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THE INFLUENCE OF STORM CHARACTERISTICS ON RUNOFF GENERATION AND CONNECTIVITY IN SEMI-ARID AREAS S Reaney (1) , L J Bracken (née Bull) (2) and M J Kirkby (1) (1) , School of Geography, University of Leeds, Leeds, LS2 9JT, UK, (2) Department of Geography, University of Durham, Durham, DH1 3LE Email: [email protected] Fax: 44 113 233 3308 Web: www.geog.leeds.ac.uk/people/s.reaney/ The Connectivity of Runoff Model (CRUM) The model developed to investigate the controls on runoff generation and flow dynamics in semi-arid en---vironments is the Connectivity of Runoff Model (CRUM). The model is divided into vertical and horizon- tal components and distributed on a grid structure. The vertical component represents interception, surface detention storage, surface depression storage, soil moisture storage and recharge, (Figure 1). The horizontal interactions occur only as overland flow because lateral flow through the soil is negligible in semi-arid environments. The flow routing between the grid cells uses the FD8 algorithm (Quinn et al.1991) which uses multiple flow directions and hence allows both the dispersion and concentration of flow. The flow velocity is determined by the Darcy-Weisbach equation. Pre-defined Storms A set of pre-defined storm hydrographs have been developed to investigate the influence of the temporal structure of the rainfall on the generation and transmission of runoff. The storms all deliver 80 mm of rainfall over a two hour period (Figure 3). The storm characteris- tics and the runoff coefficients are shown in Table 1. pulse length 0 5 10 15 20 25 0.0 0.1 0.2 0.3 0.4 0.5 0.6 maximum rainfall intensity (mm hr -1 ) 0 100 200 300 400 500 0.0 0.1 0.2 0.3 0.4 0.5 0.6 total rainfall (mm) 0 5 10 15 20 25 30 35 0.0 0.1 0.2 0.3 0.4 0.5 0.6 COV 0.0 0.5 1.0 1.5 2.0 2.5 3.0 runoff coefficient runoff coefficient runoff coefficient runoff coefficient 0.0 0.1 0.2 0.3 0.4 0.5 0.6 total rainfall (mm) 0 5 10 15 20 25 30 35 Q peak Q peak 0 2 4 6 8 maximum rainfall intensity (mm hr -1 ) 0 100 200 300 400 500 0 2 4 6 8 Figure 5 Discharge characteristics with varable rainfall The total rainfall depth shows a positive relationship with both the peak discharge and the runoff coefficient. This is related to the decrease in the infiltration rate with increasing total rainfall. However, there is a large amount of scatter in the plots with the same rainfall depths producing vastly different amounts of flow from the slope. This range of results relates to both the distrib- ution of rainfall intensities and the temporal structure of the storm. The maximum rainfall intensity results show threshold behaviour related to the intensity required to exceed in the soil infiltration capacity. However, the infiltration capacity was 55 mm hr -1 where- as the threshold is located at 84 mm hr -1 . This difference relates to the amount of excess water required to fill the surface depression store and allow the connection between the runoff gener- ation point and the slope outflow. As the storm length increases, the range of runoff coefficients increases. The rate of increase in the maximum runoff coefficient rises above a pulse length of five minutes and levels off after 13 minutes. The increase at five minutes relates to the time required to fill the surface depression store and for the runoff to reach of the outflow. The levelling off of the range of runoff coefficients at 13 minutes relates to the total travel times across the surface. The COV does not show a consistent relationship with the runoff coefficient. There are large variations in the runoff coefficient for a certain COV value. This therefore suggests that the tem- poral structure, as well as the variability, plays a significant role in the generation of runoff. Introduction The generation of high magnitude flood events at the catchment scale in semi- arid areas are caused by a combination of precipitation characteristics including amount, intensity, duration and spatial distribution (Wolman and Gerson 1978; Costa 1987). At the small scale many investigations have focused on the influ- ence of plot scale properties such as vegetation (Cerda, 1995; Bergkamp et al, 1996; Imeson et al, 1992), soils and slopes (Parsons et al 1997; Martinez-Mena et al 1998). However, there have been a limited number of investigations into how the characteristics of the rainfall input into semi-arid systems influences the gen- eration and transmission of runoff. The study uses the Connectivity of Runoff Model (CRUM) to investigate how the characteristics of rainfall input to semi-arid areas influence the runoff produced at the base of a hillslope. A simple theoretical hillslope, characteristic of a semi-arid regions, has been subjected to a range of storm events. The storm events have