WETLANDS. Vol. 16, No. 3, September 1996, pp. 347-357 c© 1996, The Society of Wetland Scientists

D E V E L O P M E N T AND APPLICATION OF THE WETLANDS DYNAMIC WATER BUDGET MODEL

Raymond Walton,' Raymond S. Chapman, 2 and Jack E. Davis 3

~ WEST Consultants, hw. Seattle, WA 98121-2357

z Ray Chapman and Associates Vicksburg. M S 39180

3 Coastal Engineering Research Center U.S. Army Engineer Waterways Experiment Station

Vicksburg. M S 39180-0631

Abstract: A Wetlands Dynamic Water Budget Model was developed and applied to support a large field investigation of processes in the Black Swamp wetlands of the Cache River between Patterson and Cotton Plant, Arkansas. The model is called the Wetlands Dynamic Water Budget Model because it provides mag- nitudes for the water budget components, as well as water depths, discharges, and flow velocities throughout the modeled system. The development of the computer program is based on concepts and approaches of a number of programs in common use. It includes three dynamically-linked modules that include all the major components of a typical water budget, including precipitation, canopy interception, overland flow, channel flow, infiltration, evapotranspiration, and horizontal ground-water flow. The surface-wate,' module of the model was applied to the Cache River in Arkansas, and augmented a comprehensive hydrologic field study by filling data gaps that occurred due to gage problems and by providing long-term simulation data for broad areas of the wetland, particularly those far away from any measurement station. The results demonstrated that these wetlands are inundated primarily from the backwater produced at downstream constrictions, rather than from the forward-moving flood wave.

Key Words: wetlands, hydratllics, hydrology, model, simulation, canopy interception, channel flow, over- land flow, infiltration, evapotranspiration, ground~water flow

INTRODUCTION

Water availability and the processes by which it moves through wetlands are critical to the quantity and quality of the functions provided by wetlands. The ability to quantitatively determine hydrology and hy- draulics is essential for effective wetland investiga- tions. This capability can be obtained through field data analysis and the development of models of wet- land processes. Scientists, engineers, and regulators can use such models to assess existing functions and to predict functions for wetlands that may be altered. Field data, simulation models, and simple predictive techniques provide the quantitative capability needed for wetland investigations_

Under the U.S. Army Corps of Engineers Wetland Resem-ch Program, the Black Swamp wetlands along the Cache River between Patterson and Cotton Plant, Arkansas, were studied. To support the field investi-

gations, a Wetlands Dynamic Water Budget Model was developed and used to expand the database for the wetlands. The simulated data were provided to re- searchers requiring spatially and temporally distributed data.

The processes by which water is introduced, tem- porarily stored, and removed from a wetland is com- monly known as the water budget (Figure I):

dS dt (Q + R + Q~ + Q,),

- (Q + E T + O~ + Q,)o (1)

where dS/dt is the rate of change of storage (S) with time (t), Q is surface water flows such as river flows and tides, R is rainfall (including throughfall and drainage), Q~ is ground-water discharge (inflow) or re- charge (outflow), Q, is source/sink terms such as basin inflows and wells, and ET is evapotranspiration. The

347

348 WETLANDS, Volume 16, No. 3, 1996

Shii M It, i{

Figure 1. Schematic of hydrologic processes,

subscript " ' i" represents inflows, and the subscript "o '" represents outflows.

Water is introduced to a wetland through direct pre- cipitation, overland flow (or runoff), channel and ov- erbank flow, ground-water discharge, and tidal inflow. Temporary storage includes canopy, channel, over- bank, basin, and ground-water storage. Water is re~ moved from the wetland through ground-water re- charge, evaporation, plant transpiration, channel, over- land, and tidal outflow.

The importance of these processes varies with wet- land type and depends on regional factors such as cli- mate, geology, and physiography. For example, the water budgets of riverinc and tidal wetlands generally have residence times on the order of hours to days and are primarily controlled by differences in channel and overbank inflows and outflows. Dcpressional wetlands, on the other hand, have residence times ranging from weeks to seasons and depend primarily on direct pre- cipitation, evaporation, transpiration, and ground-wa- ter interactions.

