It is well recognized that management of wastewater and sludge is a critical environmental issue in many countries. Wastewater treatment and sludge production take place under different technical, economic, and social contexts, thus requiring different approaches and involving different solutions. In most cases, a regular and environmentally safe wastewater treatment and associated sludge management requires the development of realistic and enforceable regulations, as well as treatment systems appropriate to local circumstances. The main objective of this paper is to provide useful information about the current wastewater and sludge treatment, management, regulations, and research in Oman. Based on the review and discussion, the wastewater treatment and sludge management in Oman has been evolving over the years. Further, the land application of sewage sludge should encourage revision of existing standards, regulations, and policies for the management and beneficial use of sewage sludge in Oman. Implications: Wastewater treatment and sludge management in Oman have been evolving over the years. Sludge utilization has been a challenge due to its association with human waste. Therefore, composting of sewage sludge is the best option in agriculture activities. Sludge and wastewater utilization can add up positively in the economic aspects of the country in terms of creating jobs and improving annual income rate. The number of research projects done on wastewater reuse and other ongoing ones related to the land application of sewage sludge should encourage revision of existing standards, regulations, and policies for the management and beneficial use of sewage sludge in Oman.

There has been growing interest in the application of smart technologies for hazard management. However, very limited studies have reviewed the trends of such technologies in the context of flash floods. This study reviews innovative technologies such as artificial intelligence (AI)/machine learning (ML), the Internet of Things (IoT), cloud computing, and robotics used for flash flood early warnings and susceptibility predictions. Articles published between 2010 and 2023 were manually collected from scientific databases such as Google Scholar, Scopus, and Web of Science. Based on the review, AI/ML has been applied to flash flood susceptibility and early warning prediction in 64% of the published papers, followed by the IoT (19%), cloud computing (6%), and robotics (2%). Among the most common AI/ML methods used in susceptibility and early warning predictions are random forests and support vector machines. However, further optimization and emerging technologies, such as computer vision, are required to improve these technologies. AI/ML algorithms have demonstrated very accurate prediction performance, with receiver operating characteristics (ROC) and areas under the curve (AUC) greater than 0.90. However, there is a need to improve on these current models with large test datasets. Through AI/ML, IoT, and cloud computing technologies, early warnings can be disseminated to targeted communities in real time via electronic media, such as SMS and social media platforms. In spite of this, these systems have issues with internet connectivity, as well as data loss. Additionally, Al/ML used a number of topographical variables (such as slope), geological variables (such as lithology), and hydrological variables (such as stream density) to predict susceptibility, but the selection of these variables lacks a clear theoretical basis and has inconsistencies. To generate more reliable flood risk assessment maps, future studies should also consider sociodemographic, health, and housing data. Considering future climate change impacts, susceptibility or early warning studies may be projected under different climate change scenarios to help design long-term adaptation strategies.

To examine the effects of the application of composted sewage sludge fertilizer (commercially sold as Kala compost) and inorganic (NPK) fertilizers on soil quality and on two crops (radish and beans) irrigated using groundwater and sewage treated wastewater (TWW) for irrigation by measuring heavy metals in the soil and plants and other parameters such as crops yield, TOC in soil, chlorophyll index and total nitrogen.