been generated in two ways. The first set uses pre-defined storm hydrographs and the second set uses stochastically generated storms. The stochastic rainfall generator has been used to generate two sets of storms. The first set consists of a fixed duration and depth with variable per minute intensities and the second set of storm has variable storms depths and durations. Rg Recharge Canopy Soil Store Runon Infiltration Runoff Detention Store Depression Storage Rd Rt Rn Figure 1 Vertical model structure TABLE 1 Storm Charts and runoff coefficiences STORM MAX INTENSITY (mm hr -1 ) MEAN INTENSITY (mm hr -1 ) COV RUNOFF COEFFICIENT a 40.0 40.0 0.00 25.3% b 109.1 40.0 1.23 57.9% c 109.1 40.0 1.23 56.9% d 109.1 40.0 1.23 55.8% e 80.0 40.0 0.58 37.1% f 80.0 40.0 0.58 35.2% g 83.2 40.0 0.60 26.2% h 170.3 40.0 0.95 26.9% similar runoff coefficients. These values are only slightly greater than from storm a with constant rainfall. This suggests that the runoff which was generated during the high intensity rainfall is rapidly infiltrated during subsequent low rainfall intensity periods. This shows the importance of the temporal fragmentation of the high intensity rainfall during the storm event. Stochastically Generated Storms The stochastic rainfall was generated using a Monte Carlo model to select random rainfall intensities. The Monte Carlo models uses a distribution function fitted to the intense rainfall sections of a measured time series, equation 1. Where rf i is the rainfall intensity (mm hr-1), is the mean per minute rainfall intensity, a is a coefficient and prob is the probability of that rainfall intensity. For a measured rainfall record from SE Spain, a = 1.74 (R2 = 0.98). rf i =–ln(1–prob).60 1 a Results 2 To investigate which properties of the rainfall time series control the amount of discharge that leaves the slope, the test hillslope was subject- ed to 1000 storm realisations of varying intensity and duration. These storm pulses varied from 1 to 20 minutes and from 40 mm hr -1 to 90 mm hr -1 , Figure 5. Results 1 The impact of variable rainfall on the discharge is shown in the box plots, Figure 4. These plots compare the difference between the runoff leaving the slope from a rainfall pulse of 75 mm hr -1 for five minutes deliv- ered at constant and variable intensity. The variable rainfall increases the median discharge. The maximum discharge volume simulated was 3.65 m 3 ; this is 480 % greater than with constant rainfall. However, 25.9 % of the simulations produced a discharge volume less than the constant rainfall, with the minimum dis- charge of 0.13 m 3 . The median peak discharge is very similar between the constant and variable rainfall. There is a greater spread of values with the variable rainfall, to a maximum of 1.38 m 3 min -1 . Constant Variable peak discharge (m min ) 0 1 2 3 4 5 Constant Variable 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 3 -1 total discharge (m ) 3 Figure 4 Box plots of discharge with constant and varable rainfall Acknowledgments This work was funded by a School of Geography, University of Leeds studentship and financial support from the EU PESERA project. References Bergkamp, G., Cammeraat, L.H., and Mertinez-Fernandez, J. 1996. 'Water movement and vegetation patterns on shrubland and an abandoned field in two desertification threatened areas in Spain', Earth Surface Processes and Landforms, 21, 1073-1090. Cerda, A. 1995. 'Spatial distribution of infiltration on the matorral slopes in a Mediterranean environment, Genoves, Spain', in Fantechi, R., Peter, D., Blabanis, P. and Rubio, J.L. (Eds), Desertification in a European Context: Physical and Socio-economic Impacts, European Commission, Brussels, 427-436. Costa, J.E. 1987. A comparison of the largest rainfall - runoff foods in the Unites States and the People's Republic of China and the world. Journal of Hydrology, 96, 101-115. Imeson, A.C. Verstraten, J.M., van Mulligen, E.J., and Sevink, J. 1992. 'The effects of fire and water repellency on infiltration and runoff under Mediterranean type forest', Catena, 19, 345-361. Lasanta, T., Garcia-Ruiz, J.M., Perez-Rontome, C. and Sancho-Marcen, C. 2000. 'Runoff and sediment yield in a semi-arid environment: the effect of land management after farmland abandonment.' Catena 38, 265-278. Martinez-Mena, M., Albaladejo, J. and Castillo, V.M. 1998. 