New Variables, Gage Data, and WREG

REGIONAL ANALYSIS

IN THE LEVISA FORK

AND TUG FORK BASINS

Carey Johnson, KY Division of Water State CTP Lead Has led Kentucky through MapMod for all

120 counties in the Commonwealth

Davis Murphy, URS Water Resources Engineer

INTRODUCTIONS

Watershed-based analysis, and establishing a greater understanding

KENTUCKY’S APPROACH TO

RISKMAP

Part of the Risk MAP Vision Credible data—reliable, accurate, watershed-based

KENTUCKY AND RISK MAP

Asking the right questions:

What’s being done throughout the nation?

What tools are available?

What can we do now?

TAKE ADVANTAGE

Review, Goals, Methods, Results,and Closing Thoughts

OUR STUDY

Review regression analyses throughout the country

Nationwide there are over 150 explanatory variables tested

From Drainage area to the Rotundity Ratio

Test new variables

Update gage peak flow estimates

PEAK FLOW STUDIES THROUGHOUT THE NATION

PEAK FLOW STUDIES THROUGHOUT THE NATION

Top 5 tested variables: drainage area1

mean annual precipitation main-channel slope main-channel length forested area

Top 5 final variables for the 1%: drainage area1

main-channel slope mean basin elevation mean annual precipitation main-channel length

OLS, GLS regression and in a few cases RoI regression Regionalization technique is commonly used

1 I nc ludes t o ta l d ra inage a rea , and con t r i bu t ing d ra inage a rea .

WREGReleased Jan. 2010OLS, GLS, and RoI*

PeakFQAnalyze many gages at once

* WREG wi l l per form RoI for demonstrat ion purposes only

TOOLS

Explanatory Variables Indentify and compute new hydrologic variables

In Progress… Re-compute explanatory variables using better data

Main-channel slope Mean basin elevation

Evaluate updated explanatory variables for significance

Gage Frequency Analysis Update B17-B analyses with new gage data Determine if updated peak flow analyses provide

statistically meaningful effects

GOALS OF ANALYSIS

Data

Watstore database of basin characteristics NHD Plus – create basin polygons, compute other variables Gage peak flows – update B17-B analyses

Software

ArcGIS & ArcHydro – variables PeakFQ – Recurrence interval flows (100-yr, etc.) Excel – OLS

METHODS

WATSTORE BASIN CHARACTERISTICS

STUDY AREA

Preferred basin orientation Borrowed from HMR-52 (PMP) Suggests average basin orientation affects extreme rainfall

events Procedure well defined and accepted

Time of Concentration Kirpich’s formula

Average basin slope Main-channel length (longest flowpath)

NEW EXPLANATORY VARIABLES

Estimate the average orientation angle at each basin

Determine the preferred basin orientation from HMR-52

Calculate the difference

PREFERRED BASIN ORIENTATION

DA vs 1%-AEPAdjusted DA vs 1%-

AEP

PREFERRED BASIN ORIENTATION

Tc (min) vs 1%-AEP Cross-correlation: Tc vs DA

TIME OF CONCENTRATION

1 10 100 1000100

1000

10000

100000

f(x) = 90.731141101775 x^1.39563011093014R² = 0.853235923041044

Tc (min)

Q (

cfs

)

1 10 100 10000.1

1

10

100

1000

10000

f(x) = 0.0689258002775357 x^2.03925669882521R² = 0.899926167531605

Tc (min)

DA

(m

i2)

2003 FLOWS VS TODAY

1%-AEP

2003 FLOWS VS TODAY

2003 flows (cfs)

MEAN = 13670

MEDIAN = 9510

Today’s flows (cfs)

MEAN = 14370

MEDIAN = 9512

ΔMEAN = 702 (0.01437)

Δ MEDIAN = 2 (9.1x10 -5)

RECAP Summarized nation’s regression studies

Tested new variables for significance No effect to very small improvement to OLS regression

Reviewed preliminary results of new gage frequency analyses Very little change in the overall pool of flow data

POSSIBLE FUTURE ANALYSIS GLS regression on new flows with and without ABO Explore RoI Incorporate pending changes to B17-B (EMA, historic data)

CLOSING THOUGHTS

LESSONS LEARNED

Unique opportunity

Consider cross-correlation of variables

Regional changes in peak flow signify need to update

Urbanization

Recent floods of record

CLOSING THOUGHTS

QUESTIONS?