StreamStats Web Application streamstats.usgs.gov

Slides:



Advertisements
Similar presentations
Questions concerning the Halloween Flood in Onion Creek Presentation by David R. Maidment Center for Research in Water Resources University of Texas at.
Advertisements

Methodology for Evaluating Hydrologic Model Parameters in an Urban Setting: Case Study Using Transferred HSPF Parameters in Midlothian and Tinley Creek.
CHARACTERISTICS OF RUNOFF
Hydrological Modeling for Upper Chao Phraya Basin Using HEC-HMS UNDP/ADAPT Asia-Pacific First Regional Training Workshop Assessing Costs and Benefits of.
Hydrologic Simulation Models
Overview of Urban Drainage Flood Prediction Methods and Approaches J.Y. Chen1 and B.J. Adams2 1. Water Survey Division, Environment Canada 2. Department.
Continuous Hydrologic Simulation of Johnson Creek Basin and Assuming Watershed Stationarity Rick Shimota, P.E. Hans Hadley, P.E., P.G. The Oregon Water.
Hydrologic Theory One of the principal objectives in hydrology is to transform rainfall that has fallen over a watershed area into flows to be expected.
Surface Water Hydrology Summarized in one equation V = velocity, fps or m/s A = channel cross-sectional area, sf or m 2.
Upper Brushy Creek Flood Study – Flood mapping and management Rainfall depths were derived using USGS SIR , Atlas of Depth Duration Frequency.
Approximate Floodplain Mapping - Procedures and Approaches to Data Challenges Troy Thielen, CFM Brett Addams, CFM May 18, 2010.
53rd ANNUAL MEETING OF THE ARIZONA-NEVADA ACADEMY OF SCIENCE UNIVERSITY OF ARIZONA TUCSON, AZ APRIL 4, rd ANNUAL MEETING OF THE ARIZONA-NEVADA ACADEMY.
Start Audio Lecture! FOR462: Watershed Science & Management 1 Streamflow Analysis Module 8.7.
Lecture ERS 482/682 (Fall 2002) Flood (and drought) prediction ERS 482/682 Small Watershed Hydrology.
Evaluating river cross section for SPRINT: Guadalupe and San Antonio River Basins Alfredo Hijar Flood Forecasting.
Texas A&M University Department of Civil Engineering Cven689 – CE Applications of GIS Instructor: Dr. Francisco Olivera Logan Burton April 29, 2003 Application.
CE 3372 – Lecture 10. Outline  Hydrology Review  Rational Method  Regression Equations  Hydrographs.
SPARROW Water- Quality Modeling: Application of the National Hydrography Dataset What is SPARROW? Use of NHD SPARROW results By Craig Johnston and Richard.
Analyses of Rainfall Hydrology and Water Resources RG744
WaterSmart, Reston, VA, August 1-2, 2011 Steve Markstrom and Lauren Hay National Research Program Denver, CO Jacob LaFontaine GA Water.
Interface data models Model 1 Model 2 Model 3 GIS Geo Database Arc Hydro data model Geographically Integrated Hydrologic Modeling Systems.
KINEROS (KINematic runoff and EROSion model) Michael Schaffner Senior Service Hydrologist NOAA National Weather Service WFO Binghamton, NY Eastern Region.
El Vado Dam Hydrologic Evaluation Joseph Wright, P.E. Bureau of Reclamation Technical Services Center Flood Hydrology and Meteorology Group.
TR-55 Urban Hydrology for Small Watersheds
U.S. Department of the Interior U.S. Geological Survey Alabama Water Science Center StreamStats: By Kernell Ries and J.
1 Flood Hazard Analysis Session 1 Dr. Heiko Apel Risk Analysis Flood Hazard Assessment.
Copyright [insert date set by system] by [CH2M HILL entity] Company Confidential Hydrologic Evaluation of the Little Thompson River Phase 2: Little Thompson.
WinTR-20 SensitivityMarch WinTR-20 Sensitivity to Input Parameters.
New Variables, Gage Data, and WREG REGIONAL ANALYSIS IN THE LEVISA FORK AND TUG FORK BASINS.
August 20th, CONTENT 1. Introduction 2. Data and Characteristics 3. Flood analysis 1. MOUSE 2. SOBEK 3. ARC-SWAT 4. Conclusions and suggestions.
U.S. Department of the Interior U.S. Geological Survey Office of Surface Water Reston, VA StreamStats: By Kernell Ries A Web.
ODOT 2015 Geo-Environmental Conference
