Modelling the Effects of Seasonal Variations in Rainfall and Production Upon the Aquifer and Surface Features of Rotorua Geothermal Field

GRC Transactions, Vol. 39, 2015 Modelling the Effects of Seasonal Variations in Rainfall and Production Upon the Aquifer and Surface Features of Rotorua Geothermal Field Thomas M. P. Ratouis, Michael J. O Sullivan, and John P. O Sullivan Department of Engineering Science, The University of Auckland, Auckland, New Zealand t.ratouis@auckland.ac.nz Keywords Geothermal modelling, resource management, reservoir recovery, springs rejuvenation, seasonal variation Abstract The Rotorua geothermal field is a shallow geothermal reservoir lying directly beneath the Rotorua city in New Zealand. It is renowned for its abundance of natural geothermal manifestations including the geysers and hot springs at Whakarewarewa. Intensive extraction of the geothermal fluid in the 1970s led to a general decline of the activity of the surface features. In 1982 an extensive Monitoring Programme was initiated to provide insight into the system behaviour and response to geothermal production. Its conclusions led to the 1986 Wellbore Closure Programme that resulted in the recovery of reservoir pressures and many of the surface features. The monitoring programme continues through to the current day and efforts to provide a robust numerical model of the geothermal aquifer and surface features are ongoing. Annual and seasonal variations impacting the state of the field (e.g. production and reinjection rates, precipitation) have been included in University of Auckland (UOA) models: UOA Annual and UOA Seasonal. The results show the inclusion of these effects in the model is important for accurately representing the complexity of the Rotorua system and thus making the model useful for assisting with sustainable management of the resource. 1. Introduction The Rotorua geothermal system is a geothermal reservoir that lies within the Rotorua Caldera and the Taupo Volcanic Zone, New Zealand. Surface activity is mainly confined to three areas within the Rotorua Township: Whakarewarewa/Arikikapakapa to the south, Kuirau Park/Ohinemutu to the northwest and Government Gardens/ Sulphur Bay/Ngapuna to the northeast (Figure 1). The Rotorua Geothermal Field (RGF) is unique in that it lies directly beneath a city and contains one of New Zealand s last remaining areas of major geyser activity at Whakarewarewa (Figure 1). Figure 1. Map of the Rotorua Geothermal Field showing the extent of the field, areas of surface activity, and locations of monitoring wells and bores. 947

Close proximity of the resource to a population centre and ease of access for end-users resulted in intensive drilling and fluid abstraction from shallow bores for domestic and commercial usage from the 1950s onwards. Increasing concern about the effect of geothermal fluid withdrawal on the decline of springs and geyser activity led to the establishment of the Rotorua Geothermal Monitoring Programme (RGMP) in 1982 (O Shaughnessy, 2000). Geothermal monitor wells and shallow monitoring bores were drilled throughout Rotorua City to monitor the pressure levels in the geothermal reservoir and in the shallow subsurface (Figure 1). By 1986, aquifer pressures declined to the lowest levels since the monitoring programme began (Bradford, 1992) and advice was given that urgent action was required to prevent further deterioration of spring and geyser activity. A Bore Closure Programme including closure of all bores within a 1.5 km radius of Pohutu Geyser (Whakarewarewa) and closure of all government owned wells in Rotorua township (Figure 1) became effective in 1986 (Gordon et al., 2005). By 1988 the programme contributed to a 66% reduction in production (10,830 tonnes per day) and a 75% decrease in net withdrawal (7,150 tonnes per day) (Bradford, 1992) and there was an immediate increase in reservoir pressures (Figure 5). During the ensuing years recovery of surface features was observed. In 1991 Environment Bay of Plenty (EBOP) assumed responsibility for managing the field under the Resource Management Act. It aims to monitor the recovery of geothermal features and protect the surface manifestations while providing allocation of the resource for present and future efficient use (EBOP, 1999). This paper describes recent modelling work aimed at matching the seasonal behaviour of the field, including aquifer pressure drawdown and recovery recorded in the monitoring wells and the response of surface features to the historical production/injection schemes in the Rotorua Geothermal Field from 1950 to 2014. It is a continuation of modelling study of Rotorua being carried out at the University of Auckland (Ratouis et al., 2014, Ratouis et al., 2015). 2. Conceptual Model The RGF encompasses an area of approximately 20 km 2 as defined by electrical resistivity measurements and downhole temperature data from 182 wells collected by the Bay of Plenty Regional Council in the 1980s (Ministry of Works, Figure 2. Cross section of the RGF conceptual model (location highlighted in Figure 3). 948

