Evaluating river cross section for SPRINT: Guadalupe and San

Antonio River BasinsAlfredo Hijar

Flood Forecasting

Outline

Introduction

Hydraulic geometry, hydraulic routing models, channel cross section extraction

Reliable channel cross section approximation

Boundary conditions – Noah Land Surface Model

Results

Future work

Introduction

Importance of understanding river networks.

Floods are a major problem in the US.

Potential hydropower plants.

Watershed management (sediment control, habitats).

Hydraulic Geometry

Leopold (1953) introduced power law relationship between hydraulic variables.

w = aQb

d = cQf

v = kQm

w, d, and v change with discharges of equal frequency.

These discharges increase with drainage area.

Hydraulic/Distributed flow routing

Flow is computed as a function of time and space.

1D unsteady flow equations – Saint Venant equations (1893).

Governed by continuity and momentum equations

2 Equations, 2 variables (Q, A).

Channel geometry – A(h).

Hydraulic/Distributed flow routing

Data requirements for hydraulic routing models:

Channel cross section geometry – level of detail?

Channel friction – Calibration

Lateral inflows or boundary conditions – hydrological models

Tool for flood forecasting & watershed management.

Channel cross section extraction

Software tools are been developed to extract spatial features from DEM or LiDAR datasets.

Extraction from ASTER GDEM.

Triangular & Synthetic XS.

Extracted XS present similar results to surveyed/bathymetric data.

New Software for XS extraction: GeoNet.

Study Area

• 5,000 streams.

• 1,500 “source” nodes.

• ≈ 30 active USGS streamflow stations

Reliable cross section approximation

Shape of cross section of river channels is a function of:

Flow

Sediments

Bed Material

Most river cross sections tend to have:

Trapezoidal/rectangular,

Rectangular, or

Parabolic forms.

Reliable cross section approximation

USGS streamflow stations:

Channel top width (ft)

Gage height (ft)/Channel mean depth (ft)

Hypothesis:

Trapezoidal XS

Floodplain

Reliable cross section approximation

Channel mean depth (ft)

Channel top width (ft)

Area in blue = Area in red

USGS Streamflow Measurement Stations

≈ 25 USGS stations.

Data collected from 2007 to 2010.

Simulation year: 2010.

Rating Curve should be the same for data.

Station Name Data CollectedNumber of

ObservationsRating Curve

NumberTivoli 2008-2011 20 2

Bloomington 2010-2012 22 2Victoria 2009-2013 23 19Cuero 2007-2010 23 8

Gonzales 2007-2010 23 5FM1117 2007-2010 27 2

NewBraunfels 2007-2010 24 9Sattler 2007-2010 23 7

SpringBranch 2009-2011 27 7Comfort 2007-2010 27 25

CenterPoint 2008-2010 19 1Kerrvile 2007-2010 23 6BearCk 2008-2010 27 7

NFk_Hunt 2007-2009 17 8McFaddin 2008-2010 22 3

Goliad 2008-2010 20 18FallsCity 2007-2010 21 5

Floresville 2007-2010 20 4Elmendorf 2009-2011 23 3

Loop410 2007-2010 20 1Mitchell 2008-2010 25 2Medina 2007-2010 22 8Bandera 2008-2010 23 12

Rating Curve

Graph of channel discharge vs. stage height.

Different Rating curves imply a change in channel XS. Storms

Artificial changes

Reliable cross section approximation

Plot data on scatter plot.

Detect trends or shifts in the data.

Kendall Correlation Coefficient (tau) – monotonic trend. Kendall correlation coefficient varies between 0.1 to 0.5.

Pearson Correlation Coefficient (r) – linear relationship. r values higher than 0.5.

