Simulating the integrated effects of topography and soil properties on runoff generation in hilly...

HYDROLOGICAL PROCESSESHydrol. Process. 24, 714725 (2010)Published online 10 November 2009 in Wiley InterScience(www.interscience.wiley.com) DOI: 10.1002/hyp.7509

Simulating the integrated effects of topography and soilproperties on runoff generation in hilly forested catchments,

South ChinaXi Chen,1* Qinbo Cheng,1 Yongqin David Chen,2,3 Keith Smettem4 and Chong-Yu Xu5,6

1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China2 Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China

3 Centre of Strategic Environmental Assessment for China, The Chinese University of Hong Kong, Hong Kong, China4 Centre for Ecohydrology, School of Environmental Systems Engineering, The University of Western Australia, Nedlands 6009, Australia

5 Department of Geosciences, University of Oslo, PO Box 1047, Blindern, NO-0316 Oslo, Norway6 Department of Earth Sciences, Uppsala University, 75236 Uppsala, Sweden

Abstract:Estimation of runoff components associated with catchment topography and soil properties is critical for planning waterresources utilization and evaluating hydrological changes due to artificially induced land surface manipulation. In this study,the modified TOPMODEL by Scanlon et al. (2000) was applied to simulate runoff-generating processes and to separate runoffcomponents in two hilly forested catchments within the Dongjiang Basin of Southeast China. The modified TOPMODEL wasimproved by integrating an evapotranspiration package with the model algorithms. Influences of catchment topography andsoil properties on runoff generation were analysed on the basis of explicit expression of catchment field capacity distributionderived from the topographic index and catchment average field capacity. Study results demonstrate that the model is capableof simulating hydrological processes and separate hydrological components in both hourly and daily time steps. Total runoffgeneration primarily depends on the effective storage capacity of unsaturated zone. A 50% decrease of the effective storagecapacity from 022 to 011 m over the soil zone leads to a 66% increase in total runoff. Topography plays a dominant rolein formation of runoff components. When the catchment mean slope increases by 87%, subsurface storm flow could increaseby 50% whilst overland flow decreases by 75% and baseflow by 67%. Vertical changes of soil permeability influence runoffcomponents as well. Decrease of the lower layer hydraulic transmissivity may result in 23% increase of overland flow andsubsurface storm flow and 5% decrease of baseflow. Copyright 2009 John Wiley & Sons, Ltd.

KEY WORDS TOPMODEL; topographic index; hydrological components; root zone storage capacity

Received 31 July 2008; Accepted 15 September 2009

INTRODUCTIONWatershed outflow in humid tropical regions is usuallyclassified as infiltration excess overland flow, saturationexcess overland flow, unsaturated subsurface flow andsaturated subsurface flow (Thomas, 1994). The formationof these flow components and their pathways dependson soil prosperities, e.g. soil texture and permeability,and topography. In forested catchments of temperateregions, substantial subsurface flow can be generated(Whipkey, 1965; Hewlett and Hibbert, 1967; Weyman,1973) because of the high infiltration capacities of theforest surface soils perched above less permeable soillayers or a slowly moving wetting front (Hammermeisteret al., 1982). Topography is regarded as a driving forcethat subsurface storm flow occurs quickly enough to con-tribute to peak stream discharge and a greater percentageof precipitation is converted to subsurface flow in thelower hillslopes (Beven and Kirkby, 1979; OLoughlin,1986; Scanlon et al., 2000).

* Correspondence to: Xi Chen, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing210098, China. E-mail: [email protected]

Distributed hydrological models possess the flexibil-ity to deal with different conditions in a wide range ofgeographical regions. They can be used to estimate thehydrological components of runoff if the model parame-ters are appropriately calibrated using a set of measuredstreamflow data and then validated using another set offlow data. Among these models, TOPMODEL (Bevenand Kirkby, 1979) has provided hydrologists with a pow-erful tool to analytically simulate the hillslope responseof site-specific topography. It operates at basin scale bymaking use of the statistics of topography, rather thanall the topographic details (Beven and Kirkby, 1979).Moreover, many efforts have been made to improve theTOPMODEL structure to better capture streamflow dis-charges or/and to increase model capability for describingmeaningfully the hydrological processes under differentclimatic and catchment conditions. Among them, Scan-lon et al. (2000) recognized that transient and perchedstormflow played a substantial role in hilly forested catch-ments and so modified TOPMODEL by augmenting thesingle subsurface flow component defined by one con-tinuous water table into two subsurface components. Themodified TOPMODEL has been successfully used for the

Copyright 2009 John Wiley & Sons, Ltd.