ArcHydro – Two Components Hydrologic  Data Model  Toolset Credit – David R. Maidment University of Texas at Austin.
U.S. Department of the Interior U.S. Geological Survey StreamStats: A Web-Based Tool for Estimating Streamflow Statistics by Alan Rea Idaho Water Science.
StreamStats: A Web- Based Tool for Estimating Streamflow Statistics by Alan Rea and Pete Steeves.
By Pete Steeves Alabama StreamStats Presented at the Alabama Water Resources Conference Perdido Beach Resort, Orange Beach, Alabama September 8, 2011 U.S.
FREQUENCY ANALYSIS.
Presented by George Doubleday 1. What is The Woodlands Purpose of this Research Build and Calibrate Vflo TM model for The Woodlands Compare storms with.
U.S. Department of the Interior U.S. Geological Survey Implementation of the U.S. Geological Survey’s StreamStats Program in Kansas— A Web Application.
Copyright © 2005 ESRI. All rights reserved. H&H Using ArcGIS Introduction to NSS.
Streamflow Statistics on the Web: A Prototype for a National Rivers Information Center By Kernell Ries USGS, Office of Surface Water Reston, VA.
Assessment of Economic Benefits of the North Carolina Floodplain Mapping Program Hydrologic and Hydraulic Case Studies Adapted from a Presentation to NRC.
U.S. Department of the Interior U.S. Geological Survey Estimating water availability at ungaged locations in New England Source:
Vision for the National Geospatial Framework for Surface Water Robert M. Hirsch Associate Director for Water U.S. Department of the Interior U.S. Geological.
Review of SWRCB Water Availability Analysis Emphasis on Dry Creek Water Availability Analysis.
WinTR-20 SensitivityFebruary WinTR-20 Sensitivity to Input Parameters.
Development of a Geographic Framework for an Integrated Flood Modeling System Oscar Robayo Tim Whiteaker August 10, 2004 University of Texas at Austin.
Description of WMS Watershed Modeling System. What Model Does Integrates GIS and hydrologic models Uses digital terrain data to define watershed and sub.
1 Integrating Water Resources Engineering and Geographic Information Systems (GIS) National Weather Service NWSRFS International Workshop October 21-23,
Model Calibration in MarylandJune Model Calibration in Maryland June 12, 2015.
Long Valley Creek: A Rainfall-Runoff Modeling Story Rob Thompson Hydrologist U.S. Army Corps of Engineers Sacramento District
Introduction to GIS in Water Resources David R. Maidment Director, Center for Research in Water Resources University of Texas at Austin CRWR.
Basic Hydrology & Hydraulics: DES 601 Module 6 Regional Analysis.
U.S. Department of the Interior U.S. Geological Survey Montana StreamStats An overview of Montana StreamStats and methods for obtaining streamflow characteristics.
U.S. Department of the Interior U.S. Geological Survey StreamStats Data Preparation Workshop October 21-22, Nashville Tennessee Pete Steeves, USGS MA-RI.
Introduction to Urban Hydrology
By Pete Steeves Rainy River and Lake of the Woods (RRLOW) StreamStats Demonstration for the International Joint Commission October 2, 2014 U.S. Geological.
Surface Water Applied Hydrology. Surface Water Source of Streamflow Streamflow Characteristics Travel Time and Stream Networks.
MRC-MDBC STRATEGIC LIAISON PROGRAM BASIN DEVELOPMENT PLANNING TRAINING MODULE 3 SCENARIO-BASED PLANNING for the MEKONG BASIN Napakuang, Lao PDR 8-11 December.
WATERWAYS AND BRIDGES IN TEXAS “Final” Presentation by: Brandon Klenzendorf CE 394K Dr. Maidment.
Sanitary Engineering Lecture 4
Rainfall-Runoff modeling
Integrating ArcHydro and HEC Models by David R
Rainfall-Runoff Modeling
Hydrologic Simulation Models
Hazards Planning and Risk Management Flood Frequency Analysis
Calculating Hydrologic Parameters for Estimating Surface Water Flow at Ungaged Locations Richard Hoffpauir Water Resources Engineering.
Flood Monitoring Tools 2011 OFMA Annual Conference
Hydrology.
INTRODUCTION TO HYDROLOGY
Presentation transcript:

