WETLAND AND WATER RESOURCE MODELING AND ASSESSMENT: A Watershed Perspective - Chapter 8 doc

They explicitly modified TOPMODEL to incorporate shallow, lateral subsurface flow by using two simultaneous TOPMODEL simulations, one describing deep baseflow and the other describing sh

8

TOPMODEL for

Streamflow Simulation

and Baseflow Separation

Pei Wen, Xi Chen, and Yongqin Chen

8.1 INTRODUCTION

The TOPMODEL concept (Beven and Kirkby 1979, Beven and Wood 1983, O’Loughlin 1986, Ambroise et al 1996) has been a popular watershed modeling tool (e.g., Anderson et al 1997, Lamb et al 1998, Guntner et al 1999, Scanlon et

al 2000) It is widely used because of its conceptual simplicity of runoff genera-tion, innovative use of topographical data, and demonstrated applicability to a wide variety of situations In recent years, however, various hydrologists have noted the inappropriateness of TOPMODEL’s conceptual basis to meaningfully describe hydrologically shallow, hilly situations where transient, perched groundwater flow plays a substantial role in runoff generation processes (Moore and Thompson 1996, Woods et al 1997, Frankenberger et al 1999, Scanlon et al 2000) Their observation

in forested catchments has suggested the presence of such a storm flow zone perched above low-conductivity layers in the soil or a slowly moving wetting front (Hammer-meister et al 1982a) A transient occurrence of storm flow through the macroporous region of the shallow subsurface may result in the rapid rise of the hydrograph Data collected from subsurface weirs (Scanlon et al 2000) showed that this flow occurs quickly enough to contribute to peak stream discharge, and that a greater percentage

of precipitation is converted to subsurface flow in the lower hill slopes

Many efforts have been made to improve TOPMODEL structure in order to account for this runoff generation mechanism Scanlon et al (2000) believe that the soil water component may arise from saturated flow disconnected from the perma-nent water table while previous models relied on a conceptual model of one continu-ous water table (Robson et al 1992, Hornberger et al 1985), where stream water concentrations are determined by the position of this water table relative to an upper and a lower soil zone They explicitly modified TOPMODEL to incorporate shallow, lateral subsurface flow by using two simultaneous TOPMODEL simulations, one describing deep baseflow and the other describing shallow interflow

90 Wetland and Water Resource Modeling and Assessment

The main objective of this study is to simulate streamflow and to estimate base-flow in a hilly forest catchment in southeastern China using the modified TOP-MODEL The model is calibrated and validated on the basis of daily and hourly observed streamflow data Simulated hydrological components reveal how much baseflow contributes to the total runoff in the study region

8.2 MODIFIED TOPMODEL

The theory underlying the modified TOPMODEL relates hydrological behavior to

the topography-derived variable ln(a/tanβ), where a is the area drained per unit

con-tour, β is the local slope angle, and ln( ) is the Naperian logarithm The model cal-culations are semidistributed in the sense that they are carried out for increments of

ln(a/tanβ) for the catchment (Hornberger et al 1985) TOPMODEL was modified to account for cases in which separate subsurface storm flow and groundwater storage mechanisms contribute to stream discharge, a generalized presentation of which is given by Clapp et al (1996) The primary modification was the addition of a second subsurface state variable, although modifications to associated fluxes were conse-quently necessary Vertical recharge to the groundwater zone is taken into account, and both the subsurface storm flow zone and the groundwater zone can contribute to episodic surface saturation near the stream (Figure 8.1)




























Q of
$%
"'

Q sf
&
"'

Q gw
#%'

S gw
!


S sf
!


FIGURE 8.1 Schematic diagram of the modified TOPMODEL (After Scanlon et al 2000 Shallow subsurface storm flow in a forested headwater catchment: Observations and

model-ing usmodel-ing a modified TOPMODEL Water Resources Research 36(9):2575–2586.)

8.2.1  suBsurfaCe floW

Following Beven and Wood (1983), the local groundwater saturated storage deficit S gwi for any value of ln(a/tan β) is related to the average catchment storage deficit, S gw, by

where m is a scaling parameter, and L is the areal average of ln(a/tan β).

