Name of Deliverable

Groundwater surface water interaction in GDE Deliverable D4.2

Partner: University of Oulu B. Kløve, P. Ala-aho, G. Bertrand, A. Erturk, A. Gemitzi, E. Gönec A. Moszczynska, M. Mileusnic H. Kupfersberger, J. Kværner, , A. Lundberg, S. Peña Haro, P. Rossi, D. Siergieiev, P. Wachniew, A. Wolak

Deliverable summary

Project title Acronym Contract GENESIS 226536 number Date due Month 28 in GENESIS Final version submitted to EC Month 32 in GENESIS Complete references Groundwater surface water interaction in GDE: GENSIS project deliverable 4.2 Contact person Björn Klöve Contact information [email protected] Authors and their affiliation University of Oulu (UOULU) Project homepage www.thegenesisproject.eu Confidentiality Key words Groundwater, ecosystems, hydrology, groundwater-surface-water interaction, conceptual and numerical models.

Summary (publishable) for This report reviews and discussed the interaction of groundwater policy uptake in GDEs. The report presents and integrates past and new results. Different methods used to measure groundwater interaction with ecosystems are presented. Various GENESIS case studies across Europe to demonstrate the variable and complex role of groundwater in GDEs. The basis for developing conceptual for GDEs is presented. Various methods to model GDEs are discussed.

List of GENESIS partners

Norwegian Institute for Agricultural and Environmental Bioforsk Norway Research (CO)

University of Oulu UOULU Finland

Joanneum Research Forschungsgesellschaft mbH JR Austria

Swiss Federal Institute of Technology Zurich ETH Switzerland

Luleå University of Technology LUT Sweden

University of Bucharest UB Romania

GIS-Geoindustry, s.r.o. GIS Czech Republic

French National institute for Agricultural research INRA France

Alterra - Wageningen University and Research Centre Alterra The Netherlands

Helmholtz München Gesundheit Umwelt HMGU Germany

Swiss Federal Institute of Aquatic Science and Technology EAWAG Switzerland

University of Science and Technology AGH Poland

Università Cattolica del Sacro Cuore UCSC Italy

Integrated Global Ecosystem Management Research and IGEM Turkey Consulting Co.

Technical University of Valencia UPVLC Spain

Democritus University of Thrace DUTh Greece

Cracow University of Technology CUT Poland

University of Neuchâtel UNINE Switzerland

Athens University of Economics and Business- Research Centre AUEB-RC Greece

University of Dundee UNIVDUN United Kingdom

University of Zagreb - Faculty of Mining, Geology and UNIZG-RGNF Croatia Petroleum Engineering

Helmholtz Centre for Environmental Research UFZ Germany

Swedish Meteorological and Hydrological Institute SMHI Sweden

University of Bologna UBOLOGNA Italy

University of Kiel UKIEL Germany

Table of contents

1. Introduction ...... 7

1.1 Groundwater in aquatic and terrestrial ecosystems ...... 7

1.2 Water Framework and Groundwater Directive ...... 9

1.3 Presentation of GENESIS studies ...... 9

2. Measurement approaches to detect groundwater in GDE ...... 12

2.1 Hydrogeological measurements in GDEs ...... 12

2.2 Temperature and EC as indicators of groundwater ...... 14

2.3 Geochemistry as indicator of groundwater ...... 16

2.4 Isotopes as indicators of groundwater ...... 18

2.5 Tracer tests ...... 21

2.6 Mapping of recharge and discharge points ...... 22

3. Results from GENESIS main GDE study sites ...... 23

3.1 Esker aquifer lake interaction, Rokua Finland ...... 23

3.1.1 Hydrogeology, site description and methods ...... 23

3.1.2 Major outcome from the study ...... 25

3.1.3 Conceptual models for surface water – groundwater interaction ...... 26

3.2 Lule river hyporheic zone interaction, Sweden ...... 29

3.2.1 Hydrogeology, site description and methods ...... 29

3.2.2 Major outcome from the study ...... 33

3.3 Riperian zone interaction, Switzerland ...... 34

3.3.1 Hydrogeology, site description and methods ...... 34

3.3.2 Major outcome from the study ...... 35

3.3.3 Conceptual models for surface water – groundwater interaction ...... 36

3.4 Dalyan Mediterranean Lagoon, Turkey ...... 42

3.4.1 Site Description and Hydrology ...... 42

3.4.2 Methods ...... 45 3.4.3 Major outcome from the study ...... 50

3.4.4 Conceptual models for surface water – groundwater interaction ...... 51

3.5 River lake lagoon interaction, Greece ...... 53

3.5.1 Hydrogeology, site description and methods ...... 53

3.5.2 Major outcome from the study ...... 54

3.5.3 Conceptual models for surface water – groundwater interaction ...... 55

3.6 Bogucice Sands - Niepolomice Forest, Poland ...... 59

3.6.1. Site description, hydrogeology and water use ...... 59

3.7 Częstochowa aquifer interaction, Poland ...... 64

3.7.1 Hydrogeology, site description and methods ...... 64

3.7.2 Major outcome from the study ...... 67

3.7.3 Conceptual models for surface water – groundwater interaction ...... 69

3.8 The Grue site, Norway (Bioforsk) ...... 71

3.8.1 Site description, hydrogeolgy and methods ...... 71

3.8.2 Major outcome from the study ...... 71

3.8.3 Conceptual models for surface water – groundwater interaction ...... 74

3.9 Sava river, interaction with groundwater ...... 75

3.9.1 Hydrodynamic pattern of the Sava River – groundwater interaction ...... 76

3.9.2 Hydrogeochemical evidence of the Sava River –groundwater interaction ...... 79

3.10 Fontanili springs, Italy, Hydrogeology, site description and methods ...... 80

3.10.1 Introduction ...... 80

3.10.2 Groundwater – Surface Water interactions: Fontanili of the Lombardy Region ...... 86

3.10.3 Major outcome from studies on selected fontanili ...... 90

3.10.4 Conceptual model for surface water – groundwater interaction ...... 91

4. Modelling of surface-groundwater interaction in aquifers ...... 92

4.1 Groundwater interaction with ecosystems ...... 92

4.2 Conceptual models ...... 93 4.3 Numerical modelling needs and approaches ...... 94

4.3.1 Numerical modelling needs ...... 94

4.3.2 Water balance calculation in GDEs...... 96

4.3.3 Surface water groundwater interaction models ...... 97

4.3.4 Stream-aquifer interaction models ...... 98

4.3.5 Leakage coefficient approach ...... 98

4.3.6 Future modeling needs...... 100

References ...... 102

Appendix 1 ...... 113

Appendix 2 ...... 118

1. Introduction

1.1 Groundwater in aquatic and terrestrial ecosystems

Groundwater dependent ecosystems (GDEs) may be defined as ecosystems for which current composition, structure and function are reliant on a supply of groundwater. GDEs are a vital but as yet not fully understood component of the natural environment. In many cases groundwater makes an important but poorly documented contribution to various aquatic and terrestrial ecosystems such as: I) rivers and lakes including aquatic, hyporheic, hypolenthic and riparian habitats, II) subterranean aquifers and caves, III) wetlands and springs, and IV) estuarine and nearshore marine ecosystems (adapted from Boulton, 2005). The aquifer itself is also an important ecosystem (Danielopol and Pospisil, 2001).

The ecosystem reliance on groundwater may be continuous, seasonal or occasional. The reliance becomes apparent when the supply of groundwater is removed for a sufficient length of time that changes in plant function (typically rates of water use decline first) can be observed. Groundwater is often the main source of water for vegetation in dry climates. Some systems, such as springs, are completely fed by groundwater and would not otherwise exist. This is also reflected in flora and fauna, with springs harbouring many species adapted to these special conditions. In general, groundwater provides water, nutrients, buoyancy, and stable water temperature, but the effects of this on GDEs are not thoroughly documented.

Fig 1.1-1 Flow lines and groundwater levels in a cross-section of soil/rock with homogeneous and isotropic hydraulic conductivity, with possible locations of GDEs (Klöve et al 2011a).

Groundwater moves along flow paths from recharge areas to discharge areas within GDEs (Fig. 1.1-1). Infiltration occurs when meteoric water (including retarded fractions such as snow and glaciers) enters the ground. Water then usually moves through the unsaturated zone and reaches the saturated part of the aquifer contributing to groundwater recharge. Some surface waters both receive and recharge groundwater. Groundwater recharge may include contribution from adjacent aquifers. Discharge from the aquifer occurs at springs, streams, lakes, wetlands, transpiration by plants with roots that extend to near the water table and by direct soil water and groundwater evaporation. Groundwater can also discharge to adjacent aquifers (e.g. downward leakage from an aquifer to a deeper one). Groundwater typically discharges to surface water bodies where the slope of the water table changes suddenly (e.g. Winter et al., 1998). In many cases springs are found where geological layer and/or hydraulic conductivity of the aquifer change. The actual conceptual model for a given aquifer will vary locally depending on geology, climate, water use, slope and topography. This should also include the unsaturated zone which plays an important role both for groundwater quantitative and quality aspects. Local groundwater flow often occurs near the surface and over short distances, i.e. from a higher elevation recharge area to an adjacent discharge area such as small springs. Intermediate and regional flows usually occur at a greater depth and over greater distance. Steeper and undulating landscapes have the most local flow points. Groundwater flow is always three-dimensional, but can often be analysed in two-dimensional cross sections (Fig. 1.1-1). Analysis of these flow paths is important when studying GDEs because it can provide valuable information about potential threats to the quantity and quality of groundwater.

Different ecosystems depend on groundwater in complex ways. Some springs, such as karstic systems, show very high variations of discharge or often run dry occasionally (intermittent springs). Peatlands fed by surface flow, rain and groundwater are adapted to stable water tables fluctuating near the soil surface. Fens receive a continuous supply of groundwater and bogs receive only precipitation on the surface but groundwater pressure provides buoyancy and prevents drainage. The hydrogeology and multi-scale flow patterns influence both the timing and duration of groundwater discharge (hydroperiod). From a hydro-ecological point of view, the concept of hydroperiod provides an interesting starting point for the classification of GDEs because it integrates several abiotic parameters (drivers), e.g. climate, extent of flow paths, aquifer type (i.e. porous or discontinuous) and land use of the catchment, which eventually constrain ecological uses of groundwater. Four types of hydroperiods can be distinguished (adapted from Alfaro and Wallace, 1994):

- Periodic: Usually a clear seasonal pattern, average discharge climatically controlled precipitation/evapotranspiration changes). - Intermittent: Great variability in flow. - Episodic: Completely irregular flow, occurring only when there are very high water levels in the aquifer. - Perennial: Continuous source year round.

As a function of these features, the importance of groundwater supply relative to other potential water sources varies. A constant supply of groundwater normally maintains dependent ecosystems such as wetlands and springs typically located in landscape depressions. Here, groundwater is most likely the sole or dominating source of water. The high contribution of groundwater compared with other water sources can be seen if i) the water quality directly reflects that of groundwater, or in dry climates ii) if the transpirative water losses from vegetation are maintained by groundwater. As these systems exhibit a rather constant temperature that differs from that of adjacent surface waters, temperature can also be used as a tracer to evaluate the degree of groundwater-surface water interaction (Anibas et al. 2011). In addition, the vegetation composition of GDEs will often reflect groundwater composition.

Biological processes in GDEs can have an influence on hydrology which is not well known. Microbial activity forms biofilms that cover stream beds potentially affecting the permeability of the stream bed. Succession of vegetation in ecosystems changees hydrological processes such as interception and evapotranspiration. Vegetation also influences flow resistance, and flow influences the vegetation composition (e.g. emergent vegetation is not present if flow is above 1 m/s, see e.g. Bertrand et al. 2011). Discharge dynamics also affect the substrate composition, which influences the diversity and nature of macrozoobenthic communities (ecologic, phenotypic and genotypic adaptations, Bertrand et al. 2011).

A spatially and temporally integrated view of relations between the GDEs and the local and regional groundwater flow systems can be provided by environmental tracers such as stable isotopes of water, tritium, noble gases, CFCs or SF6 (e.g. Kværner and Kløve, 2006). Besides their significance in developing conceptual and numerical models of flow and transport in groundwater systems, the environmental tracers allow identification and quantification of sources of discharge to GDEs as well as dating of groundwater. Knowledge of groundwater age distribution is a key factor in the assessment of GDE vulnerability to climate and land-use changes, groundwater exploitation and pollution. Dominant time scales of water flow and solute transport to the ecosystem determine time lags associated with its responses to both commencement and cessation of such disturbances.

1.2 Water Framework and Groundwater Directive

GDEs and associated aquatic ecosystems are important to protect as they provide many ecosystem services. A few GDEs, such as some wetlands, are important for migratory birds or rare species and are protected by international and local agreements and legislation. Wetlands have been protected by the international Ramsar convention on wetlands since 1971. In Europe legal actions with strong commitments for environmental protection include the Habitat Directive (EC, 1992) with the Natura 2000 network of protected sites and strict system for species protection. In Europe groundwater is threatened by land-use, pollution and extensive water use for irrigation. The Water Framework Directive (EC, 2000) aims to achieve good quality of surface and ground water by 2015. Therefore, groundwater threshold values must be set to protect associated aquatic ecosystems and human health (Hinsby et al 2008). Protection of surface waters is also need for economical and recreational point of view. The Groundwater Directive (EC, 2006) lists several pollutants that should be assessed and provides regulation to limit pollution, reverse upward trends, and protect groundwater resources. Also it requires that nearby ecosystems relying on groundwater must not be damaged due by changes in groundwater quality or quantity. For assessment of vulnerability of these ecosystems more information is needed about the role of groundwater in ecosystems (Hinsby et al. 2008).

1.3 Presentation of GENESIS studies

In GENESIS groundwater interaction with lakes, rivers, springs, peatlands, forests and costal lagoons are studied for different regions, climate and land-use pressures (Table 1.3-1, Fig. 1.3-1). Both aquatic and terrestrial systems are studied. Measurements on the sites started as the GENESIS project started in 2010 and still continues. This report gives an overview of measurements carried out and first results with focus on groundwater-surface interaction. Table 1.3-1 List of main sites studied in GENESIS.

Socio- Site and Aquifer economic Anthropogenic GDE types Climate location description use of GDE threat and aquifer

Esker, Recreation, Lakes, springs, shallow Cold Natura 2002 Rokua, Finland streams, Forestry unconfined temperate protection, peatlands sand deposit forestry

Lule river River hyporheic Cold Recreation, No aquifer Hydropower Sweden zone temperate hydropower

Rhone river floodplain, Switzerland

Confined Bogucice layered Natura 2002, Sands - Fen interaction aquifer with Potable Potable water Niepolomice with deep Temperate uphill water extraction Forest, Poland groundwater recharge extraction

areas

Lagoon Agriculture, interaction with tourism, Dalyan lagoon surface, Mediterranean Irrigation fisheries, groundwater Ramsar site and sea water

River lake Semi Agriculture, Vosvoziz river, lagoon confined Mediterranean fisheries, Irrigation Greece interaction, alluvial plain Natura 2000 Greece

Sava river,

Croatia

Cultivation and Grue, Glomma River cultivated Cold No aqui Agriculture pesticide river, Norway field interaction temperate application

Czestochowa aquifer, Poland

Fig. 1.3-1 Map of GENESIS study sites. 2. Measurement approaches to detect groundwater in GDE

2.1 Hydrogeological measurements in GDEs

Hydrological measurements form the first tool to water resources such as groundwater. These measurements give information on quantity of water at a given time and space. Sometimes this can directly indicate groundwater exfiltration. For example if base flow is high the input of groundwater to the ecosystem is usually high. Hydrological data on water quantity is also needed to establish water balances that are needed to understand many systems. Water levels and pressure head in groundwater and GDEs can directly indicate the direction of flow and show interactions. Other methods can be powerful to show flow pathways and flow lines. Here we will review some hydrogeological methods used in GENESIS that are not part of standard hydrological measurements such seepage meters (Lee 1977), and potentiometric measurements (Rosenberry and LaBaugh 2008) and present our experiments with these measurements.

Lake, groundwater or river water level measurements should be carried out with fixed points to ensure no movement of the base level and for later comparison of data. Lake stage can be monitored with a method often used in steam stage monitoring. Water level is recorded from a stilling well which is hydraulically connected to the stream. For lake or river level measurements in cold conditions, the monitoring should be done from shore undergrounds to ensure also monitoring during frost (Fig. 2.1-1). It is advisable to place loggers hidden from public.

Fig. 2.1-1 Lake level measurement with logging pressure sensor. Seepage meters are useful to measure the inflow of groundwater to and from lakes (Fig. 2.1- 2).

Fig. 2.1-2 Seepage measurement.

Potentiomanometer can be used to determine the direction of hydraulic gradient between surface water and groundwater. Method can be applied to small streams in the groundwater discharge area where seepage meter is not applicable.

Fig. 2.1-3 Use of potentiomanometer in a small streams located at peat production area (left) and groundwater discharge area (right) to determine the direction of water seepage.

In many cases also geophysical measurements provide important information in GDE. Ground penetrating radar can be used on the lake ice to give the layering of sediments as shown in Fig. 2.1-4.

Fig. 2.1-4 Lake bed profile from ground penetrating radar measurement.

2.2 Temperature and EC as indicators of groundwater

Temperature In natural systems where no significant phase change (e.g. evaporation) occurs, temperature can be used as a heat flow tracer. The interest in temperature monitoring of GDEs is based on the principle that groundwater temperature is relatively stable throughout the year whereas surface water temperature heavily depends on daily and seasonal air temperature variations. Where these two systems are hydraulically connected, heat (energy) in the subsurface is transported by flowing water (advection), as well as by heat conduction via the fluid and solid parts of the soil matrix (e.g. Stallman 1965). The advective flow strongly influences the temperature distribution in the mixing zone between groundwater and surface water, called hyporheic or hypolentic zones (HZ) respectively for flowing and lentic systems. Hence water movement between groundwater and surface water can be traced by measuring temperature distributions between the two systems (Constantz and Stonestrom, 2003; Anderson, 2005). Thus, temperature is intensively used as qualitative and/or quantitative indicator of flow in most of GDE investigations. At first, spatio-temporal thermal variability in the HZ permits to allocate zones of groundwater recharge or discharge. Schematically, gaining river reaches or lake shores are characterized by relatively stable temperatures, whereas losing reaches demonstrate vastly variable heat balance behavior (Fig 2.2-1; Shimada et al., 1993). Secondly, quantitative variables can also be estimated. Thermal patterns of the HZ can be used to derive hydraulic conductivities (Su et al., 2004) if water fluxes are known. Flux estimates are possible by fitting solutions of the heat flow equation to observed temperature distributions in the soil. This approach implies to use heat capacities and conductivities of water and rocks and to identify the hydrological state of the system that is steady-state or transient. In this later case, boundary conditions should be controlled with care, what increase the input data requirement (Anibas et al., 2009). Fig 2.2-1 Conceptual scheme of temperature use to assess SW-GW exchanges in a gaining (left) and losing (right) reach. From a technical point of view, most of the temperature sensors are portative, simple to set up, robust, accurate (accuracy ±0,1°C)and inexpensive in comparison to other environmental measurements devices. Expanded memory permits long working time. Recently, significant progress were made in the understanding of HZ processes, through high frequency monitoring (Hoehn and Cirpka, 2006; Vogt et al., 2010). This tool was also revealed to be highly useful to understand disturbed system such as hydropower regulated environment (Gerechtet al., 2011). Apart from direct measurements of temperature using deployed sensor techniques an airborne IR technology can be applied where large scale spatial distribution of recharge/discharge zones should be defined. An example of IR measurements form a stream is shown in Fig. 2.2-2.

Fig. 2.2-2 Image of temperature photography from a stream with groundwater intrusion (black color, photo Pöyry Ltd). Thus, in several Genesis case studies, temperature monitoring at various spatio-temporal scales is actively employed. For example, the evaluation of lake-groundwater interactions (localizations, fluxes) was carried out within a large esker body in Finland (UOULU); and river-groundwater interaction downstream to a dam in Sweden (LTU) in order to provide basis for flow modeling. Due to retardant behavior of temperature (especially where conduction is important in comparison to advection), this tracer cannot be easily used to evaluate water transit times over long distances. Combination with another tracer technique is often necessary. Electrical conductivity

Electrical Conductivity (EC) is an indicator of ionic content of water. Usually, there is a large difference in EC between surface water and groundwater. This difference is due to heterogeneity of transit times (generally longer within aquifer, allowing longer water-rocks interactions) and of weathering degree (alteration power is higher in sub terrain systems due to higher pCO2) (Appelo and Postma, 2005). This gradient is even greater in coastal areas where GDEs are influenced by seawater intrusions. Fluctuations of EC results from variation of total dissolved solids. Electrical conductivity propagation has the advantage to be mainly dependent on Darcian velocity through the porous media concurrently showing less smooth trend (Cirpkaet al., 2007) which is not the case for the temperature. In aquatic ecosystems, EC variability may be caused by biological carbon turnover on seasonal scale, and such factors as photosynthesis and respiration on diurnal basis (Odum, 1956). More stable signal from EC varies on a diurnal basis due to variations in bicarbonate and hardness (affect inorganic carbon cycle equilibrium, provoking phase changes – either precipitation or dissolution of calcium and magnesium carbonates), on several days basis as a result of extended precipitation, and on seasonal basis reflecting winter base flow conditions dominated by the groundwater flow (in majority of the cases). Similarly to temperature monitoring, different infiltration regimes can be registered by analyzing diurnal and seasonal EC patterns. As it has been observed by Hatch et al. (2006) daily EC variations are predominantly distinct at low river water level and high temperatures. Diurnal photosynthetical processes responsible for pCO2 fluctuations keep EC highest in the early morning, and lowest in the afternoon. Seasonal variations usually introduce discrepancies between the river and groundwater data sets and can be mathematically removed. Assuming a constant EC in the subsurface waters SW-GW interactions may be evaluated through deconvolutions of the temporal EC signal on the SW-GW interface. This technique also assumes that EC is a conservative tracer, what is not the case in reality. Consequently, to allow the direct evaluation of water transit time, EC modifications due to weathering or precipitation processes should have significantly slower kinetics than water velocity. There is a variety of conductivity measuring cells available on the market. Many of them incorporate logger, some require an external logger connection. Due to the temperature dependency of measured EC, these devices are often combined with temperature sensors. The instruments obtained high measuring accuracy however they require periodical calibration due to foiling and drift. In the Luleå case study (LTU) EC is used in conjunction with temperature and water level measurements. Higher EC values are observed at the day start when CO2 concentrations are highest and during winter when the base flow is dominant (relevant for the pristine Kalix River). High river water stages in the hydropower regulated Lule River provoke decreased EC plume in the HZ.

2.3 Geochemistry as indicator of groundwater

Geochemistry of groundwater is usually characterized by the bedrock and porous media where it flows. This leaves a signal to the groundwater that can be distinctly different from surface water. Precipitation is usually free from or low in most weathering products. The potential use of geochemistry as indicator depends on i) the stability or conservative nature of the chemical compound, ii) differences in end-members (e.g groundwater and precipitation). In theory chemical composition of water can be used to determine age and hydrograph separation to estimate the portion of groundwater. Age determination is qualitative (old or new etc).

