Seminar

Submarine groundwater discharge (SGD) has been considered as an enormous part of global water budget and significantly contributes to chemical fluxes into the coastal waters due to concentrated constituents in coastal groundwater. Large loadings of nutrients derived from SGD can lead to lots of environmental and ecological problems such as algal blooms, which can cause water discoloration and severe dissolved oxygen depletion. Traditional methods for SGD estimation based on direct measurements by seepage meters or geotracer techniques such as Rn and Ra are time-consuming and laborious; hence it is difficult to conduct a time-series monitoring. Remote sensing methods for SGD location and estimation are applicable and effective especially for a long period monitoring. The temperature anomaly between the groundwater and coastal water extracted from satellite thermal images can be used as the indicator to localize and detect SGD especially for fresh SGD. In this study, Rn samples from Tolo Harbour in 2005, 2011 and 2018 were used to correlate Rn activity and temperature anomaly. The regression model (R2=0.80) was used to estimate a two-decadal variations of fresh SGD in Tolo Harbour (159 Landsat satellite thermal images, 1998-2017). Compared with algal bloom data, it should be noted when the algal blooms occur, the fresh SGD prior to 15-30 days is increased with a high nutrient level. Also, it shows a strong positive correlation between the fresh SGD and coastal nutrients (R2=0.77). For the first time, a strong correlation between the SGD and algal blooms based on a two-decadal dataset is established; and this study provides a cost effective and robust technique to estimate SGD on a catchment scale.