The subsurface storm flow saturation deficit S sfi is determined (Ambroise et al 1996) by

A

sf sf

∫

β β

where Smax sf is the maximum subsurface storm flow zone deficit, and S sf is the average subsurface storm flow zone deficit for the catchment

Surface saturation is controlled by the interaction of both subsurface deficits,

S sf and S gw (Scanlon et al 2000) Values of S gwi≤0 and S sfi≤0 indicate the area

of groundwater saturation and storm flow zone saturation, respectively For S gw≥0

or S sf ≥0 , the soil is partially unsaturated Unsaturated zone calculations are made

for each ln(a/tan β) increment The calculations use two storage elements, SUZ and

SRZ SRZ represents a root zone storage, the deficit of which is 0 at field capacity and becomes more positive as the soil dries out; SUZ denotes an unsaturated zone stor-age that is 0 at field capacity and becomes more positive as storstor-age increases Stor-age subject to drainStor-age is represented by SUZ i for the i-th increment of ln(a/tan β) When SUZ i > 0, vertical flow to the storm flow zone is calculated as

QUZ SUZ S t i

gwi d

where SUZ iis the local unsaturated zone storage due to gravity drainage, and

param-eter t d is a time constant

Vertical drainage that depletes the water in the subsurface storm flow zone and replenishes the water stored in the groundwater zone (Scanlon et al 2000) is expressed as

Q v c S sf S sfi S gwi A

i

N

i

=

1

(8.4)

where c[T −1] is a simple transfer coefficient, N is the number of topographic index bins, and A i [L2] is the fractional catchment area corresponding to each bin

92 Wetland and Water Resource Modeling and Assessment

Evapotranspiration is taken from the SRZ istore The maximum value of storage

in this zone is described as parameter SRMAX The rate of evapotranspiration loss

E is assumed to be proportional to a specified potential rate Ep and the root zone storage SRZ, as

E Ep SRZ SRMAX= * / (8.5)

The sum of vertical flows Q v weighted by the area associated with each ln(a/

tan β) increment is added to reduce the average saturated deficit S gw An outflow

from the saturated groundwater zone, QB, is calculated as

QB e e= −Λ Sgwi m (8.6)

where Q0 is the initial stream discharge

The average subsurface storm flow zone deficit S sf changes over each simula-tion time step with inputs from overlying unsaturated zone Q uz, and outflow to the stream Q sf, and vertical drainage to the groundwater zone Q v Discharge from this zone is expressed as

Q sf Q sf S S sf

sf







0 1 max (8.8)

where Q0sf is a storm flow zone recession parameter and influences the storm flow recession slope

The water balance calculation for S gw or S sf produces a new end-of-time step value that is used to calculate a new value of S gwi or S sfi at the start of the next time step There should be no water balance error involved since the incremental change

in S gw or S sf is equal to the areally weighted sum of changes in S gwi or S sfi

8.2.2  surfaCe floW

Surface flow may be generated either due to a calculated value ofS gwi=0 or S sfi=0

in the saturated zone or due to the unsaturated zone deficit being satisfied by input

from above (SRZ = SRMAX, SUZ > S gwi or SUZ > S sfi for any increment) Both cases represent saturation excess mechanisms of runoff production Areas of high

values of ln(a/tanβ), that is, areas of convergence or low slope angle, will saturate first and as the catchment becomes wetter, the area contributing surface flow will increase Calculated surface flow at any time step is simply the water in excess of any

deficit in each ln(a/tanβ) increment

8.2.3 CHANNEL ROUTING

After both surface and subsurface water flows into the stream channel, it is routed through the channel system to the stream outlet Routing should determine the

and a constant channel wave velocity parameter, V It is assumed that all runoff

pro-duced at each time step reaches the catchment outlet within a single time step

8.3 APPLICATION

8.3.1 STUDY SITE

The study site is the Xingfeng catchment, which is situated in the forested headwater

approximately 90% of the land surface is covered by forest Soil is primarily red loam consisting of sandy loam and sand silt Ground surface elevation varies from 42.6 to 508 m The simulation program written by Beven and Wood (1983) is used for calculation of the topographic index on the basis of a DEM with a resolution of 25

m Precipitation from five observation stations in Figure 8.2 is used to calculate the area’s mean precipitation between 1982 and 1987 Additional data of pan evaporation and stream discharge from the observation station of the catchment outlet are used for model parameter calibration and model validation

Xing Feng Scale

(Kilometer)

0 0.5 1

Precipitation Station Evaporation Station Hydrologic Station

FIGURE 8.2 Map of the study catchment

94 Wetland and Water Resource Modeling and Assessment

8.3.2 MODELCALIBRATION AND VALIDATION

The observed daily precipitation, pan evaporation, and stream discharge from

1982 to 1985 are selected for model parameter calibration, and the daily data from