In many cases groundwater composition is stable whereas surface water responds more rapidly to precipitation events and biological in-stream retention and release of substances. Also the rate of erosion and decomposition rates of vegetation influence stream water composition. Typically streams have highest suspended matter and humic compounds seen as elevated color, dissolved organic matter, TOC, DOC and BOD

In groundwater the chemical composition can vary spatially from point to point. This is normally due to changes in sediment and bedrock properties, water residence time in soils and rock and pH. Changes in pH directly influence composition and concentration of many elements such as Al. Redox potential and oxygen content will also influence the composition. Recently percolated water or unsaturated soil layer (vadoze) water is normally different from groundwater.

Geochemical compounds that have been used in hydrological studies include SiO2, electrical conductivity (EC). SiO2 is a weathering product and it seems to increase with groundwater age. Similarly EC increases with age and is higher in groundwater than in rainwater. As EC is easily measured automatically, it can give information on events as shown in fig 2.3-1 where inflow and outflow hydrographs are shown for a Fen in Norway (Kværner and Kløve 2008).

Fig 2.3-1 Hourly stream water electric conductivity (lS m_1) and runoff at fen inlet and outlet during episodic events (Kværner and Kløve 2008).

Chloride (Cl) in precipitation is a useful tracer. Its mean concentration in rainwater depends on distance from the sea. It is a conservative compound with no or little reaction and it increases only due to evaporation. It is also commonly linked to pollution such as application of road salt, municipal waste and sewage. It can indicate sea water intrusion or relict sea water or salt deposits in the ground. Following Cl as a tracer can be valuable with other tracer measurements as it is conservative and therefore indicate external input from contaminated sites or different waters. It is also useful for mass balance studies in case of evaporation being a major component. Cl normally correlated well with EC which is easily and affordably measured in the environment, at least when the Cl concentration is high.

There are some difficulties in using geochemistry however. The compounds can be influenced by pH-Eh environment. Also the concentration can be time dependent so different end members are difficult to define for hydrograph separation. Also, they are not as widely used as isotopes.

2.4 Isotopes as indicators of groundwater

Fig 2.4-1 Distribution of measured 18O and artificial tracer addition in a peatland that received peat harvesting runoff water (treatment wetland). The main flow field is shown with a thick line. (Ronkanen and Kløve, 2008)

Water isotope measurement within a GDE show areas where flow occur and this can be related to flow fields in GDE which is useful for calibration of models. In systems with small amount of inflow with constant properties, areas of elevated18O would indicate stagnant zones with no flow if system is sampled after a dry period. Evaporation of surface water bodies (E) leads to enrichment of the liquid phase in heavy isotopes 2H and 18O. Consequently, stagnant zones within the wetlands will have a high evaporation/inflow (E/Q) ratio and should be characterized by elevated 2H and 18O content compared to the inflow of wetlands when E/Q is low. Therefore, properly designed survey of stable isotope composition of water within the given wetland system should yield important information concerning spatial heterogeneity of isotopic composition of water in this system. Isotopic composition can be linked to the water flow patterns, residence time and preferential flow. Stabile isotopes are useful also when the residence time in GDEs is very long and tracer additions cannot be used due to (i) unsteady flow caused by changing hydraulic load and weather, (ii) density currents (Schmid et al., 2004) and (iii) high costs or intensive time requirement. The principle of this method is highlighted in figure 2.4-1 (Ronkanen and Klöve, 2008) that shows measured 18O and artificial tracer addition in a peatland wetland that received runoff water (treatment wetland).

Areas of groundwater upwelling would be seen as different isotopic signatures than areas that receive surface water only. Studies of isotope can show areas where groundwater interacts with the GDEs.

In surface water - groundwater interaction isotopes can be used to verify this contact. A classical example is the study of stream water influence on groundwater in a pumping well along the stream bank (Fig 2.4-2, after Stichler et al. 1986). Applying mathematical flow models to environmental tracer data it is possible to obtain the following practical information in bank filtration research problems: (1) calculating the portion of river water infiltrating to the groundwater; (2) determining flow parameters: mean transit time of water, T, and dispersion parameter, D/vx; and (3) predicting possible contamination of the groundwater by pollution of the river water.

Fig 2.4-2 Schematic model of streamwater mixing into a groundwater pumping well along a stream groundwater area of the Danube river (Stichler et al 1986).

Lake–groundwater interactions isotope studies have focused on i) modelling of the water flow in the surrounding lakes (e.g. Winter, 1978, 1983; Cheng and Anderson, 1994; Kacimov, 2000, 2007; Abbo et al., 2003) and ii) application of environmental tracer data to calculate water balance in lakes (e.g. Zuber, 1983; Gonfiantini, 1986; Herczeg and Imboden, 1988; Yehdegho et al., 1997; Katz et al., 1997 or Kumar et al., 2001). A recent study below (Fig 2.4-3) shows how a groundwater well capture zone can be estimated and the portion of lake water in the groundwater can be estimated with environmental isotopes (Stichler et al 2008).

Fig 2.4-3 Simulated contour lines of hydraulic head (m. a.s.l.), lake water proportion (%) in down gradient aquifer and final contour of the capture zone (grey shade) found as a best fit for observed and simulated hydraulic heads and lake water proportion distribution (Stichler et al 2008).

2.5 Tracer tests

Artificial tracers (isotopes, salt, fluorescent dyes and color) can be added to groundwater or surface water to study flow processes in aquifers and related ecosystems. Typical additions points are groundwater wells or stream points with good mixing conditions. The benefit of using salt such as NaCl is that it can be easily measured with electrical conductivity after calibration of conductivity probes. The use of salt pose a risk of density currents and the flow velocity (Reynolds number) of the system must be sufficient. If used in groundwater piezometers, these must be properly mixed after salt addition.

Tracers show flow pathways and give information about aquifer structure including hydraulic conductivity. Tracer tests in streams can give information on hyporheic exchange. Sometimes conservative tracers are used in combination with reactive tracers if retention of substances is studied. Typically also several tracers are used in parallel. Sometimes simple tracers can be used first before a more detailed analysis with e.g. radioactive 3H. The use of radioactive tracers normally requires a permit from authorities where risk of use is estimated. Tracer test require detailed plans for monitoring design. Normally, they give important new information about the groundwater system (Fig. 2.5-1).

Fig. 2.5-1 Injection well and detection wells. This tracer experiment showed groundwater flow from injection well towards wells 1-3 (photo UNIZG-RGNF, Croatia). 2.6 Mapping of recharge and discharge points

In many cases mapping of recharge and flow patterns in space can be valuable. This can be done using maps e.g. to detect fracture zones that potentially carry groundwater (Fig. 2.6-1).

Fig 2.6-1 Groundwater exfiltration from fractured rock along faults and fracture zones (www.ngu.no).

In shallow small groundwater systems the recharge-discharge patterns can be complex. In many cases a detailed survey of discharge patterns is crucial to understand the overall flow system. A result from such a analysis is shown in Fig. 2.6-2 for the Rokua sand aquifer in Finland.

Fig. 2.6-2 Discharge measurement points (blue dots) from the Rokua recharge area (white area). Relative size of blue dot shows the amount of baseflow run-off. 3. Results from GENESIS main GDE study sites

3.1 Esker aquifer lake interaction, Rokua Finland

3.1.1 Hydrogeology, site description and methods

Esker aquifers were formed during the last deglaciation some 9000-12 000 years ago (Tikkanen 2002). Long and narrow formations of sand and gravel are associated with the retreat of the ice (Svendsen et al. 2004), which in Fenno-Scandinavia had its centre just north of the Bay of Bothnia. Eskers form important aquifers in the Fenno-Scandinavian shield and are also common in other regions covered by the last glaciation.

The Rokua esker area forms part of a long esker ridge stretching inland from the North Ostrobothnian coast (Aartolahti 1974; Ala-aho 2010). It is situated 100 km inland from the coast, has an area of 90 km2 and rises at its highest point about 80 m above the surrounding peatlands. It is clearly visible in an otherwise flat landscape. The esker material consists mainly of sand with layers varying in thickness from 30 m to more than 100 m above the bedrock. A deposit of gravel has also been found. Rokua has a rolling terrain because of kettle hole, wave action and aolian dunes (Aartolahti 1974). In contrast, the surrounding peatlands started to form some 8000 years ago between the sand deposits and in some kettle holes (Pajunen 1995). These peat layers have grown to be in some locations more than 5 m thick and have a low permeability (Fig. 3.1-1). Groundwater recharges on the esker sand areas and discharges to surrounding peatlands and nearby water bodies.

Fig 3.1-1 Cross-section of Rokua esker with location of groundwater table, potentiometric surfaces and indication of water level variation and flow patterns in ecosystems (arrows).

Eskers are often connected to rivers, lakes and wetlands, and such groundwater-dependent systems are of high ecological value (Kløve et al. 2011a; 2011b). Ecosystems protected by NATURA2000 in Rokua area include rare lake types, old forests in natural state and lichen coverings supporting endangered vegetation and insect species.

As lakes on the Rokua esker are embedded in the aquifer, both lake water levels and water quality are highly dependent on the aquifer system. The highly dynamic relationship between lake systems and aquifers is largely determined by geology, climate and topology of the area. Interactions between lakes and groundwater can be divided into three basic types. The lake can have: 1) groundwater inflow from the entire lake bed (groundwater discharge); 2) groundwater outflow from the entire lake bed (groundwater recharge); or 3) both situations occurring at the same time in different parts of the lake (Winter et al. 1998, Ala- aho 2010). Groundwater exchange not only affects lake water levels and water chemistry, but also lake ecosystems by providing nutrients, inorganic ions and stable water temperature (Hayashi and Rosenberry 2002).

Groundwater-fed kettle lakes of Rokua consist of two different types. Lakes without outlet are clear and oligotrophic. Lakes with outlet on the other hand are more humic and eutrophic. Both lake types are in a natural state and have a high recreational value though groundwater level decline has caused changes in lake vegetation (Metsähallitus 2008). Another groundwater dependent ecosystem in Rokua area are the springs in the surrounding peatlands. Many of these springs have dried due to peatland drainage which has changed the groundwater flow systems (Rossi et al. submitted). Spring ecosystems in Rokua discharge area are mostly not included in natural conservation programs as they are too heavily altered.

Groundwater-surface water interaction in the kettle lakes were studied with seepage meters (Lee 1977), chemical analysis and potentiometric measurements (Rosenberry and LaBaugh 2008). Seepage meters were used to measure temporal variation of groundwater discharge and recharge rates in a pilot lake Ahveroinen. Measurements were made during two sequential years. First year (2009) focus was more on the spatial variation, where the second year (2010) measurements focused on the temporal changes in seepage. Chemical analyses were used as natural tracers to define groundwater and rainwater ratios of lake inflow. Potentiomanometer was used to identify groundwater exfiltration areas in peatlands. Manometers will also be used in lakes for seepage definition and water sampling. 3.1.2 Major outcome from the study

Seepage measurements during years 2009-2010 revealed high spatial variation in seepage velocities around the lake (fig. 3.1-2), with values ranging from -0.95 – 56 µm/s.

Fig 3.1-2 Interpolated seepage velocity around the lake during two consecutive years. For both years inseepage is concentrated in the southern part of the lake, but outseepage shows variation between years.

Results for year 2009 show inseepage areas in the southern part of the lake, and only obvious outseepage measurements are found in north-east. During year 2010 inseepage was again measured in the southern part, but outseepage was more concentrated in the western shore. Interpolation and spatial distribution for 2010 is not as accurate as for 2009 because of only six measurement locations (2009 16 locations). Reasons for differences in measurements between 2009 and 2010 need further investigation, but are most likely related to measurement errors (more probable in 2009 measurements) and differences in hydrological conditions between years.

To reveal temporal variability in seepage velocity in lake Ahveroinen, eight seepage meter measurements were made from six locations (fig 3.1-3) during 1.6.2010 – 4.11.2010 (in total 64 measurements). Fig 3.1-3 Temporal variability for each measurement point 1-6 during year 2010.

According to seepage meter measurements seepage velocities remained quite constant during measurement period, with no dramatic changes in e.g. direction of seepage from inseepage to outseepage. Nevertheless seepage shows similar behaviour especially in points where outseepage was constantly measured (points 1,2,4 and 6). This suggests that temporal variation in seepage was not entirely caused by random variability and measurement errors, but was to some extent related to changes in hydrological conditions (groundwater and lake levels) during study period.

Spatial and to some extent also temporal variability of groundwater-lake interaction in pilot lake Ahveroinen gives valuable insight of hydrology of all the lakes in Rokua esker area. Lakes in the area are situated in different parts of the esker with unique hydrogeolological settings surrounding each lake. Thus contribution of groundwater in lake hydrology can vary significantly between individual lakes. This can lead to different behavior of lakes water levels and also possibly trophy status in changing hydrogeological conditions, such as extreme droughts.

3.1.3 Conceptual models for surface water – groundwater interaction

Lakes in the aquifer can roughly be divided to two categories with following attributes: Table 3.1-1 Attributes characterizing lake types.

Attribute Type 1 Type 2

Lake level variability high/moderate low

trophic status oligotrophic eutrophic

nutrient/ion concentration low high

connection to streamflow closed basin lake inlets and outlets

elevation on the esker lower higher

Many of the differences between two lake types can be explained by the conceptual idea of local and regional groundwater flow systems (Fig 3.1-4):

Fig 3.1-4 Conceptual model of regional and local groundwater-lake interactions.

Water levels in type 1 lakes depend on groundwater inflow from local flow system. There GW inflow and outflow are mainly determined by GW-levels adjacent to lake. Therefore changes in GW-table (resulting from changes in recharge) can have a significant impact in GW-SW interaction. Residence time of GW discharging to lake is relatively short, possibly leading to less leaching and chemically poor water (Fig 3.1-4).

In type 2 lakes, water level is affected by regional GW flow system, in addition to local flow systems. Inflow is less sensitive for GW-table fluctuation/decline, as regional flow system sustains steady inflow and local inflow can be replaced by regional inflow during season of low recharge. Also inlets and outlets connecting the lakes favor steady water table. Residence time of regional GW-flow is longer, leading possibly to more leaching from soil to groundwater (Fig 3.1.-5).

Fig 3.1-5 Silica content with respect to lake altitude and lake type. More silica can be explained by leaching and longer residence time.

3.2 Lule river hyporheic zone interaction, Sweden

3.2.1 Hydrogeology, site description and methods

Introduction

River regulation is extensive; about two thirds of fresh water flow into the sea is today delayed by dams higher than 15m (Nilsson & Berggren, 2000). Malm Renöfält et al. (2010) summarize the resultant pressure on freshwater ecosystems as:”Freshwater ecosystems now belong among the world’s most threatened ecosystems”. Further stress on rivers can be expected with pressure to increase hydropower production when phasing out of fossil fuels and increasing the use of alternative power.

The pristine northern rivers are gaining (fed by the groundwater aquifers), even if shorter stretches might be losing (e.g. Johansson et al. 2001) and the water stages in the ground and the river are synchronized so high river water and groundwater stages typically coincide. However, in regulated rivers this pattern is disturbed since high river water stages will occur when the groundwater levels are low and vice versa. When short time regulation is practiced rivers might change from gaining to loosing and back again within a day resulting in a disturbed hyporheic zone and a perturbed ecosystem (Andersson et al. 2000; Nilsson & Berggren 2000; Jansson et al. 2000; Jansson 2006).

In northern regulated boreal rivers the water is released fairly evenly throughout the year in contrast to the normal seasonal runoff pattern with a clear snowmelt runoff peak (Fig 3.2-1). Parts of the river stretches have minimum runoff while most of the water for these stretches is diverted through tunnels to a turbine and then returned to the river (Figure 1). In many rivers short time regulation is also applied in order to adjust the energy production to the energy demand (large fluxes during days and small during nights). All these river and lake alterations have impact on the groundwater in the river basin. In this study we focus on the effects of altered seasonal pattern and short time regulation on the hyporheic zone, which is the area just under and close to the river, where groundwater and river water mix.

During the last decade processes in natural hyporheic zones have been studied extensively (Johansson et al. 2001; Jonsson & Wörman 2001; Landon et al. 2001; Cardenas & Wilson 2007; Claret & Boulton 2008). However, the knowledge regarding the hydrogeochemical processes in the hyporheic zone for regulated rivers seems limited. Most studies seem to focus on the water and heat fluxes (Sawyer et al. 2009; Arntzen et al. 2010; Gerecht et al. 2011) while studies of river regulation and resulting alterations of geochemical processes seem rare (Nyberg et al. 2008).

Aim and scope

In order to increase our understanding of hyporheic zone processes when rivers are exposed to seasonal regulation and short term stage fluctuations a test site has been installed at the heavily regulated Lule River. The aim with the monitoring program was to register major changes in groundwater fluxes, temperature patterns and geochemistry of the hyporheic zone.

Fig 3.2-1 Conceptual representation of a pristine river (top) and the same river obstructed by hydropower dam (base). Seasonal pattern of river discharge, groundwater stages and groundwater flowpaths in response to river level fluctuations are shown. River basin description

The Lule River is located in Northern Sweden; the river originates in the Caledonide mountains with tundra type vegetation and flows south east through coniferous forests. The upstream parts of the river include quartzite, mica schist, and amphibolite with a little dolomite and limestone. Volcanic and plutonic rocks with till and podzol soils are prevalent downstream (Fromm, 1965). The climate is sub-arctic with monthly average temperatures ranging from –15ºC to +14ºC. Annual precipitation decreases from 1,000-1,500 mm in the mountains to 400-700 mm at the coast and about 45% of it falls as snow. Annual evapotranspiration is 100 mm in the upstream areas and 300 mm at the coast. The Lule River is typically ice covered 5 months. The river is around 440 km long with the drainage area 25110 km2 and average annual runoff 506 m3/s (SMHI, Svenskt Vattenarkiv). Site description

The Lule River case study site is located 100 km upstream from the river mouth (Fig. 3.2-2) and a couple of km below a dam. The regulation pattern implies relatively low spring peaks and high winter base flow, which favors collimation of the river bed and formation of a clogging layer. Daily water release from the dam makes the river water stage typically vary within about ±0.5 m. Fluvio-glacial and alluvial sediments dominate at the site interlaid by sand and silt in hyporheic zone, while coarse sand is seen at the deeper horizons. The average thickness of the alluvial pack is around 10m, with maximum 60-70m (SGU map service). Existence of the clogging layer that is mostly composed of silt particles complicates the exchange between the river and the hyporheic zone. Hydraulic conductivity of the hyporheic sediments and the clogging layer differ two orders of magnitude on average. We expect the clogging layer on the river-aquifer interface to increase residence time of the water in the shallow hyporheic area. The river at the test site is around 300 m wide and 10m deep.

Fig 3.2-2 Case study map with location of the study sites in the Lule and Kalix River.

Hypothesis

According to Boutt and Fleming, (2009) an advection-dispersion wave enters the hyporheic zoned during high river water stages, with a dispersion front advancing ahead of the advected water front (Figure 3). However, when the river stages fall below the groundwater stages, only the advected water is returned back into the river (Fig 3.2-3). The dispersion front may remain in the hyporheic zone for longer time thus affecting the groundwater quality.

The findings of Boutt and Fleming (2009) were used as hypothesis for this study of exchange processes on the surface water-groundwater interface in the regulated environment. It was used to design the field monitoring and the modeling.

Fig 3.2-3 Groundwater movement in the hyporheic zone with advection and dispersion front movements during raising water stage (left) and decreasing river water stage (right) for a regulated river (modified from Boutt and Fleming, 2009).

Field site experiments and sampling

Four groundwater wells and one river station were installed in a profile orthogonal to the river (Fig. 3.2-4) to collect continuous time series of water level, temperature, electrical conductivity and pH. Logging equipment with transmission units was used to record and transfer data. Water was sampled from the wells and the river for major chemical compounds and nutrients on weekly or biweekly basis. The monitoring campaign was started in July 2010 and continued for one year. A similar site was organized for monitoring the hyporheic zone in the pristine Kalix River. Additional tests were conducted in the Luleå River to determine the hydraulic conductivity of the clogging layer using constant pressure head infiltration method (Cardenas and Zlotnik, 2003). Seepage measurement technique was applied to collect information on spatial and temporal seepage distribution (Lee, 1977). Plastic seepage devices were designed to collect samples for seepage water quality analyses. A simple conservative tracer test was performed to monitor water movement in the hyporheic zone and assess importance of the hyporheic zone flow parallel to the river flow and water residence time in this zone.

Fig 3.2-4 General design of the monitoring site at the Lule and Kalix Rivers. 3.2.2 Major outcome from the study

A set of geochemical and hydrological data including time series and bi-weekly taken water samples were collected during one year monitoring period. Continuous observations revealed tight connection between the river and the hyporheic zone. Preliminary analysis showed frequent and high water stage variations in the river introducing an impulse wave with an advection and dispersion front into the subsurface, confirming the above hypothesis. Water level fluctuations in this area reached more than 1,5m at its maximum.

As a result of regulation the river water discharge was averaged throughout the year thus decreasing the spring flood. River water temperature was slightly higher in winter and lower in summer compared to the unregulated Kalix River. Altered Fe, Si, Mn, P and TOC transport patterns were also observed in the regulated river where the seasonality of the river transport was modified with a shift of spring and summer transport towards winter when the river discharge was elevated due to increased electricity demand. We expect occurrence of similar changes in water quality of the hyporheic zone.

Ground water stage response in the hyporheic zone to the varying river stages was almost instant with water stage response decreasing inland. Preliminary assessment showed that, during raising river water stages, river water with lower concentration of major dissolved elements penetrates the hyporheic zone and introduces a diluted plume. The plume is returned into the river once water stages were reverted. However, dispersion processes may retain lower concentration in the hyporheic zone (Boutt and Fleming, 2009).

A tracer injection test showed a narrow plume (orthogonal to the river) of high electrical conductivity groundwater flowing to the river suggesting absence of hyporheic flow parallel to the river.

3.3 Riperian zone interaction, Switzerland

3.3.1 Hydrogeology, site description and methods

Description

The area of interest is located near the city of Sierre, in a Swiss alpine valley (46o17’35’’N; 7o31’59’’E; Fig 3.3-1A) The site mainly consists on the alluvial plain of the upper Rhône river and occupies an area of approximatively 700 ha with an altitude varying from 500 to 700 m a.s.l. In this zone, the river flows from north-east to south-west (length ≈ 6 km) over about 50 m thick quaternary heterogenous fluvial deposits (width ≈ 1.5 km) which filled a valley located at the contact between the Penninnic units (Carbonates, anhydrite, gypse) on south and Helvetic units (Carbonates) on north. It constitutes one of the 100 most important ecological zones at the European scale, and presents a spectacular biodiversity for both fauna and flora (Bendel et al., 2006). From a hydrological point of view, the mean annual local rainfall height is about 587 mm, that leads the Pfyn forest to be the driest site in Switzerland (Schurch and Vuataz, 2000). The upper Rhone watershed regime is of mainly of nival type: the snow and glaciers melting provide a considerable amount of freshwater in the system during summer (Fette, 2005), and low-level occurs during winters. From a spatial point of view, and on the basis of the dense network or borehole located in the basin (CREALP), Schurch and Vuataz (2000) described two main recharge areas of the aquifer (Fig 3.3-1A): the northeastern limit of the studied area where surface water moves from the Rhone river bed on a front of about 700 m wide, southward into the alluvium and the east-central part of the area where subsurface flow supplies the Rhone alluvium. During low-level periods, the local subsurface flow coming from the south part of the area (Penninnic units) remains the almost unique source of water entering the alluvium. From an ecological point of view (Fig 3.3-1B), phytocoenosis vary from dry environments associations (Pinus sylvestris, Stipa sp.) to active floodplain associations (Alnus incana, Salix sp.) from upstream to downstream. Between these two end- members, a mixed transition forest took place.