/(/,' l I 9 t t

~a-l - ,

Figure 2. Schematic of link-node representation of a sys- tem.

A comprehensive model that can simulate the hy- drology and hydraulics of a variety of wetland types must include all these processes. In addition, such a model should have the ability to simulate the long- term response of wetlands to hydrologic forcing. This suggests emphasizing efficiency and reducing grid res- olution and dimensionality to perform long simula- tions in a reasonable amount of computer time.

M O D E L D E V E L O P M E N T

The development of the Wetlands Dynamic Water Budget Model is based on the concepts and approaches of a number of commonly-used programs. Various modeling approaches and methodologies were re- viewed (Walton and Chapman 1991), and it was de t ided to base the model development on the link-node method. An application of a link-node model iHales et al. 1990) to the Bolsa Chica tidal wetlands in Cal- ifornia and similar applications showed that the con- ceptually-simple, link-node scheme is flexible, easy to use, and gives accurate results. In addition, it can be readily configured to look like a finite-difference scheme or a " 'block-centered" scheme, such as in the ground-water flow model M O D F L O W (McDonald and Harbaugh 1988). It is a simple example of a "li- h i re-volume" scheme.

The link-node method (Figure 2) divides the system into a series of finite volumes called "nodes" or " junct ions" where stage is defined. Flow's are defined along one-dimensional channels called " l inks" be- tween adjacent nodes. The scheme is flexible because it can easily represent ~imple or complex geometry. The one-dimensional flow's used for the links are sim- ple to program and efficient to solve numerically.

The model developed for wetland studies has three major modules - - sur face water, vertical processes, and

Walton et aL, D Y N A M I C W A T E R B U D G E T MODEL 349

horizontal ground-water flow, and uses explicit t ime stepping, with each of the three modules using the same time interval, St. The structure of the model readily permits the dynamic linkage of horizontal (sur- face-water and/or ground-water flow) and vertical (ponding and infiltration) processes.

Surface Water Modute

The surface water module was designed to simulate channel and overbank flows, tidal forcing, river in- flows, basin inflows, wind shear, flooding and drying, various bot tom friction types, and hydraulic structures (culverts, weirs, and gates). IAnk-node models solve the one-dimensional equations that describe the prop- agation of tong waves through shallow water by con- serving momentum in links and mass or volume at nodes (Figure 21). The approach has three assumptions: (1) the flow is predominantly unidirectional along each link, (2) Coriolis and other accelerations normal to the direction of flow are negligible, and (3) individual links have uniform cross-sectional areas.

The equations for conservation of momentum and volume are written:

OQ + O(~Q2/A) + gAOY = gA(&, - Ss.) (2) Ot Ox c3x

and N

__0V = ~ Qo + Q, 0t n=,

where Q is the flow rate, 13 is the momen tum correc- tion factor, A is the cross-sectional area of the link, g is the acceleration due to gravity, y is the water depth, So is the bed slope, Sf is the friction slope, V is the nodal volume, Q. is the flow rate in link " 'n," N is the number of channels r inks) entering a node, t is the time. x is the longitudinal distance along link, and Q~ are other inflows, such as precipitation, basin inflows, etc.

The version of the hnk-node model used for the surface water module has been modified to permit a variety of link types that depend on which terms with- in the momentum equation are included. I f all the terms are included, the equation is called the "dynamic wave" equation, which is usually used to simulate channel flow. If the acceleration terms are neglected, the equation is called the "diffusion wave" equation. This form is often used to simulate overbank flow.

Most of the overland routing models formulate fric- tion in terms of either Manning's n or Chezy 's C co- eflicients. This assumes that the flow is in the rough turbulent range. In practice, however, as pointed out by Kadlec (1990), a different power law formulation

may give results in better agreement with observa- tions. Thus, in the wetlands model, a variable formu- lation is used:

C U p~ Sf = - - (4) Re,.

where R is the hydraulic radius, u is the longitudinal velocity, C is the friction coefficient, and p,, p~ are powers. If, for example, C=n: , p ,=2, p , - 4 / 3 . Man- ning's equation is obtained, where " 'n" is the Manning friction coefficient.