1986 to 1987 for model validation Additionally, nine hourly flood events are cho-sen for the model simulation The calibrated parameters are listed in Table 8.1 The Nash-Sutcliff efficiency coefficient (NSEC) is 0.79 and 0.72 in the calibra-tion and validacalibra-tion periods, respectively The root mean square error (RMSE) is 1.50 mm/d in the calibration period and 1.31 mm/d in the validation period For the hourly simulation, five flood events are selected for model calibration and the other four for model validation Calibration results demonstrate that most of the model parameters in hourly simulation are the same as those in daily simulations, except for the routing velocity (V), which becomes larger in flooding periods V

is 1,650 and 4,000 m/h in daily and hourly simulation, respectively NSEC for all flood events is between 0.77 and 0.96 in the calibration period and between 0.81

simulated and observed streamflow discharges in the daily and hourly processes generally march well

Based on the modified TOPMODEL structure, baseflow that comes from per-manent groundwater storage can be estimated by equation (8.6) or (8.7) Estimation

of mean baseflow from daily simulation is approximately 72% of the total discharge Figure 8.5 shows the simulated hydrological components of surface flow, storm flow, and baseflow for the flood (No 053008) during May 30 and 31, 1984 The subsur-face stormflow discharge is about 15.6% of the total discharge and the baseflow is 23.4% in the flood event For the nine flood events, calculated results in Table 8.2 demonstrate that the mean baseflow is 47.0% of the total discharge, and storm flow and surface flow are 7% and 46%, respectively

TABLE 8.1

Model parameters after calibration.

Parameter Description Value

m Exponential storage parameter 0.16 m

SRMAX Root zone available water capacity 0.22 m

td Unsaturated zone time delay per unit storage deficit 0.35 h

Smax sf Maximum subsurface storm flow zone deficit 0.125 m

C Recharge transfer coefficient 1.15 m –2 h –1

V Catchment routing velocity 1650 m/h

T0 Mean catchment value of ln(T0) 1.0 m 2 /h

BC Evaporation rate from root system 0.8

Alpha Forestation coefficient 0.7

Silmax Maximum water intercepted by leaf and litter cover 0.007 m

8.4 CONCLUSIONS

Traditionally, a main objective of hydrograph analysis is to decompose streamflow into the three major components of surface runoff, interflow, and baseflow Quan-tifying time-dependent volumetric contributions to total stream water from surface and subsurface hydrological pathways is critical for the development of remedial strategies in areas where contaminants may be present and is necessary for the proper conceptualization of solute transport at the catchment scale Over the past decade, chemical and isotopic methods for the separation of stream hydrographs have been a rigorously explored topic in the field of hydrology Hydrological mod-els used for this purpose must take into account and be consistent with site-spe-cific observations of runoff-generating processes, and must be compatible with the theory derived from physical and geochemical observations in catchment studies

In this study, the modified TOPMODEL with an improvement in representing the runoff generation mechanism in the forest headwater area has successfully been applied in daily and hourly streamflow simulation in the Xingfeng catchment Model calibration and validation results demonstrate that this model is able to effectively reflect watershed hydrological processes By isolating the long-term groundwater recession and using a hydrograph transformation consistent with the TOPMODEL assumptions, the individual characteristics of both the subsurface storm flow and groundwater contributions to discharge have been evaluated Simulation results demonstrate that baseflow is approximately 72% of the total discharge in the area, and therefore baseflow is very important for water resources utilization and further study on maintaining a basic baseflow is very important for environmental and ecosystem protection

TABLE 8.2

Simulation results of hourly flood discharges.

Flood

number Period NSEC

RMSE (m 3 /s)

Flood discharge error (%)

Stormflow (%)

Baseflow (%)

052808 May 25–28, 1982 0.82 1.14 –2.9 7.0 50.2

020108 Feb 1–3, 1983 0.86 1.46 7.3 4.0 52.6

052000 May 20–21, 1983 0.96 4.88 10.6 5.0 47.7

053008 May 30–31, 1984 0.77 4.58 –0.2 15.6 23.4

062500 Jun 25–28, 1985 0.81 1.83 –1.9 1.0 42.2

070219 Jul 2–4, 1985 0.90 3.31 5.4 6.0 38.9

091113 Sept 11–13, 1985 0.87 2.35 9.1 1.0 49.4

092320 Sept 23–26, 1985 0.88 2.58 –4.2 4.0 50.3

050712 May 7–24, 1987 0.81 15.84 12.1 16.0 68.7 Mean Nine flood events 0.85 4.22 3.9 6.6 47.0

96 Wetland and Water Resource Modeling and Assessment

ACKNOWLEDGMENTS

The work described in this paper was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project

No CUHK4247/03H), and partially supported by open funding from the Key Lab of Poyang Lake Ecological Environment and Resource Development, Jiangxi Normal University and by the Program for New Century Excellent Talents in University, China (NCET-04-0492)

