A comprehensive review of deep learning applications in hydrology and water resources.

The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water resources management, and climate change. Combined with the growing availability of computational resources and popularity of deep learning, these data are transformed into actionable and practical knowledge, revolutionizing the water industry. In this article, a systematic review of literature is conducted to identify existing research that incorporates deep learning methods in the water sector, with regard to monitoring, management, governance and communication of water resources. The study provides a comprehensive review of state-of-the-art deep learning approaches used in the water industry for generation, prediction, enhancement, and classification tasks, and serves as a guide for how to utilize available deep learning methods for future water resources challenges. Key issues and challenges in the application of these techniques in the water domain are discussed, including the ethics of these technologies for decision-making in water resources management and governance. Finally, we provide recommendations and future directions for the application of deep learning models in hydrology and water resources.

The dual function of the algal treatment: Antibiotic elimination combined with CO2 fixation.

The study provided an algal treatment to achieve dual function with antibiotic elimination and CO2 fixation simultaneously. Two widely used antibiotics, cefradine and amoxicillin were selected as the target compounds. First of all, we assessed the influence of light intensity on algal growth and antibiotic removal efficiency to obtain the optimal light intensity. Secondly, after the algal antibiotic treatment, the CO2 capture capacities at varied CO2 volume concentrations were assessed and compared. Significant improvement in the removal efficiency of cefradine occurred when CO2 was added into the treatment. Change in the content of photosynthetic pigments and the activities of RuBisCO and carbonic anhydrase occurred as the algal responses to the treatment condition. Our results showed that Chlorella pyrenoidosa performed better than Microcystis aeruginosa in both the antibiotic removal efficiency and the CO2 capture capacity. In the integrated algal treatment, the remove rate of antibiotic has been improved by 30.16% and at the same time, the CO2 absorption rate has been promoted by 10.94%. Metabolite analyses also revealed the mechanism involved, which proved the crucial role of the algae in the biodegradation of the target antibiotic.

Comprehensive assessment of three typical antibiotics on cyanobacteria (Microcystis aeruginosa): The impact and recovery capability.

This innovative study provided a comprehensive evaluation of the effects of three typical antibiotics exposures (cefradine, norfloxacin and amoxicillin) on Microcystis aeruginosa in two periods (exposure and post-exposure) at a new perspective. The results indicated that the irreversible growth inhibition of M. aeruginosa attributed to the norfloxacin in the exposure and the re-exposure stages. In contrast, although the algal cell size recovered to the control level after the exposure of 20 mg/L of cefradine, the significant stimulation on glutathione (GSH) still persisted even if the contaminants were removed. On the other hand, amoxicillin inhibited the activities of superoxide dismutase (SOD), GSH contents and the algal cell size in the exposure period while malonaldehyde (MDA) contents increased significantly in two periods.

Integrated toxic evaluation of sulfamethazine on zebrafish: Including two lifespan stages (embryo-larval and adult) and three exposure periods (exposure, post-exposure and re-exposure).

Persistence of antibiotics in aquatic environment may pose a risk to the non-target aquatic organisms. This study provided an integrated evaluation to analyze the toxic stress of sulfamethazine (SMZ) on zebrafish in two lifespan stages (embryo-larval and adult) and three exposure periods (exposure, post-exposure and re-exposure). Zebrafish embryos and adult zebrafish were exposed to SMZ at 0.2, 20 and 2000 µg/L, respectively. The results showed that SMZ at any given concentration inhibited the hatching of embryos at 58-96 hpf (hours post-fertilization). Our result also indicated that two major kinds of the malformation, which was induced by the antibiotic, were edema and spinal curvature. Additionally, the antibiotic stimulated the heartbeat while reduced the body length of the embryo at 72 hpf. Superoxide dismutase (SOD) activities and malondialdehyde (MDA) contents significantly increased at 120 hpf when the embryos were exposed to the lowest concentration (0.2 µg/L) of the antibiotic. On the other hand, the antibiotic induced SOD activities and MDA contents in adult zebrafish in the exposure and re-exposure periods. The MDA contents could recover while SOD activities still increased in 2 d after the exposure. Both SOD activities and MDA contents could recover in 7 d after the exposure. Levels of SOD and MDA in the re-exposure were higher than those in the first exposure. Our results suggested that SMZ had toxic effects on both embryos and adult zebrafish, and provided an integrated evaluation of the toxic effects of SMZ on zebrafish at a new perspective.