FRIEND: Flow Regimes from International Experimental and Network Data (Proceedings of the Braunschweig Conference, October 1993). IAHS Publ. no. 221, 1994. / /

Modelling the impact of groundwater abstractions on low river flows

BENTE CLAUSEN Department of Earth Sciences, Aarhus University, Ny Munkegade, Denmark ANDREW R. YOUNG & ALAN GUSTARD Institute of Hydrology, Wallingford, Oxfordshire OXW 8BB, UK

Abstract A two-dimensional numerical groundwater model was applied to the Lambourn catchment in the UK to predict the impact of ground­ water abstraction on low river flows for a representative Chalk catch­ ment. The calibration of the model using observed streamflow and groundwater data is described. A range of abstraction scenarios was simulated to estimate the impact of long term abstraction on monthly river flows as a function of the abstraction rate, seasonality and location. Relationships between low flow statistics and abstraction regimes were derived by analysing a number of simulated hydrographs.

INTRODUCTION

This paper evaluates the influence of long term groundwater abstractions on low river flows for different abstraction scenarios and different distances from the river using a two-dimensional numerical groundwater model. The objective of the study was to develop a simple numerical model of a typical Chalk catchment which could be used for a sensitivity analysis of the impact of groundwater pumping on streamflow with respect to abstraction regimes. The study is a contribution to the development of regional procedures for providing simple relationships between groundwater pumping and low flows. The study area is the Lambourn catchment on the Berkshire Downs, UK, which lies on the unconfined Chalk aquifer. The Chalk is the major aquifer in the UK both in areal extent and in the quantity and quality of water extracted from it. The Lambourn catchment was investigated intensively during the 1960s and 1970s for the purposes of the West Berkshire groundwater scheme, which had the objective of maintaining down­ stream river flows during dry periods through augmenting the River Lambourn by groundwater pumping (Hardcastle, 1978). The Lambourn catchment was chosen for the investigation because of its extensive groundwater and river flow monitoring network developed as part of the West Berkshire groundwater scheme. Furthermore, except for short periods when the abstraction scheme was operated, the catchment is relatively natural with only 3 % of the mean flow abstracted for local supply. It is important to note that the study was carried out in the context of a sensitivity analysis on a typical Chalk catchment, and there are no plans for further major development of groundwater pumping in the catchment. The aquifer in the Berkshire Downs has been extensively modelled in the past (Oakes & Pontin, 1976; Connorton & Reed, 1978; Morel, 1980), and most recently by Rushton et al. (1989), who developed a three dimensional model of the complete River 78 Bente Clausen et al.

Kennet basin for estimating the groundwater resources of the aquifer.

HYDROGEOLOGICAL SETTING OF THE STUDY AREA

The study area is the 234.1 km2 catchment of the River Lambourn gauged at Shaw in Newbury (Fig. 1). The Lambourn is a tributary of the River Kennet, which drains the Berkshire Downs to the Thames. The only streams within the catchment are the Lambourn itself and the Winterbourne, a northern tributary which joins the Lambourn just upstream of Newbury. The bourne head of the Lambourn varies by up to 7 km downstream from the upper source shown in Fig. 1. Similarly the bourne head of the Winterbourne varies by about 5 km depending on the groundwater table. The catchment topography rises from 76 m to 226 m above sea level and has a general slope towards the southeast (Fig. 1). The topography and drainage of the region are strongly controlled by geological structure. The region is situated on the northern flank of the London Basin, which is an asymmetrical syncline, dominated by Cretaceous Chalk. In the central part of the catchrnent the Chalk is overlain by more impermeable deposits of clay with flint. The Chalk has a thickness of more than 200 m and can be divided into a lower, middle and upper zone. Results of geophysical well-logging and pumping tests have

