5/25/2017. Overview. Flood Risk Study Components HYDROLOGIC MODEL (HEC-HMS) CALIBRATION FOR FLOOD RISK STUDIES. Hydraulics. Outcome or Impacts

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1 HYDROLOGIC MODEL (HEC-HMS) CALIBRATION FOR FLOOD RISK STUDIES C. Landon Erickson, P.E.,CFM Water Resources Engineer USACE, Fort Worth District April 27 th, 2017 US Army Corps of Engineers Overview Flood Risk Study Components/Parameters Parameter Development Parameter Calibration Calibrated Model Results vs Flood Frequency Analysis Results 2 Flood Risk Study Components Hydrology How much water? Hydraulics How deep will the water get and how far will it spread? Outcome or Impacts 3 1

2 Parameters and Common Methods Losses Initial Abstraction-Constant Loss Rate Transform Snyder Unit Hydrograph Routing Modified-Puls Baseflow None or Recession Rainfall USGS (2004), NOAA Atlas 14 coming soon (2018). 4 Snyder Synthetic Unit Hydrograph (UH) Method UH methodology (L.K. Sherman 1932) Synthetic Unit-Graphs by Franklin F. Snyder (1938) Synthetic UH Parameters for Ungaged Watersheds. Watersheds studied in Appalachian Highlands Drainage areas from 10-10,000 square miles 5 Snyder Synthetic Unit Hydrograph (UH) Method Unit Hydrograph Definition The basin outflow resulting from one unit of direct runoff generated uniformly over the drainage area at a uniform rainfall rate during a specified period of rainfall duration. (Sherman) t p = Ct LL c 0.3 U p A = 640 C p t p Where tp = lag time, (hour) C p = UH peaking coefficient (Range seen from 0.4 to 0.8, USACE) L = Length of the main-stem from the outlet to the drainage divide, (miles) Lc = Length of the main-stem from the outlet to the point nearest watershed centroid, (miles) Up = Peak of standard UH, (cubic feet per second) A = Area, (square miles) Ct = Basin coefficient accounting for slope and storage (Range seen from 0.4 to 8.0, USACE) 6 2

3 Snyder Synthetic Unit Hydrograph (UH) Method Limitations and Conclusions Method estimates surface-runoff time distribution and not amount. Actual lag tends to increase with storm size. Synthetic UH departs from actual UH as basin departs from a typical fan shape. Extreme care should be used in applying UH parameters derived from ordinary storms to less frequent storms The equations and coefficients given are based mainly on fairly mountainous watersheds and may need adjustment in flatter areas. This procedure can be applied in studies of flood-control, flood-routing, and flood-forecasting. Regional analysis recommended 7 USACE Regional Study Synthetic Unit Hydrograph Parameters Nelson, T.L. Synthetic Unit Hydrographs Relationships, Trinity River Tributaries, Fort Worth-Dallas Urban Area, Seminar on Urban Hydrology, Davis, CA, Rodman, P.K. Effects of Urbanization on Various Frequency Peak Discharges, USACE Water Resources Meeting, Albuquerque, NM, Regional Study (Nelson, 1970) Study Purpose: Develop method for coming up with reasonable estimates for present and future peak discharges for flood plain management studies for ungaged areas, where funds or study time are both in short supply. Rapid development during 1960s (Pre-NFIP) National Flood Insurance Act of 1968 Large number USACE SWF Flood Studies 9 3

4 Regional Study (Nelson, 1970) 8 DFW Watersheds (8-130 sq. mi.) Urbanization estimates ranged between 0-100% USGS Special Urban Hydrology Study (circa [ ]) 10 Regional Study (Nelson, 1970) Utilized methods in EM Flood Hydrograph Analyses and Computations. Correlated lag time to measurable watershed characteristics such as longest flow length, flow length to centroid, and weighted watershed slope. Literature review indicated several studies that concluded that lag time (t p ) correlated well with LL ca S 0.5 Where t p = lag time, (hour) L = Length of the main-stem from the outlet to the drainage divide, (miles) L ca = Length of the main-stem from the outlet to the point nearest watershed centroid, (miles) S = stream slope over reach between 10% and 85% of L (feet per mile) 11 Regional Study (Nelson, 1970) Literature Review of Existing Studies Slope of line is consistent for different areas ( So. California, Louisville, Houston). Scatter in study data was explained by differences in terrain type and urbanization amounts. Lag time decreased as urbanization amount increased. Southern California Study (Linsley, USACE) Louisville, Kentucky Study Houston, Texas Study 12 4

