estimating shallow groundwater recharge in the headwaters of the liverpool plains using swat

HYDROLOGICAL PROCESSESHydrol. Process. 19, 795–807 (2005)Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.5617

Estimating shallow groundwater recharge in theheadwaters of the Liverpool Plains using SWAT

H. Sun* and P. S. CornishLandscape and Ecosystems Management, University of Western Sydney, Penrith South DC, NSW 1797, Australia

Abstract:

A physically based catchment model (SWAT) was used for recharge estimation in the headwaters of the Liverpool Plainsin NSW, Australia. The study used water balance modelling at the catchment scale to derive parameters for long-termrecharge estimation. The derived parameters were further assessed at a subcatchment scale. Modelling results suggestthat recharge occurs only in wet years, and is dominated by a few significant years or periods. The results were matchedby independently observed bore data across the study area in the past 30 years. The study suggests that variationsin recharge can be primarily explained by the climatic factor rather than land-use changes. The study estimated lessrecharge than previous studies where point scale modelling results have been scaled up to the catchment scale. Itsuggests that a catchment-based approach is needed for recharge estimation at the catchment scale. The study indicatesthat the current model may overestimate runoff on cracking vertosols under dry conditions where improvement islikely needed. The need for long-term runoff and bore monitoring data to confidently establish the relationships amongwater balance/recharge estimation and groundwater level variation is discussed. SWAT provides an alternative to pointscale modelling for evaluating recharge and its response to changes in land use and land management. Copyright 2005 John Wiley & Sons, Ltd.

KEY WORDS recharge; drainage; modelling; groundwater; SWAT

INTRODUCTION

The Liverpool Plains is situated in the northwest slopes of New South Wales (NSW), covering an areaof 11 728 km2. It is part of the Namoi catchment within the Murray Darling basin. The upper Mooki Rivercatchment is part of the headwaters of the Liverpool Plains, covering an area of approximately 2220 km2. Ourstudy area is a subcatchment of the upper Mooki River with a catchment area of 437 km2. This subcatchmentincludes Big Jacks Ck, Little Jacks Ck, Millers Ck and MacDonalds Ck (referred to hereafter as the BJCcatchment). The BJC catchment has generally vertosol soils reaching dozens of metres in depth, except onrange tops and limited sandstone hill slopes (Broughton, 1994).

Before European settlement (since 1830), the Liverpool Plains was grassland on the extensive flood plains,and woodland on the ranges and sandy hills. It was predominantly used for sheep and cattle grazing until the1880s (Banks, 1998). Cropping initially developed on the lighter textured soils on the sandstone hill slopes.The extensive vertosols of the basalt slopes and plains were developed for wheat cropping only after WorldWar II, with the availability of higher powered tractors. Since the 1970s a mixed winter and summer croppingrotation has been developed. These land-use developments cleared a major part of the woodland on the hillsand pasture on the plains. Long fallow for water conservation has been a common practice, although sincethe late 1980s the practice has declined in favour of more intensive cropping.

The black, cracking vertosol soil with high clay content (up to 70% plus) is derived from the alluvialoutwash of the Liverpool Range basalts. In recent years salinity has been found in some areas of the plains. An

* Correspondence to: Dr H. Sun, Water Corporation, 629 Newcastle St, Leederville WA 6009, PO Box 1000, Leederville 6902 WA, Australia.E-mail: [email protected]

Received 20 December 2001Copyright 2005 John Wiley & Sons, Ltd. Accepted 7 May 2004

796 H. SUN AND P. S. CORNISH

estimated 50 000 ha are perceived as at high risk of being salinized, while 195 000 ha of land has groundwaterwithin 5 m of the soil surface and is regarded as potentially at risk of salinity (Broughton, 1994). This isbelieved to have resulted from the clearing of trees on foot slopes, cropping and long fallowing.

Several recent studies have focused on groundwater recharge or drainage in the Liverpool Plains (Timmset al., 2001; Abbs and Littleboy, 1998; Ringrose-Voase and Cresswell, 2000; Broughton, 1994; Greiner, 1994,1997). Broughton’s study (1994) provides detailed information on the geology and the bore data monitored inthe upper Mooki River catchment during 1971–1994. This information is valuable for understanding the locallandscape processes with regard to groundwater recharge. Timms et al. (2001) provide further information onrecharge in a nearby headwater catchment west of BJC in the upper Mooki catchment. The work of Abbsand Littleboy (1998) was based on modelling with PERFECT, a point scale crop model capable of modellinghydrological processes at the same scale (Littleboy et al., 1989). Greiner (1997) and Ringrose-Voase andCresswell (2000) both used the cropping systems model APSIM, which is also a point model. While previousmodelling efforts are helpful in understanding landscape processes on a small scale, care needs to be takenwhen applying such modelling results to a large catchment, as hydrological processes are highly dependenton the scale of modelling.