Ratouis, et al. 1985). Shallow drilling of geothermal bores, has provided information about the shallow geology, structure, hydrology, and chemistry of the geothermal reservoir. The stratigraphy of geothermal bores within the RGF reveals that the feedzones are mainly located within the Mamaku Ignimbrite in the east and extreme south sections (Whakarewarewa and Ngapuna), and the Rotorua Rhyolite forming a north-south trending ridge (Wood, 1992). These aquifers contain, respectively, boiling, high enthalpy, highchloride fluid ( 1000 mg/kg) and sub-boiling water with medium concentrations of chloride and bicarbonate ( 400 mg/ kg) (Stewart et al., 1992). Both of these units are capped by the Rotorua Sediment sequence which covers all but a tiny outcrop of the northern dome. This alluvial sedimentary sequence has an overall low vertical permeability acting as an aquitard and confining the geothermal fluid (Figure 2). Data on the well/spring chemistry (chloride, bicarbonates, sulphate) (Stewart et al., 1992) and surface CO2 flux (Werner and Cardellini, 2005), supported by the temperature distribution (Candra and Zarrouk, 2013) have highlighted three upflows; along Puarenga Stream, Whakarewarewa (slightly diluted) and Kuirau Park (diluted). This generally supports the structural settings of the field underneath Whakarewarewa and Ngapuna where depth discrepancies (linked to downfaulting) in the top of the Mamaku Ignimbrite have been recorded (Figure 3). These major, near N-S, faults (T&S, Ngapuna and Roto-aTamaheke), ring faults (ICBF) and SW-NE faults (Horohoro) (Wood, 1992) (Figure 3) are believed to act as preferential pathways for the ascending geothermal fluid. Temperature inversions in geothermal bores across the North and South Domes (Ratouis et al., 2015) suggest Figure 3. Geological and structural setting of the RGF and detailed map of Whakarewarewa. lateral fluid flow and mixing with heated groundwater. The fluid moves laterally from the faults within the faulted ignimbrite sheet and into the fractured rhyolite domes to the north of Whakarewarewa and west of Ngapuna (Figure 2, Figure 3). 3. Seasonal Variations Affecting Hydorthermal Systems Diverse factors can impact geothermal systems over various periods of time. Some affect reservoir pressures and surface features activity immediately (changes in barometric pressure) while other might take hundreds of years (deep recharge of the geothermal fluid). Major factors believed to impact the Rotorua system are listed below. Some can be estimated and are included in the simulations, while others, less quantifiable and with no direct known correlation to field data will be only briefly discussed. 3.1. Supply of Geothermal Fluid The supply of geothermal water to the shallow reservoir at Rotorua originates from the deeper part of the geothermal system through a network of faults and fractures. The predominant constituent of the deep geothermal fluid is meteoric water with a portion of arc-type magmatic waters, estimated at 17% for the Rotorua system (Giggenbach, 1995). This implies a convective circulation of meteoric water that percolates from the surface to the deeper part of the TVZ where it is heated by a silicic magma intrusion (Heise, 2014). This induces a buoyancy-driven upflow along the southern edge of the Rotorua Caldera. Therefore changes in the heat supply, strain rates or effective stresses of faults supplying the geothermal fluid (Kissling et al., 2009) as well as long term trends of rainfall can impact the supply of geothermal water. 949

