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Design Flood Estimation for Small Catchments in Southern Africa
Using The Visual SCS-SA Software
Jeff Smithers and Roland Schulze School of Bioresources Engineering and
Environmental HydrologyUniversity of KwaZulu-Natal
PietermartizburgSouth Africa
Tel: 033-2605490E-mail: [email protected]
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Introduction
Your name
Organisation
Background and expertise in design flood estimation
What you would like to learn this morning
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Flood Drought
Water in South Africa
We have either too much or too little!
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Regional Scale Floods
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Localised FloodsPietermaritzburg: 25 December 1999
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Floods in Pietermaritzburg: 1987
Floods of 1987 (Pietermaritzburg) RES2234
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FLOOD HYDROGRAPHS FOR A SMALL CATCHMENT
Time (h)Time (h)
Dis
char
ge (
mD
isch
arge
(m
33 .s.s
-1-1))
Different Peak DischargesDifferent Peak Discharges
Same VolumesSame Volumes
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FLOOD HYDROGRAPHS FOR A SMALL CATCHMENT
Time (h)Time (h)
Dis
char
ge (
mD
isch
arge
(m
33 .s.s
-1-1))
Same Peak DischargesSame Peak Discharges
Different VolumesDifferent Volumes
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FLOOD HYDROGRAPHS FOR A SMALL CATCHMENT
Time (h)Time (h)
Dis
char
ge (
mD
isch
arge
(m
33 .s.s
-1-1))
Different Peak DischargesDifferent Peak Discharges
Different VolumesDifferent Volumes
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FLOOD HYDROGRAPHS FOR A SMALL CATCHMENT
Significance of peakcapacities exceededflood damage (local)
Significance of volumefills damstransports sediments, nutrients etcflood damage (regional, inundation)
Peak = f (volume)Implication / Conclusion
need a model to simulate both stormflow volume and peak dischargeneed to be able to simulate the entire hydrograph
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What is a design flood?Magnitude of flood which has acceptable risk associated with the failure of the hydraulic structures
Risk = probability of exceedance (Pe)
Return Period: T = 1/Pe
Not an observed event
What are design floods used for?Design of hydraulic structures (e.g. waterways, culverts, bridges, dams etc)
How do we estimate design floods in South Africa?
Design Flood Estimation
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Methods of Design Flood Determination in South Africa
StandardFlood
UnitHydrograph
SCS
Rational
Design EventModel
Deterministic/ProbabilisticDesign Rainfall
FrequencyAnalysis
Continuous Simulation
Historical/Stochastic
Rainfall
Rainfall Based Methods
FloodEnvelopes
Regional
SiteFlood Frequency Analysis
EmpiricalMethods
Analysis of Streamflow Data
Design Flood Estimation Methods
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Design Rainfall Event Based Models
SCS, Rational, Unit hydrographWidely used
Lump complex, heterogeneous catchment processes into a single process
AdvantagesSimple to apply
Generally longer rainfall records at more sites, with better quality, than streamflow
Areal extrapolation of rainfall
Long flood series generally not available, often contain inconsistencies and are frequently non-homogeneous and non-stationary
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Design Rainfall Event Based Models
DisadvantagesUncertainties in inputs (e.g. storm duration, spatial & temporal distribution of design rainfall, model inputs)
Probability of rainfall taken into account, probabilistic nature of other parameters ignored
Antecedent soil moisture conditions
Assume that the exceedance frequency of the estimated flood = frequency of input rainfall
Design Rainfall Event Based Models Widely used
Need to estimate design rainfall
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WHY SCS-BASED DESIGN PROCEDURES?
There is frequent need for hydrological information recordingplanningdesign of water resourcesmanagement systems
For most small catchments the design hydrograph needs to be modelled / estimated because direct measurements are usually not availableSCS techniques were originally developed as a hydrological design tool on agricultural land uses
to generate safe limits in hydraulic designto compare effectiveness of different agricultural/conservation systems
Reasonsequations are simplerelated to physical properties of catchment (soils, land use, wetness)provides uniform answersuses daily rainfall input
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WHY SCS-BASED DESIGN PROCEDURES?
