Dataset DOI: 10.5061/dryad.d7wm37qf7

Description of the data and file structure

Traditional backwater methods are limited in variable natural channels, so we developed a model to predict dimensionless head loss through log jams for sub-bankfull flows. We developed the model from historical flume studies and tested the model application on field data from natural jams.

Files and variables

File: Non-linear_Model_1.26.26.py

Description: Python script used to develop and evaluate field utility of non-linear dimensionless head loss model using input files of "Combined_Standard_Step_Results.xlsx" ; "Field_Data.xlsx" ; "Field_Data2.xlsx" . 
1. Univariate log-log regressions for parameter evaluation
2. Runs non-linear model fit for a prediction of the non-dimensional headloss through the jam
3. Performs 10-fold cross-validation for model performance evaluation
4. Plots field and model results on single plot

File: Roughness_Calculation_Verification.py

Description: Python script used to do the following with the input file of "Data_to_Mannings_n_Combined_Ljam.xlsx".
1. Calculates Manning’s n and Darcy-Weisbach friction factor from experimental flume data
2. Computes backwater profiles via the standard step method.
3. Outputs a results table ready for nonlinear model fitting ("Combined_Standard_Step_Results.xlsx")

File: Data_to_Mannings_n_Combined_Ljam.xlsx

Description: Base file used for input into Roughness_Calculation_Verification. Note, only headers were provided for this datafile as the input data for the associated study utilized data from Schalko (2018) and Follett (2020), which are under a CC by 4.0 license.

Variables

Note column name may be in parentheses () and units are in brackets [] unless dimensionless.

We describe the input columns from the related works/datasets of Schalko (2018) and Follett (2020) that were used to develop the complete input file of Data_to_Mannings_n_Combined_Ljam.xlsx

• Input columns derived from Schalko (2018) and Follett (2020):
  • Source Dataset: Schalko, Follett
  • Test No. 
    • Follett dataset: Test No.
    • Schalko dataset: Test Series JHE
  • Flume width (B) [m]
    • Follett dataset: B (m)
    • Schalko dataset: Channel Width B
  • Discharge (Qcms) [m^3^/s]
    • Follett dataset: Q (m3/s)
    • Schalko dataset: Discharge Q
  • Jam length (L) [m]
    • Follett dataset: L (m)
    • Schalko dataset: Accumulation Length La
  • Upstream and Downstream depth (h1, h2) [m]
    • Follett dataset: H1 (m), H2 (m)
    • Schalko dataset: Backwater rise ∆h, Approach flow depth
      • h1 = Backwater rise + Approach flow depth
      • h2 = Approach flow depth
• Calculated variables: area (A1, A2) [m^2^], velocity (U1, U2) [m/s], wetted perimeter (P1, P2) [m], hydraulic radius (R1, R2) [m], and jam solid volume fraction (SVF)
  • Channel geometry equations based off a rectangular channel were used for area, wetted perimeter, hydraulic radius.
  • Velocity was determined from area and discharge.
  • SVF calculations: 
    • Follett: SVF remained constant
    • Schalko: Calculated SVF from Solid LW volume Vs, Loose LW volume Vl, and Vol% Organic Fine Material FM

File: Field_Data.xlsx

Description: Data from field measurements for application in the model for upstream and downstream Goat Creek, Monture Creek, Little Beaver Creek.

Variables

Note column name may be in parentheses () and units are in brackets [] unless dimensionless.

• Site name, Froude ratio (Fr2/Fr1), jam solid volume fraction (SVF), head loss (H1-H2), Manning's n [s/m^1/3^], Darcy Weisbach f

File: Field_Data2.xlsx

Description: Data from field measurements for application in the model for Lost Creek.

Variables

Note column name may be in parentheses () and units are in brackets [] unless dimensionless. 

• Site name, Froude ratio (Fr2/Fr1), jam solid volume fraction (SVF), head loss (H1-H2), Manning's n [s/m^1/3^], Darcy Weisbach f

File: survey_data.xlsx

Description: Example input file for EquationApplication.py. Uses survey and discharge data from Goat Creek (MT), it is referenced as "Lower Goat" in the associated manuscript. Note the file corresponds to only one discharge and one solid volume fraction and thus columns Q and SVF only have one listed value. 

Variables

Note column name may be in parentheses () and units are in brackets []. 

• Section (Upstream/Downstream), Easting [m], Northing [m], Elevation [m], Type (bed/water), Discharge (Q) [m^3^/s], Solid Volume Fraction (SVF)

File: EquationApplication.py

Description: Python code to calculate a predicted upstream depth and energy head from upstream/downstream channel surveys, downstream water depth, jam solid volume fraction, and discharge. 

• Loads survey data from survey_data.xlsx workbook
• Calculates downstream geometry using given water elevation
• Uses equation and upstream channel geometry to predict upstream water surface elevation and energy head
• Plots both upstream and downstream channel geometry and predicted water surface elevations

Code/software

Python version 3.12.4

Python packages: numpy, pandas, scipy, scikit-learn, matplotlib, openpyxl