25 30 36 40 46 50 Fig. 1 The topographic catchment of the River Lambourn. Impact of groundwater abstractions on low river flows 79 shown that groundwater movement is related to fissures mainly parallel to the bedding, and that fissure development is dependent on depth rather on stratigraphy (Owen et al., 1977; Owen & Robinson, 1978). The effective saturated thickness is about 30-50 m. The transmissivity (7) and storativity (S) vary laterally as well as vertically, the lateral variation having an apparent correlation with topography. Owen & Robinson (1978) developed a hydrogeological model based on four parameters (distance from a main valley, depth to water table, saturated thickness and the proportion of the effective aquifer in the lower Chalk). According to this model T varies horizontally from 2 x 10"2 m2 s"1 in the valley to less than 3 x 10"4 m2 s"1 near the topographical divide. The storativity varies in a similar way from 3% to 0.4%. In addition to the horizontal variation, the transmissivity decreases with decreasing water levels (Connorton & Reed, 1978) due to a reduction in saturated depth and in the hydraulic conductivity (K).

NUMERICAL BASIS OF THE ASM MODEL AND REPRESENTATION OF THE AQUIFER PROPERTIES

The ASM model (Aquifer Simulation Model), a two-dimensional finite difference model developed by Kinzelbach & Rausch (1989), was applied to the catchment. The model includes a leakage flow term, which is used to simulate the exchange flow between the aquifer and surface water. The program uses the IADI (Iterative Alternating Direction Implicit) method described by Prickett & Lonnquist (1971) to solve the differential, heterogeneous, isotropic, transient groundwater flow equation:

z z d $ + d $ H àx2 "dT" ât where x and y are orthogonal space coordinates, t is time, A is the groundwater table and q a general flow term including fixed boundary flows, recharge, leakage to/from streams and abstractions. For each iteration ris calculated as intimes the saturated depth of the unconfined aquifer. The IADI method is stable for large time steps, which allowed monthly data to be used. A rectilinear mesh was superimposed over the study area such that the grid lines lie parallel to the major valleys (Fig. 2). The grid size was selected to be 500 m in both directions. The boundary was defined as a non-flux boundary following the groundwater divide determined on the basis of the groundwater potential map marked in Fig. 3. The map is based on mean values of the maximum groundwater level (February-March 1988) and the minimum level (December 1990) observed during the period 1966-1990 in those wells shown in Fig. 3. These mean values were found to be close to the average ground­ water levels for some individual wells. The groundwater catchment area was estimated to be 210 km2, which corresponds to 90% of the topographic catchment area. The bottom of the aquifer in each cell is defined to be 40 m below mean groundwater level. This corresponds to the estimated depth of the major aquifer as published in the literature. The stream cells, shown in Fig. 2, differ from the other cells by including a leakage rate (qlea) between the aquifer and the river. When the groundwater table is higher than the elevation of the river bed (hb) the leakage rate is determined as: Bente Clausen et al.

20 25 30 35 40 45

10 15 20 25 30 35 40 45 51 Q 0.5 km x 0.5 km , Stream cell Q Location of abstraction — Nonflux boundary Q intermittent stream ceii e Gauging station _ „ Recharge boundary Fig. 2 Grid of the Lambourn catchment used in the model simulations.

P5^

• WELL OR BOREHOLE 0 12 3 OBSERVED HEAD SIMULATED HEAD (m) Fig. 3 Observed and simulated average groundwater levels.

Ilea = X($-A) for $>hh (2) where h is the water surface level of the river and A is the stream coefficient. However, when $ becomes lower than hb the leakage reaches a constant level determined as:

Ilea = Mh-hb) for §>H (3) The intermittent nature of the bourne sections of the river was simulated by defining the river depth as zero (h = hb) for the intermittent stream cells (Fig. 2) corresponding to the bourne section. Under the condition $ is less than hb the leakage rate, as defined by equation (3), is zero. Flow routing in the stream cells is achieved by summing cells to the four gauged points in the catchment. While this is sufficient when working on a Impact of groundwater abstractions on low river flows 81 monthly time step, it does assume the bourne stream cells dry up sequentially from the head waters downstream. The stream coefficient was set to 1.0 X 10"7 s"1 for all stream cells. This value was estimated from equation (2) by inserting simultaneously observed head differences and flow values for each of the four reaches shown in Figs 1 and 2. Both the average situation (mean flow and average groundwater level) and the minimum situation (the <295, which is the discharge exceeded 95% of the time, and the minimum groundwater level) were used to estimate the stream coefficients.