'Factors influencing surface runoff generation in a Mediterranean semi-arid environment: Chicamo watershed, SE Spain.' Hydrological Processes 12, 741-754. Parsons, A.J., Wainwright, J., Abrahams, A.D. and Simanton, J.R. 1997. Distributed dynamic modelling of interrill overland flow. Hydrological Processes, 11, 1833-1859. Quinn, P., Beven, K., Chevallier, P., and Planchon, O. 1991: The prediction of hillslope flow paths for distributed hydrolgical modelling using digital terrain models; Hydrological Processes, 5, 59 - 79 Wolman, M.G. and Gerson, R. 1978. Relative scales of time and effectiveness of climate in watershed geomorphology, Earth Surface Processes and Landforms, 3, 189-208 Wainwright, J. and Pasons, A.J., 2002: The effect of temporal variations in rainfall on scale dependency in runoff coefficients; Water Resources Research, 38, art 1271 Conclusions The defined storms showed that the temporal structure of the storm event has a significant effect on the generation and transmission of runoff. The highest runoff coefficient was obtained when the high intensity rainfall pulse was located at the start of the storm. The importance of the temporal structure of the rainfall time series is clearly demonstrated by the Monte Carlo based simulation results. From the Monte Carlo generation of 200 storms with the same rainfall depth and duration, it was found that the amount of runoff leaving the slope was highly variable. The majority of the realisations gave a greater runoff coefficient than with constant rainfall intensity. However, 25.9 % of the realisations gave a lower total discharge and 51.2 % gave a lower peak discharge. These results contrasts with the findings of Wainwright and Parsons (2002) who found that the use of variable intensity rainfall always resulted in an increase in the amount of runoff leaving a slope. The modelling results from the variable length of depth storms showed that no one statisti- cal property is able to explain the variations in the runoff coefficients the modelling results. The statistical properties do not directly consider the temporal structure of the rainfall time series. This work suggests that the temporal structure, as well as the variability, plays a significant role in the determination of the runoff response to a storm event. Test Hillslope The test hillslope has a slope length of 50 m at a gradient of 6° and relates to hillslopes found in the field. The infiltration model parameters relate to results from a rainfall simulation experiment from a non-vegetated area with stones at a scrub site. Figure 2 shows the discharge hydrograph and the depression storage from a 5 minute storm event at an intensity of 75 mm hr -1 . This rainfall pulse is related to a low frequency, high magnitude storm event. The peak discharge is 0.008 m 3 s -1 and the total discharge is 0.76 m 3 giving a runoff coefficient of 4.87 %. 1 a time (seconds) 0 50 100 150 200 250 300 350 400 0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014 depression storage depth (m) 0.0000 0.0005 0.0010 0.0015 0.0020 0.0025 Rainfall (mm hr) 0 50 100 150 200 250 300 discharge depression storage rainfall Figure 2 Discharge hydrograph from the test hillslope discharge (m s ) 3 -1 a b c d e f 0 20 40 60 80 100 120 0 20 40 60 80 100 120 140 160 180 0 20 40 60 80 100 120 0 20 40 60 80 100 120 140 160 180 0 40 80 120 0 20 40 60 80 100 120 140 160 180 0 40 80 120 0 20 40 60 80 100 120 140 160 180 g h time (minutes) 0 40 80 120 0 20 40 60 80 100 120 140 160 180 0 40 80 120 0 20 40 60 80 100 120 140 160 180 0 40 80 120 0 20 40 60 80 100 120 140 160 180 0 40 80 120 time (minutes) time (minutes) time (minutes) time (minutes) time (minutes) time (minutes) time (minutes) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) -1 rainfall intensity (mm hr ) 0 20 40 60 80 100 120 140 160 180 Figure 3 Pre-defined storms Results The results show that the temporal structure of the rain storm can have a significant influ- ence on the amount of water leaving the slope. Storm a has a constant rainfall intensity and produces the lowest amount of discharge. The second set of storms have a greater maxi- mum rainfall intensity at 109.1 mm hr -1 and produce more runoff that storm a. More runoff is obtained from storm b which has the high intensity storm at the beginning of the storm. The rainfall during the rest of the time series helps the transmission of the runoff. Storm e has a linear increase in intensity and storm f has a linear decrease. Storm e gives more runoff and can be related to the wetting up of the soil before the higher intensity, runoff generating, rainfall. These storms show a different behaviour to storms b and c and show the importance of conditioning the soil surface for runoff generation. Storms g and h have variable rainfall with storm h having the greater amount of variability. Storm g has a maximum rainfall intensity of 83.2 mm h -1 and storm h has a maximum inten- sity of 170.3 mm hr -1 . Despite the large difference in the maximum intensities, they give University of Durham poster_940x475mm_half size 20/4/04 4:31 pm Page 1
Transcript
Page 1: THE INFLUENCE OF STORM CHARACTERISTICS ON RUNOFF GENERATION AND CONNECTIVITY IN SEMI ...community.dur.ac.uk/sim.reaney/EGU_2004_storms.pdf · 2005-05-05 · THE INFLUENCE OF STORM

