Distributed Hydrologic Modeling
description
Transcript of Distributed Hydrologic Modeling
Distributed Hydrologic Modeling
Baxter E. Vieux, Ph.D., P.E., Professor
School of Civil Engineering and Environmental Science
University of Oklahoma
202 West Boyd Street, Room CEC 334
405.325.3600
Biosketch
Dr. Baxter E. Vieux, PhD, P.E. is a professor in the School of Civil Engineering and Environmental Science, University of Oklahoma. He specializes in the integration of computational hydrologic methods and visualization with Geographic Information Systems (GIS). Applications include simulation of water quality and flooding using WSR-88D radar estimates of rainfall. He was recently named Director of the International Center for Natural Hazards and Disaster Research, University of Oklahoma. Efforts to reduce impacts on civil infrastructures due to severe weather are being undertaken by this center with an initial focus on flooding. Prior to joining the faculty at the University of Oklahoma, he was a Visiting Assistant Professor at Michigan State University. He has performed consulting and collaborative research with agencies and private enterprises in the US and abroad in Japan, France, Nicaragua, and Poland. Over fifty publications appearing as book chapters (2), refereed journal articles (14, 3 in press), and conference proceedings (35, 2 in press) have been authored including a forthcoming text for Kluwer entitled: Distributed Hydrology Using GIS (expected 2000). He has been on the Editorial Board of Transactions in GIS since 1995, serves on the American Society of Civil Engineers Council on Natural Hazards and Disasters, and is Fellow and member of the Advisory Council of the Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma. He is a member of ASCE, NSPE, AGU, and AMS, Tau Beta Pi, Phi Kappa Phi, and ASEE. Prior to his academic career, ten years were spent in Kansas and Michigan with the USDA-Natural Resources Conservation Service (formerly, USDA-SCS) supervising design and construction of drainage, irrigation, soil conservation, and flood control projects.
Recipe for a flood
Ingredients—
Take a generous amount of rainfall
Presoak the soil so it is saturated
Add generous amounts of rainfall
Stand back
What’s wrong with this picture?
Flood disasters
More disasters
What constitutes a flash flood
No firm criteria exist to discriminate between fast response and river floodsResponse time in the range of 1-6 hoursAs opposed to river floods, flash floods have a quick response to rainfall inputUpland basins are most likely killersSlow-rise river floods have highest economic impact
Flooding
Country Date Deaths PeopleAffected
EconomicCost($bn)
Mozambique Mar-00 400 2m NAVenezuela Dec-99 30,000 0.6m 15India (Orissa) Nov-99 10,000 12m 2.5China Aug-98 3,600 200m 30Bangladesh Sep-98 4,750 23m 5
--The Economist, 11March 2000
• Last year natural disasters killed an estimated 100,000 people.
• In a typical year, floods claim half the victims of the world’s natural disasters.
Enabling Technologies
Ingest, storage and processing of data streams from radar, satellite and other mesonet sensor systemsRadar, automated sensors, remote sensing platforms are next generation technologies providing new data and information for mitigating the impact of flooding and droughtImproved modeling, warning and information dissemination technologies
Why does one basin flood and another doesn’t
Efficient drainage network
Debris clogged main channel
Denuded landscape or burned vegetation
Urbanization effects on time and volume
Steep topography
Heavy rain over large areas
Basin Characteristics
Factors that affect the basin response are—
Drainage areaDrainage networkSlopeChannel geometry and roughnessOverland flow and roughnessVegetative cover Soil infiltration capacityStorage capacity
Runoff Mechanisms
There are two runoff producing mechanisms:
1. Infiltration excess
2. Saturation excess
Mountainous watersheds tend to be dominated by saturation excess.
Infiltration excess dominates runoff in flatter agricultural watersheds.
Phreatic Surface
Saturation Excess
Rain
Saturation Excess
Rain
Runoff
Infiltration Excess
R > IR < I
Infiltration
Infiltration Excess
Horton Infiltration Equation
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Time (hr)
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in/h
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Hydraulics of Runoff
Two basic flow types can be recognized:
Overland flow This is conceptualized as thin sheet flow before the runoff concentrates in recognized channels.
Channel flow The channel has hydraulic characteristics that govern flow depth and velocity.
Lumped modeling approach
The following slides show how a lumped model may be used with distributed rainfall derived from WSR-88D
There were no rain gauges in the vicinity of the basin.
Flood magnitudes were modeled for design of a bridge and roadway re-alignment for the Oklahoma Department of Transportation
Cottonwood CreekStorm Total Oct 30 - Nov 1, 1998
Cottonwood Watershed
Storm Total Contours
HEC-HMS Model
Cottonwood Basin, Alfalfa County Oklahoma 10/30/98 - 11/01/98
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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71
Time (h)
Rai
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Hydrograph
HEC-HMS 50-Year Storm
SCS CN increased from 79 to 90
Rainfall increased by 20%
Distributed Model Advantages
Distributed has advantages because the spatial variability of precipitation input and controlling parameters are represented in the model. Incorporating spatial variability in a distributed model reduces the prediction variance.Physics-based models are generally more responsive to radar input than lumped models.River basin models based on 6-hour unit hydrographs are not suitable for basins with response times less than 6 hours.Distributed models require fewer storm events for calibration than lumped
Overall Goal
The overall goal of distributed hydrology is to better represent the spatially distributed processes using maps of parameters and precipitation input.Distributed models tend to have better prediction variance than lumped models.Applications include simulation of flash floods, soil moisture, water resources.
Rainfall
Infiltration
Runon Runon
Runoff
Stream
Overland
Direction
Flow Characteristics Channel Characteristics
- Cross-Section Geometry- Slope- Hydraulic Roughness
* Rainfall excess at each cell
- Soil infiltration rate - Rainfall rate - Runon from upslope
Grid Cell Resolution Finite ElementsConnectivity
Watershed Runoff Simulation
Runoff Simulation
Digital Elevation Model Resolution
1080 meter 60 meter
Digital Watershed
OUTPUT
Discharge Hydrograph
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Time (hrs)
Dis
charg
e (
cfs
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Radar Rainfall (R)INPUT
Land surface
Soil Infiltration (I)
Hydraulic Roughness (n)
α.Iγ.Rx5/3h.
nβ1/2s
th
h
Runoff
Model Equations
Runoff Flow Rates
Depth h is measured perpendicular to the bed and the velocity, V is parallel to the landsurface.
Continuity equation—Manning Equation—
n = hydraulic roughness
So = land surface slope
c = 1 for metric, 1.49 english
hVq *3/55.0 hS
n
cq o
Blue River Basin
• The 1200 km2 Blue River basin was delineated from a 3-arc second digital elevation model
• Aggregated to grid cell size = 270 m• Hydrographs simulated for each sub-
basin • Runoff is computed for each grid cell• Routed downslope through each cell
eventually reaching the stream network and basin outlet
Lumped Versus Distributed
Lumped modeling represents the basin and precipitation characteristics using single values of roughness, slope, and rainfall over each sub-basin.
Distributed modeling represents the spatial variability within each sub-basin or basin using grid cells, TINS or other computational element.
Lumped model?
Research efforts
1. Soil moisture with feedback (SHEELS)2. Data assimilation (LDAS/AMSR)3. Real-time radar (QPESUMS)4. Nonpoint water quality simulation of phosphorus
transport5. Calibration using optimal control theory-Optimal
values are identified by comparing simulated and observed hydrographs
6. Radar/Rain gauge calibration using the river basin as validation…
Any Questions?