A catchment is an integrated system with water, sediment and chemicals moving through the system intheir unique ways underpinned by such features as topography, geology, soils and land uses. Modelling at asmall scale is generally able to include the latter two features but not the former two, which are importantcomponents for water balance estimation at a catchment scale. It can also be quite difficult to observe andmonitor groundwater flow at a small scale. Small-scale studies often rely on soil moisture data to derivemodelling results, assuming runoff is zero or a minor factor. As a result, a model that can estimate rechargeon a catchment scale is needed to encapsulate the major processes that are important to recharge at thatparticular scale. Such a modelling approach should provide results that are supported by observed runoff data,bore data, as well as water quality data at a catchment scale.

The aim of this study is firstly to evaluate SWAT as a tool for recharge estimation at a catchment scale, andcompare the results with point scale modelling. Secondly, to identify certain areas that might be improvedin SWAT modelling in relation to modelling the vertosol soils. And thirdly, to identify potential areas whereimprovement on current crop models can be made for recharge estimation.

APPROACHES USED IN THIS STUDY

This study derives shallow groundwater recharge and long-term recharge patterns on a catchment scale inthe Liverpool Plains using the SWAT (Soil Water Assessment Tool) model. Water balance calibration andverification on a catchment and subcatchment scale with different land uses was done as the basis for rechargeestimation in the catchment. Modelling results for recharge were then compared to the independent bore datain the catchment. Estimates of recharge relating to land uses and climate were made, and recharge patternsthat occurred in the past are presented. Based on the modelling results, some important conclusions can bedrawn regarding the scale of modelling, salinity risk of the study catchment, climate and land use impact onrecharge, data needs and in particular, what can be improved in many crop models that deal with rechargeestimation.

SOME IMPORTANT COMPONENTS OF THE SWAT MODEL FOR THIS STUDY

SWAT is a catchment or river basin scale model developed for the USDA Agricultural Research Service(ARS) (Neitsch et al., 2001). It is a physically based model able to estimate the impact of land managementpractices on water, sediment and agricultural chemicals on a subcatchment and land use unit scale over longperiods of time.

Copyright 2005 John Wiley & Sons, Ltd. Hydrol. Process. 19, 795–807 (2005)

RECHARGE ESTIMATION USING SWAT 797

Potential evapotranspiration may be estimated by one of three methods: Hargreaves (Hargreaves et al.,1985); Priestley–Taylor (Priestley and Taylor, 1972); and Penman–Monteith (Monteith, 1965). The Har-greaves method uses only daily maximum and minimum temperatures to derive daily potential evapo-transpiration, while the others use more physical parameters for estimation, which are often difficult toobtain at a catchment scale. It has been shown that the Hargreaves method is close to the calculations ofPenman–Monteith. Therefore, the Hargreaves method was used in this study.

Surface runoff is computed using a modified SCS curve number method based on moisture content (SoilConservation Service, 1972). Although such a modification can be more accurate in identifying the soil watermoisture condition, it nevertheless made the runoff estimation dependent on soil profile information, such asthe soil layer classification, and in particular the soil profile depth. Compared to the original SCS method,which describes moisture condition as a function of antecedent rainfall, the modified curve number methodmay cause calibration problems relating to soil structure, profile depth and plants grown. For both runoff andrecharge estimation, the rooting depths of plants and the growth season are the primary drivers governing thesoil water processes.

Soils are divided into layers and water balance is performed in each soil layer according to saturatedconductivity and soil water content of the soil layers. When rainfall occurs, surface runoff is estimated first,and the rest of the rainfall enters into the soil profile for redistribution. Subsurface runoff is estimated using asimplified slope storage concept where water flow through soil is estimated by using the saturated conductivityof the soil layer and the slope length. Vertical water movement goes through the soil layers when the soilwater content exceeds the field capacity of the layers. It enters into an unsaturated vadose zone when itpasses through the lowest soil layer, which becomes recharge to shallow groundwater. Recharge to shallowgroundwater may discharge to the catchment outlet as groundwater. SWAT allows the recharge to ‘revap’from the shallow groundwater through the unsaturated vadose zone by capillary activity to meet the needs ofevapotranspiration when the soil profile is dry. This means that recharge to the shallow groundwater does notnecessarily all become groundwater and discharge, rather it can be redrawn upwards by soil water potentialduring dry periods. This is a distinct feature of SWAT, as many other models regard recharge beyond the rootzone as drainage lost permanently.

