StreamStats Web StreamStats Web ApplicationApplication

streamstats.usgs.govstreamstats.usgs.gov

Audrey Ishii, P.E.Illinois Water Science Center

Overview—Streamflow Statistics• What—Estimate of streamflow under some condition, such as

the 100-year flood flow, flow durations, etc.• Used in engineering design flows for bridges, culverts, mapping

floodplains, setting water allocations, determining allowable waste discharges.

• How Computed— At stream gages--statistical analysis of historic flows, the

flood-frequency or flow duration curveUngaged sites: Regression equations relating the

characteristics of the curve to basin characteristics.

Q100 = a(TDA)b(MCS)c(PermAvg)d(Rf)

Selected discharge gages with more than 25 years of record for analysis.

Streamflow gaging stations are not distributed evenly.The density impacts the quality of regional analyses.

Percentage changes in the 100-year peak flow estimate between 1987 and 2004

1Max. = 35Avg. = 6

Max. = 50Avg. = 27

Max. = 29Avg. = 4

Max. = 81Avg. = 9

Max. = 24Avg. = 7

Max. = 95Avg. = 15

Max. = - 2Avg. = - 8

Traditional Methods for Measuring Basin Characteristics

• Very labor intensive and costly• Not completely reproducible• Error-prone• Often not documented well in reports• Users need source materials and expertise• Some BC not easily reproduced by GIS methods

GIS Methods for Basin Characteristics

• Several custom software packages developed, GIS Weasel, BasinSoft, BASINS, WMS, mostly

developed for watershed modeling, often ESRI.• Needed GIS datasets not always readily available • No documented national standard methods• Several methods used for some characteristics• Users need source data and expertise• Often not documented well in reports• Some measurements are scale-dependent

StreamStats GIS computations

• Create hydro networks of rivers and streams

• Process DEM and stream network for watershed analysis

• Delineate drainage basins and measure basin characteristics

• Represent channel shape using three-dimensional models

• Connect geospatial features to time series measurements recorded at gaging sites

• Runs within ESRI Arc 8/9 software• Public domain utilities developed

jointly by U. Texas at Austin and ESRI

StreamStats Web Application• Provides published

streamflow statistics and basin characteristics for gages

• Computes basin characteristics for ungaged sites

• Provides regression-based estimates of streamflow statistics for ungaged sites

User InterfaceArcIMS

Streamflow Statistics Database

NSS Calculation

Program

GIS DatabaseArcHydro

At astreamgage

At an ungaged location

Application Examples

• Engineering Design—Bridges, culverts, flood-plain management

• Water and Land Management—Water rights adjudication, in-stream flows, fish passage/habitat studies

• Water Quality Regulation—Low flows, perennial vs. intermittent streams (TMDL’s, NPDES Permits)

• Sampling Network Design—Cover a range of desired flows

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Variation in Slope with Drainage Arean=283

StreamStats Benefits

• Cost—Time to delineate and compute basin characteristics reduced from hours to minutes

• Accuracy—As good or better than manual methods• Consistency—Important for statistical validity• Accessibility—User does not need GIS expertise or

software

National StreamStats Status

• 15 states up and running• National gages web site• 18 additional states underway• Data upgrades on 3

states (PA, ID, WA)• Each state is developed

(and funded) separately

Evaluation of Illinois StreamStats

• Basin characteristics at 283 USGS rural gaging stations

• Sensitivity of basin characteristics on estimated flood quantiles

• Flood quantiles at 169 USGS rural gaging stations (random sampling)

• Reliability testing

Q100 Estimates

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StreamStats Q100

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Q100 Estimates

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Scatter plots of preliminaryQ100 estimates using BasinSoft and manual drainage basin delineation with StreamStats

All regions, n = 164

Log-Log Scale

Arithmetic Scale

The UNIVARIATE Procedure Variable: PERDIFFIL_Q100

Schematic Plots

| 1 + | * | | 0.5 + | | * | | | | | +-----+ +-----+ | +-----+ 0 +-----+ +-----+ 0 + *--+--* *-----* *--+--* *--+--* *--+--* *--+--* *--+--* | | | + | | | +-----+ 0 | +-----+ 0 0 | | | 0 -0.5 + | | | | | -1 + 0 | | | -1.5 + 21 38 46 23 16 12 8 +--------+----------+--------+--------+-------+--------+----------- 1 2 3 4 5 6 7 REGION

