Dr. Johan Liebens

In response to increased awareness of the negative impacts of fluvial erosion on natural resources and infrastructure, efforts to understand channel sediment sources have increased so cost-effective mitigation may be achieved. Attempts to quantify the important contribution of streambank erosion to channel sediment loading have been made with modeling and in-situ measurement approaches. Many of these efforts involve time-consuming or technologically advanced techniques while practitioners often need a reliable and rapid assessment method to quantify local streambank erosion. One such method, the Bank Assessment of Non-Point Source Consequences of Sediment (BANCS) model, predicts average annual streambank erosion from field estimates of near-bank stress (NBS) and bank erodibility (BEHI) and observed erosion rates resulting from bankfull events. The model provides a means to contextually transpose observed erosion rates of streambanks to predict erosion rates of other local streambanks with similar characteristics. Given the empirical nature of BANCS, its BEHI category-based predictive models have to be established for every physiographic region to account for local environmental controls. Our study examined the applicability of the BANCS model to an area along the north coast of the Gulf of Mexico dominated by sandy soils and a warm and wet climate with frequent high-intensity precipitation events. Bank erosion incurred at 18 study sites located in 10 different stream reaches was monitored for one year and morphometric variables were recorded. Bankfull flow events, which are the critical erosion-causing events in the BANCS model, were identified through the use of constructed stage gages. Bank erosion associated with individual bankfull events was between 0.01 m and 0.12 m, but some sites experienced more than one bankfull event and some reached flood stage. The mean total annual erosion rate for all study sites was 0.054 m/yr. Based on the BANCS model, total annual erosion rates showed moderate to strong relationships with NBS for High and Very High BEHI categories. As the values for BEHI and NBS increased between sites, so did the measured erosion rates. During this study, BEHI appeared a stronger predictor of bank erosion than NBS and further evaluation of the application of the various NBS methods is needed for the study area.

In a contaminant study of surface sediments performed in Escambia Bay, Florida, in 2009, DDT was present in 13 of 30 tested sites that were located in the wetlands adjacent to the bay. Concentrations were well above the Florida Department of Environmental Protection's Probable Effect Level (PEL), and ratios of DDT and its metabolites indicated a recent introduction to the system, despite the use of DDT having been banned in 1973. A follow-up study performed in 2016 found no DDT, but did show DDE (a DDT degradation product) at several sites. Spring 2017 sampling showed no DDT, DDE at five of six sampling sites and DDD (another DDT degradation product) at two of the six sites. The appearance of degradation products suggests that DDT degraded or sediment movement brought the degradation products to the sites. In spring of 2018, sediment cores were collected to assess subsurface contaminant concentrations at five sites that consistently had detectable concentration of DDT or its degradation products in previous years. The cores, ranging from approximately 0.2-0.8 meters in depth, were sampled based upon physical characteristics of the sediment. Two methods were used to extract and analyze for DDT and its byproducts from the sediments, a soxhlet extraction (EPA methods 3540c and 3620c) and a microwave extraction (EPA methods 3051a and 3546). Extracts were analyzed using gas chromatography (GC-ECD). Results show the presence of DDE at all five sites tested, DDD at three sites, and DDT at two sites, all at various depths. Of the five tested sites, three sites clearly exhibited decreasing DDE concentration with increased depth and one site exhibited the same decreasing trend but had high levels of DDE at the bottom of the core (>0.5 m depth). DDD showed a similar pattern, decreasing with depth at two of the three sites that is was detected at. There are no evident relationships between particle size and these trends. All samples with detections exceeded the TEL for DDE (17 samples) and DDD (7 samples) but not for DDT; two samples exceeded the PEL for DDD. The trend of generally decreasing concentration with depth of DDE and DDD suggest that the reworking of sediment is not the source of the contaminants. One site had high levels of DDE at depth but is downstream from the other sites and thus cannot be a source of the contaminants, DDT, DDE, or DDD.

