Seminar

Submarine groundwater discharge (SGD) is the mixture of fresh groundwater driven by terrestri-al recharge and recirculated seawater constrained by marine forces and can import vast nutrient loadings to ocean. Current methods only lead to a limited point monitoring. Hence, we developed an approach using radon-222 (²²²Rn) and thermal remote sensing of satellites and unmanned aerial vehicles (UAV) to quantify SGD. With a refined SGD estimation, coastal algal bloom and fecal pollution were investigated. Algal blooms, denoted as the rapid growth of microscopic phytoplan-kton, are frequently observed worldwide. To explore the effects of SGD on the formation of algal blooms, data collected from field samping and process model output were analyzed. We demonst-rated that physical control (water vertical stability) and chemical control (groundwater borne phosphate) jointly formulate algal blooms. We improved the understanding of the occurrence and transport of microbe in the beach groundwater - surf zone system.By monitoring groundwater and seawater Escherichia coli (E. coli), we for the first time proposed that ²²²Rn is an effective ana-logue of E. coli. The relationship between ²²²Rn and E. coli can provide additional critical context to microbial water quality assessments. Also, we investigated the mechanism of storm disturbing the E. coli dynamics in the beach aquifer. Results illustrated that net E. coli growth was enhanced during storm periods due to the storm-induced heavy rainfall and sand erosion. The finding was constructive to the understanding of beach ecosystem affected by storms and highlighted the ecological controls of SGD on coastal water. Finally, based on the findings that UAV thermal images can reflect ²²²Rn activity, and the relationship between ²²²Rn and E. coli, we established an E. coli prediction model and validated it against in-situ data from 50 beaches. This model highlighted that UAV technology is promising as a complement of traditional E. coli monitoring, and further paved the way for effective public health risk warning. 

Additional information: CHENG KAIHAO, cheng517@connect.hku.hk