StreamStats Web Application streamstats.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 curve Ungaged sites: Regression equations relating the characteristics of the curve to basin characteristics. Q100 = a(TDA)b(MCS)c(PermAvg)d(Rf)

Streamflow gaging stations are not distributed evenly. The density impacts the quality of regional analyses. Selected discharge gages with more than 25 years of record for analysis.

Percentage changes in the 100-year peak flow estimate between 1987 and 2004 Max. = 35 Avg. = 6 Max. = 50 Avg. = 27 Max. = 29 Avg. = 4 Max. = 81 Avg. = 9 Max. = 24 Avg. = 7 Max. = 95 Avg. = 15 Max. = - 2 Avg. = - 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 Interface ArcIMS Streamflow Statistics Database NSS Calculation Program GIS Database ArcHydro At a streamgage 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

Variation in Slope with Drainage Area

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 Additional states for FY07 MN, MS, NJ, NY, RI, UT CA – basin delineation and possibly basin characteristics in southern CA

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

Arithmetic Scale Log-Log Scale Scatter plots of preliminary Q100 estimates using BasinSoft and manual drainage basin delineation with StreamStats All regions, n = 164

Distribution of differences by Region 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 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 for Region 1: Q2, Q5, Q10 percent differences. 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

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 6120 2820 1180 583 2040 1760 2510 4940 11800 574 1980 1110 2490 319 1190 573 2830 580 6110 1150 4950 1170 2.94 0.89   0.4 0.2 0.71 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 6430 2060 1790 17600 15300 7720 6860 14400 2220 2680 5100 1720 2040 4410 4810 0.15 0.49 0.56 0.23 0.16 0.69 0.45 1.13 5.5 1.18 Average absolute maximum deviation from the mode = 1.31 percent

Q100 = 1760 Q100 = 6110

StreamStats Development Past 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 Present

N

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 Overview approach for estimating the flood quantiles at sub-basins of the Blackberry Creek watershed Flood frequency analysis 100 10000 1000 DISCHARGE, IN CUBIC FEET PER SECOND 0.01 0.10 1.00 10.00 30.00 50.00 70.00 99.00 99.90 99.99 90.00 PROBABILITY OF EXCEEDANCE, IN PERCENT Actual rainfall and climatologic data Flood quantiles QTs Continuous simulation of rainfall-runoff using the HSPF Blackberry Creek watershed model Simulated flow series at specified locations Plot Title 50 100 150 200 250 300 350 20 40 60 80 120 140

To channels Precipitation Interception ET Depression Infiltration Overland flow Land Use & Management HSPF Sediment Module HSPF PEST Module Interflow To channels

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 24-hr rainfall = 6.59 in ! # THIESSEN Yorkville Montgomery St. Charles (ISWS) Aurora (NWS) 2.4 Miles ¯ 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) versus Observed Hourly Flow at Yorkville

NEXRAD Totals NWS Stage III July 17-18, 1996 EXPLANATION 48 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 Watershed July 17-18, 1996 EXPLANATION 48 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 Curves Blackberry Creek at Yorkville 1990-1999 using Thiessen approach

Uses of the inundation map of the July 18, 1996, event for verifying flows in ungaged areas Aerial video and pictures provided by Kane County and IDNR Flood inundation mapping done by: -Paul Schuch of Kane County -Phil Gaebler of USGS

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

Watershed Model Calibration and Verification 500 1000 1500 OBSERVED MONTHLY PEAK FLOW IN CFS SIMULATED MONTHLY PEAK FLOW IN CFS y = 1.00 x R 2 = 0.80 Line of perfect agreement and 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

Actual rainfall and climatologic data Approach for estimating the flood quantiles at sub-basins of the Blackberry Creek watershed Flood frequency analysis 100 10000 1000 DISCHARGE, IN CUBIC FEET PER SECOND 0.01 0.10 1.00 10.00 30.00 50.00 70.00 99.00 99.90 99.99 90.00 PROBABILITY OF EXCEEDANCE, IN PERCENT Actual rainfall and climatologic data Flood quantiles QTs Continuous simulation of rainfall-runoff using the HSPF Blackberry Creek watershed model Simulated flow series at specified locations Plot Title 50 100 150 200 250 300 350 20 40 60 80 120 140

Five long-term precipitation records were evaluated for their representativeness of the watershed (1949-1999) Exceedance probability in percent 0.1 1.0 10.0 30.0 50.0 Discharge in cfs 1000 10000 Regional flood-frequency curve Lower95% of regional estimates Upper95% or regional estimates Argonne record Aurora record O'Hare record Wheaton record Elgin record Blackberry Creek at Yorkville

Comparison of flood-frequency curves between simulated and observed data (1961-99) Exceedence probability 0.1 1.0 10.0 30.0 50.0 70.0 90.0 99.0 99.9 Discharge, cfs 10 100 1000 10000 Legend Observed Data 61-99 Lower95% Upper95% Observed Annual Peak-Data Simulated 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 0.1 1.0 10.0 30.0 50.0 70.0 90.0 Discharge, cfs 100 1000 214 12.5 km2 Exceedance probability 0.1 1.0 10.0 30.0 50.0 70.0 90.0 Discharge, cfs 100 1000 10000 280 177.7 km2 Exceedance probability 0.1 1.0 10.0 30.0 50.0 70.0 90.0 Discharge, cfs 100 1000 10000 51 32.5 km2 Exceedance probability 0.1 1.0 10.0 30.0 50.0 70.0 90.0 Discharge, cfs 10 100 1000 208 2.6 km2

Estimate of QTs in Ungaged Areas Design storms Event model Event model Synthetic frequency curves Frequency analysis Continuous simulation model Regional equations streamstats.usgs.gov