One feature of the link-node formulation is that it is easy to represent hydraulic structures, such as cul- verts, weirs, and gates, by replacing the momentum equation in that link with the appropriate hydraulic structure equation. The model allows several types of boundary conditions including (1) stage hydrographs, (2) flow hydrographs, (3) loop rating curves, (4) spec- ified rating curves, and (5) inflows from upstream ba- sins.

Vertical Processes Module

The processes simulated in the vertical direction are canopy interception and drainage, infiltration, surface- water evaporation, soil-water evaporation, and tran- spiration. The vertical direction is divided into a num- ber of soil layers (Figure 3), which correspond to the layers in the ground-water model. Above the soil lay- ers are the surface water and canopy layers.

The HELP model (Schroeder et al. 1992) and a pre- decessor, the SPUR model (Wight and Skiles 1987), define the fraction of the net radiation striking the can- opy as

f~ = 1 - e-~,,L*, (5)

where f~ is the fraction of radiation striking canopy, k, is a coefficient (=0 ,4 in HELP and SPUR models), and LAI is the leaf area index (m 2 of leaf area/m 2 of ground). The remainder, I - f~, is used in areas with- out canopies and for direct rainfall for surface water and soil water evaporation.

Of the rainfall, R, falling on each computational cell, the fraction, f~ R, strikes the canopy. Rutter et al. (1975) used a simple mass balance in the canopy that did not include evaporation (which we treat as a sep- arate process):

OC - - = R - D ( 6 ) 0t

where C is the depth of water on canopy, R is the rainfall rate, and D is the drainage from the canopy. The drainage, D, is defined by:

350 WETLANDS, Volume 16, No. 3, 1996

D = 0 f o r C < S (7)

D = D~e L''c-s' for C > S

where D+ is the drainage rate at C=S, h is the drainage coefficient, and S is the depth on canopy when drain- age starts. The drainage from the canopy and the rain directly falling on the ground not covered by the can- opy are then used to define the rate of change of vol- ume of surface water in a cell.

The Wetlands Dynamic Water Budget Model uses the Ritchie (1972) form of Penman 's combination equation that is used in version 2 of the HELP model (Schroeder et al. 1992):

H, ETp = 1.28A A + G (8)

where ETp is the potent ia l evapo t r ansp i r a t i on (ram/days), A is the slope of saturated vapor pressure curve, H~ is the net solar radiation (Langleys/day) es- t imated from the solar radiation, and G is the psychro- metric constant (= 0.68). Using the fraction of radia- tion striking the canopy, f+, the potential evapotrans- piration, ETp, is divided between canopy evaporation and transpiration, and surface water and soil evapo- ration.

Infiltration is modeled using Darcy 's equation for variably-saturated flow. The theoretical description is identical to that for horizontal ground-water flow de- scribed below, except that ks,, the vertical saturated hydraulic conductivity, replaces the horizontal saturat- ed hydraulic conductivity, ksh.

Horizontal Ground-Water Flow Module

The horizontal ground-water flow module simulates variably saturated horizontal flow in the same layers as defined for the vertical processes module. Processes s imula ted include va r i ab ly - sa tu r a t ed hor izonta l ground-water flow, fixed-head boundary conditions, and wells. The subsurface region is divided into a number of layers sufficient to describe vertical varia- tions in soil properties, or to provide sufficient reso- lution of vertical processes (Figure 3). In each layer, the horizontal discretization of the soil is the same as that used in the surface-water module (Figure 2).