In practice the supply of geothermal fluid and heat at the bottom of the model is usually modelled as constant unless clear evidence of reduction or increase is observed. In Rotorua, temperatures in monitoring wells remains largely constant throughout the monitoring campaign in Ngapuna and Whakarewarewa (Kissling, 2014) which tends to indicate little change in the geothermal fluid supply at depth. 3.2. Barometric Pressure Barometric pressure changes are transmitted to the geothermal aquifer through the near surface layers and down the geothermal bores (Bradford, 1992). Variation in air pressure is also believed to impact the filling and/or heating rates of geysers and springs and hence their surface activity (Nikrou et al., 2013). The current model does not reach the resolution required to model geyser and springs cyclic behaviour and thus changes in atmospheric pressure are not included in the model and pressures collected in monitoring wells are corrected for barometric pressures. 3.3. Temperature No direct correlation between atmospheric and Lake Rotorua temperatures and surface feature activity has been observed (Nikrou et al., 2013). In the model the Lake temperature is set at 10 C and the air temperature is fixed at 15 C. 3.4. Lake Rotorua Levels Potentially, variation of the level of Lake Rotorua changes the pressure applied at the bottom of the lake and thus may affect the amount of water flowing in or out or the bottom of the lake. However lake levels have been stable over the production stage (Bay of Plenty Regional Council, Lake Rotorua Water Level) and are set at 280 masl in the model. 3.5. Rainfall and Urbanization Changes Short-term changes in rainfall pattern affect the amount of water supplied to the shallow ground water. These changes are reflected in the groundwater G-bores. Long-term changes in mean rainfall control the deep groundwater storage. In Rotorua, mean rainfall has been variable throughout the 20 th century. It was high during the 1960s and early 1970s and then declined to the early 1980s when it stabilised at a lower level (Figure 4). Bradford (1992) investigated longterm rainfall changes and concluded that about half of the pressure drop in the production aquifers resulted from a decline in rainfall, together with the increasing urbanisation of Rotorua City and the consequent diversion of runoff waters and sub-surface drainage. Figure 4. Annual and Monthly Rainfall in Rotorua From 1950 to 2014. Rainfall and an urban zone of limited infiltration rate are included in the models described hereafter. To analyse yearly or monthly patterns of the geothermal system two models were developed; UOA Annual and UOA Seasonal which account for yearly average and monthly average rainfall, respectively. 3.6. Withdrawal Changes Withdrawal changes cause changes in the geothermal aquifer pressure and hence well water levels. Seasonal changes in mass withdrawal are clearly reflected in aquifer pressure pre-closure cyclical variations as pressure lows occurred in winter when production rates were highest (Figure 5). The effect of drawoff on the surface features was highlighted by Bradford (1992). She noted that in the mid-1980s the difference between summer and winter mass withdrawal dropped from 30,000 tonnes per day to approximately 25,000 tonnes per day, which was accompanied by a rise in pressure in the aquifer of about 0.07 bars. Natural activity of several springs increased which could not be related to climatic changes. 950

Ratouis, et al. Figure 5. Water levels transients for monitoring wells (a) M6 and (b) M16. 4. Monitoring A network of monitoring wells and geothermal bores was established in 1982 to record water levels and temperatures in the geothermal aquifer as part of the RGMP. Monitoring of these bores, along with additional bores drilled at a later stage, is still being undertaken by EBOP. Locations of monitoring bores considered in this paper are shown in Figure 1. M-series monitoring bores are drilled into the geothermal reservoir 80-180 meters deep. M1, M12 and M6 penetrate the rhyolite reservoir whereas M16 taps into the ignimbrite aquifer. Figure 5 show the variations in water level for these M-wells with the barometric pressure response removed. Dailyaveraged pressure transients for other M-wells can be found in Gordon et al., (2005). As mentioned in Section 3.6, reservoir pressure shows a yearly cyclical period. Prior to the wellbore closure the pressure low occurred in winter when production rates were highest. The wellbore closure enforced the closure of a number of wells and the overall mass withdrawal from the geothermal reservoir dropped from approximately 30,000 tonnes per day to 10,000 tonnes per day Figure 6. UOA annual and UOA seasonal mass production and reinjection estimates from 1950 to 2014. Figure 7. Distribution of geothermal wells in Rotorua city prior and following the wellbore closure programme. 951