5 Regional Study (Nelson, 1970) Final DFW area curves Percent Urban Values of Study Watersheds Houston, 70 Texas Study 13 Regional Study (Nelson, 1970) Conclusions The method accounts for differences in urban development on adjacent areas and may be used to predict the effect that urban development might have on a given area. Additional analyses will be required to improve the relationships developed, to isolate the effect that channel improvement produces, and to develop an improved method of determining the unit hydrograph peak. For the stated purpose of developing flood peaks for flood plain management studies for ungagged areas, where funds or study time are both in short supply, the present method appears to offer reasonably accurate results. 14 Regional Study (Rodman, 1977) Study Purpose: Develop a method that offers a quick, relatively consistent and reasonable procedure for estimating the effect of urbanization on the unit hydrograph for a specific watershed in a specific urban area. D-FW Clay Urbanization Curves (22 watersheds, sq. mi.) 8 watersheds from Nelson (1970) with 14 additional watersheds. D-FW Sandy Loam Urbanization Curves (4 watersheds, sq. mi.) 15 5

6 Regional Study (Rodman, 1977) Final Blackland Praire Clay Urbanization Curves 16 Regional Study (Rodman, 1977) Final Cross Timbers Sandy-Loam Urbanization Curves Regional Study(Rodman, 1977) Final DFW Urbanization Curve Comparison A complete change from rural to urban conditions would reduce the lag time by about 50%. 18 6

7 Regional Study (Rodman, 1977) Conclusions The urbanization curves offer a quick, relatively consistent and reasonable procedure for estimating the effect of urbanization on the unit hydrograph Recommended peaking coefficient of 0.72 (Cp640=460) for DFW area. The urbanization curves have been verified with observed hydrographs. Limitations This study assumed future urbanization practices will approximate those of the past. This study did not separately calibrate all the complicating factors of urbanization (Percent imperviousness, storm sewers, channelization) The data used for the Sandy-Loam Urbanization curves was very limited and could use additional verification. Only 4 watersheds (Compared to 22 for the Clay curves) ranging from 1-5 percent urban were used to develop these curves. 19 FW District Methodology in HMS Sand (%) based on Soil Permeability (inches per hour) 0 % - Less than 0.06 (Blackland Praire Clay Urbanization Curves) 33 % to % to % to 2.0 (Cross Timbers Sandy Loam Urbanization Curves) Clay (0% Sand) watersheds generally praire/grassland under natural conditions. Sandy Loam (100% Sand) generally have more trees and brush to slow down and attenuate hydrograph peak. Possible for Clay watershed with heavy brush and trees may hydrologically act as Sandy watershed. 20 FW District Methodology in HMS 21 7

8 FW District Methodology in HMS From the Component Editior 22 FW District Methodology in HMS From the Global Editior 23 River Routing Parameters Storage-Discharge Values developed in HEC-RAS (Steady Flow) Profiles computed for a range of discharges to define the relationship of storage to flow between two channel cross sections. Subreach estimate should be determined by calibration to streamflow gages. If unable to calibrate, can be estimated by computation based on flood wave travel time through reach. Subreach value can approach one for very wide floodplains with heavy attenuation. 24 8

9 Loss and Baseflow Parameters Initial Abstraction-Constant Loss From HMS Technical Reference Manual Recession Baseflow 25 Calibration Purpose Modify initial parameter estimates to improve model s ability to simulate actual/physical watershed response to observed storm events. Develop a single set of representative watershed parameters Rapid Response (Tall, narrow hydrograph) or slow response (Flat, wide hydrograph)? 26 Calibration Needs Initial Parameter Estimates NEXRAD Stage III or MPE Precipitation Data sr-wgrfc.webmaster@noaa.gov USGS Streamflow Data HEC-GridUtil (Precipitation viewing, processing, and analysis tool)

10 Calibration Process Baseflow Parameters - Match the magnitude and slope of the flow in the stream before and after the storm. Initial Loss Adjust initial loss to match beginning of runoff. Constant Loss Match the volume. Lag Time Match the time and magnitude of the peak. Peaking Coefficient Match the shape and try to keep peaking coefficient consistent among subbasins with similar slopes. Routing Subreaches Match hydrograph peak attenuation. Completed from upstream to downstream. Parameter adjustments made uniformly to all subbasins above a gage, unless there is strong evidence to adjust individual areas. Goal is to match peak, shape, timing, and volume of observed hydrograph. Keep each parameter within its reasonable, expected range. For example, do not use such a short lag time that the water would have to be traveling at > 20 ft/s to reach the outlet. Parameter calibration is compared to initial parameter estimates and calibrated parameters from other storms. 28 Calibration Process BaseflowParameters - Match flow in the stream before storm. Initial baseflow too high 29 Calibration Process Initial Loss Adjust initial loss to match beginning of runoff. Initial loss too low. Initial runoff beginning too soon Initial loss too high. Initial runoff beginning too late 30 10

