TxRR Model Along the Coast

Victoria SamuelsMay 1, 2001

Background of TxRRTexas Water Development Board model to evaluate needs for instream and freshwater flows to the estuarine systems in TexasMany of these watersheds are ungagedCalibrates rainfall-runoff relationship for a TWDB gage watershedRelates gaged to ungaged watersheds with relationship

SMMAXU = (CNG/CNU) * SMMAXG

Genetic Algorithm Optimization

Follows the survivalistic behavior of nature Nature develops life forms

at random Weaker life forms are “killed

off”, Successful life forms progress

Successful life modified, tested again

Pattern continues until MOST successful life form found

Natural or Darwinian Selection

From Introduction to Genetic Algorithms, Nick Johnson

Genetic Algorithm Optimization

Random sampling of solutions, “chromosomes” undergo natural selectionTwo “parent” chromosomes are selected from remaining population and reproduction occurs, form new children Crossover Mutation

From Introduction to Genetic Algorithms, Nick Johnson

TxRR Model Interface

1. Windows BasedInput Screen

2. Call Fortran Codeto run TxRR

2. Windows BasedOutput Screen

Courtesy ofVenkateshMerwade

TxRR Input Screen

RAINFALL/RUNOFF FILES:• “.dat” files• currently available only from TWDB

TxRR Input Screen

FIXED WATERSHED CHARACTERISTICS:• MOIST1 – assume to be initial soil moisture condition• DRAREA - catchment area in sq. mi., obtained from USGS website, http://water.usgs.gov/tx/nwis/sw• abstr1 – initial abstraction from direct runoff equations, assumed to be 0.2, as in SCS Curve Number Method

TxRR Input Screen

GENETIC ALGORITHM SETUP:• Population size – number of “life forms” (solutions) to choose from• Max # of Iterations – limit on number of iterations the optimization routine will run• Number of children per Chromosome – how many offspring are formed during reproduction• Choose Random seed – assumed starting point of random sampling of solutions

TxRR Input Screen

TxRR PARAMETERS:• GammaA – N• GammaB - k• QB1 – initial baseflow• A(n) – monthly depletion factors, which should have a sinusoidal pattern because of its seasonal nature• SMMAX – maximum soil moisture• RECES – recession constant for baseflow• WB – baseflow coefficient

TxRR Input Screen

PERIOD OF SIMULATION:• between January 1940 and December 1997• gages must have data for simulation period, or program will not run (and not tell you why)

FORM OF OPTIMIZATION FUNCTION:• A – monthly data• B – daily data• C – volume ratio

Run TxRR CodeCreate Input FilesGo to TxRR DOS codeRemove return flow?70% zero data warningComputer cranks out 200 iterations…Pop – Optimized Parameters!

TxRR Output Screen

Study Area

Basin Group CAlong Eastern Coast of TX, near HoustonAppropriate for TxRR model

Study Area-Buffalo Bayou Tidal Watershed

Calibrating the ModelGage No. 10062/8075500: Sims Bayou at Houston, 63.0 sq. mi.Initial time period of January 1990-December 1992 Results not goodShorten time period to January 1991-June 1992 Improved, but still no goodShorten to major storm sequence from December 1991-June 1992

THE SHORTER THE SIMULATION PERIOD, THE BETTER

Calibrating the ModelModeled vs. Predicted Flow for Gauge 10062

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1-Dec-91 31-Dec-91 30-Jan-92 29-Feb-92 30-Mar-92 29-Apr-92 29-May-92 28-Jun-92

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flow

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Gauged Flow Modeled Flow

Calibration Parameters

Using a time period of December 1991 – June 1992Test Return Flow valuesTest Moist1 valuesModify Genetic Algorithm information

Return Flow CalibrationRemoving return flow decreases the gaged flow by the set amount, across the boardDesired effect to better match baseflowTried 50 cfs, 40 cfs, 45 cfsWent with 40 cfsBest fit overallMinimum value of gaged flow = 40 cfs

Moist1 CalibrationDefault Value = 2.35Decreased to 1.75 no differenceIncreased to 3.0 some peaks were raised, some were lowered Larger the peak, greater it increased This result fit with the gaged flow better

