Onondaga County Regional Stream Simulation Study

Dan CoyleMajor Prof. – Dr. Hassett

MPS Degree

OUTLINE

• 1. Introduction

• 2. Study Questions and Objectives

• 3. Model Development

• 4. Results- output charts

• 5. Discussion

Water Resource Management

• Various water processes- water cycle

• Quantity- availability

• Quality- for use

• Resource- value for use

• Damages- problems

• Common to many problems & theory – need for estimates of stream flows

2. Study Questions & Objectives

• Literature search- 2 broad questions

• Model type selection?

• Model development?

• Second iteration is very limited

Categorization of Streamflow Models

• Lumped vs. spatial distributed

• Event versus continuous models

• Theoretical versus empirical

• My choice- lumped, continuous, & empirical

Develop or select model?

• Purposes- needs, ideas, motivations

• Learning curves- cost, time

• Limitations- risks, restrictions

• Assumptions- applicability

• Versatility & ease of use-extensibility

• Time & Money- budget, patience

Study Objective and Development Process

• Create and Evaluate Relatively Simple (and hence Extensible) Streamflow Model(s) Suitable for Central New York Using Readily Available Data Sources

• Utilize Model Development Process Common to Software Engineering Projects

Streamflow as Simulation Problem

• Stream flows- candidate models

• Extract model parameters- simple

• Calibrate parameter values- test

• Predict flows- validate model for ungauged flows

Considerations in Model Development

• A) Limit Streams to Those in National Water Information System (www.usgs.gov)

• B) Meteorological Data from Local National Weather Service Stations) (www.noaa.gov)

• C) Lumped Landuse Descriptors• D) User application container• E) System life cycle• F) Candidate models• G) Base flow separation• H) Application logic

Stream Selection

Name

USGS #

Area

mi2Years Land

Use

Spafford Trib. 04240149800.11 2000-2 Rural

Trib.#6, Below 042379460.32 2000-3 Rural

Meadowbrook 042452363.06 2001-3 Urban

Harborbrook 0424010010.0 2001-3 Suburban

Ley 0424012029.9 2002,3 Urban

Onondaga Cr. Cardiff 04237946

33.9. 2001-4 Rural

3. Model Development -System Life Cycle

• Problem definition- purpose

• Feasibility analysis- possible

• Project design- specifications

• Construction- write, build

• Monitoring- use & test

• Analysis- evaluate

• Control- maintain & adjust

Review of User Application Containers

• MS-Excel- time series, solver, UI

• MS-Access- DB development

• Arc GIS- newer

• Arc View- older

• VB- programming

Candidate Models

• Rainfall Excess - effective precipitation

• Base flow separation from total flow

• Rational Model

• Storages

• Soil Conservation Service Runoff

• Moisture indices & other scaling factors

• Water Balances

Rational Model

Linear Percentage of rainfall

necipitatioctionainFallFraEffectiveRRunOff Pr*

Storages

• Container outflow

servoirtRateConsFlow Re*tan

SCS Curve Numbers

• Runoff from single storm event

)*8.0/()*2.0( 2 SPSPQ

10/1000 rCurveNumbeS

Moisture Indices

• Approximate /scale precipitation

t

t

t PBAPI *

tt KB

.

Water Balance Storage

• For soil moisture flow or evaporation wells

PETPWBS

Hamon Equation

• Estimate Potential Evaporation Transpiration by #hours daylight, temperature, water vapor constant

)273/(*021.0 2 TENPET st

)3.237/(*27.17(*108.6 TTst eE

Geographic Averaging

• To weight or scale multiple weather stations

)tan/1/()tan/1( i iii cediscedisWeight

Step Absolute Relative Error

• Solver Optimization Function and averaged over time steps

)/)( observedpredictedobservedARAE

Nash-Sutcliffe Coefficient

• Model goodness

2

22

)(

/)(

erageObservedAvobserved

estimatedobservedR

Water Volume Conversions

• For stream flows and precipitation

reaCatchmentAecipiationallVolumeRa *Prinf

TimeStep

ttlumesFlowRateVoFlowVolume

Sample Application logic

• 1) Calculate parameter averages /values

• 2) Calculate slope or store (& subtract from) contribution for base / flows

• 3) Calculate other contributions

• 4) Add up for flow time step

• 5) Check if new average period (step 1)

