Abstract: This paper presents the results of a multi-year, interdisciplinary project that aimed to assess the holistic status of the khettara system in Morocco. The khettara (also known as qanat) is a traditional, earthen water management system. Historically the system was used for settlement in regions without access to reliable surface water. It is both a world and local heritage structure, found in rural and urban regions throughout 46 countries. Recent evaluations of this traditional system have advocated for its preservation and use in arid and semi-arid regions, as modern technologies (pump wells, industrial dams, drip irrigation, etc.) have proven to be unsustainable. This project evaluates remote sensing as a tool for assessing the distribution and status of the khettara in Morocco. The results of this project demonstrate that (1) the khettara system played a large role in the historic settlement of arid and semi-arid regions, and (2) the system continues to be an important part of agriculture and life in many oases across Morocco.

Abstract: Droughts and floods are weather-related hazards affecting cities in all climate zones and causing human deaths and material losses on all inhabited continents. The aim of this article is to review, analyse and discuss in detail the problems faced by urban ecosystems due to water surplus and scarcity, as well as the need of adaptation to climate change taking into account the legislation, current challenges and knowledge gaps. The literature review indicated that urban floods are much more recognised than urban droughts. Amongst floods, flash floods are currently the most challenging, which by their nature are difficult to monitor. Research and adaptation measures related to water-released hazards use cutting-edge technologies for risk assessment, decision support systems, or early warning systems, among others, but in all areas knowledge gaps for urban droughts are evident. Increasing urban retention and introducing Low Impact Development and Nature-based Solutions is a remedy for both droughts and floods in cities. There is the need to integrate flood and drought disaster risk reduction strategies and creating a holistic approach.

Abstract: Cities have experienced rapid urbanization-induced harsh climatic events, especially flooding, inevitably resulting in negative and irreversible consequences for urban resilience and endangering residents’ lives. Numerous studies have analyzed the effects of anthropogenic practices (land use changes and urbanization) on flood forecasting. However, non-structural mitigation’s effectiveness, like Nature-Based Solutions (NBS), has yet to receive adequate attention, particularly in the Middle East and North Africa (MENA) region, which have become increasingly significant and indispensable for operationalizing cities efficiently. Therefore, our study investigated the predictive influence of incorporating one of the most common NBS strategies called low-impact development tools (LID) (such as rain gardens, bio-retention cells, green roofs, infiltration trenches, permeable pavement, and vegetative swale) during the urban planning of Alexandria, Egypt, which experiences the harshest rainfall annually and includes various urban patterns. City characteristics-dependent 14 LID scenarios were simulated with recurrence intervals ranging from 2 to 100 years using the LID Treatment Train Tool (LID TTT), depending on calibrated data from 2015 to 2020, by the Nash-Sutcliffe efficiency index and deterministic coefficient, and root-mean-square error with values of 0.97, 0.91, and 0.31, respectively. Our findings confirmed the significant effectiveness of combined LID tools on total flood runoff volume reduction by 73.7%, revealing that different urban patterns can be used in flood-prone cities, provided LID tools are considered in city planning besides grey infrastructure to achieve optimal mitigation. These results, which combined multiple disciplines and were not explicitly mentioned in similar studies in developing countries, may assist municipalities’ policymakers in planning flood-resistant, sustainable cities.

Abstract: A large number of radionuclides remain in uranium tailings, and U, 226Ra and 210Pb leach out with water chemistry, causing potential radioactive contamination to the surrounding environment. In this paper, uranium tailings from a uranium tailings pond in southern China were collected at different depths by means of borehole sampling, mixed and homogenised, and analysed for mineral and chemical composition, microscopic morphology, U, 226Ra and 210Pb fugacity, static leaching and dynamic leaching of U, 226Ra and 210Pb in uranium tailings at different pH conditions. The variation of U, 226Ra and 210Pb concentrations in the leachate under different pH conditions with time was obtained, and the leaching mechanism was analysed. The results showed that the uranium tailings were dominated by quartz, plagioclase and other minerals, of which SiO2 and Al2O3 accounted for 65.45% and 13.32% respectively, and U, 226Ra and 210Pb were mainly present in the residue form. The results of the static leaching experiments show that pH mainly influences the leaching of U, 226Ra and 210Pb by changing their chemical forms and the particle properties of the tailings, and that the lower the pH the more favourable the leaching. The results of dynamic leaching experiments during the experimental cycle showed that the leaching concentration and cumulative release of U, 226Ra and 210Pb in the leach solution were greater at lower pH conditions than at higher pH conditions, and the leaching of U, 226Ra and 210Pb at different pH conditions was mainly from the water-soluble and exchangeable states. The present research results are of great significance for the environmental risk management and control of radioactive contamination in existing uranium tailings ponds, and are conducive to ensuring the long-term safety, stability and sustainability of uranium mining sites.

Abstract: The migration process of leached uranium in the in-situ leaching of uranium is considered a typical reactive transport problem. During this process, the lixiviant concentration and injection rate are important in-situ leaching process parameters (ISLPP) to efficiently recover uranium. However, several uncertain factors affect the outcomes of the ISLPP design. In addition, the repeated use of the reactive transport model (RTM) for investigating the acid in-situ leaching of uranium with the application of the Monte Carlo method leads to a substantial computational load. For this reason, a machine learning (ML)–based surrogate model was developed with the backpropagation neural network (BPNN) method to replace the RTM under the condition of uncertain parameters. Moreover, the simulated annealing optimisation model for ISLPP was created based on the proposed surrogate model. The optimal ISLPP was achieved that generated maximum profits from uranium recovery under different lixiviant prices, uranium prices and exploitation times. The optimal design framework of ISLPP based on the proposed ML algorithm was then applied in the Bayan-Uul sandstone-type uranium deposit in Inner Mongolia, China. From our analysis, it was demonstrated that the ML-based surrogate model exhibited great fitness with the RTM. The optimal results of the ISLPP indicated that the lixiviant concentration and injection rate could be adjusted based on the fluctuations in lixiviant price, uranium price and exploitation time. If the prices of sulphuric acid were high, a specific concentration of hydrogen peroxide could be injected into the injection well to promote the oxidation and dissolution of the uranium ore to increase the income from the uranium recovery. The optimisation model can also use the ISLPP scheme to boost the revenues from different lixiviant prices, uranium prices and exploitation times under the uncertainty of porosity, illustrating the applicability of the ML-based optimal design method of ISLPP in ISL mining. A general framework for developing surrogate models, as well as for conducting uncertainty analyses for a wide range of groundwater models was proposed here yielding valuable insights.