Method

For this study, 3 sites, S2, S4 and S5, were selected across the river plain (Fig 3.3-1B). Studied sites were featured by various hydrological and pedological conditions which are strongly related with the distance from the main river bed. To assess factors influencing water uses patterns, oxygen-18 and deuterium signatures in the various water cycle compartments (rainwater, soil water at various depths between 10 and 100 cm, plant water, groundwater, river) were investigated in addition to the monitoring of hydrometerorological conditions. The use of isotopic tools was described (e.g. Ehleringer and Dawson, 1992) and shown to be useful in similar environment (e.g. Sanchez-Perez et al., 2008) because of the absence of fractionation during plant water uptake. The field campaign was carried out between the 22/04 and the 31/08/2010 with a two weeks resolution and between the 31/08/2010 and 16/02/2011 once a month.

3.3.2 Major outcome from the study

At the ecosystem scale, the direct consequence of recharge seasonality is an important piezometric level variation (about 8 m) near the supplying river zone. In contrast, the downstream part of Pfyn is characterized by a lower annual piezometric variability of about 1 or 2 m (Schurch and Vuataz, 2000). The hydrological continuum between the extreme groundwater level variation zone and the buffered groundwater level variation zone could, at least partially, explain the ecological continuum between dry ecosystems, upstream that might not adapt to strong water access variability and the more typical groundwater-dependent biocenoses, downstream. In this area (S2, S4, S5), the comparison of isotopic signatures of rainwater, soil water and groundwater indicate a variability of water uses that seems to be individual, species and time dependant. As an example, presents the statistics of the δ18O and δ2H signatures for the different compartments analyzed at the site S4. Rainwater has the most important variability (δ18O= -9.9±3.6 ‰ vs VSMOW; δ2H= -74±28 ‰ vs VSMOW) whereas groundwater is very stable (δ18O= -14.9±0.7 ‰ vs VSMOW; δ2H= -107±4 ‰ vs VSMOW). It appears that isotopic signatures variability diminish from rainwater to groundwater through surface soil layers and deeper soil layers. Plants show different trends according to the considered individual.

Through temporal correlation analyses (Table 3.3-1), it appears that soil signatures variability depends on meteorological processes i.e. the rainfall input signature and an eventual evaporation effect (but generally small according to Barnes and Turner, 1998) and on the hydrodynamics of the soil layers (mixing, single of dual permeability) (e.g.; Brooks et al., 2010). Surface layers (especially 10 and 30 cm layer) seem directly influenced by meteorological processes. The deeper does not show relationships with rainwater, what indicate that isotopic signatures should be more influenced hydrodynamic processes (e.g. mixing). Plants and soils correlations are generally significant but vary between sites. In the site S2, the poplar (Populus) signatures show correlation with 80 and 100 cm layers. The wild cherry (Prunus avium) with 30 and 60 cm depths, and willow (Salix alba) with 80 cm layer. In the site S4, the poplar does not show correlation in contrast to the willow, the pine (Pinus sylvestris) shows consistency with 10 and 30 cm layers as well as the wild cherry (10 m) interacting with soil 30 cm.

These correlations should be taken with care: Temporal variability of water uptake by plants which can shift from a water source to another has been already pointed out by other studies (Chimner and Cooper, 2004, Boujamlaoui et al., 2005; Li et al., 2006). In this context, the accounting of the local specificities of each site (i.e. hydrometeorological conditions, soil water patterns, and isotopic evolutions of each compartment) has to be taken into account. For example, through Fig 3.3-2 illustrating soil and willow (showing no significant correlation with any water compartment) patterns in S2, it can be seen that:

- Soils 10 cm present an obvious seasonal patterns that should be linked with rainfall input (cf. Table 3.3-2). Soil 60 cm present a more complex pattern but variations are generally buffered, always varying between 10 cm and groundwater signatures. Sometimes (weeks of 15/07 and 29/07/2010), when piezometric level is the highest (- 3.2 m) soil 60 cm have a similar signature to groundwater (δ18O # -14 ‰). This observation suggests that groundwater might reach this zone, what would occur through capillary rise. Such process has already been involved by Chimner and Cooper (2004) and Sanchez-Perez et al. (2008) in a similar environment. Capillary rise should also be favored by the increasing of the gradient or water potential between saturated zone and root zone (Bertrand et al., in press, and references therein). As the soil water content was at their lowest values during these weeks (# 18 % weight), capillary rise could be favored.

- Willow signature varied mainly in two ways. During spring and summer, it ranged between surface (10 cm) and deeper (60 cm) layers. This suggest water uptake from both these layers. As willow presents signatures between soil 10 cm and soil 60 cm during growing period and as soil 60 cm could be supplied by groundwater, these results indicates that willow is potentially dependent on groundwater. During autumn and winter, willow signature stabilized with a signature close to the signature of the end of summer. This could indicate that the tree almost stopped to pump water, what could be consistent with the end of the growing during cold period.

3.3.3 Conceptual models for surface water – groundwater interaction

These results imply that surface water-groundwater interaction should ensure the equilibrium the whole Pfyn forest ecosystem. At the alluvial plain scale, these interactions mainly occur at the upstream site, implying a strong piezometric variation. In this area, dry ecosystem species are favored because groundwater supply varies a lot. Downstream, this interaction seems to play an important role from an ecological point of view. Capillary rises may favor groundwater supply for plants. These results permit to propose a conceptual scheme of surface water-groundwater-biocenoses interactions (Fig 3.3-3Fig). It highlights that these interactions are dependent on hydrological condition (the nival regime implies that high flow occur during growing period) and on pedological conditions because capillary rise is generally favored by fine soil texture. These factors should be taken into account to understand the importance of surface water-groundwater interactions for GDE functioning. It would be also highly valuable for scenarios proposals on the future of these systems in the context of global climate change (potentially changing river-aquifer relationships) and local soil use changes (potentially changing alluvial forest groundwater supply).

Fig 3.3-1 Location and schematic geologic map of the Pfyn forest area, Canton Wallis, Switzerland (modified from Schürch and Vuataz, 2000); (B) Ecological settings of the Pfyn forest.

Fig 3.3-2 Meteorological, hydrological and isotopic data for site S2. Lines in 18O and water content graphics represent trends through the 4 weeks mobile means.

Fig 3.3-3 Conceptual scheme of surface water-groundwater –biocenoses interaction (exemple of willow at site 2) in the Pfyn alluvial forest. Table 3.3-1 Examples of isotopic data statistics of isotopic data for plants, soil, rain, surface waters and groundwater.

Nb of Std Variable Observations Mean deviation δD (‰) Populus 15 m S4 16 -76 17 δ18O (‰) Populus 15 m S4 16 -9.8 2.4 δD (‰) Prunus avium 10 m S4 15 -81 15 δ18O (‰) Prunus avium 10 m S4 15 -10.2 2.4 δD (‰) Salix 2 m S4 16 -83 13 δ18O (‰) Salix 2 m S4 16 -10.3 2.0 δD (‰) Alnus 10 m S4 14 -90 10 δ18O (‰) Alnus 10 m S4 14 -11.6 1.4 δD (‰) Pinus Sylvestris 8 m S4 15 -70 20 δ18O (‰) Pinus Sylvestris 8 m S4 15 -8.2 3.3 δD (‰) Soil 10 cm S4 15 -68 29 δ18O (‰) Soil 10 cm S4 15 -8.8 4.2 δD (‰) Soil 30 cm S4 15 -74 28 δ18O (‰) Soil 30 cm S4 15 -9.5 4.2 δD (‰) Soil 60 cm S4 14 -79 16 δ18O (‰) Soil 60 cm S4 14 -10.9 2.4 δD (‰) Soil 80 cm S4 13 -76 13 δ18O (‰) Soil 80 cm S4 13 -10.2 1.7 δD (‰) Soil 100 cm S4 6 -74 8 δ18O (‰) Soil 100 cm S4 6 -10.0 1.5 δD (‰) Groundwater S4 16 -107 4 δ18O (‰) Groundwater S4 16 -14.9 0.7 δD (‰) Rhône S5 15 -108 4 δ18O (‰) Rhône S5 15 -15.1 1.0 δD (‰) Rainwater 13 -74 28 δ18O (‰) Rainwater 13 -9.9 3.6

Table 3.3-2 Pearson correlations between soils layers, plant and rainwater for the 3 studied site. Groundwater does not show significant correlation with the other compartments.

Significant values of Pearson correlations respectively for δD and δ18O (α=0.1) Site S2 Populus / soil 80 cm (0.585 0.737); Populus / soil 100 cm (0.558-0.588) Prunus avium / soil 30 cm (0.552-0.479 ); Prunus avium / soil 60 cm (0.559-0.502) Salix : No significant correlation Soil 10 cm /rainwater (0.641-0.618) Soil 30 cm / rainwater (0.504-0.479) Site S4 Salix / soil 10 cm (0.685-0.556 ); Salix / soil 30 cm (0.642-0.488 ) ; Salix / rain (0.536-0.572) Alnus : No significant correlation Pinus sylvestris / soil 30 cm (0.780-0.728 ); Pinus sylvestris / soil 60 cm (0.642 -0.701) Soil 10 cm /rainwater (0.820-0.759) Soil 30 cm / rainwater (0.502-0.472) Soil 60 /rainwater (0.530-0.622) Site S5 Salix : No significant correlation Alnus / Rainfall (0.765-0.685)

3.4 Dalyan Mediterranean Lagoon, Turkey

3.4.1 Site Description and Hydrology

The study area is in the Dalyan Lagoon watershed that is located in the south western Mediterranean Sea coast of Republic of Turkey (Fig 3.4-1).

TURKEY

Mediterranean Sea

Case Study Area

DalyanLagoon

Mediterranean Sea

Fig 3.4-1 The Study area.

As illustrated in Figure 3.4-2; the study that is around 70 km2 large contains high elevations on the upland up to more than 600 m above sea level, areas with high and low slopes, geological heterogeneousness, an estuarine lagoon system and a complex land use structure containing agriculture, forests

The estuarine lagoon (Dalyan Lagoon) was analyzed in previous studies and divided into different regions with homogenous hydrographical and ecological properties as illustrated in Fig 3.4-3. The details of those detailed analyses were reported by Gurel et. al. (2005).

(a) (b)

Fig 3.4-2 (a) Slope map (b) Geological map (c) Soil map (d) Land use map.

Fig 3.4-3 Lagoon regions with homogenous hydrographical and ecological properties.

The case study area has a relatively heterogeneous geological structure and geomorphology. The case study area consists of alluvial and karstic regions (Fig 3.4-4). There are hot and cold water springs (Fig 3.4-5), springs that contain high amount of salinity and hydrogen sulphide. Several of them have naturally occurring radioactivity.

(a) (b)

Fig 3.4-4 Geological formation (a) Alluvial formations (b) Karstic formations.

(a) (b)

Fig 3.4-5 Springs (a) Hot spring (b) Cold spring.

3.4.2 Methods The complexity of the Dalyan case study area necessitated application of several tools and methods; namely spatial technologies, monitoring and modelling.

Spatial technologies were utilized to create a database of all the land and aquatic ecosystems. Data from different sources as well as monitoring data were compiled together to create several map layers (such as the ones illustrated in Fig 3.5-2) that are used

- to generate the basic coverage for monitoring network design and inputs for simulation models.

- to fill in the spatial gaps in data as far as possible

Monitoring was conducted in the lagoon and in terrestrial ecosystems (as shown in Figure x.1). Groundwater monitoring was initiated utilizing a spatially high resolution monitoring network illustrated in Fig 3.4-6.

Fig 3.4-6 Initial groundwater monitoring network.

The aim of the initial groundwater monitoring network was to observe the spatial variations of groundwater quality in order to decide on the locations and structure of groundwater monitoring wells and to understand the importance of saline water intrusion into the groundwater system. The preliminary monitoring study was conducted using wells that were built for water supply. Salinity and conductivity were used to locate the sites that are likely to receive saline water because of possible seawater intrusion. Data collected from these wells indicated that there may be a weak seawater intrusion into the groundwater system.

To investigate the seawater intrusion, a network of six new groundwater wells was designed (Fig 3.4-7) where groundwater level, groundwater temperature, salinity and conductivity will be monitored.

To be able to monitor the effects of other hydrological and coastal processes related to water cycle in the case study area, surface water monitoring was conducted as well. The monitoring network is illustrated in Fig 3.4-8. For the aim of investigating surface water-groundwater interaction; temperature, salinity, pH and dissolved oxygen are monitored in surface water, where the possible anomalies in the latter two parameters can be helpful to better understand the effect of groundwater inflow into the lagoon system.

Fig 3.4-7 Groundwater monitoring wells.

To support the monitoring and modelling studies related to surface water-groundwater interaction, a stable isotope tracer study is being conducted as well. Stable isotopes of hydrogen (2H) and oxygen (18O) are monitored together with chloride (not as isotope) to investigate the origin and composition of water in different hydrological reservoirs. The related monitoring network is illustrated in Fig 3.4-9, where the circled stations are used to take stable isotope samples.

Fig 3.4-8 Surface water monitoring stations.

Fig 3.4-9 The monitoring network for stable isotope study.

A preliminary modelling study was conducted to estimate the groundwater inflow into the lagoon system. The model is coupled with a surface water hydrodynamics model to simulate the water budget components in the study area including the surface water-groundwater interaction. Vertical hydrological forcing such as evapotranspiration, groundwater recharge and upwards movement of groundwater to unsaturated soil are estimated using SWAT. More detailed information related to these calculations is given by Gonenc et al (2011) and Ekdal et al. (2011). The model formed a basis for the conceptual model for surface water-groundwater interaction explained in Section 3.4.3. Preliminary results from this model are summarized in Section 3.4.2.

3.4.3 Major outcome from the study

The preliminary modelling and monitoring studies have shown that the surface water- groundwater interaction is likely to be two directional. To better understand this interaction, an optimized monitoring system was designed. One groundwater well has already been constructed for preliminary testing and operation. Other wells will be constructed in the near future. All the wells are designed to sample from multiple depths.

Conventional models were used to quantify to link the groundwater inflow to surface water. The results from these models indicated that the groundwater inflow into the Dalyan Lagoon is considerable if compared with the average inflows from other boundaries. The relative importance increases especially in summer, when the inflows from the Koyceğiz Lake and surface runoff decreases considerably. Fig 3.4-10 illustrates the preliminary calculations for groundwater outflows to the Koycegiz Lake.

(a)

(b)

Fig 3.4-10 Estimated groundwater outflows into the Dalyan Lagoon.

The outflows from Koycegiz Lake to the Dalyan Lagoon for an average hydrological year (From 1st of October unitl 30th of September) are illustrated in Fig 3.4-11. Related details are given by Ekdal et al (2003).

Fig 3.4-11 Outflow from Koycegiz Lake (Ekdal et al. 2003).

Outflow from Koycegiz Lake has a low salinity (around 2-4 ppt) hence important for the estuarine ecosystem because it represents low salinity inflow. However according to the monitoring results in this study groundwater inflow is even less saline (0.19 ppt – 1.35 ppt) and may represent an important source of fresh water. Especially in the summer, (hydrological day 250 and later), groundwater inflow is an important freshwater source since outflows from Koycegiz Lake decreased to approximately 6 m3/s on average and surface run-off can be neglected. Considering model results given in Figure x.10a, groundwater outflow was almost the same as the Koycegiz Lake outflow to Dalyan Lagoon.

The last outcome from the study is the conceptual model described in Section 3.4.3 that has a bi-directional surface water-groundwater interaction.

3.4.4 Conceptual models for surface water – groundwater interaction A conceptual model is developed for the Dalyan case study area (Figure 3.4-12). The conceptual model does not only consider hydrological interaction between groundwater and surface water ecosystems but also the ecological interaction. The model is a fully coupled one where all components of the entire case study ecosystem are bi-directionally linked.

Fig 3.4-12 The conceptual model.

3.5 River lake lagoon interaction, Greece

3.5.1 Hydrogeology, site description and methods

The study area is located in north eastern Greece and focuses on a semi confined aquifer known as Neon Sidirochorion aquifer formed in the alluvial plain of Vosvozis river (Fig 3.5-1).It is located approximately 5 km from the Thracian sea and covers an area of approximately 45 km2. It is a plain area bounded to the north and east by low hills, to the west by Vosvozis River, and to the south by Ismarida Lake. This part comprises a very important surface water ecosystem formed by Ismarida lake and its surrounding wetland area and belongs to the Natura 2000 network (Greek Ministry of Environment, Physical Planning and Public Works 1986, 1996) and should be protected according to the Greek law, EU conservation policies or international treaties, such as the Ramsar Convention of 1971.

Fig 3.5-1 Location map of the study area aquifer.

The topography of the Ismarida plain may be classified as a part of the Vosvozis River delta. Main surface water bodies in the study area include Vosvozis River and Ismarida Lake. The overall length of Vosvozis River is roughly 40 km. Ismarida demonstrates great fluctuations in water level, area, and volume and it currently occupies part of an area previously covered by a much larger water body. Its surface area is about 3.4 km2[2]. For drainage reasons, the local authorities, in the past, opened a canal connecting artificially Ismaridalake with the sea. The initial goal, however, did not prove to work well, thus sea water entered the initially fresh water ecosystem altering its natural fresh water character. Currently, Ismaridalake is a fresh water ecosystem during rainy season (i.e. October to May) whereas during summertime it is transformed to a mixed fresh water - salt water system, where complex interactions among surface water, sea water and groundwater are taking place.[1]

The hydrogeological investigation of the study area and the conceptual model development was based on data including:

- The 1: 50,000 scale geological map of Greece. - Borehole stratigraphy data. - Groundwater level data. - Groundwater quality data. - Isotopic analyses data. - Previous studies data and results which were reassessed.

Hydrochemical data acquired during 2009 and 2010 showed that in the northern part of the aquifer the Ca-HCO3 type of water is dominant, whereas in the central and southern part Na-Cl waters prevail. An interesting aspect is the spatial and temporal distribution of Electrical Conductivity (EC) values in the groundwater throughout two years i.e, 2009 and 2010. In the southern aquifer part close to Ismarida lake groundwater demonstrates a great EC variability which ranges from 850 (May) to 4500 μS/cm (September), which is in correlation with the changes in the lake’s salinity. In the central part groundwater demonstrates much lower seasonal EC variability, with EC values ranging from 2500 (May) to 3000 μS/cm (September). The northern part has lower groundwater EC values up to 1025 μS/cm and very little seasonal variability.[1]

3.5.2 Major outcome from the study

Groundwater flow indicates the aquifer-river and aquifer-lake hydraulic interaction, as shown in Fig 3.5-2. Generally, groundwater level follows a decreasing trend, as one move from Vosvozis river to the east and flow vectors are mainly vertical to Vosvozis river, indicating aquifer-river interaction. Also, at the south boundary of the study area flow vectors follow a West-Northwest direction indicating possible aquifer-lake interaction. Groundwater levels in the aquifer show great variability, both seasonal and spatial as illustrated in Fig 3.5-3. In the northern and central part of the study area, the aquifer demonstrate seasonal variation that ranges from 10 to 30m which is the cause of intense groundwater pumping for irrigation needs. The high groundwater drawdown during summertime causes phreatic conditions to prevail to the initially semi

confined aquifer system. On the contrary, the southern part of the aquifer does not demonstrate such seasonal groundwater level variability which can be attributed to the interaction, in this part of the aquifer, with external sources of water, mainly Ismarida lake and Vosvozis river.

Fig 3.5- 2 (a) Location map of the study area with pumping boreholes and monitoring sites and (b) geological map and hydrogeological cross section of the study aquifer.

3.5.3 Conceptual models for surface water – groundwater interaction

In order to investigate the surface water – groundwater interaction in the study area, time series analysis was performed. Using two types of seasonal ARIMA models (the first one simulates groundwater abstraction time series and provides the input to the second type of ARIMA models that simulates groundwater level time series in monitoring boreholes) it could be mentioned that in the southern part of the aquifer, direct interaction with external water bodies seems to take place, which in our case seem to be Ismarida lake and Vosvozis river. However, a further clarification of the interaction of Ismarida lake with the aquifer was achieved with isotopic analysis. [1]

Stable isotopes of the water molecule are indicators of conditions at the time and place of groundwater recharge. They are influenced by processes affecting the water, rather than the solutes, and can help identify waters that have undergone evaporation, recharge under different climatic conditions, and help to resolve overall questions relating to mixing of waters from different sources. The δ2H and δ18O signatures of groundwaters are generally compared to those of the precipitation represented by the Global Meteoric Water Line (GMWL) and the Local Meteoric Water Line (LMWL)[3]. Stable isotope values that plot along the meteoric water lines are compared to local precipitation to determine if groundwaters derive from recent local recharge or originate from water that recharged the aquifer under different climatic conditions.

Deviations from the meteoric lines indicate modification of the groundwater by evaporation or extensive water interactions[4].In our study area, water samples from surface waters, groundwaters, sea water and rain water were analyzed by the UFZ – Helmholtz Centre for Environmental Research, from February 2010 to December 2010. Results showed that the isotopic composition ofδ2H and δ18O of all ground waters in the study area ranges from -41.6‰ to -36.0‰ and from -6.6‰ to -5.3‰ respectively. In the conventionalδ18O versus δ2H diagram, these ground waters plot well below LMWL but on or slightly below the GMWL.

Fig 3.5-3 (a) Piezometric map for October 2010, (b) piezometric map for May 2010, (c) groundwater level time series for the eight monitoring sites.

Fig 3.5-4 Plot of stable isotopes δ18O / δ2H for all water samples.

Generally, the plots show some differences between the isotopic composition of samples taken in winter and summer. (Fig 3.6-5 and Fig 3.6-6).

Fig 3.5-5 Plot of stable isotopes δ18O / δ2H in the summer.

Fig 3.5-6 Plot of stable isotopes δ18O / δ2H in the winter.

The isotopic signature of groundwater samples plot close to the GMWL during both seasons, implying that precipitation is one of the water sources of the aquifer and that the infiltrated water is completely mixed [5]. From the isotope values the water can be described as ‘young water’.

Regarding seasonality, during summer, seawater enters Ismarida lake and the composition of the isotopes in the lake differs from the composition of the isotopes in the winter. During summer the isotopic composition ofδ2H and δ18O in the lake ranges from -33.3‰ to -8.6‰ and from -5.2‰ to -0.4‰ respectively. In the winter the isotopic composition of δ2H and δ18O in the lake ranges from –40.0‰ to -33.4‰ and from -6.7‰ to -5.2‰ respectively. This probably indicates that during summer, seawater enters the lake and a river – aquifer interaction takes place (same isotopic composition). On the contrary, in the winter, the lake is a ‘fresh water’ aquatic system, and an interaction of river – lake – aquifer takes place. This scenario is in agreement with the findings of the time series analyses (Gemitzi and Stefanopoulos, 2011).

Further research will focus on the quantification of the interaction of the various water bodies in the study area, analyzing data from the installed lysimeters, in combination with the isotopic and hydrochemical data of the study area.

3.6 Bogucice Sands - Niepolomice Forest, Poland

3.6.1. Site description, hydrogeology and water use

The Bogucice Sands aquifer and the associated GDE (Niepolomice Forest) are located in the south of Poland (Fig.3.6-1). The aquifer covers the area of ca. 200 km2 and belongs to the category of medium groundwater basins in Poland. The system extends from ca. 49.99N- 19.97E to approximately 50.05N-20.33E. Urban areas and villages cover ca. 20% of the surface. The remaining surface is occupied by agriculture (60%) and forestry (20%). In the eastern part of the area forests and wetlands dominate (80% of area). The study area is located in the transition region between oceanic and continental climatic zone. Average annual precipitation in the area reaches 725 mm, with evapotranspiration fluctuating around 480 mm and runoff of ca. 245 mm. Groundwater recharge takes between 8 and 28 percent of precipitation. The annual average temperature is 8.2 degrees Celsius.

