Near Bank Stress Research Articles

How can stream bank erosion be predicted on small water courses? Verification of BANCS model on the Kubrica watershed

The current paper deals with the evaluation of the BANCS erosion prediction model and its two components–the Bank Erosion Hazard Index (BEHI) and Near-Bank Stress (NBS) indices. To construct the erosion prediction curves, 18 experimental sections were established on the Kubrica Stream, district of Trenčín, Slovakia. Each section was assessed through the NBS index and BEHI index and real annual bank erosion was measured using erosion toe pins. Subsequently, the relations between the BEHI and real annual bank erosion was assessed through regression and correlation analyses. The relation proved to be moderately strong, with the correlation coefficient (R) reaching 0.47. Further, the relation between the NBS index and real annual bank erosion was evaluated, which was also moderately strong, with R = 0.65. Based on the measured data, two erosion prediction curves were constructed, the first for moderate BEHI, with R = 0.69 and coefficient of determination (R2) of 0.47 and the second for high BEHI with R = 0.74 and R2 = 0.55. The prediction curves were based on data from one year of measurements and can, therefore, be used only for discharges that occurred within that year and in the region where the model was developed. In the current case, according to runoff Curve Numbers (CN), the real culmination discharge was Q = 1.88 m3/s, which is roughly equivalent to 1.5-year recurrence interval flow (Q1.5).

Acceptance of BANCS model for predicting stream bank erosion potential and rate in the left bank of Ganga river of Diara region in Malda district, North East India

River bank erosion is a hazardous problem of Malda district. Different parts of Malda are mainly eroded by hydraulic action of River Ganga. Bank assessment for non-point source consequences of sediment model is a well accepted process for predicting stream bank erosion hazard potential. In the present study, river bank stability condition has been measured form field survey on 15 sample segments for 185 km stretched from Rajmahal in Sahibganj district, Jharkhand to upstream of Farakka barrage in Malda. In the present study, bank erosion hazard index (BEHI), near bank stress (NBS) and field based data have been considered for assessing stream bank erosion. The result shows that BEHI is high along the whole given left bank line extension of river Ganga, among these BEHI is very high in the upper segments of the river and adjacent river bank line extension of Farakka barrage, overall NBS conditions along left river bank line are less compare to the BEHI. Dominant NBS conditions are belong under moderate to low along the river bank line. Loosely compact alluvial soil, sparse vegetation, steep slope, unorganized agricultural activities; sinuous channel can be responsible for river bank erosion hazard potentiality. On an average 976,068.991 metric tons of sediments entrains to the river in a year. Bank has experienced variants bank erosion from same BEHI and NBS combinations. So, it can be concluded that BEHI and NBS are potentially not significant model for predicting bank erosion in present study.

Predicting the annual erosion rates on a small stream by the BANCS model

The erosion of streambanks causes soil loss and degrades the stream habitat. To optimize the prevention of bank erosion, we first need to determine the most vulnerable places on banks. This can be done by the BANCS model. However, data are still missing on its accuracy in small streams. We measured the real annual erosion rates on 18 experimental sections established on the Lomnická stream. Using the Near Bank Stress (NBS) and Bank Erosion Hazard Index (BEHI) we developed the erosion prediction curves and evaluated the relationship between these two indices and the real annual erosion rates. We found a strong relationship between BEHI and real annual erosion rates, with R<sup>2</sup> = 0.72. The relationship between the NBS index and real annual erosion rates was also strong, with R<sup>2</sup> = 0.53. Then we constructed erosion prediction curves for very high and extreme BEHI and for moderate and high BEHI. Despite the strong correlation between BEHI and annual erosion rates, the prediction curves had no real relationship with real annual erosion rates, with R<sup>2</sup>= 0.004 and 0.15, respectively.

Bank erosion of the Tŕstie stream: BANCS model predictions vs. real bank erosion

Abstract This paper focused on predicting the bank erosion through the Bank Assessment for Non-point source Consequences of Sediment (BANCS) model on the Tŕstie water stream, located in the western Slovakia. In 2014, 18 experimental sections were established on the stream. These were assessed through the Bank Erosion Hazard Index (BEHI) and the Near Bank Stress (NBS) index. Based on the data we gathered, we constructed two erosion prediction curves. One was for BEHI categories low and moderate, and one for high, very high, and extreme BEHI. Erosion predicted through the model correlated strongly with the real annual bank erosion – for low and moderate BEHI, the R2 was 0.51, and for high, very high and extreme BEHI, the R2 was 0.66. Our results confirmed that the bank erosion can be predicted with sufficient precision on said stream through the BANCS model.

Validation of BANCS model for assessing stream bank erosion hazard potential (SBEHP) in Bakreshwar River of Rarh region, Eastern India

It is often difficult to assess stream bank erosion. Bank Assessment for Non-point source Consequences of Sediment (BANCS) model is a renowned procedure for evaluating Stream Bank Erosion Hazard Potential (SBEHP). In the present article inventory of stream bank condition have been assessed from field surveys on 24 sample segment over a consecutive 5 year period for 86.36 km stretched river Bakreshwar of Eastern India. Bank Erosion Hazard Index (BEHI), Near Bank Stress (NBS) and field based data have been considered for this appraisal. The results show that (1) BEHI is high in the upstream and near the confluence segments. (2) Compare to BEHI, NBS is less for most of the sites. (3) Fragile lateritic soil, sparse vegetation, etc., in the upstream and steep slope and barren bank, sinuous channel, loosely compact alluvial sediments, etc., in the downstream can be accountable for high SBEHP in those counterparts. (4) On the annual basis, a total of about 173595.75 metric tons of sediment entrains into the river from banks. (5) Banks have experienced varied rate of erosion from similar BEHI–NBS combinations. Therefore, we concluded that BEHI and NBS is potentially not a sound bank erosion hazard predictive model for our present study.