Horizontal ground-water flow is based on Darcy 's law for variably saturated flow:

- 4 ) ~9) Q~ = k~AO(Zox

where Os is the horizontal flow in a link, kh is the horizontal hydraulic conductivity, A is the cross-sec- tional area of link, z is the elevation above datum, q+ is the soil moisture tension, and x is the longitudinal distance. The relationship between soil moisture ten-

sion, O, and soil moisture, 0, used is (Brooks and Co> ey 1966):

e * - ;, i I0>

where 0* is the normalized soil moisture content, 0 is the soil moisture content, 0~ is the residual soil mois- ture content, ~ is the saturated soil moisture content, 4" is the air suction (air-entry) head, and k is the pore- size distribution index, giving the form of the horizon- tal hydraulic conductivity, k,, as (Brooks and Corey 1966):

kh = ksh f o r e < 4" ( i l )

kh = k s h | - - ] for + > 4" \*,J where ks h is the saturated horizontal hydraulic con- ductivity. This form for the unsaturated hydraulic conductivity is used in the HELP model and is one of the options in the three-dimensional, variably-saturat- ed, ground-water flow model. PORFLO-3 {Sagar and Runchal 1990).

Once the flow has been computed from Equation 9 and the vertical flow is computed lusing the same ap- proach), the total (potentiometric) head, Hp, at each subsurface node is calculated from the continuity equation:

S A - ~ I = ~ Q , ~ + Q , (12) n = l

where S, is the specific storativity, A, is the surface area of node, n is the link number entering node, N is the number of links entering a node, Q~ is the flow' in link n, and Q, is the source/sink flow to a node. The flow Q.~ in link n is the ground-water flow Q~ for hor- izontal links or infiltration/percolation for vertical links.

The model allows the specification of fixed-head boundary conditions. No-flow boundaries are treated automatically by n o t prescribing an exterior flux at a boundary node. Specified flux boundary conditions can be treated using "wel ls ." Wells are simulated by applying an exterior flux to a specified node in a spec- ified layer.

CACHE RIVER SIMULATIONS

The Black Swamp wetlands are located on the Cache River in eastern Arkansas (Figure 4). There are stream gages located upstream at Patterson and down- stream about 14.5 km north of Cotton Plant. The gages are about 49 river kilometers apart. Two additional temporary stage gages were installed at James Ferry and at B5 on what was termed "Transect B" (Figure

Walton et at., DYNAMIC WATER BUDGET MODEL 351

" ' '

E¢

, ~ . ~

~ ]1 4

• . : i ! i ' . . - . • . . . " . .

" , I ' L ' - : - -" " ,, • . : m l z . . . , . -7 : . ' "..

Z=Znode

z~zg 1

Z=Z TOOt

~ z = z g 3

Figure 3,

~':";i" ~ ~ a " : ' " O :¢~: ' " ~ " " "~:0 ~::~$:~, o:~ o..'~" o ~> 0~ - " ' '~'b ~ " " :~ b ~ o "" "o: "" ":~ ~x ,~ -

• ""-':.L'.-,4 ~, - ~,.,~ 'j¢, .. '"

, ~ . ~ . .~:,~ ~ . o . ~ ! ~

'%::~75%~:7~:~:~,o:".':: "~:-~: :::'~-~'7: '~'¢ ""---~ " ~ : : : ~: ~0~, ... . _ = , o..o

Aquifer i~][[~l / l l~ '""~V I n+i =0 - ' < ~ ' z ~

Aquiclude Representation of soil layers for vertical flow processes.

Z=Zg 4

z:zg n

4). The drainage basin of the Cache River upstream of Patterson is 2.686 krn ~ (Neely et al. 1987). The study area includes 350 kin z of the lower drainage basin and is located about 45kin upstream froni the confluence with the White River. Apwoximately 60 km e of the study area are bottomland hardwood forests and are typical of wooded wetland systems in the lower Mis-

sisslppi River Valley (Kleiss 1993). The wetlands gen- erally lie within 2 kin of the river channel.

A link-node grid was developed for the Black Swanip wetlands consisting of 23 main-channel nodes and 43 overbank nodes, for a total of 66 nodes (Figure 4). The nodes are connected using 115 links. Along the wider parts of the system, where overbank flows

352 WETLANDS, Volume 16, No. 3, 1996

Figure 4.

M J s s m M po,,~

~ / ~ , ~

[ t) .~

\ \ \ \

!