SIMULATING EFFECTS OF TOPOGRAPHY AND SOIL PROPERTIES ON RUNOFF 715

short term hydrological simulation in forested catchments(Scanlon et al., 2000).

For distributed hydrological modelling, site-specificinformation of soil properties and topography is usuallyneeded for unsaturated and saturated accounting. Ingeneral, site-specific soil spatial information is the leastknown of the land surface attributes (Nielsen and Bouma,1985). But the distribution of soil properties and therooting depth can be estimated by approximating the soilvariations with more easily observable variables, suchas terrain and vegetation variables (Moore et al., 1993).For catchments located at the steeper upland and thegentler lowland, a steeper catchment usually possessesshallower soil than a gentler watershed (Shaman et al.,2002). The thick soil in the gentler areas is able to holdmore water than the shallower soil in the steeper areas.However, runoff generation depends on soil moistureholding capacity or effective storage capacity (SC) of theunsaturated zone. In the hilly lowland areas, groundwateris shallow due to hillslope- (Anderson, 1982) or bedrock-(Freer et al., 1997) induced convergence of subsurfaceflow or return flow (Hewlett and Hibbert, 1967; Hewlett,1974). In the shallow groundwater table areas, becausethe rooting depth in the unsaturated zone for holding soilmoisture may be reduced due to the high groundwatertable occupation, the holding capacity or effective SC inthe unsaturated zone becomes small.

In a hilly area, the topographic index can representthe influences of terrain on the spatial variations of soilwetness. A larger topographic index is an indicator ofhigher soil wetness and smaller soil moisture deficit,which means easier runoff generation in response to rain-fall input. Besides the soil wetness distribution drivenby basin terrain, the topographic index also indicatesthe heterogeneity of the unsaturated zone SC acrossthe catchment as reflected by the spatial variations ofsoil moisture holding capacity which is termed as fieldcapacity in the Xinanjiang model (Zhao et al., 1980).Guo et al. (2000) demonstrated that the distribution ofnormalized holding capacity or effective SC (f/F SRM/WMM) can be substituted by normalized topo-graphic index (f/F IRDG). Here, f/F is a fractionof watershed area less than SC; SRM is SC at a point,which varies from zero to the maximum of the wholewatershed WMM; index of relative difficulty of runoffgeneration (IRDG) is derived from topographic index(

IRDG D max[lna/ tan ] lna/ tan max[lna/ tan ] min[lna/ tan ]

). The

distribution of normalized SC together with catchmentaverage SC SRMAX can derive SC distribution (see Chenet al., 2007 for details). Compared with distribution oftopographic index, this SC distribution can distinguishinfluences of catchment characteristics of the terrain andunsaturated zone soil on the runoff generation.

The modified model by Scanlon et al. (2000) is tar-geted for short term hydrology. The short term hydrolog-ical model, which deals with single or several rainfallevents, has developed in the way that effective rain-fall and evapotranspiration are evaluated on some simple

assumptions. For a long period of hydrological simulationin the forested watershed, however, vegetation canopyand root distribution take a critical influence on evap-otranspiration and thus soil moisture deficit and runoffgeneration. TOPMODEL follows generally adopted prac-tice in calculating actual evapotranspiration as a functionof potential evaporation and root zone moisture storage.It does not explicitly describe how rainfall interceptionand transpiration influence hydrological processes in theforest catchments. Additionally, the long term hydrolog-ical behaviours are usually simulated in a daily time stepusing daily data as the models input. Because of unevendistributed rainfall and evapotranspiration during a day,applicability of the modified model by Scanlon et al.(2000) for the long term hydrology should be validated.

The main objective of this study is to examine how dif-ferent runoff components simulated are affected by catch-ment topography and soil characteristics. For explicitlyexpressing influences of unsaturated zone dynamics onrunoff generation in the long term simulation, we incor-porate evapotranspiration package into the modified TOP-MODEL and establish the spatial variation of effectiveroot zone SC based on topography index and watershedaverage SC. The study is exemplified in two catchmentswith different topographic conditions and soil depth andproperties. The capability of the model to simulate over-land flow, subsurface storm flow and baseflow was firstassessed by calibration and validation on the basis ofobserved streamflow in two hilly forest catchments ofDongjiang River Basin, South China. A comparison ofthe simulation results between the two catchments wasthen made to reveal the influences of catchment topog-raphy and soil properties. A sensitivity analysis was per-formed in order to quantitatively evaluate the influencesof terrain slopes, soil moisture capacities and hydraulictransmissivity on the runoff components.