Has become an accepted / established model on small catchmentsprocedure “used internationally . . . . several million times annually” (Hawkins, 1980)recommended institutionally and accepted in court judgements
Tested / used widely in USA, Germany, France, mid-East, Australia, AfricaNow being used increasingly for other purposes through modification / adaptations, e.g.
daily water yield modelsremote sensing inputsenvironmental impact studiesurban areassemi-arid areasagricultural management systemslarge catchments
South African adaptions Regional differences in antecedent moisture conditionsJoint association of rainfall and runoff
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Assessment of Methods Available for Small Catchments
in SA (SRK, 1985)Rational method
easy to use
but, peak discharge only
grossly overestimated peaks under all conditions
Time area method (e.g. Illudas model) & Kinematic Method (e.g. Witwat model)
neither performed consistently well
nor gave improved simulations considering increased model complexity
SCS based methods (esp. SA adaptations)performed well enough on a number of land uses and catchment sizes to be recommended for design in South Africa
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Background : Summary
There is frequent need for estimates of stormflow volumes (Q) and peak discharges (qp) from small catchments for making economic and safe design of hydraulic structures
Stormflow volumes and peak discharges are highly sensitive to a catchment’s “wetness” (i.e. antecedent soil moisture status, ASM) just prior to runoff producing rainfall events
The SCS technique has become a standard method for estimating Q and qp from small catchments (<30 km2)
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HISTORY OF SCS METHODS IN SOUTHERN AFRICA
Concepts developed in USA in 1950sReich proposed its application in SA in 1962
Schulze & Arnold produced manual in 1979
Accepted / recommended by NTC, NPA, consultants
Considerable research effort at U of N, PmbCousens (1976), Arnold (1980), Schulze (1982), Hope (1983), Schulze (1984), Schmidt & Schulze (1984), Dunsmore, Schulze & Schmidt (1986), Weddepohl (1988), Topping (1993), Chetty (2001)
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HISTORY OF SCS METHODS IN SOUTHERN AFRICA
Water Research Commission / University of Natal contract 1984 – 1987
Update and revise SCS manual, integrating research findings
Research into joint association of rainfall and catchment moisture status to provide design runoff for different regions in SA
Production of manuals, technology transfer (700 sold)
Courses at 12 venues, 230 participants
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HISTORY OF SCS METHODS IN SOUTHERN AFRICA
WRC and consultants requests led to development of PC version in 1992
400 sold; prescribed text; SA & IHE courses
Visual SCS-SA (2004)Windows based, GUI
Regional scale invariance design rainfall estimation option added
Course @ SAIAE CPD 2004
Course @ SAIAE CPD 2005
Recent developments An internationalised version, based on concepts developed in SA
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The SCS Curve Number Model
SCS is the Soil Conservation Service of the USA Department of Agriculture
It works like this…Rainfall occurs
Initial abstraction includes all losses to surface depressions, interception and initial infiltration
Then some water is infiltrated while some water is runoff
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Source: http://www.fao.org/docrep/U8480E/U8480E3k.jpgSource: http://www.fao.org/docrep/U8480E/U8480E3k.jpg
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Runoff
Two componentsStormflow (surface)
Baseflow
SCS Estimates stormflow only
Empirical equation with some physical basis
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What factors influence stormflow depth ?