The Bogucice Sands aquifer is located on the border of the Carpathian Foredeep Basin and belongs to the Upper Badenian. It is underlain by impermeable clays and claystones of the Chodenice Beds. To the north, the aquifer is progressively covered by mudstones and claystones with thin sandstone interbeds (Grabowiec Beds). Paleoflow directional indicators suggest proximity to deltaic shoreline (Porębski and Oszczypko, 1999). The outcrops of Bogucice Sands are located in the south, covered by thin Pleistocene-Holocene sediments (sands, loesses and locally boulder clays). In the north, the aquifer is deeper and confined by marine mudstones and claystones. Its total thickness is approximately 100 m, at the maximum up to 310 m.

The hydrogeology of the aquifer can be considered in three areas: the recharge area related to the outcrops of the Bogucice Sands in the south, the central confined area generally with artesian water, and the northern discharge area in the Vistula river valley. Groundwater movement takes place from outcrops in the south, in the direction of the Vistula river valley where the aquifer is drained by upward seepage through semipermeable clayey formations of the Tertiary Grabowiec Beds. In pre-exploitation era, artesian water existed almost on the whole confined area. Intensive exploitation decreased the water table in some localities causing downward seepage. The upper shallow aquifer located in Pleistocene-Holocene sediments is related to drainage system of Vistula river and its tributaries. Unsaturated zone consists mainly of sands and loess of variable depth, from zero in wetland areas to approximately 30 meters in the recharge area of deeper aquifer layers.

The principal economic role of the deeper aquifer, consisting of two water-bearing strata separated by Badenian clays, is to provide potable water for public and private users. Estimated disposable resources are 40,000 m3/d with typical well capacities of 4 to 200 m3/h (Witczak et al., 2008). Hospitals and food processing plants also exploit some wells. The yield of the aquifer is insufficient to meet all the needs and, as a consequence, licensing conflicts arise between water supply companies and industry on the amount of water available for safe exploitation.

The recharge area of the deeper aquifer and entire shallow phreatic aquifer is vulnerable to diffuse sources of pollution from industrial emissions (big metallurgical plant in the north-west and numerous local enterprises). Point sources of pollution may also exist due to disposal of urban and rural wastes, including landfills and farm sources. There is also some evidence of contamination from a linear source of pollution, a contaminated river draining large municipal landfill located close to the southern border of the aquifer. Pollution from a newly constructed highway should also be expected in the near future. Typical usage of fertilizers on the agricultural areas of the upper aquifer amounts to ca. 70 kg N/ha year.

Fig 3.6-1 A – hydrogeological map of Bogucice case site. Groundwater Dependent Ecosystem (Niepolomice Forest) is marked in red. B – cross-section of the aquifer (line A-B in Fig. 3.6-1) with the position of wellfields Szarów and Wola Batorska. General direction of groundwater flow is from south to north. Frame indicates approximate extent of the location of GDE shown in Fig 3.6-2.

Eastern part of the shallow phreatic aquifer is occupied by Niepolomice Forest (cf. Fig 3.6-1). The Niepolomice Forest is a lowland forest covering around 110 km2. This relict of once vast

forests covering the Sandomierz Basin is protected as a Natura 2000 Special Protection Area “Puszcza Niepołomicka” (PLB120002) which supports bird populations of European importance. Additionally a fen in the western part of the Forest comprises a separate Natura 2000 area “Torfowisko Wielkie Bloto” (PLH120080), a significant habitat of endangered butterfly species associated with wet meadows. The Niepolomice Forest contains also several nature reserves and the European bison breeding centre and has an important recreational value as the largest forest complex in the vicinity of Krakow. Due to spatially variable lithologies and groundwater levels, the Niepolomice Forest is a mosaic of various forest and non-forest habitats, including wetlands, marsh forests, humid forests and fresh forests. Dependence of the Niepolomice Forest stands on groundwater is enhanced by low available water capacity and low capillary rise of soils (Kleczkowski, 1981, Suliński, 1981; Łajczak, 1997, Chelmicki et al, 2003). Groundwater conditions in the Niepolomice Forest, including Wielkie Bloto fen have been affected by meliorations carried out mostly after the Second World War and by forest management (Suliński, 1981; Łajczak, 1997; Lipka et al., 2006). Recently (September 2009) a cluster of new pumping wells (Wola Batorska wellfield) has been set up close to the northern border of Niepolomice Forest (Fig 3.6-1 – wells SW1-SW7). There is a growing concern that exploitation of those wells may lead to lowering water table in the Niepolomice Forest area and, as a consequence, trigger drastic changes of this unique groundwater dependent ecosystem.

3.4.2. Conceptual model of surface water - groundwater interaction

The conceptual hydrologic model of GDE Niepolomice Forest including Wielkie Bloto fen is shown in Fig 3.6-2. Fig 3.6-2A depicts schematically presumable surface water/groundwater interaction on the area under natural conditions, prior to major anthropogenic disturbance of the system in the form of melioration works on Wielkie Bloto fen and management of the forest (drainage trenches). Due to artesian conditions in the area and relatively thin clay layer separating Badenian aquifer from shallow Quaternary aquifer, the upward leaching of deeper groundwater may contribute in a significant way to the water balance of the investigated GDE.

In order to quantify dynamics of groundwater flow in the area of Niepolomice Forest and Wielkie Bloto fen, concentrations of environmental tracers (stable isotopes water, tritium, radiocarbon) were measured in wells existing in the recharge area of Bogucice Sands aquifer (Szarów well field) and in the newly established wellfield Wola Batorska (cf. Fig.3.6-1). Also, some surface water appearances in the area of Wielkie Bloto fen were investigated (Table 3.6- 1). These analyses are part of a larger, ongoing program aimed at characterization of spatial and temporal distribution of environmental tracers in the Bogucice Sands aquifer and establishing time scales of groundwater flow in this system (Zuber et al., 2005).

Tracer data reported in Table 3.6-1 indicate that in the recharge area, upstream of Wielkie Bloto fen (Szarów well field) groundwater is relatively young. Presence of appreciable amounts of tritium points to recharge in the past several decades. Radiocarbon content fluctuates between 48 and 65 pmc. In contrast, in the newly established well field Wola Batorska, tritium is absent while radiocarbon content drops to a few pmc. Significant age of groundwater in this area is confirmed by stable isotopes of water revealing characteristic shift towards more negative delta values indicating glacial origin of water.

Fig 3.6-2B illustrates possible impact of recent changes in the area (establishment of a new well field Wola Batorska, cf. Fig. 3.6-1) on groundwater flow regime. It is expected that intensive pumping of deeper aquifer by newly established wells, planned in the near future, may modify groundwater flow field in the area of GDE in such a way that hypothetical upward leakage will be stopped or significantly reduced.

To prove potential discharge of deeper groundwater in the area of Wielkie Bloto fen it is planned to drill an observation well and to perform sampling of groundwater at different depths. Vertical profile of tritium concentration should provide direct evidence of possible interaction between surface water and deeper groundwater in this area. In addition, appropriate modeling runs of the existing 3D flow model of Bogucice Sands aquifer (Visual Modflow Pro, version 4.3) are planned in the near future in order to investigate possible impact of the newly establish well field Wola Batorska on the groundwater flow in the Niepolomice Forest area.

Table 3.6-1 Environmental tracer data for groundwater in the area of Niepolomice Forest GDE. Uncertainty of stable isotope data is equal 0.1 ‰ (18O, 13C) and 1‰ (2H). Tritium and radiocarbon content is measured with the precision of 0.3 TU and 0.8 pmc, respectively.

Site description 18 2 Tritiu  O  H 14 Well No m C 13C (‰) (‰) VSMO VSMO content (pmc) (‰) VPDB W W (TU) Szarów well field: Well No. 11 -9.75 -70.3 9.0 64.6 -14.1 Well No. 12 -9.93 -70.1 1.1 63.6 -12.8 Well No. 22 -9.81 -69.4 16.1 n.m. n.m. Well No. 23 -9.84 -68.5 0.7 n.m. n.m. Well No. 24 -10.03 -72.1 15.2 n.m. n.m. Well No. 42 -9.68 -69.2 0.3 48.5 -12.2 Wola Batorska well field: Well SW-2 -10.19 -75.7 0.3 2.9 -10.2 Well SW-3 -10.67 -78.3 0.4 n.m. n.m. Well SW-4 -10.86 -79.9 0.1 0.8 -10.5 Well SW-5 -10.89 -79.2 0.0 n.m. n.m. Well SW-6 -10.83 -80.2 0.1 n.m. n.m. Well SW-7 -10.71 -78.2 0.1 2.2 -9.2 n.m. – not measured

It should be noted that a small spring occurring in the forest close to the Wielkie Bloto fen does not contain tritium. This might point to direct impact of relatively old groundwater discharging in this area. However, at this stage is not clear whether the spring is entirely of natural origin. There is some possibility that it may originate from old, badly liquidated well which was located in the vicinity of this spring. Further investigations will clarify that.

Fig 3.6-2 Conceptual model of surface water/groundwater interaction in the area of Niepolomice Forest under natural conditions (A) and envisaged under new steady-state imposed by heavy pumping by Wola Batorska well field (B). GDE – Groundwater Dependent Ecosystems; GDTE – Groundwater Dependent Terrestrial Ecosystem; R – riparian and alluvial forest; EWRs – Environmental Water Requirements; SY – Save Yield of aquifer.

3.7 Częstochowa aquifer interaction, Poland

3.7.1 Hydrogeology, site description and methods

The Case Study area (2365 km2) lays in the southern part of Poland, administratively belongs to the Silesian Voivodeship. It is a part of the Cracow-Częstochowa Upland - the Częstochowa Plateau which is the most impressive part of the Cracow Jurassic area. The Case Study borders correspond to the borders of the Main Groundwater Basin No 326.

The MGWB 326 aquifer is naturally divided by the Warta river into two subasins (Fig 3.7-1): MGWB 326 S and MGWB 326 N.

Average yearly precipitation varies between 600 - 800 mm/year. The climate is continental with low humidity and considerably high amplitudes of temperature; the average yearly temperature is 70C. Such climate is conditioned among others by constant Icelandic depression and arctic high- pressure whose activity can be felt mainly in winter. In summer, however, we can feel the influence of high-pressure from the Azores and other fronts from the south, whose activity is unfortunately strongly inhibited by the Carpatian massif.

In the geological structure of the Cracow-Częstochowa Upland two structural levels can be distinguished: the krakovid level containing folding and partly metamorphisized pre-Cambrian deposits up to upper Carboniferous and the level of the Mesozoic Cracow-Częstochowa monoclinal fold, The oldest formations confirmed by drilling are metamorphic slates and phyllite dating back to the pre-Cambrian. The Cambrian period is represented by argillaceous slates, mudstone and sandstone whose thickness exceeds 1000 m. Those rocks eroded and became folded, and then were covered with carbonate deposits of the Ordovician (limestone, marl, dolomites). On top, there are partly metamorphisized Silurian slates whose layers blend with course-grained sandstone and gravel. As a result of many tectonic movements taking place at the turn of lower and upper Carboniferous, the character of sedimentation changed from the sea to land type. Owing to the communicational activity of the rivers, the terrigenous material has been carried and deposited along with accumulated flora material. That was the way the upper- Carboniferous complex of sandstone, mudstone an slates came into being, including carbon deposits and inserts. The Trias and Jurassic formations are sloping at a slight angle towards the north-western direction. The Trias is represented by flat sea deposits which flooded the area at that time. Those rocks (sandstone, marl, dolomites, limestone) are revealed only in the western part of described region. Jurassic formations prevail in the whole area of the Kraków - Częstochowa Jurassic (hence the name). The most dominant form of the Jurassic landscape is rocky limestone occurring as isolated rocks called inselbergs and rocks in river valleys. Jurassic limestone`s outstanding feature is strong karst formation which developed mainly in the Tertiary. For the most part of the Tertiary described area was a land and there were various denudative

processes (erosion, weathering), which led to forming so-called palaeogene planation surface, i.e. characteristic tops, particularly in the southern part of the Jurassic, scattered with numerous limestone inselbergs. In the Miocene, as a result of sea transgression, limestone was formed at the bottom of the reservoir, and first of all scales filling mainly tectonic trenches which came into being in that period due to frequent orogenic movements. In the Quaternary, owing to Scandinavian continental glacier present in that area, clay, sand and gravel accumulated there, and at the end of the Ice Age, loess clay was wind-blown which currently covers the Cracow - Częstochowa Upland making up very fertile soil.

Fig 3.7-1 The Częstochowa Case Study. Location. Geology.

Surface water – groundwater interaction was investigated for the part of the case study – the Wiercica River catchment (349.8 km2), the tributary of the Warta River. The beginning of the river is formed by several springs, the yield of which is affected by unsteady conditions of groundwater recharge. Good water quality, as well as specific climatic conditions, is favourable for existence of mosaic of biotopes: in dry and warm conditions some southern species are met while in wet and cold - mountain and boreal ones. Average yearly precipitation in the period 2000-2004 was 670.2 mm for Częstochowa and 791.6 for Złoty Potok (Malina et al. 2007).

GDEs may be strongly dependant only on shallow waters, which means that they exist within springs zones, where there is strong relation with precipitation, groundwater levels and with humidity of aeration zone. Such conditions were found in the upper and middle parts of the Wiercica catchment (Fig 3.7-2) and finally the investigation on surface water – groundwater interaction was limited to this area. Shallow groundwater levels are observed only along river valleys and around Mokrzeska Wola. Soil types ensure good contact with surface water, only locally soil layers are semi-permeable.

Fig 3.7-2 The Wiercica watershed research area. Hydrography and land cover.

3.7.2 Major outcome from the study

Transformation of flow through the aeration zone was simulated with the help of the piston model of unsteady infiltration. Computer modeling consists of two sub-programs: i) PM – piston model of infiltration, ii) hydrological model of net precipitation.

PM model.

PM model was applied to follow current states of GDEs in a sense of prediction of groundwater recharge which is crucial for biotopes functioning. This might be made for short (seasonal) and long term (climatic) changes of meteorological conditions as well as for various anthropogenic pressures (land cover, position of groundwater table). PM model might be also applied to simulate an unsteady recharge and then to model behavior of the whole groundwater basin in models based on MES methods.

The model enables to determine increase or decrease of soil moisture as a result of precipitation and evapotranspiration which than allows to estimate the dynamics of groundwater recharge. It is a 1-D model and can be used for areas of uniform geotechnical, sozological and hydrological nature.

Net precipitation.

Net precipitation is a separate module calculating this portion of precipitation which then penetrates into soil cover. Here it was chosen a simplified model of evapotranspiration based on the Turc’s equation (Pociask-Karteczka 2003) with the following input data: radiation, local average temperature, precipitation height, plant cover in a sense of evapotranspiration capacity and local depth of rizosfera. It is also possible to use the more detailed Penman-Monteith model (Kowalik 2010) if only we are able to gather all the necessary input data.

So, the scheme of calculation of net precipitation consists of three steps: potential (total) evapotranspiration determined on the basis of daily precipitation value  biotope evapotranspiration determined with respect to rizosfera depth, soil cover, vegetation season  real evapotranspiration.

Infiltration and effective precipitation

To simulate changes of water content the classical Green-Ampt (Green and Ampt 1911) model for a sharp front is applied together with the piston model of unsaturated infiltration and the Morel-Seytoux model of moisture redistribution (Morel-Seytoux 1984). It is assumed in the model that moisture distribution in a soil after a wetting front is independent of process duration and a front position (resembles movement of a piston). The process of moisture changes itself is described by a couple of basic, commonly available parameters but this simplification does not distort the phenomenon in a significant way.

Results

- For strongly permeable soils whole precipitation infiltrates into ground, directly recharging groundwater. Along the profile low moisture is maintained, shortly after the precipitation event (rain) soil gets dry. There may be no enough moisture left for more water consuming plants. - For medium permeable soils condition can be different. Although whole precipitation infiltrates into ground, significant content remains for a few days after the rain, in approx. 2 cm subsurface layer. There is quite large seasonal moisture content remaining in deeper layers, with good availability for plants. - For low permeable soils slightly bigger precipitation event may form surface runoff. Moisture content remains stable and quite significant. Higher moisture may stay for a few days after rain, to depth of approx. 100m, however, high sucking head may prevent plants from using that moisture.

Fig 3.7-3 Infiltration graph for sandy alluvial soil type in the Wiercica research area.

Fig.3.7-4 Infiltration graph for glacial till soil type in the Wiercica research area.

Fig 3.7-5 Infiltration graph for sandy clay (loess) soil type in the Wiercica research area

3.7.3 Conceptual models for surface water – groundwater interaction

GDEs take water mainly from the aeration zone, hence moisture of this zone being dependant on precipitation as well as on capillary fringe is highly important for the process. In this case it is justified to apply the piston model of infiltration (PM – Piston Model). Moisture of the aeration zone decides about availability of water for vegetation needs; this is possible only if moisture is higher than moisture of fading. Up to the soil depth (about 0,5m), moisture is shaped by daily precipitation but here evapotranspiration plays crucial role since it causes strong fluctuation of

moisture. In the deeper sub-soil level up to about 1 m the deeper infiltration is stabilized by a between-layer runoff, which is than taken into account in a balance. All these mean that PM model might be applied only for river valleys and marshes.

Transformation of flow through the aeration zone was simulated with the help of the piston model of unsteady infiltration. For a single profile the model may be run as a simple calculation sheet but the whole catchment it is necessary to build a computer program or at least to use one of universal GIS application. The calculation scheme is presented below (Fig 3.7-6).

Fig 3.7-6 Scheme of modeling in the piston model of infiltration.

3.8 The Grue site, Norway (Bioforsk)

3.8.1 Site description, hydrogeology and methods

Site description – hydrogeology The Grue study area is situated in the Glomma valley in south eastern Norway. Whereas most of the areas in the valley bottom are used for agricultural purposes, the riparian zone in the groundwater discharge zone adjacent to the river consists of forest ecosystems dominated by broad-leaved trees, particularly Salix species. The deep valley basin at Grue is filled up by lacustrine and marine deposits beneath a top layer of fluvial sediments. Clay has been observed at a depth of 13-15 m at several locations (von der Lippe 1998). Above this level the deposits consists mainly of sand. A top layer of flood plain sediments of coarse silt and sand occurs in large parts of the river plains, however, but does not exist in the riparian zone. The depth of the unsaturated zone in the riparian zone normally ranges between 0 and several meters, and will vary during the year. Average groundwater recharge in the area has been estimated to be at a size of 300 mm year-1.

Methods Monitoring wells has also established at several locations in this aquifer to uncover local and regional flow patterns. In a selected transect through the riparian forest zone along Glomma, water levels and temperature are monitored at hourly intervals in two monitoring wells. The monitoring wells in the transect have been established in the middle of and close behind the riparian zone, respectively (Fig 3.8-1). In the transect grain size distribution and layering of sediments have also been characterized at several locations.

3.8.2 Major outcome from the study The soil in the riparian zone consist of point bar sediments of sand with low content of organic material and low storage capacity for plant-available water. The periodically high groundwater levels in the middle of the riparian forest zone (Fig 3.8-2) demonstrates that groundwater may feed the root zone and /or the capillary rise zone and thus be important for vegetation in large parts of the riparian zone. This also implicates that the riparian ecosystems may be susceptible to groundwater contaminations and changes in groundwater hydrology.

W E

$ S A $ B

$ Monitoring well Forest Open area Agricultural area

0 100 200 Meters

Fig 3.8-1 Location of riparian zones and monitoring wells in a transect crossing the riparian zone at the Grue site.

Higher groundwater table altitudes behind than in the riparian zone (Fig 3.8-3) indicate that groundwater flow from the aquifer through the riparian zones towards the river Glomma most of the year. Only in periods around flood peaks groundwater altitudes are higher in the in the riparian zone than further from the river. The main pattern with flow of groundwater outflow from the aquifer through the riparian zone is supported by the low and stable groundwater temperature in the riparian zone (Fig 3.8-4). The results in 2010 indicate relatively high groundwater tables in summer. Relatively high groundwater (and river water) tables in the first parts of the summer might partly be due to snow melting in the mountain parts of the water feeding catchments. This may counteract low groundwater tables in critical periods when temperatures and potential evaporation from vegetation are high and thus be important to ecosystems.

0 -1 -2 -3 Well A m -4 Well B -5 -6

-7

01.07.2010 15.07.2010 29.07.2010 12.08.2010 25.08.2010 08.09.2010 22.09.2010 06.10.2010 20.10.2010 03.11.2010 17.11.2010 01.12.2010 15.12.2010 29.12.2010

Fig 3.8-2 Depth to groundwater table in monitoring wells in and behind the riparian forest zone along the river Glomma at Grue.

151,0 150,5 150,0 Well A 149,5 Well B 149,0 148,5

Meter above sea level sea above Meter 148,0

01.07.2010 16.07.2010 31.07.2010 15.08.2010 30.08.2010 13.09.2010 28.09.2010 13.10.2010 28.10.2010 12.11.2010 26.11.2010 11.12.2010 26.12.2010

Fig 3.8-3 Groundwater table altitudes in and behind the riparian forest zone along the river Glomma at Grue.

6,5

6,0

Well A 5,5 Well B

Degrees C Degrees 5,0

4,5

02.07.2010 16.07.2010 30.07.2010 14.08.2010 28.08.2010 11.09.2010 25.09.2010 09.10.2010 24.10.2010 07.11.2010 21.11.2010 05.12.2010 19.12.2010

Fig 3.8-4 Groundwater temperatures in and behind the riparian forest zone along the river Glomma.

3.8.3 Conceptual models for surface water – groundwater interaction The pattern of surface water – groundwater interaction in the riparian system is illustrated in Fig 3.8-5. The balance between and importance between different components is dynamic, and varies both in space and time, e. g. in periods with elevated groundwater levels may groundwater feed the root zone at higher altitudes than in periods with lover groundwater tables.

RIVER RIPARIAN ZONE AGRICULTURAL AREA

Precipitation

Evapotranspiration Infiltration of Infiltration of river precipitatian water during floods Capillary rise

Groundwater flow

Fig 3.8-5 Hydrological processes and surface water – groundwater interactions in a forested riparian system.

3.9 Sava river, interaction with groundwater

The Sava River is the largest river in Croatia and the second largest tributary to the Danube River. It has outstanding biological and landscape diversity, hosting the largest complex of alluvial floodplain wetlands in the Danube basin and the largest lowland forests. Due to its importance at the European level, Sava river has been selected as a focal region in the Pan European Biological and Landscape Diversity Strategy (PEBLDS) of the Council of Europe (www.savariver.com). Along its course there are numerous protected areas at national and international level. Several Natura 2000 sites are situated within the case study of Zagreb aquifer The Sava River, with extremely asymmetric catchment area and 75% of the catchment situated on the right bank of the river, divides the Zagreb aquifer system into two parts. The river, which is the main source of groundwater recharge within aquifer system, is in direct hydraulic connection with the shallow aquifer. Head contour maps analysis (Posavec, 2006) showed that during high Sava river water levels the river infiltrates ground water on all parts of the flow while during medium and low water levels the river drains ground water on some parts of the flow (Fig 3.9-1). Ground water levels are also strongly affected by the small river dam. An average drop of the Sava river water level amounts 0.4 m/km while the drop of the water level downstream from the river dam can be up to 6 m on a distance of only tens of meters. This strongly affects the aquifer flow directions and ground water levels in close vicinity of the river dam.

