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The estimation of depth in optically shallow waters using satellite imagery can be efficient and cost-effective. Active sensors measure the distance traveled by an emitted laser pulse propagating through the water with high precision and accuracy if the bottom peak intensity of the waveform is greater than the noise level. However, passive optical imaging of optically shallow water involves measuring the radiance after the sunlight undergoes downward attenuation on the way to the sea floor, and the reflected light is then attenuated while moving back upward to the water surface. The difficulty of satellite-derived bathymetry (SDB) arises from the fact that the measured radiance is a result of a complex association of physical elements, mainly the optical properties of the water, bottom reflectance, and depth. In this research, we attempt to apply physics-based algorithms to solve this complex problem as accurately as possible to overcome the limitation of having only a few known values from a multispectral sensor. Major analysis components are atmospheric correction, the estimation of water optical properties from optically deep water, and the optimization of bottom reflectance as well as the water depth. Specular reflection of the sky radiance from the water surface is modeled in addition to the typical atmospheric correction. The physical modeling of optically dominant components such as dissolved organic matter, phytoplankton, and suspended particulates allows the inversion of water attenuation coefficients from optically deep pixels. The atmospheric correction and water attenuation results are used in the ocean optical reflectance equation to solve for the bottom reflectance and water depth. At each stage of the solution, physics-based models and a physically valid, constrained Levenberg–Marquardt numerical optimization technique are used. The physics-based algorithm is applied to Landsat Operational Land Imager (OLI) imagery over the shallow coastal zone of Guam, Key West, and Puerto Rico. The SDB depths are compared to airborne lidar depths, and the root mean squared error (RMSE) is mostly less than 2 m over water as deep as 30 m. As the initial choice of bottom reflectance is critical, along with the bottom reflectance library, we describe a pure bottom unmixing method based on eigenvector analysis to estimate unknown site-specific bottom reflectance. [ABSTRACT FROM AUTHOR]

The effects of runoff from land on nearshore ecosystems, including coral reef communities, are influenced by both sediment supply and removal by coastal processes. Integrated studies across the land-sea interface describing sources and transport of terrestrial sediment and its nearshore fate allow reef protection initiatives to target key onshore and offshore areas. Geochemical signatures in the fine fraction of terrestrial sediment from watersheds in southwest Puerto Rico were determined by multivariate principal component analysis and used to identify terrestrial sources of sediment runoff to nearshore coral reefs. Sediment settling out of suspension at reefs was collected at approximately 2 month-long intervals in bottom-mounted sediment traps from May 2017 to June 2018, a period that included Hurricanes Irma and Maria. Bulk sediment accumulation rates in traps exceeded a 10 mg/cm2/d threshold found to stress corals at 5 of 7 reef sites throughout the 13 month-long study. Geochemical signatures showed that watersheds 10s km to the east were a predominant, year-round source of fine sediment to reefs offshore of Guánica Bay and could have introduced sediment-bound contaminants due to a higher degree of industrialization and urbanization than the local watershed. Sediment runoff from the local watershed appeared to be constrained to a narrow band close to shore. During the 2.5 months after Hurricanes Irma and Maria, bulk sediment accumulation rates increased substantially and fine sediment geochemical signatures were indicative of predominantly distal sources, except outside of the mouth of Guánica Bay, which was strongly impacted by local runoff. Mass wasting, sediment runoff, and coastal turbidity persisted for months after Hurricane Maria and could account for the appearance of a small fraction of geochemical variance from a distal sediment source that appeared in reef traps 4 months post-hurricane and persisted through the end of the study 9 months post-hurricane. Sediment geochemical sourcing in temporally resolved records from sediment traps showed how landscape-scale changes after a major hurricane affected both near-term and long-term sediment delivery to reef communities. In addition, the importance of fine sediment advection from distal sources indicates that successful reduction of land-based pressures on nearshore ecosystems will require cross-jurisdictional strategies. • Sediment on reefs was sourced from local and distal watersheds. • Nearshore reef sediment trap time series showed post-hurricane source-switching. • Runoff from upper reaches not urban lowlands in two of the tributary basins. • Local runoff from Guánica Bay was advected westward on the inner shelf. [ABSTRACT FROM AUTHOR]

Coral reefs can mitigate flood damages by providing protection to tropical coastal communities whose populations are dense, growing fast, and have predominantly lower-middle income. This study provides the first fine-scale, regionally modeled valuations of how flood risk reductions associated with hybrid coral reef restoration could benefit people, property, and economic activity along Florida and Puerto Rico's 1005 kilometers of reef-lined coasts. Restoration of up to 20% of the regions' coral reefs could provide flood reduction benefits greater than costs. Reef habitats with the greatest benefits are shallow, nearshore, and fronting low-lying, vulnerable communities, which are often where reef impacts and loss are the greatest. Minorities, children, the elderly, and those below the poverty line could receive more than double the hazard risk reduction benefits of the overall population, demonstrating that reef restoration as a nature-based solution can have positive returns on investment economically and socially by providing protection to the most vulnerable people.