3 /s

0 10 20 30

1 - 1

1982 1983 1984 1985

1 - 1 1 - 1 1 - 1

Time, Day (a)

Observation Calculation

3 /s

0 10 20

1 - 1

1 - 1 Time, Day (b)

Observation Calculation

FIGURE 8.3 Observed and simulated daily discharges

(a) (b)

No 053008

0

Date and Hour, 1984

10

20

30

40

50

60

70

80

3 /s

0 20 40 60 80 100 120

Precipitation Observation Calculation

Date and Hour, 1985

No 062500

0 10 20 30 40

3 /s

0 10 20 30 40 50

Precipitation Observation Calculation

Date and Hour, 1985

0

10

20

30

40

50

60

70

80

90

100

3 /s

0 20 40 60 80 100 120 140

No 070219 Precipitation Observation Calculation

Date and Hour, 1987

No 050712

0 20 40 60 80 100 120 140 160 180 200

3 /s

0 20 40 60 80 100 120 140

Precipitation Observation Calculation

FIGURE 8.4 Observed and simulated hourly flood discharges

No 053008

0 10

20

30

40

50

5.30 5.31 5.31 5.31

Date and Hour, 1984

3 /s

Stormflow Baseflow Observation Calculation

FIGURE 8.5 Simulated hydrological components of surface flow, stormflow, and baseflow.

98 Wetland and Water Resource Modeling and Assessment

REFERENCES

Ambroise, B., K Beven, and J Freer 1996 Toward a generalization of the TOPMODEL

concepts: Topographic indices of hydrological similarity Water Resources Research

32(7):2135–2145

Anderson, M., N E Peters, and D Walling, eds 1997 Special Issue: TOPMODEL, Hydro-logical Processes 11(9):1069–1356.

Beven, K J., and M J Kirkby 1979 A physically based variable contributing area model of

basin hydrology Hydrological Sciences Bulletin 24(1):43–69.

Beven, K J., and E Wood 1983 Catchment geomorphology and the dynamics of runoff

contributing areas Journal of Hydrology 65:139–158.

Clapp, R B., T M Scanlon, and S P Timmons 1996 Modifying TOPMODEL to simulate

the separate processes that generate interflow and baseflow Eos Trans AGU, 77(17),

Spring Meet Suppl., S122

Frankenberger, J R., E S Brooks, M T Walter, M F Walter, and T S Steenhuis 1999 A

GIS-based variable source area model Hydrological Processes 13(6):804–822.

¨

Guntner, A., S Uhlembrook, J Seibert, and Ch Leibundgut 1999 Multicriterial validation

of TOPMODEL in a mountainous catchment Hydrological Processes 13:1603–1620.

Hammermeister, D P., G F Kling, and J A Vomocil 1982a Perched water tables on

hill-sides in western Oregon, I: Some factors affecting their development and longevity Soil Sci Soc Am J., 46(4):811–818.

Hornberger, G M., K J Beven, B J Cosby, and D E Sappington 1985 Shenandoah water-shed study: Calibration of a topography-based, variable contributing area hydrological

model to a small forested catchment Water Resources Research 21(12):1841–1850.

Lamb, R., K J Beven, and S Myrabø 1998 Use of spatially distributed water table

observa-tions to constrain uncertainty in a rainfall-runoff model Advances in Water Resources

22(4):305–317

Moore, R D., and J C Thompson 1996 Are water table variations in a shallow forest soil

consistent with the TOPMODEL concept? Water Resources Research 32(3):663–669.

O’Loughlin, E M 1986 Prediction of surface saturation zones in natural catchments by

topographic analysis Water Resources Research 22:794–804.

Robson, A., K J Beven, and C Neal 1992 Towards identifying sources of subsurface flow:

A comparison of components identified by a physically based runoff model and those

determined by chemical mixing techniques Hydrol Processes 6:199–214.

Scanlon, T M., J P Raffensperger, G M Hornberger, and R B Clapp 2000 Shallow sub-surface storm flow in a forested headwater catchment: Observations and modeling

using a modified TOPMODEL Water Resources Research 36(9):2575–2586.

Walter, M T, T S Steenhuis, V K Mehta, D Thongs, M Zion, and E Schneiderman 2002

Refined conceptualization of TOPMODEL for shallow subsurface flows Hydrol Pro-cess 16: 2041–2046.

Woods, R A., M Sivapalan, and J S Robinson 1997 Modeling the spatial variability of

sub-surface runoff using a topographic index Water Resources Research 33(5):1061–1073.

92 Wetland and Water Resource Modeling. ..

FIGURE 8. 2 Map of the study catchment

94 Wetland and Water Resource Modeling and Assessment

8. 3.2...