I i 2

\

, . . ~J

",, ~ .,'

"--221

B5 eager i c

e / 2 t-

/ b

(%., Cotton Plant ~-/" Gage

/

)

/ , , ~, River

/ /

i / I l

I I I

/

/James 'Ferry Gage

I I ¢. /

/ I

@ i

Patterson Gage

/ i

KEY . . . . Flood Plain Boundary

= ; Link

I Node

Gage (Note: There Are Links Alon~ Cache River)

0 2OOO 4000 r

Meters

0 400C 8000

Feet

Cache rivm: AR, link-node network.

are more l ikely and very c o m m o n , parallel l inks were used. These l inks cons is t o f one narrow, relatively deep l ink representing the main channel and a second wide , relatively sha l low link defining the immedia te overbank area where f low travels parallel to the main channel . S o m e l inks and nodes were used to represent of f -channel storage.

The surface-water m o d u l e o f the Wetlands D y n a m i c Water Budget Mode l was run using upstream f lows at

the P a t t e r s o n g a g e and w a t e r - s u r f a c e e l e v a t i o n s (stagesJ measured at the Cotton Plant gage down- stream (Figure 4). The m o d e l was run using the dy- namic w a v e equation for the main channel l inks and the diffusion w a v e equation for all overbank links. Ob- servat ions at the B5 and James Ferry gages for Water Year 1990 were arbitrarily chosen to calibrate the mod- el. Calibration was ach ieved by adjusting friction co- eff icients (Manning's "n") and by c l o s e l y re -examin-

Walton et al., DYNAMIC W A T E R BUDGET MODEL 353

Comparison of Stages at B5 Gauge 57'4 /

575 t

. 56"6 t

E ~ 55'21

55,4

54,6 0

i

h i

i' Ii ! [ i !l ~

i ,

j t]

200 400 600 B00 1000 1200 1400 Timefroml October1987 [days)

--- B5 Continuous • BSDiscrete - - Simulated ]

1600

Figure 5. Comparison of simulated and observed river stages along the B transect.

ing system geometry. Validation was assessed by run- ning the model for Water Years 1988 to 1991 and com- paring the results with observations at the B5 and James Ferry gages for Water Year 1991.

The model accurately simulates both the inbank and overbank water levels and downstream flows. Figures 5 and 6 show the computed and observed stages at the B5 and James Ferry gages, respectively, for the four- year validation simulation, where stages arc presented relative to the National Geodetic Vertical Datum (NGVD). In Figure 5, the main stem node adjacent to Transect B (on which the gage B5 was deployed) was used for comparison to illustrate the wetting and dry-

ing at the B5 location. The ground elevation at B5 is approximately 54.6 m and is seen in the figure as the minimum observed stage. Figure 5 also shows some water-surface elevations that were sampled manually at discrete time intervals. Table 1 shows calibration and validation statistics and further demonstrates mod- el accuracy.

Another way of evaluating the accuracy of the mod- el simulation is shown in Figure 7, where observed versus simulated stages are shown for the combined calibration-validation periods at the B5 gage location. This figure shows that the model accurately simulates inbank conditions and reasonably simulates overbank conditions up to the extreme events. Stages for the extreme events are overpredicted by as much as 0.25 m, suggesting either that the extent of flooding is greater than actually simulated or that the gages had problems recording extreme events. It is also possible that the rating curves used to estimate flows at Patter- son are less accurate at extreme events, particularly when overbank flooding is involved. The "random' scatter in the figure for some observed values close to 55.5 meters NGVD is actually related to the same event, but the reason for the differences is not yet un- derstood. Finally, observed and computed hydroper- iods for the same period are compared at the B5 gage location (Figure 8) and confirm that the distribution of model results agrees well with observations. The dis- crepancies at the smaller water depths are possibly due to local depression storage on the floodplain not ex- plicitly included in the model.

The modeling exercise provides insight into the hy

58

57 -

56

55

54

5 2 - - - - ~ - - , ~ ' - - 0 200 400 600 800 1000 12QO 1400

Timefrom 10c tober l987(days) 1600

i - - Obse rved o Simulated I

Figure 6. Comparison of simulated and observed river stages at the James Ferry gage.