THE INFLUENCE OF STORM CHARACTERISTICS ON RUNOFF GENERATION AND CONNECTIVITY IN SEMI-ARID AREASS

Reaney

(1), L J Bracken (née B

ull) (2)and M

J Kirkb

y(1)

(1), School of G

eograp

hy, University of Leed

s, Leeds, LS

2 9JT, UK

, (2)Dep

artment of G

eograp

hy, University of D

urham, D

urham, D

H1 3LE

Em

ail: s.reaney@g

eog.leed

s.ac.uk Fax: 44 113 233 3308 Web

: ww

w.g

eog.leed

s.ac.uk/peop

le/s.reaney/

The Connectivity of

Runoff M

odel (C

RU

M)

The model developed to investigate the controls on

runoff

generatio

n and

flo

w

dynam

ics in

semi-arid

en---vironments

is the

Connectivity

of R

unoff M

odel(C

RU

M). The m

odel is divided into vertical and horizon-tal com

ponents and distributed on a grid structure. Thevertical

comp

onent rep

resents intercep

tion, surface

detention

storage,

surface d

epression

storage,

soilm

oisture storage and recharge, (Figure 1).

The horizontal interactions occur only as overland flowbecause lateral flow

through the soil is negligible insem

i-arid environments. The flow

routing between the

grid cells uses the FD8 algorithm

(Quinn et al.1991)

which uses m

ultiple flow directions and hence allow

sboth the dispersion and concentration of flow

. The flowvelocity is determ

ined by the Darcy-W

eisbach equation.

Pre-d

efined S

torms

A set of pre-defined storm

hydrographs havebeen developed to investigate the influence ofthe tem

poral structure of the rainfall on thegeneration

and transm

ission of

runoff. The

storms all deliver 80 m

m of rainfall over a tw

ohour period (Figure 3). The storm

characteris-tics and the runoff coefficients are show

n inTable 1.

pulse length0

510

1520

25

0.0

0.1

0.2

0.3

0.4

0.5

0.6

maxim

um rainfall intensity (m

m hr

-1)

0100

200300

400500

0.0

0.1

0.2

0.3

0.4

0.5

0.6

total rainfall (mm

)0

510

1520

2530

35

0.0

0.1

0.2

0.3

0.4

0.5

0.6

CO

V0.0

0.51.0

1.52.0

2.53.0

runoff coefficientrunoff coefficient

runoff coefficient

runoff coefficient

0.0

0.1

0.2

0.3

0.4

0.5

0.6

total rainfall (mm

)0

510

1520

2530

35Qpeak

Qpeak

0 2 4 6 8

maxim

um rainfall intensity (m

m hr

-1)

0100

200300

400500

0 2 4 6 8

Figure 5 D

ischarge characteristics with varable rainfall

The total rainfall depth shows a positive relationship w

ith both the peak discharge and the runoffcoefficient. This is related to the decrease in the infiltration rate w

ith increasing total rainfall.H

owever, there is a large am

ount of scatter in the plots with the sam

e rainfall depths producingvastly different am

ounts of flow from

the slope. This range of results relates to both the distrib-ution of rainfall intensities and the tem

poral structure of the storm.