(Bradford, 1992) which was followed by an immediate 0.2 bars increase in reservoir pressures (Figure 5). Further overall increase was observed from 1990 to 2000. Following the recovery, the pressures in all wells have continued to vary by up to about 0.5 metres over periods of several months or years. Despite clear differences between water level histories of these wells some show common features. The cyclical behaviour observed prior to the closure is not as obvious and in some case the pressure lows occurs in summer when rainfall is lower (Figure 5 (c)). The nature of these variations is important for understanding the behaviour of the Rotorua geothermal reservoir and demonstrates the potential influences of both mass withdrawal and rainfall on the geothermal aquifer. 5. Annual and Seasonal Production Estimates In previous models the total annual production and injection rates (red and purple in Figure 6) were distributed uniformly across all the wells for which temperature data were available (Ratouis et al., 2015). For the current models, an assessment of the production and reinjection at individual wells was undertaken. Wells with current consented rates allocated by EBOP along with a few other big users (for which past maximum daily rates are known) were used in the model (Figure 7). Bradford documented total production rates by geographical zone prior to 1985 and after 1988 following the wellbore closure programme. Using the currently consented rates (EBOP, 2014), the total annual production history (Figure 6), and production per zone as defined by Bradford (1992), the consented values for 1988 and 1985 were calculated assuming 30% higher production rates prior to the closure. Figure 8 shows the production rates per zone and indicates the proportion allocated to consented wells and unconsented wells (nil after 1986). It was decided that these proportions would be used from 1950 to 1985 to model the evolution of geothermal exploitation in Rotorua. Unconsented production was then evenly distributed amongst the remaining wells that are known to be producing but for which production rates are unknown, in the appropriate geographical zone. This is major improvement on the production scheme implemented in earlier models as it explicitly includes big users and areas of important mass withdrawal as well as giving a more realistic representation of the wellbore closure. Differences between winter and summer mass withdrawal values are included in UOA Seasonal (green and cyan in Figure 6). Prior to 1991, a 20% difference between summer and winter values was estimated and after 1991 a 10% difference (Figure 6) (Bradford, 1992). Figure 8. Production rates for consented (blue) and unconsented wells (red) in (a) 2014, (b) 1988, and (c) 1985 per geographical zones. 952

6. Computer Modelling 6.1. Previous Modelling Studies In this work we use UOA Model 4a developed by the University of Auckland (Ratouis et al., 2015). It includes transport of chloride and CO 2 using the EWASG (Water Salt Gas) equation of state module (Battistelli et al., 1997) belonging to the MULKOM family of computer codes developed at Lawrence Berkeley National Laboratory. This module, named EWASG (Equation-of-State for Water, Salt and Gas in the numerical simulator AUTOUGH2 (Yeh et al., 2012), the University of Auckland s version of TOUGH2 (Pruess, 1991). For further information on the characteristics of the model refer to Ratouis et al, (2015). 6.2. Model Specifications General model parameters are summarized in Table 1. 6.3. Boundary Conditions 6.3.1. Top Boundary Atmospheric conditions are assigned at the top surface (1 bar, 15 C). Below the lake surface, the pressure is set to the hydrostatic pressure corresponding to the depth of the lake assuming a water temperature of 10 C. Historic rainfall recorded at Whakarewarewa from 1900 to 2014 provided by EBOP is used in the model and is represented by cold water injected into the top of the model. Over the urbanized zone an infiltration rate of 8% is implemented, instead of the 10% used elsewhere, to account for paved areas and the existing drainage system. 6.3.2. Side Boundaries The side boundaries are assumed to be closed. 6.3.3. Base Boundary Inflow of high enthalpy water is applied at the base of the inferred faults (Table 2) and a conductive flow of heat of 80 mw/m 2 is applied elsewhere. 7. Simulation Results: Production Modelling 1950 2014 Table 1. Comparison of grid and model parameters. Category UOA Model 4a Grid area 12.4 km x 18.3 km Grid depth 2,000 m Blocks 48,034 Layers 30 Minimum block size 125*125 m 2 Minimum block height 5 m Surface Follows topography & lake bathymetry Equation of State (EOS) EWASG (Water, NaCl, CO2) Table 2. Deep inflows at the bottom layer of the model. Area Mass t/day Temp ( C) Kuirau Park 8,300 255 Ngapuna Stream 23,100 270 Whakarewarewa 42,900 245 Total 74,300 The simulations were carried out in three distinct stages. A first stage reproduces the steady state of the system (prior to 1900). This is followed by a natural state model which represents the period from 1900 to 1950 for which rainfall data is available and is included as input for the model. From 1950 to 2014 the productions models are run to include production and reinjection from the geothermal bores. Results and comments on the steady state and natural state are given Ratouis et al., (2015) and are not repeated here. 7.1. Pressure Response in Monitoring Wells Water level responses for UOA Models for M12 and M16 and the measured data are shown in Figure 9. For all three models the pressure transients follow water level variations recorded in M12 and M16 closely. However for M12 simulation results tends to predict a more rapid recovery than shown in field measurements. For M16 the pressure drop predicted in the simulations exceeds the recorded pressure drop. UOA Seasonal is the only model to match the pre closure seasonal variations. The timing and magnitude of these variations closely follow the data. Water levels responses for M6 from 1995 to 2005 and M12 and M16 from 2009 to 2013 are presented in the following figures to show some of the finer details of the modelled response. The pressure trend for UOA Annual is mostly flat and does not account for the fine details of the response of water level to peaks in rainfall. UOA Seasonal matches closely such behaviour, and both trends are nearly superimposed. The data also reveals a correlation between rainfall and water level within the geothermal reservoir. The link between the shallow groundwater and the deep geothermal aquifer has previously been mentioned in the Rotorua geothermal bore water level assessment - 2014 report prepared by GNS (Kissling, 2014). The seasonal model is able to reproduces this 953