• 6) Step 2

Model Equations

Sample logic

))((*tan 111

ttt

t

fQuickRunOfflowstoragetRateCons

QFlow

1* tt BaseflowSlopeStepBaseFlow

Snow Melt Depth

• Snow pack contributions in mm

)(* baseTTMeltFactorP

4. ResultsTable 2. Overview of models

Model Name

Baseflow Run Off

QuickFlow

PET Years /Season

Monthly slope (sm)

sloped line %rain 11/01-10/03

Monthly store (rm)

reservoir %rain 11/01-10/03

daily slope (sd)

sloped line %rain Summers 2000-4

daily store (rd)

reservoir %rain %rain store Summers 2000-4

Runoff Models Observations

• Slower base flow from ground contributions

• Quicker runoffs from precipitation over land & interflows

• Related processes of infiltration & recharge for base flow

• Storage, slope, or constant estimations for baseflow

Month Storage, 11/01-10/02

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 5 10 15

Month

Rech

arge

Fra

ctio

n

Spafford

Below

Meadow

Harbor

Cardiff

Prec.-PET

Figure 9. Monthly model recharge fractions for first year

May Flow Curve Family

0

1

2

3

4

5

0 10 20 30 40

Area, mi^2

Tot.F

low

, in.

May-02

May-03

Month Storage

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 10 20 30 40

Area, sq.mi.

Rec

harg

e Fr

actio

n

May-02

May-03

Figure 11. Monthly model recharge fraction and area relational curves

Month Storage

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 10 20 30 40

Area, mi**2

Dec

ay R

ate

Con

stan

t

May-02

May-03

Figure 8. Monthly model decay rate curves

Month Slope

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

0 10 20 30 40

Area, mi^2

Yea

rly

slop

e

2001-2

2002-3

Figure 15. Monthly slope model base slope progressions for May

Daily Model Example

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0 10 20 30 40

Area, sq.mi.

Dec

ay R

ate

Con

stan

t

Class Line

May-02

Figure 30. Daily storage model, decay rate relation

Daily Model Example

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 10 20 30 40

Area, mi^2

Stor

e Re

char

ge F

ract

ion

Class Line

May-02

Figure 31. Daily model reservoir recharge

2002 Flow Predictions

0

50

100

150

200

250

300

-10 0 10 20 30 40

Drainage area, mi**2

% R

elat

ive

Err

or sd-Meadow, 18.2%

sd-Harbor, 12.9%

rd-Harbor, 10.7%

Figure 36. Flow estimates from Tables 6, 8, & 10

Onondaga Creek @ Cardiff

0

10

20

30

40

50

60

9/21/2002

10/1/2002

10/11/2002

10/21/2002

10/31/2002

11/10/2002

Date

Flow

(cfs

) Actual Daily AverageFlow

Simulated Flows

Figure 26. Sample simulation of daily flow

5. Discussion

• Ease of use, vesatile & situational

• PET under/over estimated winter/summer

• 50% Prediction – daily models

• Flow & area relation: rate & recharge

• Approximate PET, recharge factor yearly association

• Runoff spikes underestimated usually

Future

• Shorter parameter average periods

• Finish winter season models with snow melt

• Exponential storage relation?

• Missed key parameter association?

Optimizing function

• Error calculation - minimize

• Relative average error – steady flows

• Monthly step error summaries

• Absolute differences – peaks?

• Nash-Sutcliffe Coefficients?

• Other candidate models?

Conceptual models

• Hydrologic cycle- water budget, possible • Lumped & continuous- set choice • Simplified or approximate- analytical vs.

numerical • Historical or stochastic-simulation vs. synthesis • Physical or mathematical- analog vs. equations • Descriptive or conceptual- observations vs.

theory • Dynamic vs. static