Rainfall DepthIntensity
Initial abstractionInterceptionSurface storageInitial infiltration
Antecedent soil water Soil properties
InfiltrabilityPermeabilityStorage capacity
Land coverTypeTreatment, practice and condition
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Rainfall Excess
SCS Curve Number ModelSCS Curve Number Model
Time
Rat
e, D
epth
per
Uni
t T
ime Constant Intensity Rainfall
Infiltrated Water
Constant Runoff
Initial Abstraction (accumulated losses before runoff commences)
EvaporationEvaporation
RunoffRunoff
Depressional Storage &
Interception
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STORMFLOW GENERATION WITH THE SCS : CONCEPTS
T
Ia
Q
P F
AccumulatedF + Ia
AccumulatedStormflow (Q)
F Sas T
S
AccumulatedRainfall (P)
TIME (T)
F = accumulated infiltration from time of stormflow commencement
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SCS Stormflow Volume
Water balance
Assume that ratio of actual infiltration (F) to maximum retention (S)
is equal to the ratio of runoff (Q) to potential maximum runoff (rainfall –
initial abstraction)
Solve Equation 1 and 2 to estimate Q
Q
P - I
F
S
a
(2 )
P – I = F + Q a (1 )T
Ia
Q
P F
AccumulatedF + Ia
AccumulatedStormflow (Q)
F Sas T
S
AccumulatedRainfall (P)
TIME (T)
F = accumulated infiltration from time of stormflow commencement
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The SCS Curve Number Model
Rainfall (P) measured or design amount
Initial abstraction (Ia) occurs from:
Surface depressions
Water intercepted by vegetation
Evaporation and infiltration
Potential maximum retention of soil (S)
S)IP(
)IP(Q
a
a
2
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The SCS Curve Number Model
ProblemP known
S & Ia unknown
Ia tends to be quite variable!
But after much experimentation:Ia = 0.2 x S in the USA
Ia = 0.1 x S in SA
So substitute it back into the runoff equation:
But what about S ?
S9.0P
)S1.0P(Q
2
S)IP(
)IP(Q
a
a
2
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The SCS Curve Number Model
How can we estimate S?
where CN is a curve number according to the land use (from 0 to 100)98 = Parking lot
39 = Grassed area on a very sandy soil
CN is an index of hydrological response
Use Table 5.1
25425400
CN
S
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SATURATION (Porosity)(0 kPa)
DRAINEDUPPER LIMIT (Field Capacity)(-5 TO -33 kPa)
LOWER LIMIT (Permanent Wilt ing Point)(-1500 kPa)
AIR DRY
"WET" SOIL
= HIGH SOILWATERCONTENT
= LOW "S"
"DRY" SOIL
= LOW SOILWATERCONTENT
= HIGH "S"
S = 25400 - 254 CN
High S = Low CN = "dry" soil moisture conditions Low S = High CN = "wet" soil moisture conditions
COLUMNOF
SOIL
CONCEPT OF "S"
2.2.1.3c
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Curve Numbers
Index of catchment response
How were CNs determined?
From measurements for given land cover a soil typePlot of flood vs rainfall for annual maximum floods
Overlay of SCS stormflow equation for various values of CN
Median CN selected
CNs for “Wet” and “Dry” conditions determined and procedures for adjusting CNs for these conditions were developed
S.P
)S.P(Q
90
10 2
25425400
CN
S
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What Role do Soils Play?
INFILTRATION /INFILTRABILITY (entry into soil)
PERMEABILITY (redistribution through soil)
STORMFLOW (overland, nearsurface)
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What Role do Soils Play?