354 W E T L A N D S , V o l u m e 16, No. 3, t996

Table 1. Calibration and validation statistics for the t35 and James River gage locations. All values expressed in meters.

Calibration Period Validation Period Combined Period

Statistic B5 James Ferry B5 James Ferry B5 James Ferry

Ave. difference 0.08 0.11 0,04 0.12 0.06 0. ! I Ave. abs. difference 0.09 0.15 0.15 (t,22 0.12 0.19 Root mean square 0.14 0.20 0.19 0.29 0. [ 7 0.25 Ave. observed stage 55.27 54.22 55.46 54.61 55.36 54.41 Ave. simulated stage 55.19 54. I 1 55.42 54.49 55.30 54.29

d ro log ic and hydrau l ic p rocesses that cont ro l the Cache River we t l and sys tem. It was con f i rmed that there is a s ignif icant b a c k w a t e r effect resul t ing from the cons t r ic t ions in the o v e r b a n k s near J ames F e r r y and a lso near the Cot ton P lan t gage downs t r eam. F l o o d i n g wi th in the lower part o f the Black S w a m p is genera l ly p roduced by backwa te r from these cons t r ic - t ions ra ther than f rom inunda t ion clue to the p ropaga - t ion or d o w n s t r e a m advance o f the f lood wave (F igure 9). An ana lys i s o f h y d r o p e r i o d s for the left and right ove rbanks ( v i e w e d downs t r eam, F igure 10) shows that the percen t o f t ime that the f loodpla in is inunda ted increases wi th d i s tance downs t r eam in the l ower two- thirds o f the sys tem. The upper third o f Ihe sys t em gene ra l ly lies above this b a c k w a t e r ef fec t and is f lood- ed by lhe downs t r eam p ropaga t i on o f f loods. A no the r obse rva t i on is that f lood events on the Cache River typ ica l ly affect the sys tem for a pe r iod o f a few days to a few weeks. This t ime scale is much longer than the t ime for f loodwaters to move la tera l ly over the f loodpla ins , Hence , it may be r easonab le to approxi mate the o v e r b a n k water - sur face e leva t ions based on

the water - sur face e leva t ion es t ima ted in the adjacent sect ion o f the main r iver channel .

To e x a m i n e the effects o f ver t ical p rocesses such as inf i l t rat ion and evapo t r ansp i r a t ion on sys tem hydro lo - gy and hydrau l ics , the sur face wa te r and vert ical pro- cesses m o d u l e s were used to e x a m i n e thei r in teract ion. Hor izon ta l ground wate r flow was not inc luded . Us ing reasonab le values o f soil and g round wate r pa rame te r s (Gon th ie r and Kle iss 1995), the mode l resul ts indicat - ed that direct rainfall , infi l trat ion, and evapo t r ansp i r a - t ion p lay a minor role c o m p a r e d to su r face -wa te r in- f lows and outf lows. Whi l e the es t imates seem reason- able, it should be noted that there were insuf l ic ien t data to ca l ibra te and va l ida te the ver t ical p rocesses modu le for the Cache River.

C O N C L U D I N G R E M A R K S

Water ava i l ab i l i ty and the processes by which it moves are cr i t ical to the quant i ty and qual i ty o f the func t ions p rov ided by wet lands , In an effort to quan- t i ta t ively evalua te we t land hydro logy , we d e v e l o p e d

57

Figure 7.

~-56.5 CI > (..9 Z

g 56 v

0") 'c, 55.5 ,n) P

.O 0 55

~ • ~ S ~ . "~ , - 2 I 2 - -

' : l t - k l

,j ,:.3~, -~

c2, tJ J '~ j t J ~ ' ' l

54.5 . . . . . . . . . . . . . . . . . . . . 54.5 55 55.5 56 56.5

Simulated Stage (m, NGVD)

Compari.~on of simulated and observed river stage~ at the B5 gage.