11 Calibration Process Constant Loss Match the volume. Constant loss too low. Constant loss too high. 31 Calibration Process Lag Time Match the time and magnitude of the peak. Lag time too low. Peak is early and hydrograph is narrower Lag time too high. Peak is late and hydrograph is wider 32 Calibration Process Peaking Coefficient Match the shape. Peaking coefficient too low. Hydrograph is flatter than observed Peaking coefficient too high. Hydrograph is steeper than observed Peaking coefficient is usually set to the same value for all storm events 33 11

12 Calibration Process Routing Subreaches Match hydrograph peak attenuation. Routing subreach values too low. Hydrograph is flatter than observed Routing subreach values too high. Hydrograph is steeper than observed 34 Common Calibration Mistakes Calibrating only to peak discharge. Many different ways to match peak. Losses decreased to match peak, but volume and shape are off. Not comparing calibration results between different events. Parameter/Storm Initial Est Lag Time Peaking Coefficient Parameter/Storm Initial Est Lag Time Peaking Coefficient Final Parameter Selection Can use weighting based on subbasin runoff volume or peak discharge to select representative parameter for the subbasin. Avoid using or assign low weighting to calibration parameters that are very different from other events where the simulated hydrograph has a poor match to the observed hydrograph

13 Comparison with Statistical Analysis Interagency Flood Risk Management (InFRM) Hydrology Report for the San Marcos River Basin (Sept 2016) 37 Comparison with Statistical Analysis Blanco River at Wimberley, TX (355 sq. mi., length of record 91 years) Peak Discharge Frequency Curves Change of 100-yr Peak Discharge Over Time 95 % Confidence Limit Peak Discharges for 100-yr (1% annual chance) Statistical Analysis 154,000 cfs Calibrated HMS Model 152,600 cfs *Wimberley systematic record began in Comparison with Statistical Analysis San Marcos River at Luling, TX (838 sq. mi., length of record 79 years) Peak Discharge Frequency Curves Change of 100-yr Peak Discharge Over Time 95 % Confidence Limit Peak Discharges for 100-yr (1% annual chance) Statistical Analysis 143,600 cfs Calibrated HMS Model 142,400 cfs 39 13

14 Uncertainty in Flood Risk Estimates 163, , % Confidence Limit (Statistical Resutlts) Calibration Event Sensitivity 205,000 95,000 Statistical analysis results change significantly over time (+33% to -38%). Calibrated numerical modeling results are relatively stable over time (+6% to -12%). *Wimberley systematic record began in Summary The USACE Fort Worth District has developed urbanization curves which account for different terrain conditions and the affects of urbanization. These curves produce reasonably accurate and consistent flood risk estimates for a given area where funds and time are in short supply. The uncertainty in flood risk estimates has the potential of affecting people s property and lives. Model calibration is an effective way of reducing the uncertainty in our flood risk estimates.. 41 References Interagency Flood Risk Management (InFRM) Team, Hydrology Report for San Marcos River Basin, Submitted to FEMA Region VI, Sept. 15, Nelson, T.L. Synthetic Unit Hydrographs Relationships, Trinity River Tributaries, Fort Worth-Dallas Urban Area, Seminar on Urban Hydrology, Davis, CA, Rodman, P.K. Effects of Urbanization on Various Frequency Peak Discharges, USACE Water Resources Meeting, Albuquerque, NM, US Army Corps of Engineers, EM , FLOOD-HYDROGRAPH ANALYSES AND COMPUTATIONS, August 31, US Army Corps of Engineers, EM , FLOOD-RUNOFF ANALYSES, August 31, US Army Corps or Engineers, Hydrologic Engineering Center, HMS Technical Reference Manual, Davis, CA,

15 Questions? C. Landon Erickson, P.E.,CFM Water Resources Engineer U.S. Army Corps of Engineers Fort Worth District (SWF) 819 Taylor Street Fort Worth, TX (817) TEL 15