Soil absorbsRetains water
Releases water
Soil therefore a prime regulator of catchment response to rainfall
Evaluate soils fromagriculturalist
mechanical strength viewpoint
hydrological response
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RES6511
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RES6517
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RES6519
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RES6521
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RES6523
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Soil Categorisation in the Original USA SCS Model
There are 4 basic hydrological soil groupsGroup A
Low runoff potential, high infiltration rates, sand, loamy sand and sandy loams
Group BModerate infiltration rates, loams, silt loams
Group CLow infiltration rates, sandy clays
Group DHigh runoff potential, very low infiltration rates, clay loams, clays, etc…
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Hydrological Classification of Soils in SA
Wide spectrum of properties in South African soilsFour-fold grouping too course
Intermediate soil classification
A/B, B/C, C/D to give 7 groups
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Soil Classification System in SA
Binomial System (Macvicar et al., 1977)Soil form and series
Taxonomic System (SCWG, 1991)Soil form, family and textural class
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Hydrological Classification of Soils in SA
Classification procedure: Binomial SystemEach soil placed in one of seven groups based according to the soils properties
Series graded up or down dependent onTexture
Leaching
Water Table
Crusting
Classification procedure: Taxonomic SystemSimilar procedure
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Taxonomic System (Table 5.2)LEGEND Soil Form Code Soil Family Typical SCS
A - low runoff potential Textural Grouping B - moderately low potential Class C - moderately high potential ADDO Ad 1221 Walkraal SaClLm B/C D - high runoff potential B Ad 1221 Walkraal SaCl C
Sa - sand Ad 1222 Sylvania LmSa B
Cl - clay Ad 1222 Sylvania SaLm B/C
Lm - loam Ad 1222 Sylvania SaClLm B/C
Ad 1222 Sylvania SaCl C
Ad 2111 Maurmond LmSa A/B
Soil Form Code Soil Family Typical SCS Ad 2111 Maurmond SaLm B
Textural Grouping Ad 2111 Maurmond SaClLm B
Class Ad 2111 Maurmond SaCl B/C
ADDO Ad 1111 Glenconnor LmSa A/B Ad 2112 Airedale LmSa A/B B Ad 1111 Glenconnor SaLm B Ad 2112 Airedale SaLm B
Ad 1111 Glenconnor SaClLm B Ad 2112 Airedale SaClLm B
Ad 1111 Glenconnor SaCl B/C Ad 2112 Airedale SaCl B/C
Ad 1112 Dalby LmSa A/B Ad 2121 Felsenheim LmSa B
Ad 1112 Dalby SaLm B Ad 2121 Felsenheim SaLm B/C
Ad 1112 Dalby SaClLm B Ad 2121 Felsenheim SaClLm B/C
Ad 1112 Dalby SaCl B/C Ad 2121 Felsenheim SaCl C
Ad 1121 Centlivres LmSa B Ad 2122 Longhill LmSa B
Ad 1121 Centlivres SaLm B/C Ad 2122 Longhill SaLm B/C
Ad 1121 Centlivres SaClLm B/C Ad 2122 Longhill SaClLm B/C
Ad 1121 Centlivres SaCl C Ad 2122 Longhill SaCl C
Ad 1122 Kentvale LmSa B Ad 2211 Mimosa LmSa A/B
Ad 1122 Kentvale SaLm B/C Ad 2211 Mimosa SaLm B
Ad 1122 Kentvale SaClLm B/C Ad 2211 Mimosa SaClLm B
Ad 1122 Kentvale SaCl C Ad 2211 Mimosa SaCl B/C
Ad 1211 Spekboom LmSa A/B Ad 2212 Peperboom LmSa A/B
Ad 1211 Spekboom SaLm B Ad 2212 Peperboom SaLm B
Ad 1211 Spekboom SaClLm B Ad 2212 Peperboom SaClLm B
Ad 1211 Spekboom SaCl B/C Ad 2212 Peperboom SaCl B/C
Ad 1212 Gorah LmSa A/B Ad 2221 Suttondale LmSa B
Ad 1212 Gorah SaLm B Ad 2221 Suttondale SaLm B/C
Ad 1212 Gorah SaClLm B Ad 2221 Suttondale SaClLm B/C
Ad 1212 Gorah SaCl B/C Ad 2221 Suttondale SaCl C
Ad 1221 Walkraal LmSa B Ad 2222 Tregaron LmSa B
Ad 1221 Walkraal SaLm B/C Ad 2222 Tregaron SaLm B/C
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Binomial System (Table 5.3)LEGEND Soil Form Code Soil Series Typical SCS
A - low stormflow potential Textural Grouping B - moderately low potential Class
C - moderately high potential AVALON Av 32 Middelpos Sa B D - high stormflow potential B Av 31 Mooiveld LmSa B