Fig 3.9-1 River dam location and head contour maps showing impact on ground water flow direction in near vicinity of the river dam.

3.9.1 Hydrodynamic pattern of the Sava River – groundwater interaction

The Sava River represents the main source of water for the Zagreb aquifer system. Although recharge occurs also through precipitation, the changes in the Sava river water levels dominantly influence the changes in the groundwater levels across the whole aquifer. The strong influence of Sava River on groundwater recharge has been confirmed by multivariate statistical analysis - principal component analysis (PCA), following the procedure by Winter et al. (2000) - of the groundwater levels, which has been done in order to define groundwater table change rates and fluctuation pattern in the vicinity of the Sava River. Data analysis procedure has been tested which has allowed the use of 75 observation well locations and 10 years data series, i.e. total of 1025 measurements per location, in order to describe the groundwater dynamics.

Generally, PCA explains correlation between several variables concurrently, which helps finding simpler relations that enable insight into the concealed structure of the data. These simpler relations are expressed by a new group of variables referred to as principal components, which retain maximum quantity of information and indicate the correlation of the variables. The main objective of the PCA is to obtain certain number of principal components that will explain the maximum possible part of the total variance (Brown, 1998). The results of the PCA in Zagreb case study example revealed significant differences in groundwater table fluctuation patterns in different parts of the aquifer system. It was shown that most of the variance (70%) is explained by the first principal component, which revealed the pattern of groundwater table changes in the vicinity of the Sava River (Fig 3.9-2). Hydrographs of the observation wells near the Sava River follow the same pattern as the hydrograph component scores for the first principal component. These observation wells are installed in discharge area of the aquifer system. The fluctuation pattern is equal for the shallow and deeper layers, and it reflects the impacts of the Sava River on groundwater. Table 3.9-1 Eigenvalues from principal component analysis, the percentage of the total variance, cumulative eigenvalues and cumulative percentage explained by principal components

Principal Percentage of Cumulative Cumulative Eigenvalues Components total variance Eigenvalues percentage

1 49,28 70,41 49,29 70,41

2 8,18 11,68 57,46 82,09

3 3,96 5,66 61,43 87,75

Fig 3.9-2 Hydrographs for the observation wells near the Sava River compared with hydrograph of principal component 1 factor scores.

Spatial zonation of areas with higher impact of the Sava river on ground water levels was analyzed using recession curve models. The analysis of groundwater level time series using recession curve models was performed with Master Recession Curve Tool (Posavec et al., 2006). 278 master recession curves were obtained for 278 analyzed observation wells. Processing was performed on the computer configuration Pentium ® 4 CPU 3.40GHz with 2.0 GB of ECC RAM, and it lasted 3 hours and 45 minutes.

Analysis of the spatial distribution of the selected regression model showed that the logarithmic regression prevails in parts of the aquifer near the river Sava while polynomial regression prevails in other parts of the aquifer (Fig 3.9-3). These results are logical and reasonable with respect to changes in groundwater levels which occur faster in the vicinity of the Sava River. In other parts of the aquifer where such strong boundaries do not exist, ground water level changes occur less rapidly.

Fig 3.9-3 Regression models showing zones of higher impact of the Sava river.

3.9.2 Hydrogeochemical evidence of the Sava River –groundwater interaction

Direct evidence of the Sava River – groundwater interaction can also be revealed by the results of geochemical investigation in Zagreb aquifer system. It was shown that using groundwater modeling tool, PHREEQC (Parkhurst et all, 1980.) and multivariate statistical analysis, Cluster analysis (Ward method of hierarchical tree clustering), hydrogeochemical homogenous areas can be delineated within the Zagreb aquifer system, which are expected to react similarly or identically to natural or man-caused events (Nakić et al, 2004). These analyses revealed very similar or identical macro chemical composition of the groundwater in the area bordering with the river, which support the evidence of intensive impacts of changes in the river water levels on the groundwater tables within the belt by the river. Change in macro chemical composition on a greater distance from the river confirmed weakening of the river impact on the aquifer replenishment and domination of lasting seasonal replenishment conditions. Investigations of the geochemical characteristics in the western part of the Zagreb aquifer systems have further confirmed that direct exchange of water from the Sava River and groundwater occurs in the near vicinity of the river (Vlahović et al, 2008). It was proved that this exchange weakens further away, while the difference in hydrogeochemical characteristics between the Sava River water and groundwater increases. Direct mixing of water from the Sava River and groundwater is occurring in the near vicinity of the Sava River and it weakens further away while the differences in hydrogeochemical characteristics grow. In central part of the Zagreb aquifer system stable isotopes of oxygen and hydrogen are used to identify groundwater recharge from Sava River (Horvatinčić et al., 2011). The difference in stable – isotope signatures of river and precipitation are used to determine the relative contribution of these two sources of groundwater recharge. Stable isotope analyses indicated different infiltration times of surface water of the Sava River to different wells.

3.10 Fontanili springs, Italy, Hydrogeology, site description and methods

3.10.1 Introduction

Fontanili springs are semi-natural water emergences that create watercourses characteristic for the Po Valley. With a surface of 46,000 km² the Po Valley is the largest flat area in Italy that occupies 1/6th of the Italian territory. Situated between the Alps and the Appenines the valley is mostly located within the Italian borders apart from a small area located in Switzerland. River Po that flows along the valley is 652 km long with a delta discharge of 1540 m3s-1 and a catchment area of 74145 km2. The climate of the Po Valley is mild continental characterized by relatively cold winters and hot summers. The area has elevated air humidity and the average yearly precipitation becomes higher moving from south east towards north-west. The Mantova plain has the lowest rainfall with around 650-700 mm/year while the maximum values that exceed 2000 mm/year are noted in the vicinity of the alpine lakes. The atmospheric precipitation has two yearly peaks – one during spring time and one in autumn. The variation in land cover of the Po Valley influenced the formation of different miroclimates in the rural areas, in the urban areas and a specific microclimate associated with the great lakes (Canepa, 2011).

Fig 3.10-1 Po Valley map (Wikimedia Commons media file depository).

The Po Valley has a complex surface water network with the great alpine lakes that give birth to some of the main left-bank tributary rivers of the Po, rivers that originate from mountain springs and a particular kind of rivulets that take their beginning in the fontanili springs. (Canepa, 2011).

Fontanili springs are specific watercourses that emerge along two lines of 5-50 km width located between the upper and lower Po plains. These areas are called “linee delle risorgive" which translated from Italian means simply “lines of springs’. In the north part of the Po Valley the line of fontanili springs stretches below the Alps from the Cuneo Piemonte plain continuing east towards the Veneto–Friuli plain. The other “line of springs” is more scattered and runs south from the Po River below the Appenines along the area of Piacenza province continuing south- east towards the area of Bologna.

Fig 3.10-2 Map of North Italy with marked “lines of springs” (modified from Minelli et al., 2002)

Fig 3.10-3 Fontanili areas (modified from Ferrari and Lavezzi, 1995)

Water emergence along the “lines of springs” is caused by the difference in permeability of the alluvial deposits in the area. The subsoil of the Po Valley consist mostly of late Miocene and Quaternary deposits and sediments. The upper Po plain is built mostly of pebbles, gravel and sand, as the terrain descends however, the granulometry of the building material reduces gradually until it is no longer permeable. The lower Po plain consists mostly of silt and clay characterized by low permeability (Minelli et al., 2002; De Luca et al., 2005). This fine material creates a barrier in the flow of the shallow groundwater and causes the groundwater table to rise and eventually intersect with the topographic surface which results in water seeping out to the land. Historically these border areas between the upper and lower Po plain were covered with a mosaic of wetlands, streams and small lakes (Minelli et al., 2002) that were formed by groundwater emerging spontaneously.

Fig 3.10-4 A very general scheme illustrating the hydrogeological setting of the Po plain in cross-section (modified from Boscolo and Mion, 2008).

Fontanili springs have characteristics much different than natural springs - they are described as semi-natural springs because they were created by human interventions to facilitate and organize the outflow of groundwater along the “lines of springs” where the water was naturally conditioned to outcrop. These human interventions either modified the naturally emerging streams, or created new water resurgences (De Luca et al., 2005; Conati, 2003). The fontanili are sometimes called semi-artesian wells because their water comes from an unconfined aquifer which is pressed by the overlying impermeable layers. Fontanili waters were directed to the surface by excavation or tubular perforation of the terrain.

The first fontanili were created already in the XI-XII century by local religious congregations that organized the outflow of groundwater by tubes and barrels inserted vertically 2-3 meters deep into the earth. The resurgence of groundwater to the streams was in some cases also facilitated by constructing drainage trenches. These installations together with an excavated system of canals and ditches directed the outflow of groundwater and drained areas where stagnant waters or frequent flooding did not allow land cultivation. This adjustment generated more arable land. Additionally the network of canals allowed controlled and efficient crop irrigation. Continuous access to relatively warm water generated very advantageous conditions that favored higher crop yields and stimulated/boosted the development of agriculture in the region. At that time water-meadows – an advantageous form of cropping that utilized the fontanili waters, became a typical practice in the area (Minelli et al., 2002).

A typical fontanili begins with a “head” which is an excavation that forms a small circular pond 0,5 - 5 m deep. The water in such pond rarely exceeds the level of 2 m. The way the groundwater is facilitated to emerge depends on the specific hydrogeologic setting of each fontanili. The groundwater can flow out to the pool either through variously constructed drainage trenches or through tubular installations inserted vertically into the ground. The historic wooden barrels and tubes used initially in the medieval ages were not very durable and had to be replaced every 10- 15 years. Since XIX century the tubular wooden material has been substituted with more resistant concrete and metal. Nowadays the vertical outflow of fontanili water is facilitated by concrete rings of 1 – 2,5m depth or metal tubes that can be 3 – 10m deep. Still these installations have to be regularly conserved and periodically replaced. A fontanili head can have one or several tubular or drainage installations (Kløve et al., De Luca el at., 2005; Vitali and Moroni, 2010). In the Lombardy region the most common are small fontanili that form heads of 0,9 – 4 m diameter. The big fontanili which are rather few, have ponds of up to 150m diameter (Kløve et al., 2011).

The “throat” of the fontanili is a bottleneck which connects the fontanili head with an excavated channel that allows further water flow.

Fig 3.10-5 Morphology of a fontanili spring with one tube (modified from Minelli et al., 2002).

Fig 3.10-6 Examples of various shapes of fontanili heads with multiple fontanili tubes (modified from Ferrari and Lavezzi, 1995).

3.10.2 Groundwater – Surface Water interactions: Fontanili of the Lombardy Region

Fig 3.10-6 Map of the Lombardy region with marked locations of documented fontanili (data from 2009).

The geomorphological structure in the Lombardy region conditioned the formation of 4 aquifers that overly each other and are separated by impermeable layers of lime and clay. Aquifer A represents the shallow groundwater that on average reaches 30 m below the ground surface. This aquifer is mostly built of sand and gravel deposits and its waters recharge directly from precipitation, irrigation of the cultivated land and infiltration from the surface water bodies.

This recharge is predominantly vertical as the aquifer resides in the phreatic zone. In the area of the “line of springs” however this aquifer becomes semi-confined. Such situation is caused by the specific multilayer structure of aquifer A - multiple stratums of silt and clay inserted between the sand and gravel. Presence of these impermeable layers influence the formation of a high hydraulic gradient in the aquifer. This gradient causes the groundwater lavel to rise form water resurgences along the “lines of springs” (Carcano and Piccin, 2001; Malerba, 2009; Canepa, 2011).

The described aquifer supplies the fontanili springs in the Lombardy area. Because the mentioned groundwater body resides in such a complex geomorphological structure and has a large recharge area, it is relatively difficult to predict the spreading of contaminants within the aquifer and their entering into the fontanili watercourses. (Canepa, 2011)

Another deeper aquifer - Aquifer B - resides below the described Aquifer A isolated from the overlying waters by a continuous 5-15m thick layer of clay. This aquifer is only recharged by precipitation in the northern margin of the groundwater basins, where the prevalent material is permeable and the separation of the aquifers is less evident. The two deeper aquifers – C and D are confined deep aquifers that do not have contact or direct influence on the fontanili waters (Malerba, 2009).

As mentioned previously, the fontanili springs in the Lombardy region are supplied by water from the semi-confined shallow groundwater. In such cases the water which is under a mild pressure, is facilitated to outflow through metal tubes of various depth. These kinds of fontanili springs are called semi-artesian and the outflow of water is mostly vertical. Water emerging from the tubes is under a pressure that favors its springing out slightly above the fontanili water surface (on average 10 to 20cm). Although the outflow of groundwater to the fontanili springs is predominantly vertical, the input of the lateral flow from the phreatic zone can also be significant depending on local hydrogeological conditions. Some fontanili pools are excavated much below the phreatic zone level. In such cases the groundwater flows out not predominantly through the vertical tubes, but additionally infiltrates from the banks of the excavated fontanili pool. In this situation the lateral flow becomes a significant component of the groundwater discharge. The water which moves laterally in the phreatic zone towards the fontanili head, washes out the finer sediments, which with time makes the surrounding terrain, already built mostly of sand and gravel, become even more permeable (Ferrari and Lavezzi, 1995).

The creation of fontanili springs significantly modified the landscape of the Po Valley reducing the surface of naturally occurring humid areas by around 10%. The numerous fontanili in the area formed a net of drainage canals which eventually united forming numerous rivulets. These watercourses differ greatly from other rivers in the area that collect water from mountain springs. Rivulets of fontanili origin have a very gentle slope of approximately 1 m/km, relatively low medium flow values - 0,5 m3/s and a resulting reduced capacity of transport or erosion (Minelli

et al., 2002). The fontanili rivulets eventually discharge to the Po tributary rivers and to the Po River itself.

Geochemical and physical properties of the fontanili waters differ from the surrounding surface waters. pH of the fontanili water is usually neutral, oxygen levels do not reach saturation (Kløve et al., 2011). Because the fontanili streams are supplied by groundwater, the water temperature in these watercourses is relatively stable during the year. The mean water temperatures in the fontanili oscillate around 10 – 16 C, they are the lowest during early spring, and the highest in autumn. Other surface waters in the Po Valley are much more dependent on the atmospheric conditions and their temperatures vary between 0 and 30 C throughout the year. Some fontanili that are more depended on the phreatic zone for their water supply can have a more variable temperature regime as they are more influenced by the atmospheric temperatures (Desio, 1973).

Water flow values in the fontanili springs change slightly throughout the year. Normally they are the lowest from March until May, and the highest from August until December, however this yearly tendency can be modified by some locally occurring influences such as temporary droughts, intense rainfalls or crop irrigation (Ferrari and Lavezzi, 1995).

Fig 3.10-7 Conceptual model illustrating the groundwater – surface water interactions in a fontanili spring.

Fontanili are watercourses that are totally dependent on groundwater for their water supply. The specific conditions resulting from a continuous outflow of water with very minor temperature oscillations throughout the year create habitats with a mild microclimate that sustain various aquatic and terrestrial flora and fauna (D’Auria et al., 2006). Changes in the quantity of groundwater or deterioration of its quality can significantly affect these water bodies and change the ecosystem conditions.

Sensitivity of fontanili springs to groundwater level changes has been already documented. In the early 1960s excessive pumping to satisfy the industrial water demand caused a drastic drop of the groundwater table in the shallow aquifer. At that time many fontanili in the Lombardy area disappeared irrevocably (Minelli et al., 2002). The lowered groundwater table caused the top borders of the fontanili spring areas in Lombardy shift significantly south regarding their original location (Ferrari and Lavezzi, 1995).

Fig 3.10-7 ???

Fontanili springs are not natural watercourses and in order to remain in their initial form they need to be periodically maintained. During these maintenance operations the fontanilli heads and the channel beds are cleaned by removing the excess aquatic vegetation and sediment. The fontanili tubes are purged to remove the residing soil particles that can block the water flow. Also the fontanili banks have to be reconstructed and supported periodically, as with time they tend to erode and collapse (Vitali and Moroni, 2010). The maintenance operations are a drastic intervention in the fontanili ecosystem. Nevertheless abandoning these activities leads to progressive deterioration of the fontanili pools that can result in vanishing of these watercourses.

Most of the fontanili heads are located on private property land and therefore their fate depends on the land-owners, who sometimes fail to maintain periodical conservations of these water resurgences. Nowadays fontanili springs are losing their primary purpose as a source of water supply for agriculture, because other more efficient methods of water extraction are becoming more popular. This is why these water resurgences are often abandoned, gradually buried by the surrounding earth material, covered by plants and eventually run dry. In some cases the fontanili pools become non-controlled dump sites filled with waste of various origin that create an additional risk of groundwater contamination (De Luca et al., 2005). In response to this situation the the program of rural development of the Lobbardy region for the years 2007 – 2013 accounted funding of projects aimed to recover the abandoned fontanili springs. The funding helped reconstruct many fontanili during the recent years.

3.10.3 Major outcome from studies on selected fontanili

The Po valley represents the biggest agricultural area in Italy. 75% of the land is annually cropped with cereals, maize, alfalfa, grass and industrial crops. Fertilizers and herbicides are used extensively in the area. This creates a potentially high anthropogenic pressure on these water bodies. Fontanili water is originally poor in nutrients, however elevated nitrate and herbicide levels in water samples collected from these springs, indicate a significant impact of diffuse agricultural contamination. The springs can be contaminated indirectly because they are supplied by a shallow aquifer that recharges from waters infiltrating through the surface soils. Additionally the agricultural contaminants can enter the fontanili waters directly with local surface runoff from the cultivated fields. This risk becomes especially high immediately after herbicide and/or fertilizer application. Unfortunately the fontanili are rarely protected from direct inflow of runoff water as crops in the area are often grown without keeping any distance from the fontanili banks. As mentioned before, the complex geomorphology and large recharge area of the aquifer supplying the fontanili springs make it difficult to predict the contaminant migration to the fontanili springs.

Selected fontanili in the Lombardy region have been under continuous monitoring. Installed piezometers along the fontanili banks enabled measuring the shallow groundwater table level, monitoring the groundwater physical and chemical parameters and collecting samples for measuring nitrate and herbicide contamination. In parallel the same data was collected for the surface water in the fontanili springs.

3.10.4 Conceptual model for surface water – groundwater interaction

Fig 3.10-8 Conceptual model for groundwater – surface water interactions in a typical fontanili head.

This conceptual model is demonstrated on a cross-section of a typical fontanili head with a vertical tube that facilitates the water resurgence. The vertical tube can reach up to 10 m below ground surface. The blue arrows show the direction of water flow. The inflow of groundwater that supplies the fontanili is predominantly vertical, but the lateral flow can also become a significant component depending on the local hydrology. The fontanili is supplied by the shallow aquifer A that reaches up to 30 meters below ground level and is isolated from the underlying aquifer B by a continuous 5-15 m impermeable layer. The water that flows out into the fontanili fills the fontanili head, through the fontanili throat enters the fontanili channel and continues its flow becoming a rivulet of a relatively low medium flow.

4. Modelling of surface-groundwater interaction in aquifers

4.1 Groundwater interaction with ecosystems

Groundwater moves along flow paths from recharge areas to discharge areas within GDEs (Fig 4.1-1). Infiltration occurs when meteroric water (including retarded fractions such as snow and glaciers) enters the ground. Water then usually moves through the unsaturated zone and reaches the saturated part of the aquifer contributing to groundwater recharge. Some surface waters both receive and recharge groundwater. Groundwater recharge may include contribution from adjacent aquifers. Discharge from the aquifer occurs at springs, streams, lakes and wetlands, as transpiration by plants with roots that extend to near the water table, and by direct soil evaporation. Groundwater can also discharge to adjacent aquifers (e.g. downward leakage from an aquifer to a deeper one). Groundwater typically discharges to surface water bodies where the slope of the water table changes suddenly (e.g. Winter et al., 1998). In many cases springs are found where geological layer and hydraulic conductivity change (Fig. 4.1-1).

Fig 4.1-1 Different types of springs. In many cases springs are found where the geological layer and hydraulic conductivity change (modified after Fetter, 2001).

The actual conceptual model for a given aquifer will vary locally depending on water use, slope, topography, climate and geology. This should also include the unsaturated zone which plays a very important role both for groundwater quantitative and qualitative aspects. Local groundwater flow is often near the surface and occurs over short distances, i.e. from a higher elevation recharge area to an adjacent discharge area such as small springs. Intermediate and regional flows usually occur at a greater depth and over greater distance. Steeper and undulating landscapes have the most local flow points. Groundwater flow is always three-dimensional, but can often be analyzed in two-dimensional sections (Fig 1.1-1). Analysis of these flow paths is important when studying GDEs because it can provide valuable information about potential threats to both the quantity and quality of groundwater.

4.2 Conceptual models

A conceptual model of a GDE can is a simplified representation or drawing of the system that include main processes effecting the ecosystem. As groundwater provides water, nutrients, stable conditions (temperature, pH,) these processes might be needed to be included in the conceptual model. The model must also include the overall hydrogeological setting and the specific topography at the GDE including main inlets and outlet of water. As models are often developed to assess impacts, a conceptual model for the impact and foreseen response is needed. For a natural system, the order of making these models should be from hydrological, to geochemical and then to ecological conceptual models as hydrology influence geochemistry and both influence ecology. These models have therefore increasing complexity.

A hydrogeological conceptual model would include I) water fluxes to and from the system, II) fluxes within the system, III) pressures in nearby aquifers and in the GDE system. The hydraulic link between the aquifer and the GDE should be in focus. It is also important to include the hydrology at the recharge area and the discharge areas that influence the GDEs. Shallow and long flow paths should be distinguished as these flow paths deliver water of different composition and quality.

The main surface and groundwater systems should be included in GDE conceptual model with respective indicative water fluxes. A cross-section (2D) and an aerial (bird) perspective showing main recharge-discharge patterns and flow paths and the capture zone should be included.

It can be important to include information of soil hydraulic parameters and hydraulics thresholds (points that control water flow).

Geochemical conceptual models should include main typical concentrations found in shallow and deep groundwater and within the GDE. A cross-section showing geological layers with typical concentrations and flow lines is necessary to show the potential interaction and the portion of nutrient fluxes from groundwater.

Ecological conceptual models should include the most important processes related to hydrology and geochemistry. The model should include the most relevant flora and fauna and how they rely on the environmental factors such as temperature, pH and nutrients provided by groundwater. This could be included by a table showing most important species and their preferred environmental habitat conditions as a range or box plot.

Impact-response conceptual models are useful to show potential known or predicted changes. These can be scenarios based on no-change, positive change or negative change. In change assessment the natural variability must be considered due to climate variability, changes in dry and wet deposition patterns, and species (invasive, diseases etc.) that are not due to changes in the groundwater system itself. The main changes and pressures must be included such as land- use, industry, urbanization etc. The main source of water losses such as irrigation and potable water extraction must be shown. The potential water table drawdown must be shown also indicating the original level. Also the direction of flow before and after the pressure should be indicated. Impacts on the ecosystem services, ecology and humans must be part of such models.

Hot-spots In GDEs with groundwater input, the areas where groundwater flows into the system can be located spatially in a complex manner. This creates special environmental conditions within a more uniform environment that can be referred to as “hot-spots”. The term “hot-spots” has recently been used in peatland literature to show e.g. sources gas emission (Morris et al. 2011).