Variable: DIFFBSIL_Q100

Schematic Plots

| 4000 + | * | | * 2000 + * * | * 0 | 0 0 | * 0 | +--0--+ | +-----+ | | +-----+ | 0 + *--+--* *-----* *--+--* *--+--* *--+--* *--+--* *--+--* | | + +-----+ 0 +-----+ | | * * 0 * | | * * 0 -2000 + * 0 * | | | -4000 + * | | * | -6000 + * ---------+--------+--------+---------+--------+--------+--------+ 1 2 3 4 5 6 7 REGION

+ Mean*----* Median+---+ Interquartile Range | 1.5 x Interquartile Range 0 < 3.0 x Interquartile Range * > 3.0 x Interquartile Range

Distribution of differences by Region

Differences are found not statistically significant by paired t-test and Wilcoxon Signed Rank test (p-value < 0.05), except forRegion 1: Q2, Q5, Q10 percent differences.

Average absolute maximum deviation from the mode = 1.31 percent

Reliability Testing

1 2 3 4 5 6 7 8 9 10 11 12 13 14

5150 2050 1120 3010 2500 2280 4630 3870 4930 2800 3700 1160 575 7310

5150 2050 6120 2280 4630 3870 2820 3700 1180 583 7310

2040 1120 1760 2510 2280 4630 3870 4940 11800 3700 1180 574 7310

5150 1980 1110 6120 2490 2280 4630 3870 319 2800 3700 1190 573 7310

5150 2040 1120 3010 2500 2280 4630 3870 4940 2820 3700 1180 583 7310

5150 2040 1120 3010 2500 2280 4630 3870 4940 2830 3700 580 7310

5150 2050 1120 6110 2500 2280 4630 3870 4930 2820 3700 1150 575 7310

5150 2050 4630 3010 2500 2280 1120 3870 4950 2830 3700 1170 575 7310

0 2.94 0.89   0.4 0 0 0 0.2 0.71 0 2.54 0.09 1.39

15 16 17 18 19 20 21 22 23 24 25 26 27 28

6780 2050 1800 8440 4400 6420 5260 10100 14500 2230 2650 14300 5090 1700

6770 2050 1800 8440 4400 6430 5260 10100 14500 2230 2650 14300 5090 1700

6770 2060 1790 8440 4400 17600 5260 10100 15300 2230 7720 6860 5090 1700

2050 1800 8440 4400 6420 5260 10100 14400 2220 2680 14300 5100 1720

6780 2050 1800 8440 4400 6420 5260 10100 14500 2230 2650 14300 5090 1700

6770 2040 1800 8440 4400 6430 5260 10100 14400 2230 2650 14300 5090 1700

6780 2040 1800 8440 4410 6420 5260 10100 14500 2230 2650 14300 4810 1700

6780 2040 1800 8440 4400 6420 5260 10100 14400 2230 2650 14300 5090 1700

0.15 0.49 0.56 0 0.23 0.16 0 0 0.69 0.45 1.13 0 5.5 1.18

Q100 = 1760Q100 = 6110

StreamStats Development

• Massachusetts ArcViewIMS application 2000 - 2007• First prototype ArcHydro based Dec 2002• Development/Testing throughout 2003-04• Idaho public release Oct 2004

• Porting to ArcGIS Server• Web services• NHD Navigation/Reach indexing• Drainage-area ratio for ungaged sites• Weighted estimates for ungaged basins that cross state lines

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Flood frequencies estimated by regional equations and continuous

simulation modeling in ungaged areas of the Blackberry Creek watershed, Kane County, Ill.

Actual rainfall and climatologic data

Continuous simulation of rainfall-runoff using the HSPF Blackberry

Creek watershed model

Flood quantiles

QTs

Overview approach for estimating the flood quantiles at sub-basins of the Blackberry Creek watershed

Flood frequency analysis

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PROBABILITY OF EXCEEDANCE, IN PERCENT

Simulated flow series at specified locations

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Precipitation Interception ET

Depression Infiltration

Overland flow

Land Use & Management

HSPF Sediment ModuleHSPF PEST Module

Interflow

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Blackberry Creek HSPF model

• 49 sub-basins with drainage area varying around 1 mi2 at the headwater, flows are routed through each basin

• 6 pervious land (PERLND): cropland, grassland, forested and wooded land, pervious residential, wetland, and barren and exposed land

• 3 impervious land (IMPLND): high density urban, impervious residential, and transportation