Prediction of Annual Streambank Erosion for Sequoia National Forest, California

AbstractMany bank erosion models have limitations that restrict their use in wildland settings. Scientists and land managers at the Sequoia National Forest would like to understand the mechanisms and rates of streambank erosion to evaluate management issues and post‐wildfire effects. This study uses bank erosion hazard index (BEHI) and near‐bank stress (NBS) methods developed in Rosgen (2006 Watershed Assessment of River Stability and Sediment Supply [WARSSS]) for predicting streambank erosion in a geographic area that is dominated by colluvium and in which streambank erosion modeling has not been previously evaluated. BEHI evaluates bank susceptibility to erosion based on bank angle, bank and bankfull height, rooting depth and density, surface protection, and stratification of material within the banks. NBS assesses energy distribution against the bank measured as a ratio of bankfull near‐bank maximum depth to mean bankfull depth. We compared BEHI classes and NBS to actual bank erosion measured from 2008 to 2012. This index predicted streambank erosion with clear separation among BEHI ratings with R2 values of 0.76 for extreme, 0.37 for high/very high, 0.49 for moderate, and 0.70 for low BEHI. The relationships between measured erosion and BEHI extend the application of BEHI/NBS to a new region where they can inform management priorities, afforestation, stream/riparian restoration projects, and potentially burned area rehabilitation.

Application of Rosgen’s BANCS Model for NE Kansas and the Development of Predictive Streambank Erosion Curves1

Sass, Christopher K. and Tim D. Keane, 2012. Application of Rosgen’s BANCS Model for NE Kansas and the Development of Predictive Streambank Erosion Curves. Journal of the American Water Resources Association (JAWRA) 48(4): 774-787. DOI: 10.1111/j.1752-1688.2012.00644.x Abstract: Sedimentation of waterways and reservoirs directly related to streambank erosion threatens freshwater supply. This study sought to provide a tool that accurately predicts annual streambank erosion rates in NE Kansas. Rosgen (2001, 2006) methods were employed and 18 study banks were measured and monitored from 2007 through 2010 (May-June). Bank profiles were overlaid to calculate toe pin area change due to erosional processes. Streambanks experienced varied erosion rates from similar Bank Erosion Hazard Index (BEHI)-Near Bank Stress (NBS) combinations producing R2 values of 0.77 High-Very High BEHI rating and 0.75 Moderate BEHI rating regarding predictive erosion curves for NE Kansas. Moderate ratings demonstrated higher erosion rates than High-Very High ratings and BEHI trend lines intersected at lower NBS ratings, suggesting a discrepancy in the fit of the model to conditions in the NE Kansas region. BEHI model factors were evaluated and assessed for additional influences exerted in the region. Woody vegetation adjacent to the stream seemed to provide the most variation in erosion rates. This study’s findings allowed us to calibrate and modify the existing BEHI model according to woody vegetation occurrence levels along streambanks with high clay content. Modifications regarding vegetation occurrence of the BEHI model was completed and the results of these modifications generated new curves resulting in R2 values of 0.84 High-Very High BEHI and 0.88 Moderate BEHI ratings.

Streambank erodibility and lateral instability hazard in the Manahara River, Kathmandu basin, Nepal

The Manahara River, a large tributary of the Bagmati River, is located in the northeast of the Kathmandu basin. Recently, the river (especially, its lower reach) has been excessively mined for sand and gravel. Such anthropogenic activities together with the natural processes have led to rapid and haphazard shifting of its channel. As a result, its banks and adjacent areas are subject to failures and other mass movements. In this paper, the river course is evaluated in terms of its bank erosion and lateral instability (BELI) hazard by considering bank erodibility hazard index, near-bank stress index, lateral instability hazard index, and anthropogenic disturbances.
 The downstream reaches of the fourth-order stream belong to a moderate BELI hazard, whereas the fifth-order stream in the middle reach, near Mulpani, falls under a very high hazard. The rest of its fifth-order stretch exhibits a high hazard. An increase in the degree of anthropogenic disturbances increases the BELI hazard in the downstream stretch of the river. Poor riparian vegetation seems to be one of the factors aggravating the bank erodibility hazard in the river. Hence, the restoration of bank vegetation and establishment of riparian vegetation buffer zones can significantly reduce the BELI hazard.

EVALUATION OF ROSGEN'S STREAMBANK EROSION POTENTIAL ASSESSMENT IN NORTHEAST OKLAHOMA1

ABSTRACT: In this study three components of the Rosgen Level III Stream Reach Condition Assessment were tested for their ability to predict short‐term erosion rates. Rosgen's bank erosion potential (BEP) ratings and near bank stress (NBS) estimates and the Pfankuch channel stability ratings were evaluated. Thirty‐six banks with a range of BEP ratings and NBS estimates were selected on the 101 km Upper Illinois River in northeast Oklahoma. The Upper Illinois River is a meandering, gravel‐dominated, riffle/pool channel. Cumulative erosion data measured with bank pins after four 2.0 to 2.5‐year return period flows from September 1996 to July 1997 were used in the analyses. When integrated as indicated in Rosgen (1996), the BEP indices and NBS estimates were poor predictors of bank erosion. Individually, the grouped BEP ratings and Pfankuch ratings performed relatively well compared to grouped NBS estimates in predicting erosion; however, the variability of erosion was large within each rating group. Linear regression between erosion and BEP numerical indices and Pfankuch scores was significant (a = 0.05), but variability was high (illustrated by low r2 values). Regression between erosion and NBS estimates was not significant.