The maxim

um rainfall intensity results show

threshold behaviour related to the intensity requiredto exceed in the soil infiltration capacity. H

owever, the infiltration capacity w

as 55 mm

hr -1w

here-as the threshold is located at 84 m

m hr -1. This difference relates to the am

ount of excess water

required to fill the surface depression store and allow the connection betw

een the runoff gener-ation point and the slope outflow

.

As the storm

length increases, the range of runoff coefficients increases. The rate of increase inthe m

aximum

runoff coefficient rises above a pulse length of five minutes and levels off after 13

minutes. The increase at five m

inutes relates to the time required to fill the surface depression

store and for the runoff to reach of the outflow. The levelling off of the range of runoff coefficients

at 13 minutes relates to the total travel tim

es across the surface.

The CO

V does not show

a consistent relationship with the runoff coefficient. There are large

variations in the runoff coefficient for a certain CO

V value. This therefore suggests that the tem

-poral structure, as w

ell as the variability, plays a significant role in the generation of runoff.

Introduction

The generation of high magnitude flood events at the catchm

ent scale in semi-

arid areas are caused by a combination of precipitation characteristics including

amount, intensity, duration and spatial distribution (W

olman and G

erson 1978;C

osta 1987). At the sm

all scale many investigations have focused on the influ-

ence of plot scale properties such as vegetation (Cerda, 1995; B

ergkamp et al,

1996; Imeson et al, 1992), soils and slopes (P

arsons et al 1997; Martinez-M

ena etal 1998). H

owever, there have been a lim

ited number of investigations into how

the characteristics of the rainfall input into semi-arid system

s influences the gen-eration and transm

ission of runoff.

The study uses the Connectivity of R

unoff Model (C

RU

M) to investigate how

thecharacteristics of rainfall input to sem

i-arid areas influence the runoff produced atthe base of a hillslope. A

simple theoretical hillslope, characteristic of a sem

i-aridregions, has been subjected to a range of storm

events. The storm events have

been generated in two w

ays. The first set uses pre-defined storm hydrographs

and the second set uses stochastically generated storms. The stochastic rainfall

generator has been used to generate two sets of storm

s. The first set consists ofa fixed duration and depth w

ith variable per minute intensities and the second set

of storm has variable storm

s depths and durations.

Rg

Recharg

e

Canop

y

Soil S

tore

Runon

Infiltration

Runoff

Detention S

tore

Dep

ressionS

torage

Rd

Rt

Rn

Figure 1 Vertical m

odel structure

TAB

LE1 S

torm C

harts and runoff coefficiences

STO

RM

MA

X IN

TEN

SITY

(mm

hr-1)

ME

AN

INTE

NS

ITY(m

m hr

-1)C

OV

RU

NO

FF C

OE

FFICIE

NT

a40.0

40.00.00

25.3%

b109.1

40.01.23

57.9%

c109.1

40.01.23

56.9%

d109.1

40.01.23

55.8%

e80.0

40.00.58

37.1%

f80.0

40.00.58

35.2%

g83.2

40.00.60

26.2%

h170.3

40.00.95

26.9%

similar runoff coefficients. These values are

only slightly greater than from storm

a with

constant rainfall. This suggests that the runoffw

hich was generated during the high intensity

rainfall is rapidly infiltrated during subsequentlow

rainfall intensity periods. This shows the

importance of the tem

poral fragmentation of

the high

intensity rainfall

during the

stormevent.

Stochastically G

enerated S

torms

The stochastic rainfall was generated using a M

onte Carlo m

odel to select randomrainfall intensities. The M

onte Carlo m

odels uses a distribution function fitted to theintense rainfall sections of a m

easured time series, equation 1.

