Suspended-sediment and sand concentrations, streamflow, acoustic data, linear regression models, and loads for the Lower Minnesota River, 2012-2019

A series of linear regression models were developed and calibrated for two Lower Minnesota River sites. The linear regression models were either calibrated using acoustic or streamflow data to estimate suspended-sediment or sand concentration data. Data were collected during calendar years 2012 through 2019. The estimates of suspended-sediment and concentrations from the linear regression were used to calculate loads. The calibrated models were used to improve understanding of sediment and sand transport processes and increase accuracy of estimating sediment and sand concentrations and loads for the Lower Minnesota River, as part of the associated report, U.S. Geological Survey Open File Report 2021?1005 (https://doi.org/10.3133/ofr20211005).

针对明尼苏达河下游两处监测点位，开发并校准了一系列线性回归模型。本系列线性回归模型分别采用声学监测数据或径流数据进行校准，以估算悬沙浓度与沙粒浓度。数据采集时段覆盖2012年至2019年各日历年。基于线性回归模型得到的悬沙与沙粒浓度估算值，可用于计算输沙量。经校准的模型可用于加深对明尼苏达河下游泥沙与沙粒输运过程的理解，并提升该区域泥沙、沙粒浓度及输沙量的估算精度。本研究作为配套报告《美国地质调查局公开报告2021-1005》（https://doi.org/10.3133/ofr20211005）的组成部分完成。