CATCHMENT DESCRIPTION AND PARAMETER DERIVATION

Figure 1 is the studied catchment (BJC) and its position in NSW, Australia. The 437 km2 catchment ispartitioned into 12 subcatchments. The catchment was derived from a 25 ð 25 m2 digital elevation map andoverlaid with a digital land-use map. The middle and lower part of the catchment is primarily cropping area,surrounded by pasture and some remnant forest and ranges situated largely at the upper catchment boundary.Runoff was observed at the catchment outlet, Warrah Ridge, from 1996 to 2000 (DLWC, 2001). WarrahRidge is located on the flood plain where slope gradients are generally less than 1%. Observed data fromAugust 2000 were also obtained at the outlet of subcatchment 12 (Sandstone), which has subcatchment 9draining into it (at the lower right-hand side of Figure 1). The combined subcatchment of 12 and 9 is namedBJU �67 km2�, which was further partitioned into nine subcatchments and modelled separately (Figure 2).‘Sandstone’ is located just above the flood plain.

Daily rainfall data were obtained from 14 rain stations surrounding BJC over the past 44 years. Rainfallwas derived for each subcatchment using up to four of the closest stations to the centre of the subcatchment.A distance-weighted method was used to derive the subcatchment rainfall using the chosen stations. Averageannual rainfall for the study catchment is 738 mm, which is slightly summer dominant.

Modelling was first run on the larger BJC catchment (a mixture of cropping and grazing plus a small portionof woodland and forest), which has 5 years of observed runoff data, to derive the necessary parameters. SWATwas then run on the smaller BJU, which is predominantly pasture with less than 10% of forest and cropping,respectively. Observed data for BJU was used to confirm that parameters obtained from modelling of the



Study Area

MacDonalds Ck.

North

Warrah RidgeQuirindi

Grazing

Cropping

Sandstone

Big Jacks Ck.

5 km

Woodland

10

12

9

64

511

8

1

2

3

7

Figure 1. The studied catchment BJC �437 km2� partitioned into 12 subcatchments, its land use, drainage system and relative position inNSW, Australia; BJC is part of the upper Mooki River catchment forming part of the Liverpool Plains—the Mooki drains into the Namoi

River and forms part of the Darling River in the Murray Darling basin

whole catchment can be applied to subcatchments having different land uses and further subdivided. Figure 2shows the partitioned BJU and its land uses of predominantly grazing with limited areas of cropping andforest. For catchment BJC, two major land uses of grazing and cropping were formulated, as the forest andother land uses are minor, while for BJU a forest part is added, as it is more prominent. The differentiationin land uses is a measure to derive better parameters by distinguishing the land uses modelled on the twocatchments. This is seen as a further measure for improved catchment modelling and parameter verification.Land uses of BJC and BJU are shown in Table I.

For catchment BJC, runoff from MacDonalds Ck and part of the runoff from Millers Ck (the creek on theimmediate right-hand side of the MacDonalds Ck in Figure 1) was diverted out of the catchment throughartificial drainage channelling, so that observed runoff at Warrah Ridge represents only part of the totalcatchment runoff. The area with runoff diverted is estimated at 200 km2. Runoff from these areas wastherefore deducted from the total runoff estimated for the catchment. For simplicity, the deduction was doneon an areal basis once the estimated daily runoff for the whole catchment was obtained. That is, of the437 km2 of the catchment, only 237 km2 contributes runoff to the catchment outlet at Warrah Ridge.