Where rfi

is the rainfall intensity (mm

hr-1), –is the m

ean per minute rainfall

intensity, ais a coefficient and prob

is the probability of that rainfall intensity. For am

easured rainfall record from S

E S

pain, a=

1.74 (R2 =

0.98).

rfi =–ln(1–prob).601a

Results 2

To investigate which properties of the rainfall

time series control the am

ount of discharge thatleaves the slope, the test hillslope w

as subject-ed to 1000 storm

realisations of varying intensityand duration. These storm

pulses varied from 1

to 20 minutes and from

40 mm

hr -1to 90 m

m

hr -1, Figure 5.

Results 1

The impact of variable rainfall on the discharge is show

n in the box plots, Figure 4. These plots compare

the difference between the runoff leaving the slope from

a rainfall pulse of 75 mm

hr -1for five m

inutes deliv-ered at constant and variable intensity. The variable rainfall increases the m

edian discharge. The maxim

umdischarge volum

e simulated w

as 3.65 m3; this is 480 %

greater than with constant rainfall. H

owever, 25.9

% of the sim

ulations produced a discharge volume less than the constant rainfall, w

ith the minim

um dis-

charge of 0.13 m3. The m

edian peak dischargeis very sim

ilar between the constant and variable

rainfall. There is a greater spread of values with

the variable rainfall, to a maxim

um of 1.38 m

3

min

-1.

Constant

Variab

le

peak discharge (m min )

0 1 2 3 4 5

Constant

Variab

le 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

3 -1

total discharge (m )3

Figure 4 B

ox plots of d

ischarge w

ith constant and varab

le rainfall

Acknow

ledg

ments

This work w

as funded by a School of G

eography, University of Leeds studentship and financial support

from the E

U P

ES

ER

A project.

References

Bergkam

p, G., C

amm

eraat, L.H., and M

ertinez-Fernandez, J. 1996. 'Water m

ovement and vegetation patterns on shrubland and an abandoned field in tw

o desertification threatened areas in S

pain', E

arth Surface P

rocesses and Landforms, 21, 1073-1090.

Cerda, A

. 1995. 'Spatial distribution of infiltration on the m

atorral slopes in a Mediterranean environm

ent, Genoves, S

pain', in Fantechi, R., P

eter, D., B

labanis, P. and Rubio,

J.L. (Eds), D

esertification in a E

uropean Context: P

hysical and Socio-econom

ic Impacts, E

uropean Com

mission, B

russels, 427-436.C

osta, J.E. 1987. A

comparison of the largest rainfall - runoff foods in the U

nites States and the P

eople's Republic of C

hina and the world. Journal of H

ydrology, 96, 101-115.Im

eson, A.C

. Verstraten, J.M., van M

ulligen, E.J., and S

evink, J. 1992. 'The effects of fire and water repellency on infiltration and runoff under M

editerranean type forest', Catena, 19, 345-361.

Lasanta, T., Garcia-R

uiz, J.M., P

erez-Rontom

e, C. and S

ancho-Marcen, C

. 2000. 'Runoff and sedim

ent yield in a semi-arid environm

ent: the effect of land managem

ent after farmland

abandonment.' C

atena 38, 265-278.M

artinez-Mena, M

., Albaladejo, J. and C

astillo, V.M. 1998. 'Factors influencing surface runoff generation in a M

editerranean semi-arid environm

ent: Chicam

o watershed, S

E S

pain.' Hydrological

Processes 12, 741-754.

Parsons, A

.J., Wainw

right, J., Abraham

s, A.D

. and Sim

anton, J.R. 1997. D

istributed dynamic m

odelling of interrill overland flow. H

ydrological Processes, 11, 1833-1859.

Quinn, P., B

even, K., C

hevallier, P., and Planchon, O

. 1991: The prediction of hillslope flow paths for distributed hydrolgical m

odelling using digital terrain models; H

ydrological Processes,

5, 59 - 79W

olman, M

.G. and G

erson, R. 1978. R

elative scales of time and effectiveness of clim

ate in watershed geom

orphology, Earth S

urface Processes and Landform

s, 3, 189-208W

ainwright, J. and P

asons, A.J., 2002: The effect of tem

poral variations in rainfall on scale dependency in runoff coefficients; Water R

esources Research, 38, art 1271

Conclusions

The defined storms show

ed that the temporal structure of the storm

event has a significanteffect on the generation and transm

ission of runoff. The highest runoff coefficient was

obtained when the high intensity rainfall pulse w

as located at the start of the storm.

