Internal waves can influence water properties in coastal ecosystems through the shoreward transport and mixing of subthermocline water into the nearshore region. In June 2014, a field experiment was conducted at Dongsha Atoll in the northern South China Sea to study the impact of internal waves on a coral reef. Instrumentation included a distributed temperature sensing system, which resolved spatially and temporally continuous temperature measurements over a 4‐km cross‐reef section from the lagoon to 50‐m depth on the fore reef. Our observations show that during summer, internal waves shoaling on the shallow atoll regularly transport cold, nutrient‐rich water shoreward, altering near‐surface water properties on the fore reef. This water is transported shoreward of the reef crest by tides, breaking surface waves and wind‐driven flow, where it significantly alters the water temperature and nutrient concentrations on the reef flat. We find that without internal wave forcing on the fore reef, temperatures on the reef flat could be up to 2.0°C ± 0.2°C warmer. Additionally, we estimate a change in degree heating weeks of 0.7°C‐weeks warmer without internal waves, which significantly increases the probability of a more severe bleaching event occurring at Dongsha Atoll. Furthermore, using nutrient samples collected on the fore reef during the study, we estimated that instantaneous onshore nitrate flux is about four‐fold higher with internal waves than without internal waves. This work highlights the importance of internal waves as a physical mechanism shaping the nearshore environment, and likely supporting resilience of the reef.

Internal waves strongly influence the physical and chemical environment of coastal ecosystems worldwide. We report novel observations from a distributed temperature sensing (DTS) system that tracked the transformation of internal waves from the shelf break to the surf zone over a narrow shelf slope region in the South China Sea. The spatially continuous view of temperature fields provides a perspective of physical processes commonly available only in laboratory settings or numerical models, including internal wave reflection off a natural slope, shoreward transport of dense fluid within trapped cores, and observations of internal rundown (near-bed, offshore-directed jets of water preceding a breaking internal wave). Analysis shows that the fate of internal waves on this shelf-whether transmitted into shallow waters or reflected back offshore-is mediated by local water column density structure and background currents set by the previous shoaling internal waves, highlighting the importance of wave-wave interactions in nearshore internal wave dynamics.

The oceanic response to high‐frequency local diurnal wind forcing is examined in a small coastal embayment located along an understudied stretch of the central California coast. We show that local diurnal wind forcing is the dominant control on nearshore temperature variability and circulation patterns. A complex empirical orthogonal function (CEOF) analysis of velocities in San Luis Obispo Bay reveals that the first‐mode CEOF amplitude time series, which accounts for 47.9% of the variance, is significantly coherent with the local wind signal at the diurnal frequency and aligns with periods of weak and strong wind forcing. The diurnal evolution of the hydrographic structure and circulation in the bay is examined using both individual events and composite‐day averages. During the late afternoon, the local wind strengthens and results in a sheared flow with near‐surface warm waters directed out of the bay and a compensating flow of colder waters into the bay over the bottom portion of the water column. This cold water intrusion into the bay causes isotherms to shoal toward the surface and delivers subthermocline waters to shallow reaches of the bay, representing a mechanism for small‐scale upwelling. When the local winds relax, the warm water mass advects back into the bay in the form of a buoyant plume front. Local diurnal winds are expected to play an important role in nearshore dynamics and local upwelling in other small coastal embayments with important implications for various biological and ecological processes.

Distributed Temperature Sensing (DTS) uses Raman scatter from laser light pulsed through an optical fiber to observe temperature along a cable. Temperature resolution across broad scales (seconds to many months, and centimeters to kilometers) make DTS an attractive oceanographic tool. Although DTS is an established technology, oceanographic DTS observations are rare since significant deployment, calibration and operational challenges exist in dynamic oceanographic environments. Here, results from an experiment designed to address likely oceanographic DTS configuration, calibration, and data processing challenges provide guidance for oceanographic DTS applications. Temperature error due to sub-optimal calibration under difficult deployment conditions is quantified for several common scenarios. Alternative calibration, analysis and deployment techniques which help mitigate this error and facilitate successful DTS application in dynamic ocean conditions are discussed.