Two soil layers are defined in modelling for the main catchment BJC, for both land uses of grazing onperennial pasture and cropping, with rooting depths of 2 m and 1Ð3 m, respectively. For the subcatchmentBJU, a forest part with rooting depth of 3Ð5 m is added to further characterize land uses at a smaller scale.These rooting depths are the default values defined in the land cover/plant databases of SWAT, which aretaken as standard estimates for the land uses involved. Wheat was the predominant crop in the upper Mookicatchment until the 1970s, when summer cropping was gradually introduced, hence annual wheat is used as



North

Sandstone

Cropping

Grazing

Woodland

1 km

1

9

2

4

3

6

78

5

Figure 2. Subcatchments 12 and 9 which form BJU at Sandstone (67 km2, lower right corner of BJC in Figure 1) were further divided intonine smaller subcatchments with a land use of predominantly pasture. This is the headwater of Big Jacks Ck

Table I. Land use and catchment areas of BJC and BJU

Land uses: Agriculture(%)

Pasture(%)

Forest(%)

Other(%)

Catchment area�km2�

BJC 28Ð10 65Ð83 5Ð91 0Ð15 437Ð40BJU 5Ð77 85Ð31 8Ð92 0 66Ð92

a major scenario in crop modelling. Grazing on perennial pasture is simulated for most of the year (lowestmonthly temperature above 0 °C). Major soil parameters and values used are listed in Table II, and majorrunoff estimation parameters and values used are listed in Table III. These parameters are explained in theAppendix. The soil parameter values were adapted from soil surveys (Banks, 1998) and consensus data andrepresentative estimations for clay soils (e.g., Schwab et al., 1996). Runoff parameters (surface, subsurfaceand groundwater) are essentially derived by fitting the observed hydrograph. Other than soil depth differences,the soil parameters for all land uses are assumed to be the same at the same depth. Parameters not listed areused with their default values, which were considered as minor parameters.

MODELLING RESULTS

Runoff data during 1996–1998 was used for calibration for catchment BJC, with the first two years being dryyears and the last a very wet year. Figure 3 shows the observed and calibrated runoff for 1998, which was thewettest year since 1957 for catchment BJC. Annual rainfall frequency analysis over 119 years rainfall datafrom nearby Quirindi (15 km from catchment outlet) showed that rainfall in 1998 has an average recurrenceinterval (ARI) of 40 years (Sun and Cornish, unpublished work). Observed high peak flows in 1998 weretempered by overbank flow during the high flood period, noting that the BJC gauging site is located at the



Table II. Soil layers and soil parameters in association with land uses, defaultrooting depths for wheat, sorghum and perennial pasture, and forest/rangesare 1Ð3, 2 and 3Ð5 m respectively (a description of the parameters is found in

the Appendix)

Soil depth

Soil parameters 0–1 m 1–2 m 2–3Ð5 m

SOL-Z (mm) 1000 2000 3500SOL-BD �g/cm3) 1Ð1 1Ð1 1Ð2SOL-AWC (mm/mm) 0Ð2 0Ð15 0Ð1SOL-K (mm/h) 10 5 1CLAY (% soil weight) 55 70 60

Table III. Surface and subsurface runoff, groundwater estimation parameter values used in SWAT for the studied catchment(a description of the parameters is found in the Appendix)

Sur/Sub runoffparameters:

CN2/Pasture

CN2/Crop

CN2/Forest

ESCO EPCO OV-N LAT-TTIME

SLSOIL CH-N1 CH-N2

Calibrated values 71 78 70 0Ð001 1 0Ð15 5 10 0Ð04 0Ð1

Groundwaterparameters:

SHALLST GW-DELAY

ALPHA-BF

GWQMN GW-REVAP

REVAPMN

Calibrated values 1 100 0Ð003 2 0Ð02 10

0

5

10

15

20

25

1 156 187 218 249 280 311 342

Run

off (

mm

)

32 63 94 125

Days of 1998

Observed Predicted

Figure 3. Observed and calibrated runoff for BJC in 1998, one of the wettest years in 44 years of modelling; major observed peaks aretempered by overbank flow effect, which is not modelled in simulation

flood plain. As with most catchment models, the predicted values do not take the overbank effect into account,so that predicted high peak flows are higher than those observed. The availability of both dry and wet yeardata for model calibration is significant to define parameter values, and it is very fortunate to have observed



wet year data in a short monitoring period, considering the generally dry conditions often found in manyAustralian catchments.

Verification of runoff prediction for BJC used data for 1999 and 2000. Figure 4 shows the predicted andobserved runoff for catchment BJC in the years 1996–2000. Since the calibration process is primarily basedon storm fitting rather than annual total runoff fitting, the overall annual runoff is overestimated. For the wetyears (1998, 2000), this was related to overbank flow as observed runoff is likely an underobservation of thereal runoff during flood events. For dry years, overestimation of runoff appears to be a result of bypass flowunder dry soil conditions, when the soil is deeply cracked. This was not effectively modelled, and is a majorcause of estimation error. Improvement to the SWAT model appears to be needed in this regard.