Sa - sand Av 25 Newcastle SaLm A/B
Cl - clay Av 17 Normandien SaCl B
Lm - loam Av 22 Rossdale Sa A/B
Av 16 Ruston SaClLm B Av 36 Soetmelk SaClLm B/C
Av 21 Uithoek LmSa A/B
Av 30 Viljoenskroon LmSa B
Av 23 Villiers SaLm B
Soil Form Code Soil Series Typical SCS Av 11 Welverdien LmSa A Textural Grouping Av 35 Windmeul SaLm B
Class Av 15 Wolweberg SaLm A
ARCADIA Ar 40 Arcadia Cl C/D BAINSVLEI Bv 23 Ashkelon SaLm A/B C/D Ar 11 Bloukrans Cl C/D A/B Bv 36 Bainsvlei SaClLm B
Ar 21 Clerkness Cl C/D Bv 12 Camelot Sa A
Ar 41 Eenzaam Cl C/D Bv 20 Chelsea LmSa A
Ar 20 Gelykvlakte Cl C/D Bv 30 Delwery LmSa A/B
Ar 10 Mngazi Cl C/D Bv 13 Dunkeld SaLm A/B
Ar 32 Nagana Cl C/D Bv 16 Elysium SaClLm A/B
Ar 12 Noukloof Cl C/D Bv 10 Hlatini LmSa A
Ar 31 Rooidraai Cl C/D Bv 34 Kareekuil SaLm B
Ar 30 Rydalvale Cl C/D Bv 31 Kingston LmSa A/B
Ar 42 Wanstead Cl C/D Bv 26 Lonetree SaClLm A/B
Ar 22 Zwaarkrygen Cl C/D Bv 25 Maanhaar SaLm A
AVALON Av 13 Ashton SaLm A/B Bv 11 Makong LmSa A B Av 26 Avalon SaClLm B Bv 27 Metz SaCl B
Av 12 Banchory Sa A Bv 22 Oosterbeek Sa A
Av 27 Bergville SaCl B/C Bv 37 Ottosdal SaCl B/C
Av 37 Bezuidenhout SaCl C Bv 24 Redhill SaLm A/B
Av 33 Bleeksand SaLm B/C Bv 32 Trekboer Sa A/B
Av 34 Heidelberg SaLm B/C Bv 15 Tygerkloof SaLm A
Av 20 Hobeni LmSa A/B Bv 33 Vermaas SaLm B
Av 14 Kanhym SaLm A/B Bv 21 Vungama LmSa A
Av 24 Leksand SaLm B Bv 35 Wedgewood SaLm A/B
Av 10 Mastaba LmSa A Bv 17 Wilgenhof SaCl B
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Sensitivity of Hydrological Response to Soil Properties
For a given catchment:Area = 2 km2
Mean slope = 8%
Hydraulic length = 1500 m
Rainfall = 50 mm
Land use: veld cover : fair, i.e. plant cover 50 -75%
Soil moisture status : initial
Clovelly Oatsdale (Cv16) : A/BStormflow depth : 1.73 mm Peak discharge : > 1 m3.s-1
Glenrosa Robmore (Gs18) : B/CStormflow depth : 9.22 mm Peak discharge : 4 m3.s-1
Estcourt Estcourt (Es36) : DStormflow depth : 19.39 mm Peak discharge : 7 m3.s-1
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Land Cover and Treatment
Land cover also makes a differenceParking lots run off more than golf courses
Hydrologic condition makes a differenceGood or poor condition
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Urban Stormflow
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Ms10
Gf13 A/B
C
A/BC/D
Example of soil units within a catchment at soil form and series level
Assignment of hydrologicalsoil groups to soil units
2.2.4.51c
DETERMINATION OF CURVE NUMBERS ON HETEROGENEOUSCATCHMENTS . . . 1
2.2.4.51c
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Sensitivity of Land Use on Hydrological Response
For a given catchment Area = 2 km2 Rainfall = 100 mmResponse time (lag) = 0.5 h Intensity Distribution Type = 3
A/B : Griffin Farmhill, Veld in good hydrological conditionCN-II = 51 Stormflow volume = 35760 m3 Peak Discharge = 6.7 m3.s-1
A/B : Griffin Farmhill, Veld in poor hydrological condition CN-II = 74 Stormflow volume = 92000 m3 Peak discharge = 19.2 m3.s-1
B : Clovelly Clydebank, Veld in good hydrological condition CN-II = 61 Stormflow volume = 57000m3 Peak discharge = 11.4 m3.s-1
B : Clovelly Clydebank, Veld in poor hydrological conditionCN-II = 79Stormflow volume = 108200 m3 Peak discharge = 22.8 m3.s-1
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Adjustment of Initial Curve Numbers: Original Procedure
Stormflow is highly sensitive to a catchment's "wetness" (i.e. soil moisture status, SMS) just prior to the rainfall event
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Adjustment of Initial Curve Numbers: Original Procedure
Stormflow is highly sensitive to a catchment's "wetness" (i.e. soil moisture status, SMS) just prior to the rainfall event "Classical" categorisation of SMS
This is an oversimplification ….ET considered only in gross termsDrainage ignoredDiscrete “jumps” in SMS vs CNAMC – 5 days?
