Sediment Source Fingerprinting Database

Our lab compiled all existing sediment fingerprinting data that has been collected within the Mississippi River Basin into a coherent database, which contains 225,035 samples and a total of 3,715,811 geochemical measurements.

Data Overview:

MRB Database Map

Data Schema:

MRB Map 2 - Figure 1

Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, the determination of the relative importance of sediment sources is complicated at the scale of large river basins. Geochemical sediment fingerprinting provides an opportunity to constrain the relative importance of sediment sources, the basin-scale application of which requires a comprehensive understanding of the status quo and a full utilization of existing datasets. Accordingly, we compiled a database containing all available fingerprinting data throughout the entire Mississippi River Basin (MRB), which contains 225,035 samples and a total of 3,715,811 geochemical measurements.

Download the database file (compressed SQLITE File) 

Download database schema instructions

Download summarizing statistics for the database

Floodplain and Terrace Mapping Tools

Our lab has developed several tools for automated mapping of floodplain and terrace features.

TerEx Tool

screenshot of Ter text tool

TerEx Tool: for automated mapping of terrace and floodplain surfaces from lidar using local relief and a few other user-specified criteria. This tool can be run as an ArcGIS plugin or in a Python environment. For more information, see:

Stout, J. and Belmont. P. (2014) TerEx Toolbox for semi-automated selection of terrace and floodplain features from lidar. Earth Surface Processes and Landforms, 39(5), 569-580.

A huge thank you to Michael A. Rahnis (Franklin and Marshall College), who cleaned up the code and made TerEx compatible with ArcGIS 10.6!

Download TerEx Tool that is compatible with ArcGIS 10.6.
Or here for TerEx that is compatible with ArcGIS 10.4.
Or here for TerEx that is compatible with older versions of ArcGIS.

Barr-NCED Floodplain Mapper

Barr-NCED Floodplain mapper

Barr-NCED Floodplain Mapper: for automated mapping of floodplain inundation on lidar from user inputs of water surface elevation at multiple cross sections. This tool is a plugin for ArcGIS. For more information, see:

Belmont, P. (2011) Floodplain width adjustments in response to rapid base level fall and knickpoint migration. Geomorphology. 128 (1-2): 92-102.

Download Floodplain Mapper.

HydroME Toolbox

Our lab developed the hydrome toolbox, which contains several tools useful for calibrating watershed hydrologic models.

HydroME Toolbox

hydrome screenshot

The HydroME Toolbox contains several tools to aid with the calibration of a hydrologic model in the time and frequency domains. HydroME generates box plots to illustrate the full distribution of common model performance metrics, such as NSE or R2, Euclidian distance and empirical Quantile-Quantile (Q-Q) plots, and flow duration curves, as well as magnitude squared Fourier coherence and wavelet coherence plots to localize frequency mismatches in time. The accompanying MS Excel files contain example data in the format needed for the toolbox to generate the plots. Update with your data to generate the plots.

Download HydroME Toolbox.

FDC Toolbox

Screenshot of FDC toolbox

The FDC toolbox is a subset of the HydroME Toolbox for generating Flow Duration Curve plots that can be used to compare measured and simulated flows. Use the accompanying MS Excel file as example data.

Download FDC Toolbox.

Sediment Rating Curve Analysis Toolbox

Sediment rating curves (SRCs) quantify the empirical relationship between flow and suspended sediment concentration in a river. Our SRC toolbox takes flow and suspended sediment data as inputs and generate plots similar to those shown to the left. The scripts log transform the suspended sediment data, parse the dataset into rising versus falling limb, and normalize the sample flow values by the geometric mean of flows. The last step allows you to compare SRCs for rivers of different size and also eliminates the autocorrelation between the rating parameters (the coefficient and exponent of the power law relation). The scripts run regression analysis on the rising limb and falling limb samples independently, as well as all data combined. Vaughan et al., 2107 used these scripts to identify 3 distinct relationships between flow and suspended sediment (plots a-c) in rivers all throughout Minnesota and used statistical modeling to determine which factors controlled the shape, steepness and vertical offset of the SRCs. Lastly, the scripts quantify aggregate hysteresis as the integral of the area between the rising and falling limb regressions divided by the range of discharge over which the regressions are conducted (plot d).

Vaughan, A. A., Belmont, P., Hawkins, C. P., & Wilcock, P. (2017). Near‐Channel Versus Watershed Controls on Sediment Rating Curves. Journal of Geophysical Research: Earth Surface, 122(10), 1901-1923.

 Lab Info

My lab is located in the Biology-Natural Resources building and is equipped to do the following:

GIS, Computing, and Modeling

Belmont lab

Our meeting and computer lab, adjacent to our wet lab.

Bathymetric Mapping, Discharge and Velocity Measurements

Acoustic Dopplar Current Profiler

The photo to the left shows our Acoustic Dopplar Current Profiler (ADCP) rigged to the front of a cataraft in the Yampa River. Attached to the ADCP is a Leica rtkGPS. With these two devices we can measure river discharge, the velocity profile with depth in a river, and map the bathymetry of a lake or river. Recently, we have mapped over 150 km of the mainstem Minnesota River.

Bathymetric Maps Developed in 2015 For Select Reaches of The Minnesota River


st peter


Terrestrial, Fluvial, and Alluvial Sediment Flux and Grain Size Measurements

Figures below show grain size distributions for three samples, the first collected from a floodplain, the second collected as suspended sediment in a river, and the third sample was sieved for very fine sand.

grain size graph

tss grain size graph

sieved grain size graph