A grant from the California Department of Parks and Recreation Natural Resources Division – Coastal Program (“Estuary Inlet Evolution & Dynamics”, January 2022-December 2022) extends work started from a prior grant (“Estuary Inlet Dynamics & Analysis”, July 2017- December 2021) in collaboration with Dr. Timu Gallien (UCLA, Coastal Flood Lab) to examine the interaction between estuary inlets and the adjacent beaches. The purpose of this research is to compare the complex, coupled beach-inlet morphological dynamics of two State Parks intermittently closed estuary mouths and provide output products useful to beach and estuary managers now and in the face of a changing climate. Inlet morphological response to climate change (i.e., sea level rise, changes in river discharge) and anthropogenic modification (e.g., manual breaching, altering upstream freshwater sources) are critical to understanding evolving coastal vulnerability. Coupled beach-estuary berm hydro-morphodynamic evolution is particularly important, directly modulating beach and estuarine hazards (e.g., erosion, coastal flooding, inlet closure, hypoxia), yet remain an active area of research due to their complexity limiting current predictive model skill. This new contract extends data collection begun under the prior contract, but also incorporates new analyses and collaborative aspects that expand the scope and impact of the work to include Northern California systems through a collaboration with Dr. Mara Orescanin (NPS, Coastal Dynamics Lab). Moreover, this second contract seeks to improve output products in anticipation of a more holistic analysis of the results, geared towards managerial needs in future years.
Comparison between UAV and LiDAR topo/bathymetry shows very strong agreement between these methodologies and suggests optimal future sampling schemes. Figure 3 shows the full extent and data from each survey type on the upper panels and difference maps on the lower panels. The drone is able to capture inside the estuary mouth while the LiDAR can capture a longer stretch of beach, but without any data upstream of the HW1 bridge, i.e., upstream of the mouth. The Jumbo surveys are able to cover a similar along-beach extent as the LiDAR with the benefit of extending deeper into the water (because of the jetski ability to capture sub-tidal), however with a drawback of significantly coarser spatial resolution and significantly more person-hours and resources. Differences between the UAV and LiDAR versus the jumbo can be as high as 0.3 m because these were not taken concurrently and thus likely include real morphodynamic change (Figure 3). Differences between the UAV and LiDAR taken concurrently however are typically less than 3 cm except for the pixel right next to the highway bridge (Figure 4). This suggests very strong agreement between the UAV and LiDAR methodologies. It also suggests that an optimal sampling scheme would survey the beach using LiDAR (longer along-beach extent) and the estuary upstream of its mouth using UAV and then stitching them together. We plan to test this again to confirm on a future set of flights/scans.
In addition to comparing collection platforms, we have also worked on creating improved difference maps and new algorithms for water detection. Postdoctoral scholar, Dr. Alexandra Simpson tested several automatic water-detection algorithms including image segmentation based on classification using k-means and based on elevation. K-mean classification groups pixels into clusters based on similarity of pixel values, here the user can adjust the number of clusters. In some cases k-mean classification worked well, however in other cases a combination of k-mean classification plus an elevation cutoff was ideal, and in some cases, neither approach completely removed all water pixels. Ultimately we decided that a modified semi-automatic water-detection algorithm that includes automatic water-detection with both k-mean classification and elevation cutoffs, followed by manual editing is optimal. An example difference map using this semi-automatic water-detection algorithm and improved difference mapping is in Figure 5.
Analysis of the Pajaro River Estuary/Zmudowski State Beach region has so far shown some similarities. Both estuaries are subject to mouth closure and experience truncated lower-low water levels due to the sill at their mouth. They also both experience overtopping events during closure. A closure index developed by collaborator Dr. Orescanin for a nearby estuary, performs fairly well for indicating when the Pajaro estuary mouth is closed. This particular index is not a predictive index, rather it uses existing observations to assess when the estuary mouth is closed. Specifically, the metric subtracts the upstream water levels from the offshore tides and an exceedance value is defined beyond which the estuary is assumed closed. In the Pajaro River Estuary, there is connectivity from the coastal ocean, through the estuary, upstream into the significantly human managed and modified region upstream including clear influence of sill overtopping events propagating upstream of flow diversion structures. We are working on finalizing comparisons between systems and applying similar sill-height metrics.