1. Hydrology of Fast Response Basins Baxter E. Vieux, Ph.D., P.E. School of Civil Engineering and Environmental Science University of Oklahoma 202 West Boyd Street, Room CEC334 Norman, OK 73019 bvieux@ou.edu

2. Biosketch Dr. Baxter E. Vieux, PhD, PE specializes in the integration of computational methods and visualization with Geographic Information Systems (GIS). Applications include simulation of water quality and flooding. 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.

3. Recipe for a flood Ingredients Take a generous amount of rainfall Presoak the soil so it is saturated Add the rainfall to steeply sloping land Look out!

4. Flood Statistics Flooding is the most deadly and costly of all natural disasters. Read the document Summary of Natural Hazard Statistics.Summary of Natural Hazard Statistics. From this document what would you conclude to be the single most important factor that might cause death during a flood?

5. What constitutes a flash flood No firm criteria exist to discriminate between fast response and river floods Response time in the range of 1-6 hours As opposed to river floods, flash floods have a quick response to rainfall input Upland basins are most likely killers Read the document flash floods.flash floods.

6. Flooding --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.

7. Enabling Technologies Ingest, storage and processing of data streams from radar, satellite and other mesonet sensor systems Radar, Mesonets, remote sensing platforms are next generation technologies providing new data and information for mitigating the impact of flooding and drought Improved modeling, warning and information dissemination technologies

8. WSR-88D or NEXRAD Weather Surveillance Radar-1988 Doppler Prototyped in Norman at NSSL Scans Every 5 or 6 minutes during precipitation 150+ installed in US and abroad 0.5° 1.5° 2.5°

9. Why does one basin flood and another doesn’t Efficient drainage network Debris clogged main channel Denuded or burned vegetation Urbanization effects on time and volume Steep topography Heavy rain over large areas Read the document Flash Flood Factors.Flash Flood Factors.

10. Basin Characteristics Factors that affect the basin response are— Drainage area Drainage network Slope Channel geometry and roughness Overland flow and roughness Vegetative cover Soil infiltration capacity Storage capacity

11. Hydraulics Hydraulics of overland and channel flow Turbulent flow Chezy or Manning Conservation of momentum and mass Discharge computations using conservation equations is the basis for distributed hydrologic modeling.

12. 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.

13. 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.

14. Saturation Excess

15. Infiltration Excess

16. Horton Infiltration Equation

17. Probabilistic Concepts Key concepts-- Intense rainfall happens infrequently The return period is inversely proportional to the frequency of being equaled or exceeded. Intensity-Duration-Area-Frequency

18. Regional Frequency Analysis Using regression analysis applied to stream gauge records, we can estimate the discharge associated with a particular frequency. Most states have developed regression equations for ungauged basins. For example in Oklahoma given the drainage area, A, in sq.mi. and the 2-year 24-hour storm depth, I, in inches we can calculate:

19. USGS Regression Equations for Oklahoma For Cherokee County, the 2-year 24-hour rainfall is 3.5 inches. Calculate the following for the Cottonwood Basin: A= 49 sq mi I = 3.5 inches

20. 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.

21. Cottonwood Creek Storm Total Oct 30 - Nov 1, 1998

22. Cottonwood Watershed

23. Storm Total Contours

24. HEC-HMS Model

26. Hydrograph

27. HEC-HMS 50-Year Storm

28. SCS CN increased from 79 to 90

29. Rainfall increased by 20%

30. Rainfall Infiltration 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 Elements Connectivity Watershed Runoff Simulation Runoff Simulation

31. OUTPUT Radar Rainfall (R) INPUT Land surface Soil Infiltration (I) Hydraulic Roughness (n) h Runoff Model Equations

32. 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=landsurface slope c=1 for metric, 1.49 english

33. 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

36. Sensitivity to Initial Conditions

37. Distribute 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.

38. Self Examination Label the following with a + or – according to the effect on flood levels at a given location— Debris clogged main channel Denuded or burned vegetation Urbanized landsurface conditions and channels Steep terrain Clayey soil Dry intial moisture conditions

39. --Ganges River Distributary, Bangladesh Questions...