SMS by water budgeting needed
SMS class Accumulated 5-day
Antecedent Rainfall
Dormant Season Growing Season
SMS-I (CN-I) < 12 mm < 36mm
SMS-II (CN-II) 12-28 mm 36-53 mm
SMS-III (CN-III) >28mm >5 3mm
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Adjustment of Initial Curve Numbers: Hawkins Procedure
ΔS = P – E –Q – D
Adjustment of CN-II therefore requiresCN-II
consideration of soil depth, soil texture, vegetation cover
regional climatic conditions
C N(1+ c)1000
(1+ c)1000
C N II
P E Q D
25.4
f
S25400
C N25f
f
4
Q(P - c S )
P + (1 - c)Sf
f2
f
C N
(1+ c)1000(1+ c)1000
C N II
S
25.4
f
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Adjustment of Curve Numbers to Account for Antecedent Soil
Moisture Conditions in SCS-SA
Median Condition Method
Joint Association Method
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Method 1: Median ConditionBasic Premise
Final CN (CNf)needs to be determined from soil moisture budgeting considerations
Compute the soil moisture status expected (statistically) to occur most frequently at a location prior to a design event (50th percentile, median)
Use this SMS information in CNf calculations to determine design Q
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Method 1: Median ConditionProcedure
For a combination of input of location (one of 712 hydrologically homogeneous zones in SA)
CN-II
soil depth category (one of 3)
soil texture category (one of 3)
vegetation category (one of 3)
Compute a change in soil moisture storage (ΔS)by the ACRU model
from an initial soil moisture storage
for a 30-day antecedent period
for the 5 highest rainfall events of a year
for each year on record
The median condition of ΔS is computed
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Method 1: Median ConditionComputations
Use median ΔS to compute a final Curve Number, CNf
Use CNf to compute find potential maximum retention, Sf
Use Sf with design rainfall to compute final design stormflow
C N1100
1100
C N II
S
25.4
f
S25400
C N25f
f
4
Q(P - 0.1S )
(P + 0.9Sff
2
f
)
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Method 2: Joint Association Method
Basic PremiseAssumption that T-year return period rainfall produces T-year return period stormflow is invalid
2nd, 3rd, 4th or 5th ranked daily rainfall may produce highest annual Q, depending on antecedent SMS
Conclusion : "Assumption inherent in current flood design methods of simulating the T-year return period flood from the T-year return period rainfall does not provide the engineer with a sound basis for analysis in small catchments" (Dunsmore, Schulze, Schmidt, 1986)
Compute the highest daily Q per year, with a model, and use the series of simulated Q to determine design Q
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Method 2: Joint Association Method
Procedures & ComputationsFor a combination of input of
location (one of 712 homogeneous zones in SA)CN-IIsoil depth category (one of 3)soil texture category (one of 3)vegetation category (one of 3)
Compute a change in soil moisture storage (ΔS)by the ACRU modelfrom an initial soil moisture storagefor a 30-day antecedent periodfor the 5 highest rainfall events of a yearfor each year on record
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Method 2: Joint Association Method
Procedures & Computations
For CN-II’s of 50, 60, 70, 80 and 90Use ΔS to compute CNf for each of 27 land use/soil combinations
Calculate Qf for all combinations
Frequency analysis of Qf
50, 80, 90 and 95 perentiles
2, 5, 10 and 20 year return periods
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Estimation of Daily Design Rainfallin South Africa
Option 1Search database containing Adamson’s (1981) TR102 report which accesses a 2200+ rainfall station information base for southern Africa
5 closest stations reported
Use select most appropriate
station
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Estimation of Daily Design Rainfallin South Africa
Option 2Design rainfalls up to 20 year return periods computed for the representative station chosen for each of 712 zones
Zone number determined from user input latitude and longitude
Option 3User input design rainfall depths
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Estimation of Daily Design Rainfall in South Africa
Option 4 (recommended)Design rainfall estimated using a regional, scale invariance approach (Smithers and Schulze, 2003)
Methodology to estimate design rainfall at 1’ x 1’ lattitude/longitude grid in South Africa
durations 5 minutes to 7 days
2 to 200 year return periods
WRC reports
Visual SCS-SA: 1 day design rainfall
http://www.beeh.unp.ac.za/HydroRisk/
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What Factors Affect Peak Discharge?