57

W a l t o n et al., D Y N A M I C W A T E R B U D G E T M O D E L 355

500 , :

g 400

300

200

~- 100

54.5 55.0 55.5 56_0 56.5 57.0 Elevation (rn)

Observed ~ Cumulative Observed • Predicted A Cumula i ivePred ic ted]

Figure 8. Hydroperiod statistics at the B5 gage.

60

58

~ 5 6

O~

~, 54

52

50

: I ? i i i ~ I , i ~ I i q } i , i , I ~ I

0 30 60 90 120 150 180 210 240 270 300 330 360 Time (Days from 1-Oct-1989)

I c~ P~ttorson - - B5 ~ James Ferry - - Cotton Plant 1

Figure 9. Stages for water year 1990.

356 WETLANDS, Volume 16. No. 3, 1996

40

3o

r - i o )

._E 20 I - "5 e - 0~

g_10

r~

I " . .

i . i

J /

' / ! ! t/+ !

/ +; I . ~I!

m.\ / ,," I "m

0 . . . . . . .

0 5 10 15 20 Distance from Upstream Gauge (km)

I

/

I I

25 30

f I i q Left Overbank i [

• -I-- Right Overbank

Figure 10. Percentage of time that the left and right overbank areas are inundated.

the Wetlands Dynamic Water Budget Model to dynam- ically incorporate the important hydrologic and hy- draulic processes found in various wetland types. The model has three modules - - sur face water, vertical pro- cesses, and horizontal ground-water flow. It is based on an e, xplicit, link-node technique, and includes many of the processes, algorithms, and solution methods found in commonly used models. The result is a model that is relatively simple, efficient, and flexible, which can be used to simulate the long periods often needed by wetland researchers to evaluate functions.

Model simulations on the Cache River wetlands confirmed that the downstream constrictions create a backwater effect during large flow events that inun- dates the upstream wetlands. A database was devel- oped from the model simulations that provides addi- tional information to support field data collection el- torts. The database contains histories of stage and vol- ume at each of the 66 nodes in the model and histories of flows and velocities at each of the 115 links. The information developed from the model simulation was used, lbr example, to examine the frequency of inun- dation at the B5 gage location (Figure 8). Aside from the ability of the model to extend the existing field information to provide spatial coverage, useful for syn- optic interpretation of wetland conditions, it also pro- vides useful temporal information. This ability enables interpretation of the system between discrete sampling periods and during periods of instrument failure, such

as during January 1991 (Figure 5), when the water level overtopped the B5 gage at about simulation day 1,200. Finally, the model was used to demonstrate how the effects of wetland modifications could be assessed.

To date, the Wetlands Dynamic Water Budget Mod- el and its predecessor program have been successfully applied to riverine and tidal wetlands. We believe that the surface-water routines have been adequately veri- fied. In order to more completely test the accuracy and adequacy of the remaining process modules, it would be useful to apply the model to wetlands characterized by pr imary interactions between horizontal ground+ water flow, infiltration, and evapotranspiration pro- cesses. An excellent example of such wetlands is the prairie potholes of the northern plains (Winter 1989). Finally, the interactions between all the modules can be studied by applying the water-budget model at the landscape or watershed (basin) level. At this level, the relative importance of each of the water-budget com- ponents will vary both spatially and temporally.

A C K N O W L E D G M E N T S

The work was funded by the U.S. Army Corps of Engineers Wetland Research Program. Permission to publish this paper was granted by the Chief of Engi- neers.

W a l t o n e t a l . , D Y N A M I C W A T E R B U D G E T M O D E L 357

L I T E R A T U R E C I T E D

Brooks, R.H. and A.T. Corey. 1966 Properties of porous media affecting fluid flow. ASCE Journal of Irrigation and Drainage Di- vision 92:61-88.

Gonthiet, G.J. and B.A. Kleiss. 1993. Ground-water flow patterns and water budget of a bottomland forested wetland: Black Swamp, Eastern Arkansas. U.S. Geological Survey Water Resources Re- port 95-4192.

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Manuscript received 28 March 1995; revision received 8 September 1995; accepted 17 January 1996.