behaviour; a clear correlation with rainfall is visible for the simulation result in Figure 11 (b) highlighted by the orange ovals. The most obvious section of the results is the high rainfall event at the start of 1998, which is followed by a significant increase in water level in both the field data and in the simulation results. A similar correlation between a high rainfall event and water level increase can be seen in well M12 (Figure 12). The most evident events are in 2008, 2011 and 2012. The model reproduces similar behaviour but with a lower magnitude. Monitoring well M16 however does not seem to be affected by such rainfall events, a phenomenon also reproduced by the model. The different response of the two M-wells may give insight into the shallow recharge of the system; rainfall seems to percolate into the system in the vicinity of well M6 (west of Whakarewarewa), a phenomenon not observed directly north of Whakarewarewa. Figure 9. Simulation results for (a) UOA Model 4a, (b) Annual Model, and (c) Seasonal Model vs field data for water level response to production in monitoring well M12. Figure 10. Simulation results for (a) UOA Model 4a, (b) UOA Annual, and (c) UOA Seasonal vs field data for relative water level response to production in monitoring well M16. 954

Ratouis, et al. Figure 11. Simulation results for (a) UOA Annual and (b) UOA Seasonal showing pressure changes and rainfall from 1996 to 2005 for monitoring well M6. 7.2. Individual Thermal Features Pressure, temperature, mass flow and chloride concentration of some individual geothermal features within the RGF, represented in the model as a discrete 125m2 5m blocks, were plotted against time. Modelled data for UOA Model 4a, Annual and Seasonal for blocks within Whakarewarewa and Kuirau Park show the same trends (Figure 13, Figure 14). From 1950 to 1986 the plots show a general decrease in surface temperature and mass flow together with pressure and by 1990 following the Wellbore Closure Programme, a significant recovery of all modelled features is observed. This is consistent with the recovery of geysers which began erupting again in the late 1980 s - early 1990 s for the first time since the 1970 s. Springs in Kuirau Park began overflowing again during this period as they had prior to the exploitation of the field. Figure 12. Simulation results for UOA Seasonal showing the pressure changes and rainfall from 2008 to 2013 for monitoring wells (a) M12 and (b) M16. Figure 13. Temperature, pressure, and mass flow transients for Whakarewarewa for (a) UOA Model 4a, (b) UOA Annual, and (c) UOA Seasonal. 955

Figure 14. Temperature, pressure, and mass flow transients for Kuirau Park for (a) UOA Model 4a, (b) UOA Annual, and (c) UOA Seasonal. Figure 15. Rainfall, water level, and temperature response for Lake Roto-a-Tamaheke (Graham et al., 2013). (a) Field data and (b) UOA Seasonal. Temperature, pressure and mass flow changes for Whakarewarewa are consistent for all three models. Differences between outputs of the three model lie within the higher level of detail of the yearly and seasonal variations themselves linked to rainfall changes implemented into the model. Kuirau Park outputs show a similar increase in the degree of details but unlike Whakarewarewa, there are some noticeable difference in mass flow transients from the UOA Model 4a and models Annual and Seasonal. This is likely to be due to the difference in the well production history. There are some big users around Kuirau Park (Rotorua Hospital) and small changes in pressure induce a high decline in surface mass flow at Kuirau Park. Lake Roto-a-Tamaheke also provides interesting insight into the effects of seasonal changes in rainfall and production. It had a 6 C decline in temperature in the winter of 2013. The water level and temperature recorded for the lake respond immediately to the high rainfall during this period. There is an inverse correlation between temperature response and the water level response caused by the local high rainfall events (Graham et al., 2013). This behaviour is replicated in the model with the mass flow out of the block and the block pressure acting as indicators of the lake water level (Figure 15). It is worth noting that the model only predicts a temperature decline of 0.2 C rather than the 6 C observed. A difference in magnitude is expected because the model represents the temperature of the whole block averaging rock and fluid temperatures over a large volume, whereas sampling accounts only for the water in the pool. 8. Conclusion A new model of the Rotorua geothermal field has been developed that represents the shallow unsaturated zone and includes the seasonal variations that impact the geothermal system. 956