4.3 Numerical modelling needs and approaches

4.3.1 Numerical modelling needs

Groundwater-dependent ecosystems require an allocation of water to maintain their persistence in the landscape. The following four fundamental questions are identified as being central to the effective management of groundwater-dependent ecosystems (Eamus et al., 2006): 1) Which species, species assemblages or habitats are reliant on a supply of groundwater for their persistence in the landscape? 2) What groundwater regime is required to ensure the persistence of a GDE? 3) How can managers of natural resources successfully manage GDE? 4) What measures of ecosystem function can be monitored to ensure that management is effective? Numerical hydrological modelling is fundamental to estimate the groundwater regime that is required to ensure the persistence of a GDE. Moreover those models should be capable to model the responses to different management policies. More specifically models should be able to give information about the following attributes: 1) The depth of the saturated zone.

2) Hydraulic head within an aquifer. 3) Groundwater flow rate. 4) Quality of the groundwater. 5) Groundwater discharge and location. Models should be able to give information about those attributes spatially and temporally. Moreover, in order to accurately simulate GDEs it is necessary to model groundwater in an integrated manner. Numerical models of GDEs are needed to i) understand the temporal and spatial variation in hydrology and hydraulics, and to ii) make scenarios of impacts of past and future changes. Spatial variation of flow influences vegetation and species composition as the amount of flow controls temperature and nutrient fluxes in GDE. The temporal variation is important too as many species in GDE are adapted to stable conditions. It could be important to simulate impacts of droughts and floods to groundwater discharge to reveal the extreme natural conditions GDEs will have to face in the future.

The typical scenarios to be simulated are related to climate change, land use changes, drainage, urbanization, water extraction, increase nutrient input from land-use or atmospheric fallout. Typical land-uses are agriculture, forestry, and mining. In riverine systems dredging and hydropower regulation is important.

The models need to simulate impacts of future changes in water and land use. This includes change in vegetation, climate and also the socio-economic system. Sometimes policies impact agriculture, forestry, peat harvesting etc which influence water use and this must be included in scenarios.

In some cases the impact of biological and geomorphological processes on hydrology needs to be included in simulations. These include impacts of biofilms and eroded sediments on stream bed and its permeability. In the littoral zone the vegetation can influence mixing conditions. It’s likely that vegetation has also other feedbacks on hydrology.

For climate change scenarios it is important to distinguish between climate variability and climate change. The length of climate data record must be sufficient to separate natural cycles and long-term trends and shifts in climate.

For winter conditions we need snow and frost models having routines that can handle the following processes; canopy snow, ground snow accumulation and melt and in some cases soil frost. For soil frost we need models that take into account the impact of frost on soil hydraulic conductivity and overland flow in a realistic way.

The hydrological models need to simulate some of the following outputs: I) water fluxes to and from the GDE: runon-runoff-evapotranspiration, II) flow patterns in the GDE, III) water level variation in the GDE, IV) water pressure in GDE soil and adjacent aquifer, V) the size of the GDE aquifer capture zone, VI) water flow paths in the aquifer to the GDE, VII) residence time distribution of water delivered to the GDE from the aquifer, VIII) temperature in the GDE (this

might be different between aquifer and the nearby surface waters), IX) snow depth and water equivalent, X) snow melt rate, XI) and frost depth. The most important would perhaps be fluxes to and from the system, internal flow patterns, pressure in GDE and aquifer and temperature in the system. GDEs can be modeled in different ways using e.g numerical models, statistical models, water balance calculation etc. In the sections below we present some approached and issued to be considered in modeling of GDEs. In Appendix 1 different aspects related to recharge modeling and I Appendix 2 surface water modeling are reviewed.

4.3.2 Water balance calculation in GDEs

In GDEs supplied by several sources of water, the water balance equation can be written to include the contribution of groundwater. The water balance equation for a groundwater dependent system with an upland catchment where surface water and groundwater components are separated would be:

P + Rgwi + Rswi = ET+ Rgwo + Rswo ± ΔS where water input is from precipitation and snowmelt (P), groundwater input from the aquifer (Rgwi) and surface water runoff from the surrounding catchment area (Rswi). Water lost by evapotranspiration is denoted by (ET), groundwater outflow to the aquifer by (Rgwo), and runoff to surface waters by (Rswo). A storage term (ΔS) is needed to account for short term changes in water levels and soil moisture. In cold conditions, additional snow and ice storage, accumulation and melt must also be accounted for. In coastal regions, sea water intrusion must be included in the water balance terms. For peatlands (e,g fens) the outflow of groundwater will usually be low as the deeper soil layers have low permeability (Kvœrner and Kløve 2008). For systems with a considerable groundwater input and negligible groundwater output the terms Rgwo would be zero so the water balance would be:

Rgwi + Rswi + P = ET ± ΔS + Rswo The change in storage ΔS are regulated by surface and groundwater input and by precipitation and ET. In dry conditions with little surface water excess, the terms Rswi and Rswo could be small at least in some periods of the year. In cold climate the term Rswi becomes negligible in winter as precipitation is stored in snow and surface runoff is not generated.

P and Rswi can be estimated for ungauged catchments from the available climate data and regional hydrological data, such as specific runoff (mm/year). The The estimation of Rgwi is not straight forward as the drainage area for GDEs is not always evident. The regional specific runoff may be used to estimate the sum of Rgwi and Rswi, however, this would not separate the two components but be a sum of upland catchment input. In many cases, the groundwater input could be difficult to define as the groundwater catchment boundaries are not easily defined without complex geological surveys and modelling. Difficulties in catchment boundary determination could occur if the surface water divide is different from the groundwater divide by

e.g. water input is from fractures outside of the watershed. Exchange of groundwater can also take place between aquifers at different depths through semipermeable layers. This exchange can be quantified from the hydraulic conductivity of the semipermeable layer and the piezometric levels in the two aquifers.

4.3.3 Surface water groundwater interaction models Surface water bodies are integral parts of groundwater flow systems. Our models should be able to properly simulate groundwater-surface water interaction. There are various coupling schemes for the integration of surface water and groundwater models, for example sequential, iterative or fully coupled (see Deliverable 5.1 for more details). Some considerations must be made when selecting an appropriate model for a project, like the desirable temporal duration and resolution, the objective of the model, the spatial dimensions, and model solution method (numerical, analytical, physically based, or data driven). We can distinguish different type of models: 1) Physical based models a. Groundwater and surface channel flow models b. Groundwater and watershed models 2) Operational models a. Lumped b. Embedding c. Response matrix d. Eigenvalue

Physical models can couple channel routing models with 3D/2D flow groundwater models. They solve the partial differential equations using numerical methods. Solutions are then found for the points or nodes defined by the space-time discretization. These models are very attractive since they can give important information regarding of the groundwater and surface water regime; however they are time consuming to run, especially when integrated into management models. In the groundwater watershed models, instead of channel routing models, watershed models are coupled with groundwater flow models. Usually in this type of models, surface water are modelled using distributed lumped hydrologic equations, therefore the output is not as detailed as in the distributed physical models. On the other hand, these models have the advantage that can simulate land use, irrigation demand, evapotranspiration, surface runoff and climatological impacts. Operational management models were designed to handle management objectives like water allocation. In this type of models lumped and distributed parameter models have been used to simulate aquifers and quantify stream-aquifer interaction. Two main techniques have been used to incorporate distributed-parameter groundwater representations in management models, namely, the “embedding” and the “response matrix” methods (Gorelick, 1983). In the “embedding method” the system of equations obtained by numerical approximation of the governing groundwater flow equation is embedded within the optimization model constraint set.

This approach results in very large constraint sets that bring numerical difficulties and carry a high computational cost. When linearity can be accepted the principles of superposition and translation in time are applicable, which allows the use of influence functions or response matrices. The main advantage of response matrices is their condensed representation of external simulation models. A third approach is the eigenvalue method (Sahuquillo, 1983; Andreu and Sahuquillo, 1987). Hydraulic heads, flux vectors, and surface and groundwater interactions are obtained by explicit state equations as a function of the initial conditions and external stresses in the period.

4.3.4 Stream-aquifer interaction models River passing through a region underlain by a phreatic aquifer may either contribute water to the aquifer or serve as a drain. Depending on stream stage, ground water elevation, and saturation state between streambed and the aquifer, they can be hydraulic connected or disconnected. Hydraulic connection occurs when the water table intersects the streambed. On the other hand when an unsaturated zone develops between the streambed and the phreatic surface, the two water bodies are hydraulically disconnected. When the system is hydraulically connected, the stream–aquifer relationships can be subdivided to gaining stream where the water flows from the groundwater to the river and losing stream when river gives water to the aquifer. The exchange fluxes depend on the hydraulic head differences between the aquifer and the surface water, as well as the hydraulic conductivity of the riverbed. When the water bodies are disconnected the river infiltration becomes nearly independent of aquifer head. However, Peterson and Wilson (1988) showed that even when the unsaturated condition is present, the stream and aquifer may in fact be connected, in the sense that further lowering of the regional water table could increase channel losses. At some critical depth to the water table, however, further lowering has no influence on channel losses. At this depth, which depends mostly on soil properties and head in the channel, the aquifer becomes hydraulically disconnected from the stream.

4.3.5 Leakage coefficient approach When the stream is hydraulically connected to the aquifer, the exchange fluxes between them depend on the hydraulic head differences between the aquifer and the surface water, as well as the hydraulic conductivity of the riverbed. Leakage into an aquifer is given by (McDonald and Harbaugh, 1984):

hhriver  qKleakage riverbed driverbed -1 where: qleakage is the leakage coefficient [LT ], Kriverbed is the hydraulic conductivity of the river -1 bed [LT ], driverbed is the thickness of the semipervious layer [L], hriver is head in the river [L] and h is the head in the aquifer [L].

When combining the Kriverbed and driverbed we obtain the leakage coefficient:

Kriverbed lleakage  driverbed As the riverbed has usually a lower hydraulic conductivity than the underlying or adjacent aquifer, the riverbed controls the leakage rate. If unsaturated conditions prevail between river bottom and aquifer the exchange can be approximated by (Doppler et al., 2007): qleakage l leakage h river z riverbottom  where the hydraulic head h below the river bed is replaced by the level of the river bottom assuming zero water pressure below the clogging layer.

Surface water and groundwater interaction is usually modelled with temporally constant leakage coefficients. However, leakage coefficient is not constant (Blaschke et al., 2003; Doppler et al., 2007; Engeler et al., 2011), various reasons can affect it as flood events and sediment transport processes. Furthermore leakage coefficient depends on temperature since the hydraulic conductivity of the riverbed, which besides its dependence on soil properties, is also controlled by fluid viscosity: kg K   where K is the hydraulic conductivity [LT-1], k is the permeability [L2], g is the gravitational acceleration [LT-2], and ΰ is the kinematic viscosity of the fluid [L2T-1]. The kinematic viscosity is temperature dependent; therefore the exchange fluxes between the river and the aquifer are also temperature dependent. Doppler et al. (2007) found that the leakage coefficient on the river Limmat in Switzerland, which has temperature of about 4oC in winter and about 24oC in summer, differs by a factor of 1.7 between summer and winter. Especially in case of larger head gradients between river and aquifer, it is relevant to take into account that the leakage coefficient is temperature-dependent. This occurs in rivers, which have an unsaturated zone below the riverbed, as often is the case in arid regions. Infiltration from the river will vary as a function of temperature, and if the river only carries a small amount of water, also diurnal fluctuations in infiltration rate (due to diurnal temperature variations) might be of importance. It is expected that infiltration increases during the day, which could reduce the discharge rate of such rivers (Engeler et al., 2011). Colmation process can also affect the leakage coefficient. Colmation is the retention processes that can lead to the clogging of the top layer of the riverbed sediments; which directly affects the leakage coefficient. Clogging of the river increases the hydraulic resistance; this resistance is strongly spatially variable within the riverbed. Moreover the resistance can be time-dependent due to transient sedimentation and erosion or biochemical processes. Doppler et al. (2007) found

that the leakage coefficient on the river Limmat changed by a factor of 2.7 after a major flood event. Colmation can be affected by several activities, like increased sewage lading often leads to clogging by promoting the development of dense mats, or by causing the sedimentation of an organic layer on the river bed (Sophocleous; 2002). In many streams gradual colmation occurs naturally through the deposition of fine material during low discharge, alternating with a reopening of the interstices during flooding or exfiltration (decolmation) (Sophocleous; 2002). For the formation of a clogging layer it is also important whether infiltration or exfiltration conditions prevail. Infiltration conditions favour the forming of clogging layers; on the contrary, such a layer formation may be inhibited in the case of exfiltration conditions. The assumption of a linear relationship between the specific leakage rate and the hydraulic head difference between the aquifer and the river is not necessarily valid. High river stages lead to inundations of adjacent land and enhanced bank infiltration, for such situations the leakage coefficient is apparently larger than in a normal situation. Beside the leakage coefficient there are other factors that can affect the river-aquifer interaction. One of the factors is the distribution of the hydraulic properties of the aquifer below the riverbed; the distribution of the hydraulic properties in the aquifer can be highly heterogeneous. The exchange fluxes between the river and the aquifer also depend on the geometry of the riverbed as well as the orientation of the river with respect to the main flow direction of the groundwater (Woessner, 2000), both of which may vary over time due to variable flow regimes and the related sedimentation and erosion processes. A major difficulty is the determination of the leakage coefficient. It can be locally measured by seepage meters which measure the infiltration flux (Murdoch and Kelly, 2003); however due to the spatial heterogeneity of the riverbed and the surrounding hydrogeological settings, a local seepage measurement is expected to give only local information. The infiltration rate of losing river reaches can be also assessed by differential river discharge measurements. The usual way to estimate leakage coefficients is by model calibration using head data, tracers have been also used.

4.3.6 Future modeling needs GDEs comprise a range of various ecosystems with different hydrogeology setting and hydraulic contacts with aquifers and surface waters. To understand the hydrology of GDEs, fully integrated models will be useful where the interaction with surface water or sea water can be included. In cold conditions winter climate, snow and frost processes must be included in models. For management of aquifers connected to GDEs impacts of management must be included in models and scenarios. Besides hydrologic and hydraulic model development, models need to be linked to geochemistry, biology and management of aquifers.

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In many cases models must include heat transport , which is important for ecosystems and needed when impacts of climate change are predicted. The main impact on GDEs is change in water balances and temperature. The use of air temperature alone to predict changes GDEs is not sufficient. Also the feedback that biological and geomorphological processes have on flow need to be considered in modeling (e.g. flow resistance produced by biofilms, plants, and sediments).

Non-linear behavior need to be considered in the leakage coefficient.

A clear need is also to gain more information on the hydraulic contact between aquifers and GDEs to obtain realistic boundary conditions.

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References

Aartolahti T (1973) Morphology, vegetation and development of Rokuanvaara, an esker and dune complex in Finland. Fennia 127: 1–53.

Ala-aho P (2010) Water budget and interaction between surface water and groundwater in kettle lake Ahveroinen at Rokua esker formation. MSc thesis, University of Oulu, 104 pp.

Anderson, M.P. 2005.Heat as a ground water tracer. Groundwater 43(6):951-968.

Andersson E. Nilsson C. and Johansson ME. 2000. Effects of river fragmentation on plant dispersal and riparian flora, Regulated Rivers: Research & Management, 16, 83-89.

Andreu, J., and Sahuquillo, A. 1987. Efficient aquifer simulation in complex systems. J. Water Resour. Plann. Manage., 113(1), 110– 129.

Anibas C., Fleckenstein J.H., Volze N., Buis K., Verhoeven R., Meire P., Batelaan O. 2009. Transient or steady-state?Using vertical temperature profiles to quantify groundwater–surface water exchange.Hydrol.Process. 23, 2165–2177

Appelo C.A.J., Postma D. 2005. Geochemistry, groundwater and polution.Balkema Publishers, Leiden, The Netherlands, 649 p.

Arntzen EV. Geist DR. Dresel PE. 2006. Effects of fluctuating river flow on groundwater/surface water mixing in the hyporheic zone of a regulated, large cobble bed river. River Research & Applications 22: 937 - 946.

Averjanov S.F. (1950) About permeability of subsurface soils in case of incomplete saturation; Eng. Collect 1950/7.

Barnes J.B. and Turner J.V. (1998): Isotopic Exchange in Soil Water. In Kendall C. and McDonnell J.J. (Eds.). “Isotopes tracers in catchment hydrology”, Elsevier Science B.V., Amsterdam. pp. 137-164

Bear, J. Cheng, A. 2010. Modeling groundwater flow and contaminant transport. Springer

102

Bendel M. ,Tinner W. and Ammann B. (2006) : Forest dynamics in the Pfyn forest in recent centuries (Valais, Switzerland, Central Alps): interaction of pine (Pinus sylvestris) and oak (Quercus sp.) under changing land use and fire frequency. The Holocene 16, 1: 81-/89.

Bertrand G., Goldscheider N., Gobat J-M., Hunkeler D. (in press): Review: from multi-scale conceptualization for groundwater-dependent ecosystems to a classification system for management purposes. Hydrogeology Journal.

Blaschke, A.P., Steiner, K.H., Schmalfuss, R., Gutknecht, D., Sengschmitt, D., 2003. Clogging processes in hyporheic interstices of an impounded river, the Danube at Vienna, Austria. Int. Rev. Hydrobiol. 88 (3-4), 397–413.

Boscolo, C., Mion, F., 2008; Le Acque Sotterranee della Pianura Veneta, I risultati del Progetto SAMPAS; Arpav – Agenzia regionale per la Prevenzione e Protezione Ambientale del Veneto

Boujamlaoui Z., Bariac T., Biron P., Canale L., Richard P. (2005) : Profondeur d’extraction racinaire et signature isotopique de l’eau prelevee par les racines des couverts vegetaux. C. R. Geoscience 337 : 589-598.

Boutt D. Flemming B. 2009. Implications of anthropogenic river stage fluctuations on mass transport in a valley fill aquifer. Water resources research 45 (W04427), doi:10.1029/2007WR006526.

Bouwer H. (1976) Infiltration into increasingly permeable soils. J. Irrig. Drain. Div. 102(IR1): 127-136.

Brooks J.R., Barnard H.R., Coulombe R. and Mcdonnell J.J. (2010). Ecohydrologic separation of water between trees and streams in a Mediterranean climate. 2010, Nature Geoscience, v.3 : 100-103.

103

Brown, C.E. (1998): Applied Multivariate statistics in geohydrology and related sciences. Springer-Verlag. 248 p.

Canepa, P., 2011; Il Bilancio delle Acque Sotterranee nella Pianura Lombarda in relazione agli Efetti del Cambiamento Climatico; Dottorato di ricerca in Scienze Ambientali, Ciclo XXIII, Universita degli Studi di Milano – Bicocca

Carcano, C., Piccin., A., 2001; Geologia degli Acquiferi Padani della Regione Lombardia; Regione Lombardia, Eni Divisione Agip Cardenas M and Wilson JL. 2007. Exchange across a sediment–water interface with ambient groundwater discharge J. Hydrology 346: 69-80.

Cardenas M. Zlotnik V. 2003. A simple constant-head injection test for streambed hydraulic conductivity estimation. Groundwater 41(6): 867-871.

Charbeneau R.J. (2000) Groundwater hydraulics and pollutant transport; Prentice Hall: Upper Saddle River.

Chełmicki W., Ciszewski S., Żelazny M, 2003, Reconstructing groundwater level fluctuations in the 20th century in the forested catchment of Drwinka (Niepołomice Forest, S. Poland), [w:] L. Holko, P. Miklanek (ed.): Interdisciplinary approaches in small catchment hydrology: Monitoring and research, Proc. of the 9th ERB Conference (Demanovska dolina, Slovakia, 25- 28 September 2002), IHP Technical Documents in Hydrology, 67, Unesco, Paris, 203-208.

Chełmicki W., Klimek M., Żelazny M., 2003 – Rekonstrukcja wahań zwierciadła wód gruntowych w Puszczy Niepołomickiej za pomocą sieci neuronowych (Reconstructing groundwater level fluctuations in Niepołomice Forest with the aid of neural network approach).. Przegląd geograficzny, s. 251 – 269, [in Polish].

Chimner R.A. and Cooper D.J. (2004): Using stable oxygen isotopes to qualify the watersource used for transpiration by native shrubs in the San Luis Valley, Colorado U.S.A. 2004, Plant and Soil 260: 225-236.

Cirpka, O.A., Fienen, M.N., Hofer, M., Hoehn, E., Tessarini, A., Kipfer, R., et al. Analyzing bank filtration by deconvoluting time series of electrical conductivity. Ground Water 45: 318- 28.

Claret C, Boulton AJ. 2008. Integrating hydraulic conductivity with biogeochemical gradients and microbial activity along river–groundwater exchange zones in a subtropical stream. Hydrogeology Journal 17(1):151-160.

104

Conati, F., 2003; Caratterizzazione idrofaunistica ed ambientale di due tipiche risorgive della provincia di Verona (comuni di Mozzecane e di Povegliano Veronese); Tesi di Laurea in Scienze Naturali, Universita degli Studi di Parma, Facolta di Scienze Matematiche, Fisiche e Naturali Constantz, J. 2008. Heat as a tracer to determine streambed water exchanges. Water resources research 44, W00D10, doi:10.1029/2008WR006996.

Constantz, J., Stonestrom, D.A., 2003. Heat as a tracer of water movement near streams. In: Stonestrom, D.A., Constantz, J. (Eds.), Heat as a Tool for Studying the Movement of Ground Water Near Streams. US Geological Survey, US Geological Survey Circular 1260. US Geological Survey, Reston, VA, pp. 1–6.

CORINE Land Cover 2000.

D’Auria, G., Mosconi, E.M., Visconti, A., 2006; Il Terrirorio Come Ecomuseo. Nucleo Territoriale; N. 7. I Fontanili di Farinate, Fantigrafica s.r.l. - Cremona

De Luca, D.A., Ghione, R., Lasagna, M., 2005; Studio dei Fontanili della Pianura Piemontese; Giornale di Geologia Applicata 2 (2005) 377–382, doi: 10.1474/GGA.2005–02.0–55.0081

Desio, A., 1973; Geologia Applicata alla Ingegneria; p. 1193, Ulrico Hoepli Editore S.p.A., Legoprint S.p.A., Lavis (Trento)

Doppler, T., Hendricks Franssen, H.J., Kaiser, H.P., Kuhlman, U., Stauffer, F., 2007. Field evidence of a dynamic leakage coefficient for modelling river–aquifer interactions. J. Hydrol. 347 (1–2), 177–187.

Dotsika E., Lykoudis S., Poutoukis D., (2009). Spatial distribution of the isotopic composition of precipitation and spring water in Greece.Global and planetary change.71:141-149

Ehleringer J:R. and Dawson T.E. (1992): Water uptake by plants: perspectives from stable isotopes composition. Plant, Cell and Environment 15. 1073-1082.