The importance of the tem

poral structure of the rainfall time series is clearly dem

onstratedby the M

onte Carlo based sim

ulation results. From the M

onte Carlo generation of 200

storms w

ith the same rainfall depth and duration, it w

as found that the amount of runoff

leaving the slope was highly variable. The m

ajority of the realisations gave a greater runoffcoefficient than w

ith constant rainfall intensity. How

ever, 25.9 % of the realisations gave a

lower total discharge and 51.2 %

gave a lower peak discharge. These results contrasts w

iththe findings of W

ainwright and P

arsons (2002) who found that the use of variable intensity

rainfall always resulted in an increase in the am

ount of runoff leaving a slope.

The modelling results from

the variable length of depth storms show

ed that no one statisti-cal property is able to explain the variations in the runoff coefficients the m

odelling results.The statistical properties do not directly consider the tem

poral structure of the rainfall time

series. This work suggests that the tem

poral structure, as well as the variability, plays a

significant role in the determination of the runoff response to a storm

event.

Test Hillslop

e

The test hillslope has a slope length of 50 m at a gradient of

6°and relates to hillslopes found in the field. The infiltration

model param

eters relate to results from a rainfall sim

ulationexperim

ent from a non-vegetated area w

ith stones at a scrubsite.

Figure 2 shows the discharge hydrograph and the depression

storage from a 5 m

inute storm event at an intensity of 75 m

mhr -1. This rainfall pulse is related to a low

frequency, highm

agnitude storm event. The peak discharge is 0.008 m

3s

-1

and the total discharge is 0.76 m3

giving a runoff coefficient of4.87 %

.

1a

time (second

s)

050

100150

200250

300350

4000.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

depression storage depth (m)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

Rainfall (mm hr)

050100

150

200

250

300

dischargedepression storage

rainfall

Figure 2

Discharg

e hydrog

raph from

the test hillslope

discharge (m s )3 -1

ab

cd

ef

020

4060

80100

1200 20 40 60 80

100120140160180

020

4060

80100

1200 20 40 60 80

100120140160180

040

80120

0 20 40 60 80100120140160180

040

80120

0 20 40 60 80100120140160180

gh

time (m

inutes)0

4080

1200 20 40 60 80

100120140160180

040

80120

0 20 40 60 80100120140160180

040

80120

0 20 40 60 80100120140160180

040

80120

time (m

inutes)tim

e (minutes)

time (m

inutes)tim

e (minutes)

time (m

inutes)tim

e (minutes)

time (m

inutes)

-1rainfall intensity (mm hr )-1rainfall intensity (mm hr )

-1rainfall intensity (mm hr )-1rainfall intensity (mm hr )

-1rainfall intensity (mm hr )-1rainfall intensity (mm hr )

-1rainfall intensity (mm hr )-1rainfall intensity (mm hr )

0 20 40 60 80100120140160180Fig

ure 3 Pre-d

efined storm

s

Results

The results show that the tem

poral structure of the rain storm can have a significant influ-

ence on the amount of w

ater leaving the slope. Storm

a has a constant rainfall intensity andproduces the low

est amount of discharge. The second set of storm

s have a greater maxi-

mum

rainfall intensity at 109.1 mm

hr -1and produce m

ore runoff that storm a. M

ore runoffis obtained from

storm b w

hich has the high intensity storm at the beginning of the storm

.The rainfall during the rest of the tim

e series helps the transmission of the runoff.

Storm

e has a linear increase in intensity and storm f has a linear decrease. S

torm e gives

more runoff and can be related to the w

etting up of the soil before the higher intensity,runoff generating, rainfall. These storm

s show a different behaviour to storm

s b and c andshow

the importance of conditioning the soil surface for runoff generation.

Storm

s g and h have variable rainfall with storm

h having the greater amount of variability.

Storm

g has a maxim

um rainfall intensity of 83.2 m

m h

-1and storm

h has a maxim

um inten-

sity of 170.3 mm

hr -1. Despite the large difference in the m

aximum

intensities, they give

University of D

urham

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