DESCRIPTION OF STUDY SITE AND DATA

Dongjiang Basin has a drainage area of 35 340 km2above Shilong hydrologic station (Figure 1). Subtropi-cal monsoon climate dominates the region with aver-age annual rainfall of 1750 mm and potential evap-oration of 1297 mm. The region is characterized bya highly seasonal rainfall and considerable streamflowvariability. Over 75% of the rainfall occurs during thewet season (AprilSeptember). Dry-season streamflow(OctoberMarch) accounts for only about 20% of theannual streamflow. The basin has a complex geologi-cal structure and Precambrian, Silurian and Quaternarygeological formations are encountered at the surfacewith granites, sandstones, shale, limestone and alluvium.The stream networks have developed on deeply weath-ered granite and sandstones. Drainage densities of thebasin are high with an average value of 53 km/km2.The landscape is characterized by hills and plains, com-prising 781 and 144% of the basin area, respectively.Forest covers headwater areas and intensive cultivation

Copyright 2009 John Wiley & Sons, Ltd. Hydrol. Process. 24, 714725 (2010)

716 X. CHEN ET AL.

Figure 1. Catchments (Lianping, Xingfeng and others) in the Dongjiang basin

Table I. Catchment characteristics

Catchment Area(km2)

Stream Length,Dmax (km)

Elevation (m) Average BasinSlope (%)

Mean annualRainfall (mm)

Forest Cover(%)

Max. Min. Mean

Lianping 372 14 1262 247 5930 166 19483 950Xingfeng 426 10 508 149 2676 986 18716 914

dominates hills and plains lower in the basin. Veg-etation species and coverage were estimated on thebasis of remote sensing images (data sources fromhttp://www.naturalresources.csdb.cn). Dongjiang Basinis extensively covered by vegetation and the cov-erage is 539% on average. The vegetation speciesinclude low shrub (369% in area in 1998), subtropi-cal evergreen and deciduous broad-leaved mixed forest(266%), evergreen coniferous forest (134%), subtrop-ical evergreen broad-leaved forest (39%), subtropicalevergreen broad-leaved forest (23%), herb (04%) andcrops (165%). Normalized difference vegetation index(NDVI) in the whole Dongjiang Basin is approximately055, smaller in the downstream area of Pearl River(Zhujiang) Delta region and larger in the upper water-shed. The monthly NDVI in the whole watershed variesfrom smallest of 043 in March to the largest 065 inJuly.

The Dongjiang Basin has been experiencing rapideconomic growth over the past two decades and as aresult there has been an increasing competition for water.Dongjiang is also a major water supply basin for HongKong and other cities in the region. Understanding runoffgeneration mechanism associated with basin character-istics is essential for managing water resources in thecoming decades as the demand for water is predicted togrow significantly.

To evaluate the influences of topography and soil onrunoff response, we selected two catchments of similarsize in the Dongjiang Basin (Xingfeng and Lianping)with different terrain and soil properities (Figure 1).With elevation from 247 to 1262 m above mean sealevel, Lianping catchment is situated in the forestedheadwater area and more than 90% land surface iscovered by forest (Table I). Located in central part ofthe upper Dongjiang Basin, the ground surface elevation



of Xingfeng catchment varies from 149 to 508 m, andits basin relief and slope are much smaller than thosein Lianping (Table I). Soil in the two catchments isprimarily red loam consisting of sandy loam and sandysilt. In the whole Dongjiang Basin, the soil thickness is12 m over the weathered rock which fracture is filledwith impervious silt (grain size

718 X. CHEN ET AL.

Discharge from this zone is expressed as:

Qsf D Q0sf(

1 SsfS maxsf

)4

where Q0sf is a storm flow zone recession parameter andinfluences the storm flow recession slope.

Ssf is reduced by inflow from the overlying unsaturatedzone, Quz, and is increased by outflow to the stream,Qsf, and vertical drainage to the groundwater zone, Qv.The change in average storm flow zone deficit over asimulation time step is expressed as:

Ssft

D Quz C Qsf C Qv 5

Baseflow. Vertical drainage that depletes the water inthe subsurface storm flow zone and replenishes the waterstored in the groundwater zone (Scanlon et al., 2000) isexpressed as:

Qv DN

iD1min

[cS maxsf Ssfi, Sgwi

]Ai 6

where c is a simple transfer coefficient, N is the numberof topographic index bins, and Ai is the fractionalcatchment area corresponding to each bin. Thus, Qvis calculated with the condition that recharge for eachtopographic index bin i is limited to the correspondinglocal groundwater saturation deficit Sgwi. There is notime delay between variations in subsurface storm flowdrainage and groundwater discharge because the vadosezone thickness tapers to zero at the base of the slope.

