Over the past few decades, solid waste production, specifically construction waste, in Middle Eastern Arab countries has dramatically increased. This is characterized by several factors, including rapid urbanization, common food wasting habits, diverse culture, lack of proper planning of solid waste processes, insufficient equipment, as well as lack of proper funding. The exponential growth in solid waste generation rates has led to hazards to health and the environment, causing issues related to air and water pollution under the already increasing pressure of climate change. In this review, we analyze the current solid waste challenges in 13 Arab countries, common diseases, and actual projects applied. The selection of Arab countries was mainly based on the countries with the highest population as well as the availability of data in the field of study. This review also highlights the efforts of the Arab governments that implemented several pilot projects that are not sustainable or effective in the long term. We discuss the main issues facing each Arab country and the main challenges they have in common, as well as the potential to use the great amounts of construction waste in these countries. It is recommended that proper disposal and collection plans should be prioritized in the municipalities’ agendas since air and water pollution represent the main challenge in all Arab countries. Adequate treatment, recycling, and compost production facilities should be initiated and monitored regularly to take advantage of the relatively high percentage of organic matter in most Arab countries. Proper cooperation between the informal sector, private companies, and governments should be ensured in order to achieve long-term goals in the solid waste management (SWM) sector in MENA (Middle East and Northern Africa) Arab countries. This review provides a comprehensive study of the construction waste in MENA Arab countries that will help reach the goal of achieving sustainable countries.

Accurate reservoir inflow predictions are critical for effective flood control and optimizing hydropower generation, thereby enhancing water resource management. This study introduces an advanced hydrological modeling approach that leverages a basic recurrent neural network (bRNN), convolutional neural network (CNN) with gated recurrent units (GRU) (bRNN-CNN-GRU), GRU with long short-term memory (LSTM) (GRU-LSTM) hybrid models, and deep neural network (DNN) to predict daily reservoir inflow at the Sefid Roud Dam. By utilizing historical data from 2018 to 2024, this study examined the following two multivariate scenarios: one incorporating water parameters such as water level, evaporation, and temperature extremes, and another focused solely on inflow delays. Training and testing sets were created from the dataset, with 80% for training and 20% for testing. For benchmarking purposes, the performance of the bRNN-CNN-GRU was evaluated against a deep neural network (DNN) and a GRU-LSTM hybrid. The evaluation metrics used were root mean square error (RMSE), correlation coefficient (r), and Nash Sutcliffe coefficient (NSE). Results demonstrated that, while all models performed better under the scenario incorporating inflow delays, the bRNN-CNN-GRU model achieved the best performance, with an RMSE of 0.71, r of 0.97, and NSE of 0.95, outperforming both the DNN and GRU-LSTM models. These findings highlight the significant advancements in hydrological modeling and affirm the applicability of the bRNN-CNN-GRU model for improved reservoir management in diverse settings.

The Sultanate of Oman is in the south-eastern part of the Persian Gulf. Oman's coast causes Oman to be exposed to tropical cyclones occasionally. The damages occur when hurricanes reach the land, but some hurricanes dissipate in the sea without any noticeable harm. Generally, these strong storms hit Oman every 3 or 4 years between June and October, and it is mostly in the southern part of the Sultanate. One of these cyclones was Gonu on June 1, 2007, which caused 50 deaths in total and the damaged areas cost around $4.2 billion (2007 US dollars). This paper reviews and tracks the tropical cyclone Shaheen, which hit the Omani coast on October 2, 2021. We have used the hydrological data of previous cyclones to state the level of damage the cyclone caused. As expected, the cyclone caused a lot of human and material losses in a very short period due to the inadequate flood drain systems in Al-Khaboura city. Results showed the necessity of a proper stormwater drainage system to be installed in the northern cities of Oman. These effects were followed by a 2-day holiday for both government and private sectors for the sake of people's safety.