Tried 4.0, 5.0 Studied the results by breaking into 4 time periods Focused approach led to Moist1=4.0 having the

best fit

Genetic Algorithm CalibrationPopulation SizeDefault = 100 Increased to 150, 200Results similar if not worse to size of 100 Increased processing timeDefault retained

Genetic Algorithm CalibrationNumber of Children Default = 1 Toggled to 2 Results appeared to be identical Default retained

Random Seed Default A, ranged from A – F Tried each seed option Seed D had the best fit

Final Calibration

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12/01/91 01/20/92 03/10/92 04/29/92 06/18/92

time (days)

flow

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Gauged Flow Modeled Flow

Calibration of Gage 10062 for January - May 1990

Assumed input parameters used to calibrate the first time would apply, with a little tweakingWrong! Peaks far ovestimated, from two to ten times greater than the gaged flowChanged many of the parameters

Calibration of Gage 10062 for January - May 1990

Removing return flow had no effectDecrease Moist1 back to default 2.35, 1.5, 0.5Decreasing Moist1 reduces peaks above

500 cfs but increases peaks below 500 cfs

Changed Random Seed to AIncreased range of TxRR parameters

NO REAL EFFECT

Calibration with Moist1

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01/01/90 01/21/90 02/10/90 03/02/90 03/22/90 04/11/90 05/01/90 05/21/90

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flow

(cfs

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Moist1 2.35 Moist1 1.5 Moist1 0.75 Gauged Flow

My Crazy IdeaDecrease the drainage area from the USGS reported 63 sq mi to 50 sq miIt worked!Trial and Error process to increase the smaller peaks and decrease the larger peaks

Final Calibration, Gauge 10062, January 1990-May 1990

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1/1/90 1/21/90 2/10/90 3/2/90 3/22/90 4/11/90 5/1/90 5/21/90

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Gauged Flow Modeled Flow

Calibration of Gage 10061 for January - May 1990

Removing return flow of 97 cfsTry default parameter values & USGS Drainage Area of 94.9 sq miBaseflow okay, underestimated small peaks, overestimated larger peaksSame problem as before…. Look to the drainage area!

Final Calibration, Gauge 10061, January - May 1990

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1/1/1990 1/21/1990 2/10/1990 3/2/1990 3/22/1990 4/11/1990 5/1/1990 5/21/1990

time (days)

flow

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Gauged Flow Modeled Flow

Use a Drainage area of 30 sq mi vs. USGS 94.9 sq mi

Ungaged Watershed Relationship

SMMAXU = (CNG/CNU) * SMMAXG

Treat one watershed as if it was ungauged and the other was, and compare the results

Gauge CN SMMAXG SMMAXU

10061 80.42 0.001 0.0123

10062 78.03 0.0127 0.001

Ungaged Watershed Relationship

Default input values and USGS drainage areas did not yield satisfactory resultsCalibrated values led to much better modeled flows in both casesUpsetting, because the user would not have gaged flow to compare toGrossly overestimates flow using default, uncalibrated factors

10061 "Ungaged" Watershed

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32874 32894 32914 32934 32954 32974 32994 33014

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Gauged Flow Calibrated Values Default Values Default and Calibrated Values

10062 "Ungaged" Watershed

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1/1/90 1/21/90 2/10/90 3/2/90 3/22/90 4/11/90 5/1/90 5/21/90

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Gauged Flow Default Values Some Calibrated Values

Why?Does more rain fall on the gauges than the entire watershed, so the contributing area to the gage is much less?

Gage Gage Precip.

Watershed Precip.

% Diff. USGSArea

Calibrated Area % Diff.

10061 47.56 46.09 3.19 94.9 30 68.4

10062 49.43 47.50 4.26 63.0 25 60.3

ConclusionsCalibration is an Art FormOnly parameter that leads to significant change is the drainage area Moist1 parameter has slight effect

Does not serve its purpose well Drastically overestimates flow for ungaged

watersheds (if I’m doing this right)

No real rationale for drainage area calibration