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

bvieux@ou.edu

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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infa

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in/h

r)

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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

nfa

ll (i

n)

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?