Evaluation and application of the Bank Assessment for Non-Point Source Consequences of Sediment (BANCS) model developed to predict annual streambank erosion rates

Abstract

Excess sediment is a leading cause of stream impairment in the United States, resulting in poor water quality, sedimentation of downstream waterbodies, and damage to aquatic ecosystems. Numerous case studies have found that accelerated bank erosion can be the main contributor of sediment in impaired streams. An empirically-derived "Bank Assessment for Non-Point Source Consequences of Sediment" (BANCS) model can be developed for a specific hydrophysiographic region to rapidly estimate sediment yield from streambank erosion, based on both physical and observational measurements of a streambank. This study aims to address model criticisms by (1) evaluating the model’s repeatability and sensitivity and (2) examining the developmental process of a BANCS model by attempting to create an annual streambank erosion rate prediction curve for the Central Great Plains ecoregion. To conduct the repeatability and sensitivity analysis of the BANCS model, ten stream professionals with experience utilizing the model individually evaluated the same six streambanks twice in the summer of 2015. To determine the model’s repeatability, individual streambank evaluations, as well as groups of evaluations based on level of Rosgen course training, were compared utilizing Kendall’s coefficient of concordance and a linear model with a randomized complete block design. Additionally, a one-at-a-time design approach was implemented to test sensitivity of model inputs. Statistical analysis of individual streambank evaluations suggests that the implementation of the BANCS model may not be repeatable. This may be due to highly sensitive model inputs, such as streambank height and near-bank stress method selection, and/or highly uncertain model inputs, such as bank material. Furthermore, it was found that higher level of training may improve model implementation precision. In addition to the repeatability and sensitivity analysis, the BANCS model developmental process was examined through the creation of a provisional streambank erosion rate prediction curve for the Central Great Plains ecoregion. Streambank erosion data was collected sporadically from 2006 to 2016 from eighteen study banks within the sediment-impaired Little Arkansas River watershed of south-central Kansas. Model fit was observed to follow the same trends, but with greater dispersion, when compared to other created models throughout the United States and eastern India. This increase in variability could be due to (1) obtaining streambank erosion data sporadically over a 10-year period with variable streamflows, (2) BEHI/NBS ratings obtained only once in recent years, masking the spatiotemporal variability of streambank erosion, (3) lack of observations, and (4) use of both bank profiles and bank pin measurements to calculate average retreat rates. Based on the results of this study, a detailed model creation procedure was suggested that addresses several model limitations and criticisms. Recommendations provided in the methodology include (1) more accurate measurement of sensitive/uncertain BEHI/NBS parameters, (2) multiple assessments by trained professionals to obtain accurate and precise BEHI/NBS ratings, (3) the use of repeated bank profiles to calculate bank erosion rates, and (4) the development of flow-dependent curves based on annually assessed study banks. Subsequent studies should incorporate these findings to improve upon the suggested methodology and increase the predictive power of future BANCS models.