Should the water balance calibration be based on annual total runoff rather than storm fitting as in thisstudy, the matching in Figure 4 can be greatly improved; however, this may involve changes in soil waterparameters and rooting depth for cropping, which has been dealt with in a further study (Sun and Cornish,2003).

In addition to modelling on a catchment scale, modelling was also done on a subcatchment scale to evaluateif the parameters estimated in the bigger catchment can also be applied at subcatchment scale with a forestpart added to the existing land uses of cropping and pasture. The predicted runoff for the smaller catchmentBJC during August–December 2000 (observed runoff starting from August 2000) is 110 mm compared tothe observed of 93 mm. Other than a minor adjustment to the exponential decay coefficient of groundwaterflow, the estimation in BJU was done with the same set of parameter values as used in the larger catchmentBJC. The adjustment of the groundwater parameter delays the groundwater flow to a perennial baseflow asobserved in BJU, which is slightly different to that observed at the larger catchment scale.

The process of simulating runoff in the study catchment not only resulted in soil and runoff parametersbeing defined, it also allows the delineation of the amount of recharge that is associated with groundwaterestimation. In other words, once the runoff calibration and prediction is finished, recharge estimation is finishedas well. Figure 5 shows the estimated annual recharge from 1957 to 2000 assuming no change in land usesover the period, with annual wheat cropping on the agricultural land and grazing on perennial pasture. It isclear from Figure 5 that recharge in the last 20 years has been dominated by the period surrounding 1989 and1998. The estimated annual average recharge for the past 44 years is 5Ð3 mm/yr. Figure 5 also shows a trendof dry and wet cycles in recharge throughout the modelling period. Over the last two decades (1980s and1990s), the estimated recharge rate was approximately 6 mm/yr (1980s) and 8 mm/yr (1990s), respectively,while the two decades before these showed a recharge of approximately 3 mm/yr. Estimated recharge in thelast two decades is more than double that of the previous two decades, suggesting that the climate factor

0

20

40

60

80

100

120

140

160

1996 1997 1998 1999 2000

Run

off (

mm

)

Years

Predicted runoff Observed runoff

Figure 4. Estimated and observed runoff for BJC during 1996–2000. Estimation is based on storm fitting rather than annual total runofffitting. Some overestimation of runoff is apparently due to overbank flow effect in wet years (1998, 2000) and bypass flow in dry years



0

10

20

30

40

50

60

70

80

57 60 63 66 69 72 75 78 81 84 87 90 93 96 99

Rec

harg

e (m

m/y

ear)

Years

Figure 5. Estimated recharge for BJC of 44 years during 1957–2000, which showed cycles of wet and dry periods; this is particularly sofor the last two decades of modelling—1989 and 1998 make up over 50% of the total recharge in 44 years

needs to be considered along with land clearing and cropping as potential contributors to groundwater levelrises.

RECHARGE AND INDEPENDENTLY OBSERVED BORE DATA

Bore data from 1971 to 1992 has been investigated comprehensively in the upper Mooki catchment using369 bores (Broughton, 1994). The two major aquifers in the studied area, the flood plain alluvium and theLiverpool Ranges, had a median water level rise of 55 mm/yr and 60 mm/yr, respectively (Broughton, 1994).In a study on recharge in Yarramanbah Ck, approximately 10 km west of the study catchment, also in theupper Mooki catchment, Timms et al. (2001) derived a specific yield (the ratio of drainable volume to thebulk volume of soil) of 0Ð067, based on observation of water level rise in one of their piezometers in a stormin June 1998. Similarly, a specific yield of 0Ð089 was derived from another observation close to the study area(Young et al., 2003). The average annual recharge during 1971–1992 over the catchment BJC is estimated(using SWAT) at 4Ð9 mm/yr in this study. Using an average specific yield of 0Ð078 would result in an annualwater level rise of 62 mm (i.e. 4Ð9/0Ð078). This is close to the observed average annual water level rises forthe two major aquifer types in the study area, of 55 and 60 mm/yr between 1971–1992 (Broughton, 1994).This demonstrates that estimated recharge in this study is matched closely by the independently observed boredata in the upper Mooki catchment.