The transmissivity of lower layer T0i is exponentiallydecreased with saturated deficit (Ambroise et al., 1996).

T0i D T0 exp(Sgwi

m

)7

where T0 is transmissivity of lower layer surface and mis a scaling parameter related to soil properties (Bevenand Wood, 1983).

Following Beven and Wood (1983), the local ground-water storage deficit Sgwi for any value of lna/ tan isrelated to average catchment storage deficit, Sgw, by

Sgwi D Sgw C m[ lna/ tan gwi] 8where is the areal average of lna/ tan .

The average groundwater storage deficit Sgw changesover each simulation time step with inputs from verticalrecharge Qv and outputs to stream discharge Qgw:

Sgwt

D Qv C Qgw 9

TOPMODEL computes the recession of hydrograph byrelating groundwater discharge Qgw to average ground-water deficit Sgw:

Qgw D Q0eSgwim 10

where Q0 D T0e^ is a model parameter related tosoil hydraulic properties and topography according to theTOPMODEL concept (Beven and Wood, 1983; Wolock,1993).

Equations (9) and (10) demonstrate that baseflow Qgwis large during the rainfall period when groundwateraquifer gains more recharge and keeps a high ground-water table. When recharge to the groundwater aquifer iszero (Qv D 0), a linear relationship between 1/Q and timeon the recession hydrograph should therefore be obtained.

After both surface and subsurface water flow intothe stream channel, they are routed through the channelsystem to the basin outlet. The number of time steps forrouting should first be determined based on a specifiedmaximum channel flow distance, Dmax and a constantchannel wave velocity parameter, RV.

Evapotranspiration. Effective rainfall and evapotran-spiration are important in a long term hydrological model.Our modified model includes an evapotranspiration pack-age which deals with canopy and evapotranspiration pro-cesses in detail. The total evapotranspiration (ET) is thesum of (1) direct evaporation from the top shallow soillayer, Edir; (2) transpiration via canopy and roots, ET;and (3) evaporation of precipitation intercepted by thecanopy, Ec.

A simple linear method is used to calculate Edir(Mahfouf and Noilhan, 1991):

Edir D 1 fEp 11where f is the green vegetation fraction (cover) whichis estimated by a scaled NDVI (Zeng et al., 2000), DSRZ/SRMAX, SRZ and SRMAX are root zone storageand SC, respectively, Ep is the potential evaporation cal-culated using a Penman-based energy balance approachthat includes a stability-dependent aerodynamic resis-tance (Mahrt and Ek, 1984). ET is calculated by

ET D fEpBc[

1 (

WcS

)n]12

where Bc is a function of canopy resistance, and Wcis intercepted canopy water content estimated from thebudget for intercepted canopy water, and S is the max-imum canopy capacity and n D 05. Finally, the thirdcomponent of the total evapotranspiration (ET), Ec, canbe estimated by

Ec D fEp(

WcS

)n13

The budget for intercepted canopy water is

Wct

D fP Dp Ec 14

where P is total precipitation. If Wc exceeds S, the excessprecipitation or drip, Dp, reaches the ground. For addi-tional details concerning each term in Equations (11)(14), the reader is referred to Chen and Dudhia (2001).



Table II. Model parameters after calibration and validation

Catchment m (m) td(m h)

RV(m/h)

S maxsf(m)

SRMAX(m)

C(m2/ h)

T0sf(m2/h)

T0(m2/ h)

Lianping 004 05 1650 0100 012 08 31 1Xingfeng 016 035 1650 0125 022 07 20 1

Table III. Model calibration and validation results

Catchment Period Rainfall(mm/day)

Evapotranspiration(mm/day)

Runoff (mm/day) NSC RMSE(mm/day)

Ec ET C Edir Observed Simulated

Lianping 19821985 5572 0959 0768 3768 3921 085 04919861987 4864 0769 1096 3004 3012 083 050

Mean 5218 0864 0932 3386 3467 084 050Xingfeng 19821985 5452 0946 1300 3187 2889 078 038

19861987 4490 0759 1265 1994 2112 074 032Mean 4971 0853 1283 2591 2501 076 035

MODEL SIMULATION RESULTS AND ANALYSIS

Model calibration and validation

The model was calibrated for stream discharge from1982 to 1985 using the trial and error method andvalidated from 1986 to 1987, generating the modelparameters presented in Table II. The calibration andvalidation results at a daily time step for both catchmentswere summarized in Table III.

