maps within GIS is crucial for prioritizing high-risk areas and implementing effective conservation methods in the Wadi Sahel watershed, Algeria. The assessment in the Oued Sahel-Soummam watershed involved overlaying five RUSLE factor maps using Arc GIS spatial analysis, resulting in an aver-age annual soil loss of 4.22 tons per hectare. The DNN and CNN models were integrated with GIS for detailed calculation of annual average soil loss (tons per hectare per year) and mapping erosion risk areas in Wadi Sahel-Soummam watershed. Using the CNN model, estimated annual soil loss in Sahel-Soummam wadi was about 4.00 tons per hectare per year, while the DNN model estimated around 4.13 tons per hectare per year. This study employed two deep learning models for erosion prediction, with the DNN model featuring six hidden layers performing no-tably better than the compared CNN model.

This article presents a study on the daily reliability analysis of a full-scale activated sludge wastewater treatment plant located in Northern Jordan. The coefficient of reliability (COR) is calculated to assess the performance of the plant in regard of wastewater concentrations of COD, BOD5, and TSS. The results indicate that the global effluent performances for COD, BOD5, and TSS comply with Jordanian standards. However, the BOD5 performance is found to be below the quality level due to issues in the ventilation basin and exceeding treatment capacity, while the TSS performance is affected by problems in the grit chamber and variations in influent quality and quantity. The study fills a research gap by focusing on the reliability of wastewater treatment plants using activated sludge technology and utilizes a probabilistic model proposed by Niku et al., (1979) to evaluate the reliability. The findings provide valuable insights into the daily variability of the treatment plant and suggest measures for improving reliability and overall efficiency

Even though the Kingdom of Jordan is moving in the right direction and adopting clean energy sources such as PV plants, the waste problem will eventually emerge within a few decades and will be an overwhelming issue if not addressed early on. According to reports, the installed PV capacity worldwide was around 410 GW in 2017 and is projected to increase to 5000 GW by 2050. Global solar PV waste is anticipated to reach between 5% and 15% of total generation capacity by 2030, with a 25-year average panel lifespan. This study aims to provide an estimation of the amount of PV waste expected within the next decade, and finally expand on the economic and environmental effects. Moreover, this paper’s target is to explore the possible effects of PV waste materials in the northern part of Jordan, and the obtained results can be applied to other regions in Jordan. Information about renewable energy in Jordan, retrieved from databases of electricity companies, is utilized to reach an accurate estimation of the amounts of materials that will occur at the end of life. The solar PV panel end of life (EOL) management is a developing field that necessitates additional research and development The obtained findings, figures, and facts about the photovoltaic solar energy sector presented in this study highlight the urgency to develop a suitable system for the collection and management of photovoltaic modules at their end of life.

Due to limited rainfall and precipitations, different developing countries depend on groundwater (G.W.) resources to challenge water scarcity. This practice of continuous and excessive G.W. pumping has led to severe water shortages and deteriorated water quality in different countries. Recharging of treated wastewater (TWW) into G.W. provides a critical solution for solving water scarcity, extending the well’s service life, and maintaining the G.W. supply. However, effective injection practice requires accurate tools and methods to determine the best location for groundwater recharge (GWRC). This work offers a new tool based on GIS–Multi-Criteria Analysis to identify the potential site and locations for GWRC with TWW. The developed methodology was applied to one of the most used well-field areas in Jordan (Dhuleil-Halabat). The G.W. flow for the B-B2/A7 formation system in the area of study was simulated using Processing Modflow (version 8.0). The analysis combined six thematic maps produced following the environmental, technical, and economic criteria to draw conclusions and recommendations. Both steady and transient conditions were used to predict the future changes that might occur under different stresses and after continuous GWR. The study evaluated three possible scenarios of artificial GWRC to evaluate the process efficiency and determine the effect on the water table level. The results revealed that only 0.05% (0.14 Km²) of the total surface area of 450 Km² is suitable for GWRC. A GWRC with TWW at a rate of 3.65 Mm³/year (MCMY) would provide a good G.W. table recovery to 39.68 m in the year 2025, maintain a steady-state water table ≥ of 50.77 m for up to six years, and secure water supply for future generations. The proposed methodology can be used as a useful tool that can be applied to regulate the GWRC practice worldwide.

With the increase in oil prices, developing nations end up paying expensive electricity and heating bill. This leading study investigates the experimental development of a new energy-saving system by integrating a solar water heater and solar cooling absorption cycle with a conventional boiler for domestic hot water and heating purposes. The heating and cooling load calculations for space heating of the building were calculated using TRNSYS 14.1 computer software and the results were used in calculating the energy-saving value. A 65 flat plate solar collector-chiller system with a total surface area of 130 m² was integrated with the boiler and used to supply heating and cooling for a three-story building (1500 m²) in Al Bayt University, Jordan. The integrated system helped to save energy, reduced the emission of CO₂ into the atmosphere, supplied hot water, and space heating/cooling requirements to the building year-round, and reduced the overall energy cost of heating and cooling by 55% and 48%, respectively. Moreover, the techno-economic analysis showed that the payback period of the combined system with a total cost of $18,650 is roughly 2.5-year. The solar water heating/cooling system has the potential to provide more than 50% of the house energy demand free of charge with a significant reduction in carbon footprint.

Jordan is located in an arid and semi-arid climatic zone, where about 80% of the country, known as the "Badia". Generally, this is classified as a dry or arid region. Climate change is expected to exacerbate the current aridity and scarcity of water resources in Jordan. Sudden and extreme weather events are becoming more common; this likely means longer and drier summers, more severe droughts, harsher winters, and an increase in flash floods. Jordanian Civil Defense reported that during 1963-2019, 451 people were killed and about one million people affected by flash floods. This research aims to determine the critical locations of flash floods in the Amman Zarqa Basin. This research methodology depends on using four variables (slope, vegetation cover/density, soil type/texture, and land use/cover) under the GIS environment to calculate the Flash Flood Potential Index (FFPI). This index has not been used in Jordan (up to our knowledge). Five scenarios were used in this study, based on previous reviews and the last one (scenario 5) based on Jordanian experts of flash floods in Jordan. The results show that increasing the weight of slope and land use in different FFPI equations will increase the values of FFPI. Reducing the vegetation density by 50% resulted in limited effects on the importance of FFPI. The risk level is divided into four categories (extreme, high, medium, and low) related to the FFPI values. Scenario two, which uses equal weights for all parameters, had the lowest risk level all over the area. Scenario four, which double the consequences of the slope and the land use with respect to the other two parameters. This has the highest risk level over the study area. Based on equation no. 5, which is modified based on Jordanian experts' opinion, the low-risk level covered 9.01% of the basin. Besides, the medium, high, and extreme risk levels covered 72.96%, 15.89%, and 2.14% of the study area, respectively.