Thiessen Method for July 1996 Storm

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Yorkville

Montgomery

St. Charles (ISWS)

Aurora (NWS)

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Blackberry Watershed

Explanation# Stream Gage

! Rain Gage

24-hr rainfall = 16.91 in

24-hr rainfall = 6.59 in

Simulated July 1996 Flow (using Thiessen method) Simulated July 1996 Flow (using Thiessen method) versus Observed Hourly Flow at Yorkvilleversus Observed Hourly Flow at Yorkville

NEXRAD TotalsNWS Stage III

July 17-18, 1996

EXPLANATION48 hour Rainfall(inches)

> 7.0 - 8.5> 8.5 - 9.5> 9.5 - 10.5>10.5 - 11.5>11.5- 12.5>12.5- 13.5>13.5- 14.5>14.5- 15.5>15.5- 17.0

NEXRAD Totals Averaged to WatershedJuly 17-18, 1996

EXPLANATION48 hour Rainfall(inches)

> 7.0 - 8.5> 8.5 - 9.5> 9.5 - 10.5>10.5 - 11.5>11.5- 12.5>12.5- 13.5>13.5- 14.5>14.5- 15.5>15.5- 17.0

Simulated Flow (using NEXRAD) and Observed Hourly Flow at Yorkville

Comparison of Flow Duration CurvesComparison of Flow Duration Curves

Blackberry Creek at Yorkville1990-1999 using Thiessen approach

• Aerial video and pictures provided by Kane County and IDNRAerial video and pictures provided by Kane County and IDNR

• Flood inundation mapping done by:Flood inundation mapping done by:

-Paul Schuch of Kane County-Paul Schuch of Kane County

-Phil Gaebler of USGS-Phil Gaebler of USGS

Uses of the inundation map of the July 18, 1996, event for verifying flows in ungaged areas

Verification with 1996 inundation map generated from video imagery—after routing with HEC-RAS

Watershed Model Calibration and Verification

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OBSERVED MONTHLY PEAK FLOW IN CFS

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Line of perfect agreementand regression line

Calibration period 1990-1995

Coefficient of Model Fit Efficiency 0.816

Correlation Coefficient 0.90

Verification period 1996-1999

Coefficient of Model Fit Efficiency 0.806

Correlation Coefficient 0.94

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Observed Monthly Peak Discharge, in cfs

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Line of perfect agreement

Regression line

Actual rainfall and climatologic data

Continuous simulation of rainfall-runoff using the HSPF Blackberry

Creek watershed model

Flood quantiles

QTs

Approach for estimating the flood quantiles at sub-basins of the Blackberry Creek watershed

Flood frequency analysis

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PROBABILITY OF EXCEEDANCE, IN PERCENT

Simulated flow series at specified locations

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Five long-term precipitation records were evaluated for their representativeness of the watershed (1949-1999)

Exceedance probability in percent0.11.010.030.050.0

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10000Regional flood-frequency curveLower95% of regional estimatesUpper95% or regional estimatesArgonne recordAurora recordO'Hare recordWheaton recordElgin record

Blackberry Creek at Yorkville

Comparison of flood-frequency curves Comparison of flood-frequency curves between simulated and observed data (1961-99)between simulated and observed data (1961-99)

Exceedence probability0.11.010.030.050.070.090.099.099.9

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LegendObserved Data 61-99Lower95%Upper95%Observed Annual Peak-DataSimulated with Argonne 61-99 Data

Blackberry Creek at Yorkville

Thomas, (1986) — (~60 years flood series generated from lumped unit hydrograph model; Observed streamflow has at least 20 or more years of records)

• Simulated AMS series underpredicted Q100 by 12% but overpredicted Q2 by 13% on average. The synthetic flood-frequency curves are flatter than observed flood-frequency curves

• The model tended to underpredict flood peaks for small watersheds (1 mi2) and overpredict flood peaks for large watersheds (10 mi2)

Exceedance probability

0.11.010.030.050.070.090.0

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5132.5 km2

Exceedance probability0.11.010.030.050.070.090.0

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Exceedance probability0.11.010.030.050.070.090.0

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Exceedance probability0.11.010.030.050.070.090.0

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Estimate of QTs in Ungaged Areas

Design storms

Frequency analysis

Event model

Regionalequations

streamstats.usgs.gov

Synthetic frequency curves Continuous

simulation model

Event model