The parameters in Table II and their differencesbetween the two catchments reflect the hydrological char-acteristics influenced by topography and soil properties.Thick soil usually deposited in gentle slope catchment haslarge value of available water capacity SRMAX in theroot zone and large maximum saturation deficit S maxsfin the storm flow zone. Calibration results demonstratethat SRMAX in Xingfeng is approximately two times ofthat in Lianping, which is a clear evidence of the rel-ative difficulty in total runoff generation in Xingfeng.Larger maximum saturation deficit S maxsf, along withsmaller values of C and T0sf in Xingfeng are indicatorsof the difficulty of subsurface storm flow generation. Themuch larger scaling parameter m in Xingfeng implies thatbaseflow recession in Xingfeng is much slower than inLianping and thus Xingfeng is capable to contribute morebaseflow than Lianping.

As shown in Table III, for Xingfeng catchment,NashSutcliff efficiency coefficient (NSC) is 078 and074, and root mean squared error (RMSE) is 038and 032 mm/d in the calibration and validation periods,respectively. For Lianping catchments, NSC is 085 and084 and RMSE is 049 and 050 mm/d in the calibra-tion and validation periods, respectively. Simulated andobserved stream discharges are shown in Figures 3 and 4.The agreement between simulated and observed stream-flow demonstrates the reliability of the modified modelfor streamflow simulation.

Simulated evapotraspiration and runoff componentsSimulated total evapotranspiration ET (D Ec C ET C

Edir) during the whole period of 19821987 is 1796and 2135 mm/d for Lianping and Xingfeng catch-ments, respectively (Table III). In both catchments, sub-stantial amount of ET is from precipitation inter-cepted by the canopy Ec, e.g. about 48 and 42%of the total ET for Lianping and Xingfeng catch-ments, respectively. The total of direct evaporation fromthe top shallow soil layer Edir and transpiration viacanopy and roots ET is 52 and 58% of the total ET,respectively.

The three simulated components of overland flow, sub-surface storm flow, and baseflow in 1983 were shownin Figure 5 for Lianping and Xingfeng. Proportionsof contribution of the three components to the totalrunoff during 19821987 were presented in Table IV.In Xingfeng, contributions of baseflow, subsurface stormflow and overland flow are 7162, 1107 and 1731%of the total flow, respectively, and in Lianping, 5258,3349 and 1393%, respectively. Contribution of sub-surface storm flow to the total streamflow in Lianpingis much larger than that in Xinfeng. On the contrary,groundwater flow in Lianping is significantly less impor-tant. This implies that subsurface storm flow is easilygenerated in the steeper slope catchment where moreperched water flows out and less remains in the rela-tively impermeable layer or percolates downward intoaquifer. As a result, the amounts of baseflow and overlandflow will decrease as more water runs off as subsur-face storm flow. The flow duration curve analysis alsoshowed that in comparison with 1-day stream flow at50% of the time (Q50), the low flow ratios of Q75/Q50and Q95/Q50 in Lianping are 05 and 032, respec-tively, smaller than the corresponding values of 064 and037 in Xingfeng (Zhang et al., 2009). The smaller lowflow ratio in Lianping indicates quick baseflow recession


720 X. CHEN ET AL.

Calibration

0

10

20

1982 1983 1984 1985

Disc

harg

, m3 /s

SimulatedObserved

Validation

0

10

20

1986 1987

Disc

harg

e, m

3 /s

SimulatedObserved

(a)

(b)

Figure 3. Daily simulated and observed streamflow discharge of Lianping catchment for 19821985 (a) and for 19861987 (b)

Calibration

0

5

10

15

20

25

1982 1983 1984 1985

Disc

harg

e, m

3 /s

SimulatedObserved

Validation

0

10

20

1986 1987

Disc

harg

e, m

3 /s

SimulatedObserved

(a)

(b)

Figure 4. Daily simulated and observed streamflow discharge of Xingfeng catchment for 19821985 (a) and for 19861987 (b)

and small groundwater contribution in comparison withXingfeng.

Comparison of daily and hourly simulated resultsTOPMODEL uses two simple linear storage reservoirs

for computation of the subsurface and groundwater zonedynamics [Equations (4) and (5), and Equations (9) and(10), respectively]. Hydrological dynamics of the twozones can be integrated as following:

dSsfdt

D Quz C Qv C Qsf01 SsfSmax

D f t, Ssf 15

dSgwdt

D Qv C Q0eSgwm D f t, Sgw 16

For the model parameters in Table II, Equations (15)and (16) are mathematically convergent and stable in bothdaily and hourly time steps because they meet Lipschitzcondition: jf x, y1 f x, y2j Ljy1 y2j, where Lis a constant. Therefore TOPMODEL can be applied forshort term (an hour) and long term (a day) streamflowsimulation in the study catchments.