The predicted recharge is also supported by the four bore wells located in the flood plain area of BJC.These four bores returned an average water level rise of 45 mm during 1971–1992. Figure 6 shows that thetrend of recharge follows bore water level changes closely. From Figure 6 it is clear that 1991 returned thehighest water levels for two of the four bore data records, while the other two were marginally lower thantheir highest water levels ever recorded. This suggests that it does not take long (up to two years for thesebores) for major recharge to reach the groundwater surface.

Further modelling was undertaken to determine the impact of land use changes on recharge. If the croppingland of BJC, which is approximately 25% of the catchment area, is planted with sorghum every summer (witha rooting depth of 2Ð0 m) rather than wheat every winter (with a rooting depth of 1Ð3 m), the estimated annualcatchment recharge (cropping and grazing) would reduce from 5Ð3 mm to 3Ð1 mm. If the total catchment BJCis assumed to be perennial pasture with a rooting depth of 2 m, or the cropping area is converted to perennialpasture, then the annual average recharge is further reduced to 2Ð2 mm. These predictions suggest that rechargeis related to the growth (almost continued growth for pasture and seasonal growth for crops) and root depth of



71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92

Bor

e w

ater

leve

l (m

)

Rec

harg

e (m

m)

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

50.00

40.00

30.00

20.00

10.00

5.00

15.00

25.00

35.00

45.00

0.00

Years

Bore 30059 Bore 30060 Bore 30061 Bore 30175 percolation

Figure 6. Comparison of water level changes of four bores at the flood plain area of BJC (left axis) with recharge (right axis) during1971–1992, showing annual groundwater level fluctuations follow recharge consistently

plants, and soil water holding capacity plays a major role in estimated recharge. Based on the above rechargeestimates on perennial pasture and mixed land uses and the area of each land use, recharge for a single landuse in the catchment can be estimated. This was done by solving the equation that the sum of recharge oneach land use multiplied by its area (% of catchment area) equals the catchment recharge rate.

Table IV shows the recharge levels of different land uses within BJC and a comparison with some previousstudies. The result suggests that generally less recharge is predicted in this study than the point scale studies.The last two rows in Table IV show the estimates from soils throughout the Liverpool Plains. The ‘Hudson’site is situated on the foot slopes of the Liverpool Ranges 5 km west of BJC (Ringrose-Voase and Cresswell,2000).

DISCUSSION

The two studies that were based on observed runoff data shown in Table IV are this study and the ‘Hudson’experiment where 4 years of data are available. The estimation differences between this study and ‘Hudson’are not surprising, considering there are six orders of difference in size, from a plot scale of 600 m2 at

Table IV. Estimated average annual recharge for different land uses in the catchment and comparison with otherstudies. The study of Ringrose-Voase and Cresswell (2000) used APSIM on ‘Hudson’ as well as on soils in the

Liverpool Plains; the study of Abbs and Littleboy (1998) used PERFECT on soils in the Liverpool Plains

Recharge (mm/yr) byland uses/studies

Forest/ranges

Perennialpasture

Annualwheat

Annualsorghum

Catchment

BJC/SWAT 0 2 15 6 5Ð3Hudson/APSIM 0 0 37 1 55LP soils/APSIM 0 15 70 29 n/aLP soils/PERFECT n/a n/a 55 50 n/a

n/a, not available.



‘Hudson’ to the BJC at 437 km2. An analysis of long-term runoff studies at the plot scale showed thatobserved runoff could be an order apart for adjacent plots of the same land use (Edwards, 1987). Obviously,runoff observation and estimation would have a major impact on estimated recharge. A parameter sensitivitytest showed that a 15% change in the curve number (used for surface runoff) has a 36% impact on theestimated recharge (Sun and Cornish, 2003). Studies without runoff observations may expect much largeruncertainties in recharge estimation. The first two estimations in Table IV (shown in rows 2 and 3) includerunoff data, while the bottom two rows lack a runoff estimation component.

The ‘Hudson’ study (Ringrose-Voase and Cresswell, 2000) was extended to a catchment scale resulting inlarge runoff and recharge estimations, which are not supported by observed runoff data at the catchment scaleor the published groundwater data of Broughton (1994). This underlines the risk of scaling up from pointto catchment scale. Observed catchment runoff plays a controlling part in defining the modelling processes,such as the soil water parameters, the component of surface, subsurface and groundwater in water balance,and their temporal distribution. Without such a critical component to control errors that might arise frommodelling, the risk of modelling is substantially increased. Spatial scale is clearly one of the most importantcontrollers in hydrological processes, and this is the very reason that all hydrological models have definedspatial application ranges. Extending point models to catchments without observed data at the catchment scaleas a catchment error controller should be avoided.