Reliable cross section approximation

Develop a linear regression model: Determine parameters:

intercept (b0) and slope (b1)

Determine significance of slope (b1) – t statistics

Compute residuals

Examine residuals distribution

Plot residuals vs. time or space

Channel bottom width

Channel side wall slope

Reliable cross section approximation

Station Code Station Name N Linear b1 bo r t tcritDrainage

Area (km^2)

08188800 Guadalupe Rv nr Tivoli, TX 14 Yes 3.15 114.71 0.62 2.72 2.179 26220.88008176500 Guadalupe Rv at Victoria, TX 23 Yes 1.92 98.67 0.57 3.20 2.08 13456.24008175800 Guadalupe Rv at Cuero, TX 18 Yes 5.68 90.92 0.70 3.96 2.1 12781.15008173900 Guadalupe Rv at Gonzales, TX 18 Yes 8.93 14.42 0.94 11.47 2.1 8998.47808169792 Guadalupe Rv at FM 1117 nr Seguin, TX 20 Yes 8.44 35.41 0.87 7.57 2.1 4873.88408168500 Guadalupe Rv aat New Braunfels, TX 16 Yes 25.25 67.33 0.89 7.21 2.15 3934.60708167500 Guadalupe Rv nr Spring Branch, TX 19 Yes 22.71 33.65 0.97 15.33 2.1 3456.59508167000 Guadalupe Rv at Comfort, TX 13 Yes 15.80 12.14 0.91 7.33 2.2 2174.37408166250 Guadalupe Rv nr Center Point, TX 15 Yes 7.17 29.21 0.79 4.65 2.16 1431.01608166200 Guadalupe Rv at Kerrville, TX 17 Yes 36.97 26.73 0.91 8.47 2.13 1259.10408165300 N Fk Guadalupe Rv nr Hunt, TX 11 Yes 8.52 11.19 0.85 4.84 2.26 435.99208188570 San Antonio Rv nr McFaddin, TX 20 Yes 1.44 71.74 0.76 4.99 2.1 10722.33008188500 San Antonio Rv at Goliad, TX 21 Yes 2.84 69.53 0.96 15.02 2.1 10120.08008183500 San Antonio Rv nr Falls City, TX 17 Yes 9.17 55.39 0.99 28.58 2.13 5464.45708183200 San Antonio Rv nr Floresville, TX 18 Yes 2.18 42.04 0.94 11.16 2.12 5091.58308181800 San Antonio Rv nr Elmendorf, TX 12 Yes 2.79 16.99 0.92 7.59 2.23 4528.45808178565 San Antonio Rv at Loop 410, TX 14 Yes 10.98 14.98 0.97 14.67 2.18 296.77308178000 San Antonio Rv at San Antonio, TX 11 Yes 3.72 15.01 0.84 4.57 2.262 109.8945

Reliable cross section approximation

Boundary conditions – Lateral inflows River network – NHDPlus

V.2. COMID, slope, areas,

divergence, topological connection, length, etc.

Noah (LSM) provides lateral inflow to river network. Surface runoff

Subsurface runoff

Boundary conditions – Lateral inflows

5,000 catchment areas – km2.

Runoff data hourly for year 2010 – mm/hr.

Lateral inflow = CA * Runoff

Hydraulic Flow Routing Complexities

Supercritical and Subcritical Mixed Flows

SPRINT can not handle supercritical flows at the junction nodes.

Lateral flow calculation produces flow peaks – no time of concentration.

Hydraulic Flow Routing Complexities

• Flow peaks up to 100 m3/s.• Unstable and

convergence failure – SPRINT.

• Low-pass filter – 1st order.• Mass

conservation.

Simulation Program for River Networks (SPRINT) Fully dynamic Saint-Venant

Equations. Channel network, geometry,

forcing terms (initial conditions) and boundary conditions are specified as a “NETLIST”.

At each node, “A” and “Q” are computed by solving the Saint Venant Eq.

Results – SPRINT 2010

Results

Conclusions & Future Work

Trapezoidal cross section approximation provides acceptable results.

Spin-up time ≈ first 2 to 3 months.

Noah provides acceptable lateral inflows – 10km x 10km grids.

Calibration for Manning’s n (0.05 for all reaches) – PEST.

Use GeoNet for XS extraction and run SPRINT - 10m DEM.

Use finer grids 3km x 3km LSM – WRF-Hydro models.