The influences of time steps and model inputs onsimulated results of runoff and hydrological components



Lianping

0

5

10

15

Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec

Overland flow Subsurface storm flow Base flow

Xingfeng

0

5

10

15

20

Disc

harg

e, m

3 /sD

ischa

rge,

m3 /s

Overland flow Subsurface storm flow Base flow

Figure 5. Simulated overland flow, subsurface storm flow and baseflow in 1983

Table IV. Model simulated flow components

Catchment Period OverlandFlow (%)

SubsurfaceStorm Flow

(%)

Baseflow(%)

Lianping 19821985 1402 3386 521219861987 1386 3311 5303

Mean 1393 3349 5258Xingfeng 19821985 1738 1186 7076

19861987 1675 1027 7298Mean 1731 1107 7162

were analysed as following. Firstly, the model wasexecuted in an hourly step during a heavy rainfallperiod of 724 May 1987, using parameters from dailycalibration (Table II) except that c in Equation (6) ischanged as c/24 for hourly computation. The modelinputs are hourly observed rainfall and hourly evendistributed rainfall within a day (Phour D Pday/24). Thehourly simulated results are shown in Figure 6. Secondly,the model was executed in a daily step during theheavy rainfall period. The daily simulated hydrologicalcomponents were compared with the daily accumulatedresults from the hourly simulation (Figure 7). Lastly,model was executed for a long period of 19821985 intime steps of an hour and a day, using daily and hourlyeven distributed rainfall and potential evapotranspirationas the model inputs, respectively (Table V).

The simulated results demonstrate: (1) model simu-lation using daily data or hourly even distributed datareflects average state of hydrological processes within aday, and can not capture hydrological dynamics of thehourly flood events. For a large rainfall event unevendistributed within a day, the even distributed treatment

01020304050607080

0 96 144 192 240 288 336 384Time (hour)

Disc

harg

e (m

3 /s)

Observation (hourly)Simulation (hourly observed data)Simulation (hourly even distributed data)

48

Figure 6. Hourly simulated and observed streamflow discharge ofXingfeng catchment during May 724

decreases rainfall amount during the short term heavyrainfall period and increases rainfall amount during therest small rainfall period. Peak discharges of hourly stormflow resulting from an hourly heavy rainfall are severelyunder predicted using hourly even distributed data. Forexample, with hourly observed inputs, the hourly simu-lated storm flood discharge at the time step of 216th houris 629 m3/ s, three times larger than the simulated dis-charge of 1751 m3/ s with hourly even distributed inputs(Figure 6). However, based on hourly even distributedinputs, the simulated discharges during the rest smallrainfall period are significantly increased. (2) Therefore,the total runoff for different time steps and model inputsis very close, e.g. during the heavy rainfall period of724 May 1987, 5198, 5117 and 5115 m3/ s for thedaily step using daily observed rainfall as model inputs,and for the hourly step using hourly observed and hourlyeven distributed data, respectively. (3) Moreover, for dif-ferent time steps and model inputs, daily processes andthe total amount of simulated hydrological components


722 X. CHEN ET AL.

Subsurface storm flow

0

1

2

3

4

120 144 168 192 216 240 264 288 312 336 360 384Time (hour)

Daily observed dataHourly observed dataHourly even distributed data

Base flow

0

1

2

3

4

120 144 168 192 216 240 264 288 312 336 360 384Time (hour)

Disc

harg

e (m

3 /s)

Disc

harg

e (m

3 /s)

Daily observed dataHourly observed dataHourly even distributed data

0 24 48 72 96

0 24 48 72 96

Overland flow

0

5

10

15

20

Disc

harg

e (m

3 /s) Daily observed dataHourly observed data

Hourly even distributed data

120 144 168 192 216 240 264 288 312 336 360 384Time (hour)

0 24 48 72 96

(a)

(b)

(c)

Figure 7. Daily hydrographs of simulated overland flow (a), subsurfacestorm flow (b) and baseflow (c) with model inputs of daily and hourly

observed data, and hourly even distributed data during May 724

of the overland flow, subsurface storm flow and baseflowduring the heavy rainfall event and the 4-year period arevery close as well (Figure 7 and Table V).

DISCUSSION

With its proven capability for distinguishing runoff com-ponents, the modified TOPMODEL can be used to evalu-ate effects of variations of topography and soil propertieson runoff generation and to separate subsurface stormflow from groundwater flow in the two study catchments.