ESTIMATING GROUNDWATER RECHARGE

The series of monthly streamflows used for the modelling study were the 29 years from 1962 to 1990. During this period four gauging stations (Fig. 1) were operational. The mean flow from the catchment at Shaw is 1.72 m3 s"l, equivalent to 25 8 mm year"l using the groundwater catchment area. The Base Flow Index (Gustard et al., 1992) is very high at all four gauging stations (0.96-0.98) indicating that rapid response runoff is very limited, a feature which is supported by Morel (1980). This is represented in the model by assuming that all streamflow is derived from groundwater, that is the mean recharge is assumed to be equal to the mean flow. The mean precipitation (1941-1970) varies from 700 mm year"1 in the valleys to 760 mm year"1 on the Downs. Based on the distribution of rainfall and catchment geology the mean recharge was assumed to be 235 mm year"1 in the eastern area (Fig. 2) and 280 mm year"1 in the western area, where the precipitation is higher and there is no cover of clay with flint. The seasonal variation of recharge was derived from time series of the effective precipitation for grassland calculated using MORECS (Meteorological Office Rainfall and Evaporation Calculation System). The land use in the Lambourn catchment is dominated by grassland and arable farming, with a limited area of woodland. The mean value of the effective precipitation for grassland (1962- 1990) calculated from MORECS is 212 mm year"1. This is lower than the value of 258 mm year"1 calculated from long term gauged flow records at Shaw. To derive values of monthly recharge, the monthly values of effective precipitation were multiplied by a factor of 1.32 (280 mm year"V212 mm year"1) for the western area and 1.11 (235 mm year"V212 mm year"1) for the eastern area. The final step in estimating the recharge times series was to estimate the transit times of the infiltration through the unsaturated zone. The catchment transit times were optimized during the calibration procedures.

CALIBRATING THE MODEL

The model was calibrated by optimizing the hydraulic, conductivities, the storativities and the transit times for the unsaturated zone by comparing model outputs with observed data of groundwater levels and streamflow. The model simulations showed the K values from the hydrogeological model developed by Owen and Robinson (1978), ranging from 1 x 10"s to 5 x 10"4 m s"1, were too low. Using these values the simulated groundwater level was 200 m near the western divide, which is about 50 m higher than the observed value (Fig. 3). Using only groundwater levels the lvalues were optimized to range from 4 x 10"5 82 Bente Clausen et al. to 3 x 10"3 m s"1 using a least squares method. However, these values were too high with respect to the streamflow distribution in that insufficient water flowed from the upper western catchment. The erroneous flow distribution was insensitive to the values of the stream coefficients and is probably due to ignoring the vertical variation of transmissivity and errors relating to the use of the mean groundwater levels. By using both groundwater levels and streamflow the lvalues were optimized to values ranging from 2 x 1(T5 to 1 x 10~3 m s"1. This was achieved so that the simulated mean flow values at all four gauging stations were equal to the observed ones, and the average groundwater levels (Fig. 3) were similar to the observed ones except in the western catchment where the simulated values exceed the observed levels by 5-10 m. These final lvalues were similar to those used by Morel (1978). With the optimization of the hydraulic conductivity completed, the storativity values and the transit time in the unsaturated zone were optimized from non steady state simulations. The amplitude of the seasonal variations in streamflow are influenced by both parameters, whereas only the latter influences the phase of the flows. The resulting S value was 1.5% in the peripheral area above approximately 160 m and 3% in the remaining area. The boundaries between the areas follow the contour lines of the topography. The transit times were optimized to be two months in the peripheral areas, one month in the middle area, and zero in the valleys. Comparisons between the simu­ lated and observed streamflows are presented in the form of the annual flow duration curve (Fig. 4(a)) and an example of the hydrograph for the station at Shaw (Fig. 4(b)).