Recharge level varies significantly over the years, while average annual catchment rainfall in the fourdecades since 1957 has not shown significant variations on a long-term or decadal basis. There appear to becycles of wet and dry periods (in terms of drainage generation) occurring during the 44 years of modelling,with major wet years dominating recharge in the catchment. Estimated recharge in 1989 and 1998 constitutesover 50% of the total recharge in the 44 years. The last two decades have shown increased levels of recharge,mostly due to the climatic factor. The introduction of summer crops (after the 1970s), such as summer grainsorghum, has a positive effect on reducing recharge compared to traditional spring wheat in the study area.All the studies cited predict this to varying degrees. This is because summer is the major rainfall season inthe study area, and summer crops are generally able to take more moisture out of the soil profile, leaving adrier soil profile to hold subsequent rainfall.

Long-term bore data in the upper Mooki catchment provides the best independent evidence for rechargeestimation. Using bore data of 1992–1999 in Yarramanbah Ck next to BJC, Timms et al. (2001) foundthat there was no significant rise in the shallow groundwater table during the period. Most water tablechanges were of the nature of seasonal changes, particularly in the flood plain area of lower Yarramanbah Ckwhere groundwater level is shallower and dominated by seasonal variations in groundwater table. The middleYarramanbah Ck, however, showed a declining trend of groundwater table from 1992 to early 1998 before themajor storms that occurred after mid-1998 (Timms et al., 2001). Modelling results show little recharge between1992–1997 inclusive, which dictates a declining groundwater table. This is further evidence, in addition tothe bore data in BJC from 1971 to 1992, that long-term recharge (regardless of seasonal variations) followsthe pattern as modelled in this study (Figure 5).

The level of recharge at the catchment scale as estimated in this study (e.g. 5Ð3 mm/yr) is substantiallylower than earlier studies. Earlier estimations (Zhang et al., 1997; Abbs and Littleboy, 1998; Ringrose-Voaseand Cresswell, 2000; Greiner, 1997) have reported recharge up to 100 mm/yr and more for the headwatercatchment of the Liverpool Plains. These predictions are generally scaled up from paddock or point scalemodelling results to the catchment level. Should the 100 mm/yr plus recharge estimate be right, the floodplains of the Liverpool Plains would probably be under water by now. The bore water level and the runoffobservation and estimation in the studied catchment do not support such high recharge estimations. This studyhighlights the need for catchment or landscape-based modelling to determine recharge at the catchment scale.By using a catchment-based approach, recharge can be estimated and verified by observed runoff data andobserved bore data at a catchment scale, which can be critical for recharge estimation in a catchment.



The observed runoff was compromised by the overbank flow and flow divergence in the study catchment.This is due to the flat nature of the flood plains that are easily subject to alterations to waterways. Theestimation of runoff is also impacted by bypass flow during dry years, which tends to overestimate flow indry years. The combined observation and modelling errors are likely to lead to an overestimation of long-term annual runoff. The estimated median annual runoff of 28 mm/yr is higher than the long-term runoffobservation in adjacent catchments of 16 mm/yr (Baron et al., 1980). The estimated runoff, however, appearsto fit well with Australian runoff maps for the study area (AWRC, 1978). Most of the overestimation seemsto be related to bypass flow during dry periods. Since the model assumes no recharge before profile saturationor that dry periods does not generate recharge, we suspect that the overestimation of runoff would have onlylimited impact on the recharge estimated. There appears to be a need to improve the bypass flow modellingin SWAT, which would offer some more tools or means to better model the process and clarify the issue.