Distribution of effective SC and its influence on runoffgeneration

In the two study catchments, topographical influenceson runoff generation are represented by the IRDG indices

in Figure 8b derived from the relative frequency of topo-graphic indices in Figure 8a. As shown in the two figures,Lianping catchment has larger areas with smaller val-ues of lna/ tan than Xingfeng catchment (Figure 8a),and correspondingly the IRDG of Lianping catchment islarger than Xingfeng catchment (Figure 8b). Therefore,regarding the topographic influence, runoff generationin response to rainfall input in Lianping is more diffi-cult than that in Xingfeng. In terms of the soil proper-ties, however, runoff generation becomes easier in Lian-ping catchment with thinner soil deposit than Xingfengwhere the areal average SC, SRMAX, is larger and thusmore infiltrated water in soil layers will be lost throughevapotranspiration.

Figure 8c shows the spatial distribution of SC derivedfrom IRDG in Figure 8b and SRMAX in Table II. ForLianping, SC varies from zero in the wet lowland andnearby stream channels to the largest of 150 mm in thehilly ridges; for Xingfeng, SC ranges from 0 to 280 mm.Figure 8c indicates that, due to the integrated influencesof topography and soil deposit, Lianping catchmentcan produce more runoff than Xingfeng catchment forthe same atmospheric forcing. Model results show thatthe total recharge rate over the Lianping catchmentis 30 mm/d, approximately 50% larger than that inXingfeng catchment. A greater rate of recharge and morerapid outflow in Lianping when compared to Xingfengindicates that the catchment with steeper topography ismore hydrologically responsive to atmospheric inputs.Such steep catchments may be more prone to extremesof flood and drought, leading to difficulties of waterresource utilization. This conclusion is consistent withthe statistical results that runoff coefficient (mean annualrunoff divided by mean annual rainfall) in Lianping islarger than Xinfeng, 065 versus 052, on the basis of themulti-year mean of rainfall and runoff during 19821987.

Sensitivity analyses of topography and SC on streamflowcomponents

Sensitivity analyses were performed to analyse theinfluences of topographic index determined by slope gra-dient and effective SC on overland flow (OF), subsurfacestorm flow (SSF) and groundwater flow (GF). To demon-strate the effects of topographic variations, we raised theground surface elevation Hgs of Xingfeng catchment tobe as high as 1220 times of Hgs in 02 Hgs increment;the corresponding hillslope angles increase by 119187times on the average. When all the altitudes are doubled,

Table V. Model simulated results of flow components for different time steps and model inputs

Period Time Step and Model Input Overland Flow(%)

Subsurface Storm Flow(%)

Baseflow(%)

A heavy rainfall during May 724 1-h observed data 4291 2252 34531-h even distributed data 4338 2223 34381-day observated data 4460 2332 3205

19821985 1-h even distributed data 1789 1089 71221-day observed data 1738 1186 7076



050

100150200250300

Cumulative frequency (f/F)

SC (m

m)

LianpingXingfeng

0.20.0 0.4 0.6 0.8 1.0

0

0.04

0.08

0.12

0.16

0.2

0 10 15 20 25ln(a/tan) value

Rel

ativ

e fre

quen

cy

LianpingXingfeng

5

(a)

(c)

0.00

0.20

0.40

0.60

0.80

1.00

0.0 0.2 0.4 0.6 0.8 1.0Cumulative frequency (f/F)

IRD

G

LianpingXingfeng

(b)

Figure 8. Integrated effects of variations of topography and unsaturatedzone soil on runoff: relative frequency distribution of lna/ tan values(a), cumulative frequency of IRDG (b), cumulative frequency of effective

storage capacity (c)

the uneven increase of ground surface elevation wouldcause 87% increase in hillslope angles and reduce thebasin average topographic index from 1414 to 1343.As shown in Figure 9, such changes of reducing topo-graphic index or increasing hillslope angles would sub-stantially increase subsurface storm flow by 50% andslightly decrease overland flow and groundwater flow by75 and 67%, respectively.

0

10

20

30

40

50

60

13.4 13.5 13.6 13.7 13.8 13.9 14 14.1 14.2Topgraphic index

Chan

ge of

SSF

(%)

8

6

4

2

0

Chan

ge o

f OF

and

GF

(%)

Subsurface storm flow (SSF)Overland flow (OF) Groundwater flow (GF)

Figure 9. Changes of OF, SSF and GF with the topographicindex

0

2

4

6

8

0Percent of SRMAX decrease (%)

Chan

ge o

f run

off c

ompo

nent

s (%) OF

SSFGFTotal flow

10 20 30 40 50

Figure 10. Changes of OF, SSF, GF and total flow with SRMAX

Figure 10 shows the influences of the catchment aver-age SC SRMAX on the amounts of overland flow, sub-surface storm flow and groundwater flow, i.e. increase ofrunoff as a result of SRMAX decrease. A 50% decreaseof SRMAX from 022 to 011 m leads to 66% increaseof the total runoff, and 70, 73 and 65% increases foroverland flow, subsurface storm flow and groundwaterflow, respectively.