PREDICTING THE LOW FLOW RESPONSE OF GROUNDWATER ABSTRACTIONS

The long term flow response was investigated by simulating constant and seasonal abstractions in different locations and with different abstraction rates using the historical recharge data for the years 1962 to 1990. The model simulated four years of data before equilibrium was reached, and so the first four years of simulated streamflow were

1 JAN APR JJL' OCT 'jAN APR AfM JUL OCT1 'JAM APR 'jJL 1970 1972 1973 Percentage of monthly discharge exceeded Fig. 4 Comparison between gauged and modelled streamflow: (a) flow duration curve at Shaw; (b) hydrograph at Shaw for 1970 to 1973. Impact of groundwater abstractions on low river flows 83

omitted from the analysis. The hypothetical abstractions were located 0.5 km, 1 km, 2 km or 3 km from the River Lambourn as shown in Fig. 2. The transmissivity decreases with increasing distance from the river. The storativity drops from 3 % to 1.5 % where the distance from the river exceeds 2 km. For each simulation the monthly stream depletion rate (SDR) was calculated as:

SDR = ^ (4) Q where AQd is the stream depletion, i.e. the difference between the simulated natural flow and the flow influenced by the abstraction, and Q is the pumping rate. For seasonal abstractions the monthly pumping rate is used to define the SDR even in those months when pumping ceases. The results of the analysis have shown that: (a) The SDR is independent of the pumping rate up to at least 500 m3 h"1. (b) A constant continuous abstraction results in seasonal variation of the SDR. The variation increases with the distance of the abstraction from the river due to an increasing storage capacity. This is illustrated in Fig. 5(a) which shows the mean monthly SDR resulting from constant abstractions. Lines have been drawn between the monthly values to illustrate the different SDR regimes more easily. The SDR is smallest in the autumn when the groundwater levels are low and the leakage from the river to the aquifer is limited, partly because the upper reaches dry up, partly because the leakage in the perennial cells is limited according to equation (3). The figure also illustrates the relative decrease in aquifer storage in the summer to supply the excess of groundwater abstraction over stream depletion. Conversely, in the winter there is a relative increase in storage when the streamfiow depletion is greater than the abstraction. (c) The introduction of a seasonal abstraction results in a seasonal depletion. The seasonal depletion depends primarily on the duration of the abstraction and the distance from the river. The dependence on distance is illustrated in Fig. 5(b) which shows the mean monthly SDR for abstraction scenarios of two months duration for different distances from the river. For clarity only the SDR relationship for 0.5 km

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Ncv Dec Fig. 5 The mean monthly stream depletion rate (SDR) for different locations for (a) constant abstractions; (b) two month abstractions (the middle peak results from abstracting in May and June). 84 Bente Clausen et al. has been drawn for the January-February and September-October simulation. The figure shows that the amplitude of the monthly variation in SDR is increasingly damped as the distance from the river increases. For the distance of 0.5 km the SDR reaches its maximum in the last of the two abstraction months, whereas for the distance of 3 km the maximum value is found a month later. The SDR is only marginally higher when the abstraction takes place in January-February and correspondingly lower when the abstraction takes place in September and October. It should be noted that the definition of SDR, whilst enabling easy comparison between scenarios (all values are lower than 1), does not conserve mass for intermittent pumping scenarios. Based upon the impacts described it is possible to summarize the impacts on low river flows. A constant abstraction will result in a minor seasonal variation in the amplitude of stream depletion. The amplitude increases with the distance from the river. For a given distance from the stream, the smallest depletion rates occur during periods of low flow. This means that low flow measures such as the 95% exceedance and the annual minimum discharge will be reduced more by abstractions close to the river (SDR close to 1.0) than by abstractions away from the river (SDR less than 1.0). This is illustrated in Fig. 6(a) which shows the flow frequency curve of the annual minima for the natural river flow and the flow influenced by constant abstractions at different distances from the river. The figure also shows the almost constant influence from year to year. The impact of a seasonal abstraction will depend primarily on the abstraction rate and the distance from the river. In contrast to a constant abstraction, the influence of a seasonal abstraction on low flow statistics is more dependent on the year to year variability of low flows in both their timing and magnitude and how they relate to the timing and magnitude of the depletion. In the case of annual minimum discharges the month of the minimum is critical in terms of the direct effect of depletion. Annual minima will be reduced more severely when the month with the natural minimum is coincident with the month of the maximum depletion (Fig. 6(b)). Thus, in Chalk streams such as the Lambourn where the minimum flow normally occurs in October or