Ekdal A., Gurel M., Guzel C., Erturk A., Tanik A. and Gonenc I. E. Application of WASP and SWAT models for a Mediterranean Coastal Lagoon with limited seawater exchange. Journal of Coastal Research, 64, 1023

Ekdal, A., Erturk, A., Gurel, M., Yuceil, K., Tanik, A. 2003. Developing a Computational Framework for Estimating Inflows to a Coastal Lagoon form its Basin, Sixth Int. Symposium&Exhibition on Environmental Contamination, Prague, Czech Republic

105

Engeler, I., Hendricks Franssen, H.J., Müller R., Stauffer, F., 2011. The importance of coupled modelling of variably saturated groundwater flow-heat transport for assessing river–aquifer interactions. J. Hydrol. doi:10.1016/j.jhydrol.2010.12.007

Ferrari, V., Lavezzi F., 1995; I Fontanili e i bodri in provincia di Cremona; Provincia di Cremona, Centro di documentazione ambientale

Fette M.W. (2005): Tracer studies of river-groundwater interaction under hydropeaking conditions. PhD dissertation, Swiss federal institute of technology of Zurich,117 p. Available on: http://www.rhone-thur.eawag.ch/Diss_Fette.pdf

Fromm E. 1965. Beskrivning till jordartskarta över Norrbottens län, nedanför lappmarksgränsen. Sveriges Geologiska Undersökning, Ser. Ca39: 236 p. (in Swedish with English summary).

Gemitzi A. and Stefanopoulos K. (2011), Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis. Journal of Hydrology,403: 130-140.

Gerecht, K E. Cardenas, MB. Guswa, AJ. Sawyer, A H. Nowinski JD., and Swanson T E. 2011.Dynamics of hyporheic flow and heat transport across a bed-to-bank continuum in a large regulated river Water resources research, 47 (W03524), doi:10.1029/2010WR009794, 2011

Gerecht, K. E., Cardenas, B. M., Guswa, A. J., Sawyer, A. H., Nowinski, J. D., & Swanson, T. E. (2011). Dynamics of hyporheic flow and heat transport across a bed-to-bank continuum in a large regulated river. Water resoures research, 47.

Gonenc I.E., Erturk, A., Guzel, C. 2011. Modelling with SWAT Dalyan Watershed Case Study Site, Turkey, Internal Report Submitted to GENESIS Project Partners on 23/05/2011

Gorelick, S. M. 1983. A review of distributed parameter groundwater management modeling methods. Water Resour. Res., 19(2), 305–319.

Green W.H., Ampt G.A. (1911) Studies on soil physics, 1.The flow of air and water through soils. J. Agric. Sci. 4: 1-24.

Hatch C.E., Fischer A.T., Revenaugh J.S., Constantz J., Ruehl C. 2006. Quantifying surface water-groundwater interactions using time series analysis of streambed thermal records: Method development.Water resources research 42, W10410, doi:10.1029/2005WR004787.

Hayashi M, Rosenberry DO (2002) Effects of ground water exchange on the hydrology and ecology of surface water. Ground Water 40: 309-316.

106

Hoehn E., Cirpka O.A. 2006. Assessing residence times of hyporheic ground water in two alluvial flood plains of the Southern Alps using water temperature and tracers.Hydrol Earth Syst Sci. 10(4): 553–563.

Horvatinčić, N., Barešić, J., Krajcar Bronić, i., Obelić, b., Kármán, K., Fórizs, I. (2011): Study of the bank filtered groundwater system of the Sava River at Zagreb (Croatia) using isotope analyses, Central European Geology, Vol. 54/1–2, pp. 121–127

Hyporheic network. A knowledge transfer network on groundwater - surface water interactions and hyporheic zone processes http://www.hyporheic.net/ Accessed 2011-09-06.

Jansson R. 2006. The effect of dams on biodiversity in Dams under Debate, B Johansson & B Sellberg eds, pp. 77- 84, Formas Research Council.

Jansson R. Nilsson C. Dynesius M, Andersson E. 2000. Effect of river regulation effects on river margin vegetation- a comparision of eight boreal rivers. Ecological Applications 10: 203- 224.

Johansson H. Jonsson K, Wörman A. 2001. Retention of conservative and sorptive solutes in streams - simultaneous tracer experiments. The Science of the total Environment 266: 229-238

Jonsson K. Wörman A. 2001. Effect of sorption kinetics on the transport of solutes in streams, The Science of the Total Environment 266:239-247.

Kleczkowski A. (ed.), 1981. Resources of the Natural Environment of the Niepolomice Forest and Problem of its Protection. Studies of Documentation Centre for Physiography, v.IX. Polish Academy of Sciences – Cracow Branch. 409pp. Wroclaw.

Kløve B, Ala-aho P, Guillaume B et al. (2011a) Groundwater Dependent Ecosystems Part I: Hydroecological status and trends. Environmental Science and Policy (accepted).

Kløve B, Allan A, Bertrand G et al. (2011 b) Groundwater Dependent Ecosystems: Part II - Ecosystem services and management under risk of climate Change and Land-Use Management. Environmental Sciences and Policies (accepted).

Kløve B., Ala-aho P., Bertrand G., Boukalova Z., Erturk Z., Goldscheider N., Ilmonen J., Karakaya N., Kupfersberger H., Kvoerner J., Lundberg A., Mileusnic M., Moszczynska A., Muotka T., Preda E., Rossi P., Siergieiev D., Simek J., Wachniew P., Angheluta V., Widerlund A., 2011; Groundwater dependent ecosystems. Part I: Hydroecological status and trends; Environmental Science and Policy 14 (2011) 770 – 781

Kowalik P.(2010) Agrohydrologia obliczeniowa, KGW PAN: Warszawa.

107

Książyński K.W. (2007) Tłokowy model filtracji w strefie niepełnego nasycenia (Piston model of seepage in unsaturated zone); Seria Inżynieria Środowiska: Monografia 353; PK: Kraków, 188.

Książyński K.W., (2010) The piston model of groundwater recharge. Proceedings of the IAH Congress, Kraków, September 2010

Łajczak A., 1997. Geomorfologiczna i hydrograficzna charakterystyka rezerwatu przyrody Długosz Królewski” w Puszczy Niepołomickiej. (Geomorphological and hydrographic characterisation of the „Royal Fern” nature reserve in the Niepolomice Forest). Ochrona Przyrody 54, 81-90.

Landon MK. Rus DL. Harvey FE. 2001. Comparison of instream methods for measuring hydraulic conductivity in sandy streambeds. Ground Water 39(6):870–885.

LassaadDassi. (2011) Investigation by multivariate analysis of groundwater composition in a multilayer aquifer from North Africa: A multi-tracer approach. Applied Geochemistry, 26: 1386-1398

Lee D.R (1977) A device for measuring seepage flux in lakes and esturies. Limnol. Oceanogr. 22: 140-147.

Lee DR. 1977. A device for measuring seepage flux in lakes and estuaries. Limnology and Oceanography 22: 140-147.

Li S-G., Romero-Saltos H., Tsujimura M., Sugimoto A., Sasaki L., Davaa G. and Oyunbaatar D. (2006): Plant water sources in the cold semiarid ecosystem of the upper Kherlen River catchment in Mongolia : A stable isotope approach. 2006, Journal of Hydrology 333 : 109-11 7.

Lipka K., Zając E., Zarzycki J., 2006. Course of plant succession In the post-harvest and post- fire areas of the Wielkie Bloto fen in the Niepolomice Primeveal Forest. Acta Agrophysica 7, 433-438.

Malcolm I.A., Soulsby C., Youngson A.F., Tetzlaff D. 2009. Fine scale variability of hyporheic hydrochemistry in salmon spawning gravels with contrasting groundwater-surface water interactions. Hydrogeology Journal 17(1):161-174.

Malerba, G., 2009; Studio Geologico di Supporto alla Redazione del P.G.T, L.R. 11-03-2005 n° 12 _ D.G.R. 28-05-2008 n° 8/7374, Relazione Integrativa; p 30 – 47; Comune di Carpegnanica, Provincia di Cremona, Regione Lombardia

108

Malina G., Kaczorowski Z., Mizera J. (2007) Zintegrowany system gospodarowania i ochrony zasobów wodnych GZWP 326; Wodociągi Częstochowskie, Częstochowa.

Malm Renöfält B, Jansson R. Nilsson C. 2010. Effects of hydropower generation and opportunities for environmental flow management in Swedish riverine ecosystems. Freshwater Biology 55(1): 49-67.

Maloszewski P., Moser H., Stichler W., Bertleff B., Hedin K. 1990. Modelling of groundwater pollution by river bank filtration using oxygen-18 data. Proceedings of the Dresden Symposium, March 1987. IAHS Publ. no. 173, 1990.

Matuszkiewicz J.M. (2008) Potential natural vegetation of Poland; IGIPZ PAN: Warszawa.

McDonald, M. G. and Harbaugh, A. W., 1984, A modular three-dimensional finite-difference groundwater flow model, USGS Report.

Metsähallitus (2008) Rokuan kansallispuiston ja valtion omistamien Natura-alueiden hoito- ja käyttösuunnitelma. Metsähallituksen luonnonsuojelujulkaisuja sarja C37. ISBN 978-952-446- 601-1 (PDF).

Minelli, A., Ruffo, S., Stoch, F., Cosentino, A., La Posta, A., Morandini, C., Muscio, G., Lapini, L., Paradisi, S., Sburlino, G., Solari, M., 2002; Risorgive e fontanili. Acque sorgenti di pianura dell’Italia Settentronale; p 13 – 28; Ministero Dell’Ambiente e Della Tutela del Territorio , Museo Friulano di Storia Naturale, Comune di Udine

Morel-Seytoux H.J. (1984) Some recent developments in physically based rainfall-runoff modeling; Frontiers in Hydrology; Water Resources Publications: Littleton/Colorado.

Morris PJ, Waddington JM, Benscoter BW, Turetsky MR. 2011. Conceptual frameworks in peatland ecohydrology: Looking beyond the two-layered (acrotelm-catotelm) model. Ecohydrology 4: 1-11, doi:10.1002/eco.191.

Murdoch, L.C., Kelly, S.E., 2003. Factors affecting the performance of conventional seepage meters. Water Resour. Res. 39 (6), W1163. doi:10.1029/ 2002WR001347.

Nakić, Z., Posavec, K. and Parlov, J. (2004): Hydrogeochemical model of the heterogeneous aquifer system: the case of Zagreb, Croatia, Groundwater flow understanding from local to regional scales, Congress XXXIII – 70 ALHSUD, Zacatecas City.

Nilsson C. Berggren K. 2000. Alterations of Riparian Ecosystems Caused by River Regulation. BioScience 50(9): 783-792.

Nyberg L. Calles, , O. Greenberg L. 2008. Impact of short-term regulation on hyporheic water quality in a boreal river River. Res. Applic. 24: 407–419 DOI: 10.1002/rra.1075

109

Odum H.T. 1956. Primary production in flowing waters. Limnology and Oceanography 1: 102- 117.

Pajunen, H (1995). Holocene accumulation of peat in the area of an esker and dune complex, Rokuanvaara, central Finland. Geological Survey of Finland, Special paper 20: 125-133.

Parkhurst DK, Thorenston DC and Plummer NL 1980. PHREEQE – a computer program for geochemical calculations. U.S. Geological Survey Water Resource Investigations 80-96.

Peterson DM, Wilson JL 1988. Variably saturated flow between streams and aquifers. Tech Completion Rep 233, New Mexico Water Resources Research Institute, Socorro

Pisinaras V.,Petalas C. , Tsihrintzis V. A., ZaganaE. ,(2007). A groundwater flow model for water resources management in the Ismarida plain, North Greece.Environmental modelling and Assessment. 12: 75-89

Pociask-Karteczka J. (2003) Zlewnia. Właściwości i procesy, IGGP UJ: Kraków.

Porębski S.J., , Oszczypko N., 1999. Lithofacies and origin of the Bogucice sands (Upper Badenian), Carpathian Foredeep, Poland. Prace Państwowego Instytutu Geologicznego, CLXVIII, 57-62.

Posavec, K. (2006): Identification and prediction of minimum ground water levels of Zagreb alluvial aquifer using recession curve models. Dissertation. University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering.

Posavec, K., Bačani, A. and Nakić, Z. (2006): A Visual Basic Spreadsheet Macro for Recession Curve Analysis, Ground Water 44, 764–767.

Potencjalna roślinność naturalna; Internetowy Atlas Polski; Pracownia Kartografii i GIS IGIPZ PAN.

Rosenberry DO, LaBaugh JW, 2008. Field Techniques for estimating water fluxes between surface water and ground. U.S. Geological Survey Techniques and Methods 4-D2 :128.

Rossi PM, Ala-aho P, Ronkanen A-K, Kløve B Groundwater discharge mechanisms from esker aquifer to peatland ditches. Submitted for publication.

Sahuquillo, A. 1983. An eigenvalue numerical technique for solving unsteady groundwater models continuously in time. Water Resour.Res., 19(1), 87–93.

Sanchez-Perez J.M., Lucot E., Bariac T. and Trémolières M. (2008) : Water uptake by trees in a riparian hardwood forest (Rhine floodplain, France). Hydrological Processes 22 (3): 366–375.

110

Sanchez-Perez J.M., Lucot E., Bariac T. and Trémolières M. (2008) : Water uptake by trees in a riparian hardwood forest (Rhine floodplain, France). Hydrological Processes 22 (3): 366–375.

Sawyer AH. Cardenas MB. Bomar A. Mackey M. 2009. Impact of dam operations on hyporheic exchange in the riparian zone of a regulated river, Hydrol. Processes 23: 2129 - 2137.

Schmidt A., Santos R. I., Burnett C. W., Niencheski F., Knoller K. (2011). Groundwater sources in a permeable coastal barrier: Evidence from stable isotopes. Journal of Hydrology, 406: 66-72

Schürch M. and Vuataz F.D. (2000): Groundwater components in the alluvial aquifer of the Alpine Rhone River valley, Bois de Finges area, Wallis Canton, Switzerland. Hydrogeology Journal 8: 549-563.

SGU map service, http://vvv.sgu.se/sguMapViewer/web/sgu_MV_brunnar.html, accessed 2011- 09-06.

Shimada J., Kayane I., Shimano Y., Taniguchi M. 1993.Use of several environmental tracers to detect the surface-subsurface water interaction in an alluvial fan.Tracers in Hydrology, Proceedings of the Yokohama Symposium, publ.no.215.

SMHI, Svenskt Vattenarkiv, http://svarwebb.smhi.se, accessed 2011-09-06.

Sophocleous, M., 2002. Interactions between groundwater and surface water: the state of the science. Hydrogeol. J. 10 (1), 52–67.

Stallman S. 1965. Steady one-dimensional fluid flow in the semi-infinite porous medium with sinusoidal surface temperature. Journal of Geophysical Research 70(12): 2821–2827.

Stichler W., Maloszewski P., Bertleff B., Watzel R. 2008. Use of environmental isotopes to define the capture zone of a drinking water supply situated near a dredge lake. Journal of Hydrology J.362, 220-233 p. doi:10.1016/j.jhydrol.2008.08.024

Stichler W., Maloszewski P., Moser H.1985. Modelling of river water infiltration using oxygen-18 data. Journal of Hydrology J.83, 355-365 p.

Su, G. W., Jasperse, J., Seymour, D., &Constantz, J. (2004).Estimation of hydraulic conductivity in an alluvial system using temperatures. Ground Water, 42(6), 890-901. doi:10.1111/j.1745-6584.2004.t01-7-.x

111

Suliński J., 1981. Zarys klimatu, rzeźba terenu i stosunki wodne w Puszczy Niepołomickiej. (An outline of climate, land relief and water relations in Niepolomice Forest). Studia Ośrodka Dokumentacji Fizjograficznej 9, 25-69.

Svendsen JI, Alexanderson H, Astakhov VI et al. (2004) Late Quaternary ice sheet history of northern Eurasia. Quaternary Science Reviews 23: 1229–1271

Tikkanen M (2002) The changing landforms of Finland. Fennia 180 (1–2): 21–30.

Vitali, G., Moroni, G., 2010; Piano di Miglioramento Ambientale a Fini Faunistici, Quaderno delle opera e degli interventi “Tipo”; Provincia di Bergamo, Settore Caccia, Pesca e Sport

Vlahović, T., Bačani, A. and Posavec K. (2009): Hydrogeochemical stratification of the unconfined Samobor aquifer (Zagreb, Croatia), Environ. Geol. 57, 8; 1707-1722.

Vogt T., Hoehn E., Schneider P., Freund A., Schirmer M., Cirpka O.A. 2010. Fluctuations of electrical conductivity as a natural trace for bank filtration in a losing stream.Advances in water resources 33, 1296-1308.

Winter, T.C., Mallory, S.E., Allen, T.R. & Resenberry, D.O. (2000): The use of Principal component analysis for interpreting ground water hydrographs. Ground Water, Vol.38, No.2, p. 234-246.

Witczak S., Zuber Z., Kmiecik E., Kania J., Szczepańska J., Różański K., 2008, Tracer based study of the Badenian Bogucice Sands aquifer, Poland. [in] Edmunds W.M., Shand P. - Natural groundwater quality Oxford : Blackwell Publishing Ltd, cop. ISBN: 978-14051-5675-2; 335– 352

Woessner, W.W., 2000. Stream and fluvial plain ground water interactions: Rescaling hydrogeologic thought. Ground Water 38 (3), 423–429. www.savariver.com - Protection of Biodiversity of the Sava River Basin Floodplains (Life project)

Younger P. 2007. Groundwater in the environment: an introduction. Blackwell Publishing, UK.

Zuber A., Witczak S., Różański K., Śliwka I, Opoka M., Mochalski P., Kuc T., Karlikowska J., Kania J., Korczyński-Jackowicz M., Duliński M., 2005. Groundwater dating with H-3 and SF6 in relation to mixing patterns, transport modelling and hydrochemistry. Hydrological Processes, 19, 2247-2275.

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Appendix 1 Groundwater recharge models - basic approach: Piston flow model

Recharge models - basic approach

The main phenomenon governing interaction between surface and ground water is ground water recharge. It has usually been modelled using a discrete model of flow in aeration zone. If even the applied model is of the one-dimensional type (meaning actually a vertical cylinder), it may be seriously complex and difficult to use, just because of the spatial distribution of parameters. A large number of detailed data on infiltrating stream is needed by that complicated model. In case when only the general groundwater movement is to be considered, rather than the infiltration itself, the full model can be quite uneconomical to use

In this case a model which needs only a couple of most important data, but which would be simpler in use, is much more needed, if, however, it is able to describe a fully unsteady process. The above conditions are met by the piston model of infiltration (PM), now under development.

Fig A1-1 Schematics of water circulation in soil aerated zone.

Net precipitation computing

Net precipitation computing is usually done in a separate module (as a computer implementation). It is used for determining of how much of precipitation can infiltrate further into soil/ground. Simplified model is used in PM, using Turc equation [1]. For that model the following data is needed: mean sun radiation (from astronomical tables), mean local

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temperature, known local precipitation, type of vegetation (as for assessment evapotranspiration level) and rhisosferic width. These are readily-available data, model based on them can be used for further analysis using main module of PM. There is however a possibility of using the Penmann-Monteith evapotranspiration model [2], if all data for this model can be collected. (as for Turc equation, plus the following: Earth surface mean albedo, cloud cover, water vapour pressure, wind speed).

Evapotranspiration in dry soils can be greatly reduced (even the transpiration part can be entirely stopped), as plants stop do grow. That process begins when the suction height (meaning the height which must be cleared by water-conducting capillary vessels in the plant) equals to 7m. For 160m there is final cessation of breathing activity - last part of wilting point [3]. As the dry soils have high insulation properties (for heat and vapour transport) on surface level, direct evaporation can be ignored here, so evapotranspiration equals to transpiration (which, as stated above, can be close to zero).

Real evapotranspiration must then be calculated based on rhisisferic zone moisture, so moisture characteristics must be known - for current PM model it is based on Corey-Brooks [4] formula.

Net precipitation is therefore computed the following way: Potential evapotranspiration is determined based on actual precipitation data (from meteorological records). Then biota evapotranspiration is assessed (taking into account: rhisosferic width, dominant vegetation type, current vegetation season). Finally actual evapotranspiration is calculated (with above mentioned remarks).

Effective precipitation and infiltration determination using piston model

Modelling of moisture content changes can be based on classical piston model with a sharp wetting front of Green-ampt [5], and on the model of unsaturated infiltration and moisture redistribution formula of Morel-Seytoux [6].

Moisture content after the front passing is considered to be constant, not depending on duration of infiltration process and actual position of the front (therefore it can look like “a piston” of moisture – hence the name of the model). Process of moisture change is modelled in such a way that it can be described using a few basic parameters. Unavoidable distortion of the description of the process is not significant for the purpose of the model.

In PM model it is assumed that active capillary zone is completely saturated, and that passive zone has maximal moisture content. Residual moisture (meaning moisture between last vetting front and capillary zone) is constant in profile of aerated zone, but it can be changing in time, depending on recharge balance.

Infiltration is then calculated the following way: non-saturated infiltration (for maximum two wetting fronts, when hydraulic head = 1.0), then saturated but non-submerged infiltration (with hydraulic head determined by recharge) and finally submerged infiltration (with hydraulic head

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determined by height of submersion). For the latter maximum soil moisture holding capacity is considered, surface flow forms when it is exceeded.

Infiltration speed, and therefore recharge volume of deeper ground layers, can be restricted by decreasing hydraulic head (slowing of moisture movement) caused by shallow-lying ground water table. (it is “supported infiltration” as opposed to “free infiltration”). PM model can be used for both types of infiltration.

Precipitation events happen from time to time, but mostly (between those events) moisture content within soil is determined by moisture redistribution process. It allows for movement of existing wetting fronts near surface and concerns only the zone above first front. Redistribution effect appears only when recharge from precipitation falls below maximum moisture conductivity. In case when evapotranspiration is the only process moisture will be taken (using capillary suction) from deeper ground layers. Darcy-Buckingham formula is used to describe this:

dh d d v   k  s  k   D    k , d dz w dz for entire blocks with constant moisture content (humidity). Dw means here moisture diffusion coefficient. In PM moisture redistribution is calculated taking into account above mentioned “supported infiltration”.

Model use, field examples

PM can be used for GDE current state monitoring, as it allows for predicting of ground water recharge values, which are very important for that type of biota.

Overall functioning of GDE areas can be predicted, concerning periodic, seasonal and permanent climatic changes. Impact of human development (in form of surface cover changes and ground water table position) on GDE also can be addressed. That infiltration model can also be used for unsteady infiltration simulations for other models, concerning functioning of the entire ground water reservoir –including models build on MES principle.

All of above mentioned assumptions were used to build a computer model of ground water recharge for data collected for Wiercica river catchment area (sląskie voivodship on border with łodzkie in southern-central Poland.

Wiercica is a medium right-side tributary of river Warta). Hydrogeological data needed for modeling were taken from detailed research of that area done for local tape water distribution company (Wodociągi Częstochowskie). That research was a part of protection and rehabilitation effort for ground water reservoir, called GZWP 326. Meteorological data were from polish meteo authority – IMGW (albeit indirectly). Data concerning land cover and vegetation came partly from CORINE Land Cover 2000 Programme [7] and partly from other sources [8].

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There are a few requirements for a functioning water infiltration model.

Firstly it should be able to show the real mechanism of infiltration. Amount of infiltration should be computed in the time scale, at given intervals. All of the results shall be prepared in such a way that other models (concerning ground water bodies movement - for example) can use it, including its spatial distribution.

Secondly, all the developed models (including infiltration ones) must be prepared in such a way that the data needed for them (for calculations) can be easily obtained. It is especially important for models which are supposed to describe a larger area. Use of very advanced methods may be greatly hampered by lack of suitable data for their actual operation. If there is no other choice simplified models for some parts may be considered (like substituting a simplified Turc evapotranspiration model instead of the full model in PM).

Models should be easy for practical use and their results must be as straight forward as possible. It is not an easy task, as it must not lose the actual physics of the process.