Sensitivity analyses of hydraulic transmissivityon streamflow components

In this implementation of TOPMODEL fromEquation (7), the lower layer soil depth is indirectlydefined by m as m controls the depth of active hydraulicconductivity. For the fixed upper layer hydraulic trans-missivity T0sf in Table II, changes of hydrological com-ponents are computed as m ranges from 004 to 020(Figure 11). For small m, the lower layer soil becomescompact and hydraulic conductivity decreases fast asthe depth to groundwater increases. The overland flowand subsurface stormflow is expected to be increasedand groundwater flow decreased because more infiltratedwater perches on the lower layer surface.

Sensitivity of m on hydrological components is con-ducted in Xingfeng catchment. When the depth togroundwater reduces to 1 m below the lower layer sur-face, hydraulic transmissivity at the lower layer decreasesto 214 105 and 0067 m2/ h as m is 004 and 016,respectively. Figure 11 shows that when m increases from004 to 016, overland flow and subsurface flow are

66

67

68

69

70

71

0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18m

Chan

ge of

GW

(%)

10

12

14

16

18

20

Chan

ge o

f OF

and

SSF

(%)

Groundwater flow (GF)Overland flow (OF)Subsurface storm flow (SSF)

Figure 11. Changes of OF, SSF and GF with m


724 X. CHEN ET AL.

decreased by about 2 and 3% of the total flow, respec-tively, and meanwhile groundwater flow is increasedby 5%.

CONCLUSIONS

Traditionally hydrograph analysis involves the decom-position of streamflow into three major components ofsurface runoff, interflow and baseflow. Distinguishingrunoff components is often very difficult because theyare influenced by highly complicated and spatially vari-able conditions. This study demonstrates that hydrologi-cal models can offer an approach for investigating runoffcomponents and their influences by topography and soilproperties. The modified TOPMODEL is proven to bemathematically convergent and stable for both daily andhourly simulations and successfully applied in two catch-ments. The calibrated model suggests a certain separationof runoff components for a fixed parameter set.

Simulation results demonstrate that in the forest catch-ment, evapotranspiration from precipitation interceptedby the canopy is more than 40% of the total ET,indicating that forest takes a significant regulation onrainfallrunoff processes. Topography and soil proper-ties are two dominantly physical drivers of flow and areprimary determinants of catchment response. To examinethe influence of individual factors, we found that topog-raphy is less influential on the total amount of runoff butsignificantly alters constituent components. The steeperslope catchment generates more subsurface storm flowunder the same climate forcing. When the hillslopeincreases by 87%, subsurface storm flow could increaseby 50% whilst overland flow and baseflow decrease by75 and 67%, respectively. This study demonstrates thatthe distribution curve of catchment effective root zoneSC, which integrates the topographic index and the catch-ment average SC, is a better way to illustrate the com-bined influences of both topography and soil propertieson runoff generation. We showed that the hilly Lian-ping catchment, located in the upper headwater regionswith a steep slope and thin soil deposit, generates morerunoff and has larger proportion of quick flow than theXingfeng catchment which has a gentle slope and thicksoil deposits. A 50% decrease of average effective SCfrom 022 to 011 m results in a 66% increase of thetotal runoff, and 70, 73 and 65% increases for over-land flow, subsurface storm flow and groundwater flow,respectively.

Vertical variations of soil permeability influence runoffcomponents as well. Decrease of hydraulic transmissivityas the lower layer soil becomes compact results inmore overland flow and subsurface storm flow, and lessbaseflow. However, this influence on runoff componentsis less significant than topographic variations.

Changes of runoff components are implicated as possi-ble alternations of catchment pathway for water flow andcontaminant transport, and possible alternations of tem-poral distribution of streamflow during the drought and

flood period. This study is very important for environ-mental protection and for water resources utilization inthe rapidly changing region of Dongjiang watershed.

ACKNOWLEDGEMENTS

The work described in this paper was supported bythe Key Project of Chinese Ministry of Education (No.308012), the National Natural Science Foundation ofChina (No. 50679025), and partially supported by Gled-den Visiting Senior Fellowship, Australia. Thanks to theeditor and two anonymous reviewers for their construc-tive comments on the earlier manuscript, which lead to agreat improvement of the paper.

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