Sedimentation limits the benefits of storage reservoirs, especially in areas with higher sediment yields, such as Agongdian Reservoir in southern Taiwan. Although drawdown flushing is a known strategy that releases large amounts of fine sediment into a downstream channel, there is limited information on the long-term monitoring and multiple metrics being used to evaluate flushing efficiency. The objectives of this study were three-fold: (1) to continue collecting valuable long-term observed data, since Agongdian Reservoir is one of the few reservoirs currently conducting sediment flushing operations; (2) to evaluate and identify the hydrological parameters that are highly related to the flushing efficiency; (3) to execute numerical simulations of different reservoir flushing scenarios at multiple water levels to discuss potential strategies to improve the flushing efficiency. The findings of this study revealed that long-term monitoring data was valuable for identifying factors highly related to the flushing efficiency, which included the initial water level; average water level; average velocity. Based on simulations, compartmentalizing the reservoir is a proposed strategy that has demonstrated high levels of improvement in terms of the flushing efficiency, depending on particular scenarios involving partition desilting, empty flushing, or a combination of both. Recommendations to increase the flushing efficiency include lowering the initial water level, creating a narrower gorge-like geometry by partitioning, and further considering to modify the operation rules.

Seagrasses are a crucial indicator species of coastal marine ecosystems that provide substratum, shelter, and food for epiphytic algae, invertebrates, and fishes. More accurate mapping of seagrasses is essential for their survival as a long-lasting natural resource. Before reflectance spectra could properly be used as remote sensing endmembers, factors that may obscure the detection of reflectance signals must be assessed. The objectives in this study are to determine the influence of (1) epiphytes, (2) water depth, and (3) seagrass genus on the detection of reflectance spectral signals. The results show that epiphytes significantly dampen bottom-type reflectance throughout most of the visible light spectrum, excluding 670–679 nm; the depth does influence reflectance, with the detection of deeper seagrasses being easier, and as the depth increases, only Heterozostera increase in the exact “red edge” wavelength at which there is a rapid change in the near-infrared (NIR) spectrum. These findings helped improve the detection of seagrass endmembers during remote sensing, thereby helping protect the natural resource of seagrasses.

Seagrasses are a vulnerable and declining coastal habitat, which provide shelter and substrate for aquatic microbiota, invertebrates, and fishes. More accurate mapping of seagrasses is imperative for their sustainability but is hindered by the lack of data on reflectance spectra representing the optical signatures of individual species. Objectives of this study are: (1) To determine distinct characteristics of spectral profiles for sand versus three temperate seagrasses (Posidonia, Amphibolis, and Heterozostera); (2) to evaluate the most efficient derivative analysis method of spectral reflectance profiles for determining benthic types; and to assess the influences of (3) site location and (4) the water column on spectral responses. Results show that 566:689 and 566:600 bandwidth ratios are useful in separating seagrasses from sand and from detritus and algae, respectively; first-derivative reflectance spectra generally is the most efficient method, especially with deconvolution analyses further helping to reveal and isolate 11 key wavelength dimensions; and differences between sites and water column composition, which can include suspended particulate matter, both have no effect on endmembers. These findings helped develop a spectral reflectance library that can be used as an endmember reference for remote sensing, thereby providing continued monitoring, assessment, and management of seagrasses.