For the Piston Model of unsteady infiltration the following data are required:

Soil parameters: - filtration coefficient - conductivity exponent (as for Irmay-Awierjanov) - porosity coefficient - residual moisture - capillary height - aerated zone depth - type and state of vegetation coefficient (as for Turc equation)

Precipitation diagram (hydrogram) parameters: - time interval - initial precipitation - duration of analysis

In addition detailed precipitation data is required, that is: time and intensity of precipitation event (in mm), temperature at that moment, mean solar radiation (for evapotranspiration calculations).

The results are: net amount of water infiltrating into the saturated zone, soil layer (layers) cross- section diagrams with moisture and vetting fronts.

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As for now land use and vegetation characteristics (for evapotranspiration calculation) are described by one coefficient ("type and state of vegetation"). Works are underway to do it in a more comprehensive way.

What do we expect in the future?

In the near future we shall finish refining the model internal structure ("supported infiltration"). Evapotranspiration module (in the computer implementation) should be able to receive data directly from other models (for example based on Penmann-Monteith standard model). We will start work on using the already developed model on a wider area, thus trying to build a quasi-2D approach.

References:

[1] Turc, L Estimation of irrigation water requirements, potential evapotranspiration: a simple climatic formula evolved up to date Ann. Agron, 12, 13-49, 1961

[2] Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. (1998). Crop Evapotranspiration— Guidelines for Computing Crop Water Requirements. FAO Irrigation and drainage paper 56. Rome, Italy: Food and Agriculture Organization of the United Nations.

[3] Kowalik p, Eckersen h, Water transfer from soil through plants to the atmosphere in willow energy forest Ecol. Model. Vol. 26, pp251-284

[4] R.H. Brooks and A.T. Corey (1964). "Hydraulic properties of porous media". Hydrological Papers (Colorado State University).

[5] Green, W.H. & Ampt, G.A. (1911) Studies on soil physics, 1.The flow of air and water through soils. J. Agric. Sci. 4, 1-24.

[6] Morel-Seytoux, H.J. (1984) Some recent developments in physically based rainfall- runoff modeling; Frontiers in Hydrology; Water Resources Publications: Littleton/Colorado.

[7] European Environment Agency – Corine Land cover data – version 15

[8] Jan Marek Matuszkiewicz / Potential natural vegetation of Poland; IGIPZ PAN: Warszawa 2008

[9] Potencjalna roślinność naturalna; Internetowy Atlas Polski; Pracownia Kartografii i GIS IGIPZ PAN

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Appendix 2 Surface water models Surface water models have two different components, a hydrodynamic component where the transport due to flow and turbulence is handled and a kinetic component where the biogeochemical reactions and the ecological behaviour are handled. The transport processes are very dynamic and should be represented in a temporal resolution of seconds to minutes, where kinetic processes are much slower and can be represented on the order of hours. Several surface water models available nowadays have either a transport component or both components. In this section some examples of surface water models that have both components were described.

Surface Water Models for Rivers and Streams QUAL2E/QUAL2E-UNCAS QUAL2E is a steady stream water quality model developed by United States Environmental Protection Agency. It is not supported anymore; however it is the “ancestor” of many stream water quality models such as QUAL2K, HEC-RAS Water Quality Components or SWAT Stream Water Quality sub model. Therefore it is worth to be described in this section.QUAL2E and QUAL2-UNCAS are very well known generally purposed water quality models applied to many streams of the world so that their reliabilities are approved. QUAL2E-UNCAS was designed to perform uncertainty analysis. QUAL2E uses a simplified representation on stream hydraulics and solved one dimensional advection diffusion reaction equation to simulate transport and conversion of water quality constituents. The model discretizes the stream into computational elements, which represent completely mixed reactors that exchange material through advection and dispersion (Fig A2-1). The state variables and their kinetic relations are shown in Fig A2-2.

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Fig A2-1 Model network of QUAL2E (Brown and Barnwell, 1987)

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Fig A2-2 QUAL2E Kinetics Even though not supported by USEPA anymore, the source code can still be found on the Internet so that integration of QUAL2E to more comprehensive multimedia watershed models is possible so that it could be a component of a modelling framework dealing with groundwater dependent ecosystems. QUAL2K QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987). QUAL2K is similar to QUAL2E in the following respects: It is one dimensional along the stream channel. The channel is well-mixed vertically and laterally. Steady state hydraulics with non-uniform, flow is simulated. The heat budget and temperature are simulated as a function of meteorology on a diurnal time scale. All water quality variables are simulated on a diurnal time scale. Point and non-point loads and abstractions are simulated. QUAL2K has a more comprehensive representation of surface water quality than QUAL2E. The enhancements are listed below:

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- Carbonaceous BOD speciation: Q2K uses two forms of carbonaceous BOD to represent organic carbon. These forms are a slowly oxidizing form (slow CBOD) and a rapidly oxidizing form (fast CBOD). In addition, non-living particulate organic matter (detritus) is simulated. This detrital material is composed of particulate carbon, nitrogen and phosphorus in a fixed stoichiometry.

- Anoxia: Q2K accommodates anoxia by reducing oxidation reactions to zero at low oxygen levels. In addition, denitrification is modelled as a first-order reaction that becomes pronounced at low oxygen concentrations.

- Sediment-water interactions: Sediment-water fluxes of dissolved oxygen and nutrients are simulated internally rather than being prescribed. That is, oxygen (SOD) and nutrient fluxes are simulated as a function of settling particulate organic matter, reactions within the sediments, and the concentrations of soluble forms in the overlying waters.

- Bottom algae: The model explicitly simulates attached bottom algae.

- Light extinction. Light extinction is calculated as a function of algae, detritus and inorganic solids.

- pH: Both alkalinity and total inorganic carbon are simulated. The river's pH is then simulated based on these two quantities.

- Pathogens: A generic pathogen is simulated. Pathogen removal is determined as a function of temperature, light, and settling.

The state variables of QUAL2K are given in Table A2-1

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Table A2-1 State variables of QUAL2K.

Variable Symbol Units*

Conductivity s mhos

Inorganic suspended solids mi mgD/L

Dissolved oxygen o mgO2/L

Slowly reacting CBOD cs mgO2/L

Fast reacting CBOD cf mgO2/L

Organic nitrogen no gN/L

Ammonia nitrogen na gN/L

Nitrate nitrogen nn gN/L

Organic phosphorus po gP/L

Inorganic phosphorus pi gP/L

Phytoplankton ap gA/L

Phytoplankton nitrogen INp gN/L

Phytoplankton phosphorus IPp gP/L

Detritus mo mgD/L Pathogen X cfu/100 mL

Alkalinity Alk mgCaCO3/L

Total inorganic carbon cT mole/L

2 Bottom algae biomass ab mgA/m

2 Bottom algae nitrogen INb mgN/m

2 Bottom algae phosphorus IPb mgP/m Constituent I

Constituent ii

Constituent iii

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Fig A2-3 illustrates the mass balance around any computational element. The model kinetics is illustrated in Fig A2-4 whereas the state variables and processes subjected to sediment diagnosis are illustrated in Fig A2-5.

atmospheric transfer mass load mass withdrawal

inflow outflow i dispersion dispersion

bottom algae sediments

Fig A2-3 Mass balance for a QUAL2K segment.

rda ds h cT o m rod cs cf o c cf sod s ox se ox T X o s o s cT m n dn i r h s Alk na no na nn s se se

cT d p o u h IN rpa a p p o i u IP s s s se r o e e c T Fig A2-4 QUAL2K Kinetics. Kinetic processes: dissolution (ds), hydrolysis (h), oxidation (ox), nitrification (n), denitrification (dn), photosynthesis (p), respiration (r), excretion (e), death (d), respiration/excretion (rx). Mass transfer processes are reaeration (re), settling (s), sediment oxygen demand (SOD), sediment exchange (se), and sediment inorganic carbon flux (cf)

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Jpom cf o na o nn pi WATER

CH4 CO2 NH4p NH4d NO3 N2 PO4p PO4d AEROBIC

CH (gas) POC 4

PON NH4p NH4d NO3 N2 ANAEROBIC POP PO4p PO4d

DIAGENESIS METHANE AMMONIUM NITRATE PHOSPHATE

Fig A2-5 Sediment oxygen demand and diagenesis in QUAL2K.

The state variables and processes, especially incorporation of sediment cycles makes QUAL2K a good template water quality model for groundwater dependent streams. QUAL2K is implemented within the Microsoft Windows. It is programmed in the Windows macro language: Visual Basic for Applications (VBA). Excel is used as the graphical user interface. The model itself is written in Fortran, but the source code is not supplied. However, the core of the model uses text based input and produces text based output so that using it as a steady state river water quality engine in larger modelling problems by input output level coupling is possible.

EPD-RIV1 EPD-RIV1 is a system of programs to perform one-dimensional dynamic hydraulic and water quality simulations. The computational model is based upon the CE-QUAL-RIV1 model developed by the U.S. Army Engineers Waterways Experiment Station (WES). This modelling system was developed for the Georgia Environmental Protection Division of the Georgia Department of Natural Resources and the U.S. Environmental Protection Agency.

EPD-RIV1 is a one-dimensional (cross-sectionally averaged) hydrodynamic and water quality model. It consists of two parts, a hydrodynamic code which is typically applied first, and a quality code. The hydraulic information, produced from application of the hydrodynamic model, is saved to a file which is read by, and provides transport information to, the quality code when performing water quality simulations.

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The water quality code can simulate the interactions of 16 state variables (Fig A2-6), including water temperature, nitrogen species (or nitrogenous biochemical oxygen demand), phosphorus species, dissolved oxygen, carbonaceous oxygen demand (two types), algae, iron, manganese, coliform bacteria and two arbitrary constituents. In addition, the model can simulate the impacts of macrophytes on dissolved oxygen and nutrient cycling.

Fig A2-6 State variables and processes of EPD-RIV1 model.

EPD-RIV1 is equipped with a graphical user interface, pre-processor and postprocessor, however the hydrodynamic and water quality computation engines are found as separate exe files and they accept text based input data, so that coupling EPD-RIV1 with other models on input/output level is easy and straightforward. If a source level coupling is required, the user can still use CE- QUAL-RIV1, which is open source and slightly different from EPD-RIV1 only.

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Surface Water Models for Lakes, Reservoirs and Estuaries

WQRRS (HEC, 1978) It is a one dimensional dynamic model which calculates the temporal variations of state variables in vertical dimension (z) for reservoirs and horizontal dimension (x) for rivers. WQRRS is an acronym for Water Quality for River and Reservoir Systems, and was created by U.S. Army Corps of Engineers (USACE), Hydraulic Engineering Centre (HEC). The model is intended to simulate the effects of reservoir systems on river-reservoir systems. Yet, process kinetics and water quality state variables covered in the WQRRS makes it also useful for ecosystem modelling in lagoons. In addition to the many water quality state variables; phytoplankton, zooplankton, fish, and benthic organisms can be simulated by the model. The reservoir module is a horizontally well mixed and vertically layered one dimensional transport and aquatic ecology model (Fig A2-7, Fig A2-8 and Fig A2-9).

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Fig A2-7 Model domain of WQRRS Reservoir Module.

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Fig A2-8 Transport as considered by WQRRS Reservoir Module.

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Fig A2-9 State variables and processes considered in WQRRS.

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The river module is a one dimensional stream ecology model that has additional state variables dealing with aquatic invertebrates. The model network and computational elements are similar to the structures in QUAL2E; however WQRRS River module is a fully dynamic model with more advanced capabilities. The stream hydrodynamics are simulated using 6 different options, from simple backwater computations for steady flows to the solution of the full St. Vernands equations with all nonlinear terms.

WQRRS was coded with FORTRAN IV which usually runs on relatively old computer systems. The last known port of WQRRS to PC’s was conducted in early 1990’s and the executables have incompatibility problems with modern operating systems such as 64 bit ones. The executables use/create text based input and output files so that they can be coupled with other watershed/groundwater modelling software on input/output level. At least for reservoir module there is an alternative solution if source code level coupling is required. EGOLEM is a modification of WQRRS. Gönenç et al. (1990) rearranged the reservoir module of original WQRRS designed for old main frame computes to enable it running on IBM-PC compatible systems. No alteration has been made in the process kinetics and other module properties of the original model, and it was used successfully in water quality simulation of Küçükçekmece Lagoon (Gonenc et al., 1997). Source code is still available.

CE-QUAL-R1 (Environmental Laboratory, 1995) It is a modification of WQRRS Reservoir model by U.S. Army Corps of Engineers (USACE), Waterways Experiment Station (WES), so that it can also simulate iron and manganese, and as well as anaerobic conditions. The transport is handled similar to WQRRS Reservoir module (Fig A2-7 and Figure A2-8), however the aquatic kinetics have been enhanced (Fig A2-10). As seen in Figure x.11 the model has two components, one for simulating transport and temperature and another one for simulating reservoir water quality and ecology.

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Fig A2-11 State variables of CE-QUAL-R1

CE-QUAL-R1 provides a very good template as an aquatic ecology template for groundwater dependent ecosystems. It is free, however only part of the source code that is dealing with transport and temperature simulations (CE-THERM-R1) are open. The last executables of the full model developed for MS-DOS and do not correctly run on modern operating systems. However using a virtualization environment such as DOS-BOX it is possible to couple CE- QUAL-R1 with other modelling software such as groundwater modelling software on input/output level.

CE-QUAL-W2 It is a two-dimensional model which does both hydrodynamic and water quality simulations in longitudinal and vertical dimensions (x, z). It is suitable for applications in rivers (also large rivers), reservoirs and estuaries. Water quality state variables constituted in the model are temperature, salinity, dissolved oxygen, CBOD, organic material composed of carbon, nitrogen,

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and phosphorus (dissolved and labile, dissolved and refractory, particulate and labile, particulate and refractory), ammonia nitrogen, nitrate nitrogen, phosphorus, dissolved and particulate silica, multiple groups of phytoplankton, epiphytes and zooplankton (Fig A2-12).

Fig A2-12 State variables of CE-QUAL-W2.

LDOM : Labile dissolved organic matter LPOM : Labile particulate organic matter RDOM : Refractory dissolved organic matter RPOM : Refractory particulate organic matter CBOD : Carbonaceous biochemical oxygen demand

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It was developed by Portland University and Supported by U.S. Army Corps of Engineers, and latest version of the model is CE-QUAL-W2 3.7 with open source code. One drawback of the model is that sediment processes are not touched upon adequately, yet it has been claimed by the developers that new versions of the software will be simulating sediment process in more detail.

CE-QUAL-ICM (Cerco and Cole, 1994; Cerco and Cole, 1995) This model is capable of simulating sediment processes in detail, and was developed by U.S. Army Corps of Engineers (USACE). However, it only includes water quality code and to run the model outputs of CH3D hydrodynamic model (or compatible outputs from another model), are necessary. The model is mainly designed and optimized for estuaries and coastal ecosystems. Together with the CH3D, CE-QUAL-ICM can make water quality simulations in three spatial dimensions. The state variables and their relations are illustrated in Fig A2-13.

Fig A2-13 State variables and their relations in CE-QUAL-ICM.

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A copy of the software and the source code can be obtained by contacting the developers. CE- QUAL-ICM is written in FORTRAN 77 and uses text based input and output so that coupling it with other models is easy and straightforward.

Surface Water Models for General Application

WASP (Water Quality Analysis Simulation Program) WASP is a well known dynamic water quality/water ecology model. It has been developed for three decades and is supported and distributed by USEPA. WASP is a general purposed water quality/ecology model applicable to streams, lakes, estuaries and the coastal ocean. As shown in Fig A2-14, it is a so called “box model” based on integrated finite differences methods, where the control volumes (model segments) and their water exchanges (links) are defined in the model domain.

Fig A2-14 WASP model network.

WASP has a simplified hydrodynamic transport modelling capabilities more suitable to model shallow and vertically well mixed channel networks; however it has a generalized hydrodynamic interface that allows easy one-way linking of results from more sophisticated other multi dimensional hydrodynamics models that can represent large lakes, estuaries and coastal ecosystems. WASP has several modules: EUTRO (for simplified eutrophication analysis),

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Advanced eutrophication module, HEAT (for temperature, suspended solids with simplified bacteria simulation capabilities), TOXI (for toxic organic chemicals, but no ecological interaction with organisms) and Mercury (a modified version of TOXI optimized for mercury cycle).

These modules are not coupled to each other and run separately. For example, one cannot run Advanced Eutrophication Module together with TOXI and simulate the inhibition effects of toxic chemicals on primary production. However the modules can be run sequentially and the results from one module can be directly imported by the next module. An example is to import the temperature results produced by the HEAT module into the EUTRO module.

The water column variables and processes in the Advanced Eutrophication Module is illustrated in Fig A2-15. The Advanced Eutrophication Module allows interaction between surface water quality and sediment diagenesis processes as well (Fig A2-16).

photosynthesis and respiration atmosphere

Periphyton Biomass Phytoplankton Biomass IP Group 3 D : C : N : P : Chl D : C : N : PGroup : Si: Chl 2 DO

IN D : C : N : GroupP : Si: Chl 1 oxidation

D : C : N : P : Si : Chl nitrification death TIC Particulate Detrital OM - 2- uptake H2CO3 – HCO3 – CO3 excretion D C N P Si excretion

Total dissolution Inorganic Nutrients pH Alkalinity

Dissolved OM SiO2 PO4 NH4 NO3

CBOD1 Si sorption Inorganic Solids CBOD2 P mineralization S1 S2 S3 oxidation CBOD3 N

Fig A2-15 State variables and processes in the water column.

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Particulate Dissolved Organic Matter Constituent

Net

WaterWaterColumnColumn WaterColumn Surface Settling Exchange

Reactions

Products Particulate Dissolved

LayerLayer1 1 Layer1 Reaction Products

Mixing Sedimentation Diffusion

G1 Reactions Diagenesis Particulate Dissolved

G2 Reaction Products

LayerLayerLayer2 2 2

Products G3 Sedimentation

Sedimentation Fig A2-16 Water column and sediment interaction incorporated in the WASP Advanced Eutrophication Module.

TOXI module contains a detailed representation of the following chemical processes: Hydrolysis, Ionization, Oxidation, Volatilization, Photolysis and Biodegradation As illustrated in fig A2-17. TOXI can simulate the reactions of three chemicals among each other in many combinations.

WASP is a windows based application. It is free but not completely open source. Even though it is a GUI based computer application, WASP still allows text based input and output so it can be coupled with other models such as surface runoff or multi species ground water transport models easily. This is an important advantage. Another advantage is that it is a very well known model and has been applied to many aquatic ecosystems. WASP has a limited representation of aquatic ecology that does not reach beyond primary production. Effect of zooplankton on phytoplankton can be included as a forcing function, however other effects of zooplankton such as grazing on detritus is not considered. Ecological processes are not coupled with water quality especially if toxic chemicals are of concern. Another disadvantage is that the model segments are not allowed to dry which jeopardizes the application of WASP on geographical compartments such as ephermal rivers or wetlands that are examples for groundwater dependent ecosystems.

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Fig A2-17 Reactions in TOXI

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AQUATOX AQUATOX assess dynamic effects of various stressors such as temperature, toxic chemicals, nutrients, sediment; which is applied to aquatic environments from experimental tanks to lake systems. AQUATOX known as a process based model, since it simulates the transfer of biomass, chemicals and energy from one compartment to another in an ecosystem by simultaneously computing the daily chemical and biological processes. Process-based models are not based on statistical relationships, opposed to that empirical models could establish that correlation between the existing variables, but do not explain the reasons or the mechanism of the relationship (Park & Clough, 2009). Moreover, AQUATOX also predicts both direct and indirect effects of chemicals in the aquatic ecosystems to the resident organisms, besides their environmental fate. The model fills the gap between chemical water quality and biological reaction and provides a better understanding by linking them together (Park & Clough, 2009). AQUATOX outclasses many other models by its capability of multi-compartment ecosystem modelling, while others can provide few biological compartments. It also includes plants, invertebrates and fish, and expresses their physical and chemical interaction with the ecosystem (Park & Clough, 2009). State variables of AQUATOX are listed below: - Phytoplankton (multiple species) - Periphyton and submerged aquatic vegetation (multi species) - Planktonic and benthic invertebrates (multi species) - Zooplankton, zoobenthos and fish (multi species) - Forage, game, and bottom fish - Nutrients and dissolved oxygen - Organic and inorganic sediments - Toxic organic chemicals (up to 20 different chemicals simultaneously) - Perfloroalkylated Surfactants (bioaccumulation only)

Due to the fact that AQUATOX is a process-based model, it predicts the environmental fate and ecological effects of the various environmental stressors by simulating various numbers of biological and ecological processes which are the actual links between the system components, the organisms. The main biological processes and processes environmental fate by different processes are listed below: - Photosynthesis and respiration - Food consumption - Growth and reproduction - Natural mortality - Lethal and sublethal toxicity from organic toxicants, ammonia and low dissolved oxygen - Trophic interactions - Changes in biological communities under changing environmental conditions - Sloughing of periphyton due to high stream velocity - Smothering of benthic organisms by suspended and bedded sediments - Nutrient cycling and oxygen dynamics - Release of phosphorus from anaerobic sediments and sediment diagenesis

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- Calcite precipitation and removal of phosphorus under alkaline conditions - Partitioning of organic toxicants to water, biota and sediments - Toxic organic chemical transformations - Bioaccumulation through gills and diet

The structure of the model makes it very valuable if ecological effects of external forces are to be quantified for an aquatic ecosystem. Therefore it is a good template for an aquatic ecology component of a modelling framework for groundwater dependent ecosystems. Moreover its source code is open. The only disadvantage of the model is that it is more suited for shallow water bodies and it provides an oversimplified representation of vertical stratification for deeper ones. This disadvantage is a minor one for GENESIS project, since most of the groundwater dependent ecosystems are shallow.

References Brown, C.L., Barnwell, T.O. 1987. The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual, US Environmental Protection Agency, Environmental Research Laboratory, Athens Georgia, EPA/600/3-87/007. Cerco, C.F., Cole, T. 1994. Three Dimensional Eutrophication Model of Chesapeake Bay; Volume 1, Main Report, Technical Report EL 94-4, U.S. Army Corps of Engineers Waterways Experiment Station, Vicksburg, MS. Chapra, S.C. 1997. Surface Water-Quality Modelling, WCB/ McGraw-Hill, United States of America. Cerco, C.F., Cole, T. 1995. User’s Guide to the CE-QUAL-ICM Three Dimensional Eutrophication Model, Release Version 1.0, Technical Report EL-95-15, US Army Corps of Engineers Waterways Experiment Station, Vicksburg, MS. Environmental Laboratory CE-QUAL-R1 1995. A Numerical One Dimensional Model of Reservoir Water Quality; User’s Manual, Instruction Report E-82-1, Rev. Ed., US Army Engineer Waterways Experiment Station, Vicksburg, MS. Gönenç, İ.E., Baykal, B.B., Çakır, A., Bederli, A., Kabdaşlı, N.I. 1990. A model for Water Quality Management in Lakes -EGOLEM, II. Proceedings of hr Symposium for Computer Applications in Civil Engineering, (in Turkish). HEC 1978. Generalized Computer Program, Water Quality for River-Reservoir Systems, The Hydrologic Engineering Center, United States Army Corps of Engineers. Park, R. A., & Clough, J. S. (2009). AQUATOX (Release 3) Technical Documentation (Vol. Volume 2). Washington DC: USEPA Office of Water Office of Science and Technology.

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