1°) 1.8- 1.8- A A No abstraction No abstraction A o 1.6-1 a 1.6- O Abstraction at 0.5 km Abstraction at Jan-Feb a S m —. 14- o °i-. Abstraction at 3 fan •r 1-4- " "". Abstraction at Sep-Oct « Si "_ £ F •""_ 1.2- % 3. 1.2-I •i o-m 1- %, am f am f O) °te~ V. "*** 03 V. CO 0.8- 0.8- *ft~ am 0 0.6- 0.6- B m

04- 0 4- -1 0 1 -1 0 1 Normal variate Normal variate 1.25 2 2.5 5 10 25 100 1.25 2 2.5 5 10 25 100 Fig. 6 The impact of groundwater abstraction on the one month annual minima series caused by (a) constant abstractions (500 m3 h"1); (b) two month abstractions (500 m3 h'1) at the distance of 0.5 km from the river. Impact of groundwater abstractions on low river flows 85

November, the maximum impact of a seasonal abstraction would be from a borehole close to the river with a maximum abstraction in September and October.

CONCLUSIONS

The influence of long term groundwater abstractions on a natural flow regime has been investigated using a two dimensional regional groundwater model. The model was calibrated on observed groundwater levels and streamflow. The calibrated values of hydraulic conductivity and storativity were found to be in accordance with values found from field measurements and calibration of other numerical models. After the model was calibrated it was possible to simulate the natural flow at the gauging stations. The analysis of the simulations showed that the stream depletion with a constant abstraction depends on the abstraction rate, the distance from the river and river discharge. The depletion of a seasonal abstraction depends on the abstraction rate, the distance from the river, the duration of the abstraction, but not the time of the year. The influence of a seasonal abstraction on low flows depends on the factors cited above and the natural low flow variability.

Acknowledgements The study is a contribution to a National River Authority project in the UK which is developing regional procedures for providing simple relationships between groundwater pumping and low flows. We are grateful to the National River Authority Thames Region for supplying the river flow and groundwater level records and to the Meteorological Office for providing the meteorological data. We would also like to thank the British Geological Survey for information and useful discussions.

REFERENCES

Connorton, B. J. & Reed, R. N. (1978) A numerical model for the prediction of long term well yield in an unconfmed Chalk aquifer. Quart. J. Eng. Geol. 11, 127-138. Gustard, A., Bullock, A. & Dixon, J. M. (1992) Low flow estimation in the United Kingdom. Institute of Hydrology Report no. 108, Wallingford, Oxfordshire, UK. Hardcastle, B. J. (1978) From concept to commissioning. In: Thames Groundwater Scheme, 5-31. Institution of Civil Engineers. Kinzelbach, W. & Rausch, R. (1989) Aquifer Simulation Model "ASM", Documentation. Kassel Universitât, Kassel, Germany. Morel, E. H. (1980) The use of a numerical model in the management of the Chalk aquifer in the upper Thames basin. Quart. J. Eng. Geol. 13, 153-165. Oakes, D. B. & Pontin, J. M. A. (1976) Mathematical modelling of a Chalk aquifer. Technical Report TR24, Water Research Centre. Owen, M., Connorton, B. J. & Robinson, V. K. (1977) The hydrogeology of the Thames ground water scheme. In: International Association of Hydrogeologists, Mémoires (Proc. Birmingham, UK, Congress), vol. XIII, parti, D20- D31. Owen.M. & Robinson, V. K. (1978) Characteristics and yield in fissured Chalk. In: Thames Groundwater Scheme, 33-49. Institution of Civil Engineers. Prickett.T. A. &Lonnquist,C. G. (1971) Selected digital computer techniquesforgroundwaterresourceevaluation.7Hino/i State Water Survey Bull. 55. Rushton, K. R., Connorton, B. J. & Tomlinson, L. M. (1989) Estimation of the groundwater resources of the Berkshire Downs supported by mathematical modelling. Quart. J. Engng. Geol. 22, 329-341.