Results presented here confirm that seasonal variations such as the seasonal changes in production/reinjection history and rainfall are important to include in the model in order to match the detailed behaviour of Rotorua geothermal field. To some extent the model can reproduce water level and temperature responses of individual surface features. In order to provide a useful tool for assessing the impact of various production schemes on the surface features, it is important to have a model that can reproduce the system behaviour as realistically as possible. The model UOA Seasonal is largely meeting this objective and should assist with efficient field management, allowing the development and allocation of the resource, while limiting the adverse effects on the surface features of Rotorua. References Bay of Plenty Regional Council. Lake Rotorua Water Level. Retrieved 30/04/2013, from http://monitoring.boprc.govt.nz/monitoredsites/cgi-bin/ hydwebserver.cgi/sites/details?site=238&treecatchment=26. Bradford, E. 1992. Pressure changes in Rotorua geothermal aquifers, 1982-90. Geothermics 2111-2: 231-248. Candra, A., Zarrouk, S. 2013. Testing Direct Use Geothermal Wells in Rotorua, New Zealand. Proc. 35th New Zealand Geothermal, Workshop, Rotorua, New Zealand. Environment Bay of Plenty Regional Council (EBOP). 1999. Rotorua Geothermal Regional Plan. Resource Planning Publication 99/02. ISSN 1170 9022. Technical report of the Rotorua geothermal task force / prepared by officials from the task force. 1985. Rotorua Geothermal Task Force, New Zealand. Oil and Gas Division (Eds.), Wellington, N.Z.: Oil and Gas Division, Ministry of Energy. Giggenbach W.F. (1995) Variations in the chemical and isotopic composition of fluids discharged from the Taupo Volcanic Zone, New Zealand. Journal of Volcanology and Geothermal Research, 68. Graham, D.J., Pearson, S.C.P., Seward, A., O Halloran, L. 2013. Rotorua Geothermal System: Measurements and Observations July to September 2013. GNS Science Consultancy Report 2013/306. Heise, W. 2014. 2-D Magnetotelluric Imaging Of The Rotorua And Waimangu Geothermal Fields. Proceeding New Zealand Geothermal Workshop. Kissling, W., Ellis, S., Charpentier, F., Bibby, H. Convective flows in a TVZ-like setting with a brittle/ductile transition. Transp. Porous Media, 77. Kissling, W. 2014. Rotorua Geothermal Bore Water Level Assessment - 2014. GNS Science Consultancy Report 2014/199. Nikrou, P., Newson, J., and McKibbin, R. 2013. Time series analysis of selected geothermal spring temperature recordings. Waikato Regional Council Technical Report 2013/17. O Shaughnessy, B.W. 2000. Use of economic instruments in management of Rotorua geothermal field, New Zealand. Geothermics 29, 539 555. Pruess, K. 1991. TOUGH2: A general-purpose numerical simulator for multiphase nonisothermal flows. Lawrence Berkeley Lab., California USA. Ratouis T.M.P., O Sullivan M., and O Sullivan J. 2014. Modelling of the Rotorua geothermal field including chemistry. 36th New Zealand Geothermal Workshop, University of Auckland, Auckland, New Zealand, 18-21 November 2014. Ratouis T.M.P., O Sullivan M. and O Sullivan J. 2015. An Updated Numerical Model of Rotorua Geothermal Field. Proceedings World Geothermal Congress 2015 Melbourne, Australia, 19-25 April 2015 Stewart, M.K. 1978. Stable isotopes in waters from the Wairakei geothermal area, New Zealand. Robinson, B.W. Stable isotopes in the earth sciences. Wellington: DSIR. DSIR Bulletin 220. Stewart, M.K, Lyon, GL, Robinson, BW and Glover, RB. 1992. Fluid Flow in the Rotorua Geothermal Field Derived from Isotopic and Chemical Data. Geothermics 21 (1/2) Special Issue: Rotorua Geothermal Field, New Zealand, 141-163. Werner, C. and Cardellini, C. 2005. Carbon dioxide emissions from the Rotorua hydrothermal system. Proceedings of World Geothermal Congress 2005. Wood, C.P. 1992. Geology of the Rotorua geothermal system. Geothermics, 21(1), 25-41. Yeh, A., Croucher, A. & O Sullivan, M.J. 2012. Recent developments in the AUTOUGH2 simulator. Proceedings TOUGH Symposium 2012, Berkeley, 957

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