Many years of data are needed to sufficiently interpret bore water level changes. In determining water levelchanges over a period of time, it is important to identify the dry and wet cycles of climate. For example,if we use the data for the four bores shown in Figure 6 from 1971 to 1986, rather than 1971 to 1992, wewould arrive at a declining, not rising, water level (average 4 mm/yr lower) with 17 years of bore data. Thisis because the year 1986 is at the end of a major dry period. Therefore, it makes good sense to derive theaverage water level changes between 1971 and 1992, as both the starting and the ending years are in or justafter wet cycles. Given the dry and wet cycles that may occur sporadically and persist for irregular intervals,and the different levels of recharge during the wet years, there can be risk involved with the extraction oflong-term trends in bore water level change even with 22 years (1971–1992) of observed data. For that reason,there is little wonder that Timms et al. (2001) encountered problems in trying to extract a long-term trend ofwater table change from 9 years (1992–1999) of data, particularly when there is no water balance componentinvolved in the study. A short-term interpretation of data would likely lead to the erroneous conclusion ofenormous recharge in the Liverpool Plains (Holmes et al., 1991). This indicates that long-term groundwaterobservation is needed to confidently interpret the bore water level data, and that it is absolutely necessary tocontinuously monitor the bore wells in the Liverpool Plains. This study demonstrates the importance of usingwater balance modelling tools at the right scale to derive the long-term trends of groundwater recharge, andverify them by independently observed long-term bore data.

The flood plain area of the Liverpool Plains was historically grassland before European settlement, excepton the sandstone hills and the Liverpool Ranges, which were covered by forest and woodland. Modellingresults showed that recharge occurs only in wet years during which groundwater table rises; during a drycycle, recharge may not occur for quite a number of years, which will cause the water level to be graduallylowered. The latter is modelled by an upward moisture flux or ‘revap’ during dry periods. This mechanismis an important feature of the SWAT model, which balances the groundwater variations in wet as well asdry periods. Traditional recharge models regard recharge or drainage beyond the root zone as moisture lostpermanently, resulting in high recharge levels that are often not explained by the bore data. Therefore, itseems imperative that all recharge models need to have a ‘revap’ component built into them to take moistureout of the lower soil profile or groundwater during dry periods. This would significantly improve currentrecharge modelling practices in many crop models.

CONCLUSIONS

Research shows that recharge in BJC, a headwater catchment of the Liverpool Plains, is substantially lowerthan previous studies, particularly on a catchment scale. Estimated recharge was verified by independentlyobserved bore data in the study catchment.

The study suggests that a catchment-based approach as with SWAT is needed for recharge estimation ona catchment scale. Point scale models have their value in improving understanding of processes, but care is



needed when extrapolating to large catchments without some observed data at catchment scale to limit theestimation error.

Estimated recharge is closely related to assumed plant rooting depth, soil water holding capacity, as wellas the calibration of runoff. The set of parameters leading to the estimation results may be unique buthighly unlikely in many cases. Therefore, there are always risks involved with recharge estimation. Theseuncertainties are best resolved with observed quality data, such as long-term groundwater data at a catchmentscale.

Improvements on SWAT may be needed with regard to bypass flow modelling under dry conditions,particularly with cracking vertosol soils. Improvements on crop models to include a ‘revap’ componentduring dry periods may also be needed.

ACKNOWLEDGEMENTS

We would like to thank Tim Watts, Brian Parsons, Warwick Mawhinney, Will Dorrington, Andrew Cutlerand Gary Coady of the Department of Land and Water Conservation of NSW; the Barwick family at WillowTree, NSW; and Patrick Hanson at University of Western Sydney for assisting with the project. This studywas funded by the Grains Research and Development Corporation, Australia (DNR9).

APPENDIX: DESCRIPTION OF PARAMETERS USED IN SWAT MODELLING

SOL-Z depth from soil surface to the bottom of the layer (mm)SOL-BD soil bulk density �g/cm3�SOL-AWC available soil water content of the soil layer (mm/mm)SOL-K saturated hydraulic conductivity (mm/h)CLAY clay content of the soil layer (%)CN2/Pasture runoff curve no. for moisture condition II for pastureCN2/Crop runoff curve no. for moisture condition II for cropCN2/Forest runoff curve no. for moisture condition II for forestESCO soil evaporation compensation factorEPCO plant transpiration uptake compensation factorOV-N Manning’s N for overland flowCH-N1 Manning’s N for tributary channelsCH-N2 Manning’s N for the main channelLAT-TTIME lateral flow travel time (days)SLSOIL slope length for lateral subsurface flow (m)SHALLST initial depth of water in the shallow aquifer (mm)GW-DELAY groundwater delay time (days)ALPHA-BF baseflow reduction exponent factorGWQMN threshold depth of water in the shallow aquifer for return flow to occur (mm)GW-REVAP groundwater ‘revap’ coefficient (water in groundwater available to plant at dry times)REVAPMN threshold depth of water in shallow aquifer for ‘revap’ to occur

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estimating shallow groundwater recharge in the headwaters of the liverpool plains using swat

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