Stream restoration practitioners often rely upon empirical models to quantify annual streambank erosion rates and identify streambank erosion hotspots. Such models are designed to be widely applicable by incorporating readily available field measurements, but they must be calibrated to each hydrophysiographic region and may not reflect the dominant streambank erosion processes in a given region. Here, we present statistical models for streambank erosion using physical and environmental data collected at 53 locations throughout the northern
Gulf of Mexico coastal plain. The data include channel geometry, bank characteristics, precipitation, aboveground biomass density, and root density, the latter two surveyed using techniques introduced here. We developed a statistical model selection process using Akaike's Information Criterion (AIC) and repeated crossvalidation (CV). Models derived from the literature that were applied a priori were only weak predictors of erosion rate, but AIC-CV model selection identified 3 strong statistical models. The best model according to AIC showed a significant correlation to lateral streambank erosion rates (R²=0.54) and included the five strongest covariates of our dataset (bank slope, biomass density, curvature index, BEHI, and understory cover). When volumetric erosion rate (m²/year) was predicted, the fit of this model increased (R²=0.65). CV-based selection resulted in a more conservative model with the four strongest covariates and a lower fit (R²=0.47). The similarity of the AIC and CV models indicates the stability of the two-tier model selection approach, and suggests it has utility for modeling phenomena with many potential variables. Our models also showcase the ability of our biomass survey to quantify root reinforcement of streambanks. Our approach incorporates measurements familiar to the stream restoration community and can be applied throughout the northern Gulf of Mexico coastal plain, a region characterized by low relief fluvial valleys, unconsolidated alluvium and meandering single thread sand bed channels. The approach, which is based on field observations and robust statistical modeling, offers an alternative for stream restoration practitioners to more traditional streambank erosion prediction methods that underperform in the region, and may have applicability elsewhere.

Dichlorodiphenyltrichloroethane (DDT) was a commonly used pesticide from World War II through the 1960's. DDT is generally used to control mosquito populations and as an agricultural insecticide. The pesticide and its degradation products (DDD and DDE) can bioaccumulate within ecosystems having negative implications for animal and human health. Consequently, DDT usage was banned in the United States in 1973. In a contaminant study performed in Escambia Bay, Florida, in 2009, DDT was present in 25% of study sites, most of which were located in the upper bay wetlands. Concentrations were well above the Florida Department of Environmental Protection's (FDEP) Probable Effect Level (PEL) and ratios of DDT and its metabolites indicated a recent introduction to the system. A follow-up study performed in 2016 found no DDT, but did show DDE at several sites. The current study repeated sampling in May 2017 at sites from the 2009 and 2016 studies. Sediment samples were collected in triplicate using a ponar sampler and DDT, DDD and DDE were extracted using EPA methods 3540c and 3620c. Extracts were analyzed using a gas chromatograph with electron capture detection (GC-ECD) as per EPA method 8081c. Sediment was also analyzed for organic carbon and particle size using an elemental NC analyzer and a laser diffraction particle sizer. Results show the presence of breakdown products DDE and DDD at multiple sites, but no detectable levels of DDT at any site. Sampling sites with high levels of DDT contamination in 2009 show only breakdown products in both 2016 and 2017. Particle size has little influence on DDD or DDE concentrations but OC is a controlling factor as indicated for contaminated sites by Pearson correlations between OC and DDE and DDD of 0.82 and 0.92, respectively. The presence of only DDD and/or DDE in the 2016 and 2017 studies indicates that the parent, DDT, has not been re-introduced into the watershed since 2009 but is degrading in the environment.

The Bank Assessment of Nonpoint source Consequences of Sediment (BANCS) framework allows river scientists to predict annual sediment yield from eroding streambanks within a hydrophysiographic region. BANCS involves field data collection and the calibration of an empirical model incorporating a bank erodibility hazard index (BEHI) and near-bank shear stress (NBS) estimate. Here we evaluate the applicability of BANCS to the northern Gulf of Mexico coastal plain, a region that has not been previously studied in this context. Erosion
rates averaged over two years expressed the highest variability of any existing BANCS study. As a result, four standard BANCS models did not yield statistically significant correlations to measured erosion rates. Modifications to two widely used NBS estimates improved their correlations (r² = 0.31 and r² = 0.33), but further grouping of the data by BEHI weakened these correlations. The high variability in measured erosion rates is partly due to the regional hydrologic and climatic characteristics of the Gulf coastal plains, which include large, infrequent precipitation events. Other sources of variability include variations in bank vegetation and the complex hydro- and morphodynamics of meandering, sand bed channels. We discuss directions for future research in developing a streambank erosion model for this and similar regions.

Predictive field-based models have been developed to rapidly identify streams that can be expected to experience accelerated erosion and should be prioritized for restoration. One of the most widely applied models, the Bank Assessment for Non-point Source Consequences of Sediment (BANCS) model, correlates observed rates of streambank erosion with near-bank stress (NBS) and bank erodibility (BEHI). The BANCS model is region specific and has to be calibrated in every hydrophysiographic
region. Our study tried to calibrate the BANCS model for the northern Gulf of Mexico coastal plain by collecting field data over a two year period at 75 sites in the Florida Panhandle, South Alabama, and Southwest Georgia