Coral reefs are increasingly threatened by rising seawater temperatures, and the collapse of reefs on a global scale has been predicted to occur in the near future (Donner, 2009; Hoegh-Guldberg et al., 2007; Van Hooidonk et al., 2016). Understanding the variation in environmental conditions over small spatial and temporal scales has become increasingly important when considering the variation in the physiological responses of coral colonies within a reef to stressors (

Interferometric Synthetic Aperture Radar (InSAR) is a type of active remote sensing whereby a satellite transmits electromagnetic radiation (microwaves) at the ground and measures the differential phase of the reflected signal over multiple images (or multiple antennas on a single satellite). InSAR has the potential to provide centimeter and even millimeter-scale measurements of displacement over time, but is sensitive to vegetation, topography, and atmospheric effects. We consider herein, the application of InSAR at two known landslides on the Enbridge pipeline system, and discuss the strengths, weaknesses, values, and limitations of its application in the Geohazard Management of landslides impacting pipeline ROW’s. We compare information provided at each site by InSAR (both L-band and X-band) to data derived by mapping using Light Detection and Ranging (LiDAR) or air photographs, to differential LiDAR techniques, and to data derived from subsurface measurements (slope inclinometers). In doing so we find that L-Band data can be an effective tool to establish the extent or footprint of movement (or lack of movement) at known landslide locations, extending the interpretive power of a specialist and the understanding of event magnitude, and potentially affecting the mitigation options. Further, L-Band InSAR can be used in a supporting role to pre-screen areas for active landslides along the right of way (ROW), however, data gaps, a lack of explanatory power, and considerable noise in the results mean that a user step that further considers the terrain, other sources of data, and the identified magnitude, is essential. X-Band InSAR appeared impractical for ROW monitoring where vegetation prevented coherence between images, however, X-Band InSAR was able to detect small displacements at above ground infrastructures.

Coral reef calcification is expected to decline due to climate change stressors such as ocean acidification and warming. Projections of future coral reef health are based on our understanding of the environmental drivers that affect calcification and dissolution. One such driver that may impact coral reef health is heterotrophy of oceanic‐sourced particulate organic matter, but its link to calcification has not been directly investigated in the field. In this study, we estimated net ecosystem calcification and oceanic particulate organic carbon (POCoc) uptake across the Kāne'ohe Bay barrier reef in Hawai'i. We show that higher rates of POCoc uptake correspond to greater net ecosystem calcification rates, even under low aragonite saturation states (Ωar). Hence, reductions in offshore productivity may negatively impact coral reefs by decreasing the food supply required to sustain calcification. Alternatively, coral reefs that receive ample inputs of POCoc may maintain higher calcification rates, despite a global decline in Ωar.

Much of North America, and indeed much of the global landscape, is comprised of either locally or regionally steep slopes, river valleys, and weak or unstable geology. Landslides and ground movements continue to impact pipelines that traverse these regions. Pipeline integrity management programs (IMP’s) are increasingly expecting quantitative estimates of ground movement or pipe failure as part of pipeline risk management systems. Quantitative analysis usually relies on one or more of statistics, physical models, and expert judgment. Statistics incorporate ground and pipe behavior (for hazard and vulnerability respectively) over a broad area to infer local probabilities. They carry the weight of big data, but the local application is almost certainly incorrect (variability even for regions exceeds 2 orders of magnitude). Detailed geotechnical (hazard) and soil-pipe interaction and stress (vulnerability) models provide rigorous results, but require substantial effort and/or expert judgment to parameterize the inputs and boundary conditions. We present herein a structured tool to calculate probability of failure (PoF) using expert judgment supported by known, instrumented or observable conditions and statistics (where available). We provide a series of tables used as a basis for nodal calculations along a branch path of a decision tree, and discuss the challenges and results from actual application to over 100 sites in the Interior Plains. The method is intended to be a practical informative approach based on, and limited by, data inputs. It is a flexible fit for purpose assessment that takes advantage of the best available data, however, the method relies on the user to articulate a level of confidence in, or the basis of the results.