Time (h)Time (h)
Dis
char
ge (
mD
isch
arge
(m
33 .s.s
-1-1))
Different Peak DischargesDifferent Peak Discharges
Different VolumesDifferent Volumes
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Estimation of Peak Discharge Using SCS Procedures
Unit HydrographsThe T-hour Unit Hydrograph (TUH) is defined as the surface runoff hydrograph resulting from a unit depth of effective rain falling uniformly in T hours over a catchment
Characteristic response from a catchment
Response is invariable
qp = f (Q)
SCS ProceduresBased on dimensionless Unit Hydrograph developed from large number of natural UHs
Shape of UH idealised to be triangular
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SCS Triangular UH
3
8
TTbb
TTpp TTrr
qqpp
5
8
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Time Distributions Of Design Rainfall Intensity
The timing and magnitude of peak discharge in relation to rainfall intensity
Small catchmentsshort catchment response timeshort design storm duration critical (Why?)high intensity storms are critical
Large catchmentslong catchment response timelong design storm duration critical (Why?)lower intensity storms
Regional design rainfall intensityf (regional rainfall producing mechanisms)f (regional synoptic conditions) result in synthetic time distribution curves
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Synthetic Time Distributions Of Rainfall Intensity In SA
One - day rainfall is distributed over timeDistribution assumed symmetrical over time
Element of conservatism built into procedures
Distribution based on PD : P24 h ratios
Four general types of time distribution curves identified for SA
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Synthetic Temporal Storm Distributions for South Africa
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 4 8 12 16 20 24
Time (h)
Ra
tio
of
P(D
) / P
(1
-da
y)
Type 1 Type 2 Type 3 Type 4
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Regionalisation of Temporal Distribution of Rainfall in SA
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Synthetic Time Distributions Of Rainfall Intensity
Using SCS outside South AfricaDetermine dominant design rainfall producing storms
Convective? : Type 3
General rains / frontal /
longer duration? : Type 2
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Synthetic Time Distributions Of Rainfall Intensity In SA
Semi-stochastic rainfall disaggregation developed by Knoesen and Smithers (2005) not incorporated yet
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Elapsed Time (hrs)
Fra
ctio
n o
f D
ail
y R
ain
fall
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.1 .2 .3 .4 .5 .6 .7 .8 .9 1. 2. 3. 4. 5. 6. 7. 8. 9..5
1
2
3
45
10
20
304050
7090
Flow Velocity ( m.s-1)
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Visual SCS-SA
Visual SCS-SA IS A computerised version of the 1988 SCS documentation for southern Africa
designed specifically for southern Africa,
but applicable (with limitations) universally
essentially a user manual
a "small" catchments design hydrograph technique
areas < 30km2
no ARF applied
where specific characteristics ofprecipitation
land use
soils
physiography
dominate the hydrograph size and shape
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Visual SCS-SA
Visual SCS-SA IS NOTA comprehensive flood estimation package for
multiple hydrographs
flow routing
An estimator of the PMF
A comprehensive theory document on the SCS techniques
A "large" catchments design hydrograph technique
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Hands On Exercises