THE SUBARNAREKHA RIVER BASIN, (EAST SINGHBHUM DISTRICT Jharkhand State

P H Négrel
email: p.negrel@brgm.fr

B Lemière
email: b.lemiere@brgm.fr

H Machard De Grammont

P Billaud
email: p.billaud@brgm.fr

B Sengupta

HYDROGEOCHEMICAL PROCESSES, MIXING AND ISOTOPE TRACING IN HARD ROCK AQUIFERS AND SURFACE WATERS FROM

Keywords: hydrochemistry, fracture type aquifer, strontium isotopes, weathering, stable isotopes

The chemical and isotopic compositions of river and groundwater reflect the different natural processes that provide chemical elements to the dissolved load, i.e. mainly the weathering of rocks and soils, atmospheric inputs and anthropogenic disturbances.

This study reports on the geochemistry of surface-and groundwater along a part of the Subarnarekha River system (north-eastern India) collected during monsoon and dry season, during a monitoring program aimed at evaluating impacts of mining and metallurgy on the river system.

The aquifer is of fracture type and the seasonal behaviour, groundwater flow conditions and pollutant transfer were observed through a network of 69 wells with typical depths of 50 meters.

Geochemical observations, including major cations and anions, trace element concentrations and isotopic tracing (stable isotopes of the water molecule, strontium isotopes) come to conclusions on the origin and the relationships between the surface-and groundwater in the studied catchment.

A large range of salinities is observed in surface-and groundwater, both for dry or wet periods.

Surface water samples plot within the field HCO 3 -Ca during both water stages. Most groundwater samples plot within the field of Ca-SO 4 water type and HCO 3 -Ca water type. This reflects the high Ca input in groundwater, other than weathering. Such inputs could be related to (i) carbonate amendments used in agricultural practices and (ii) residues from ore processing.

With regards to stable isotopes  18 O and  2 H, many groundwater samples plot between local meteoric water lines and the global meteoric water line, reflecting a meteoric origin for the water without any major transformation like evaporation. This suggests that transfer from rainfall towards groundwater storage through soils and the non-saturated zone is fast. The scatter of 87 Sr/ 86 Sr signatures in surface-and groundwater cannot be explained by less than 3 end-member compositions. The most dilute end-member should be compatible with rainwater inputs. The most mineralised end-member has isotopic compositions very similar to the dilute one, and is believed to represent anthropogenic inputs. The third end-member is characterised by an intermediate Sr content and a more radiogenic signature. It is believed to be controlled by a natural background, however affected by human activities (e.g. drainage of mine waste).

Potential flow paths were investigated north of the area. Under the light of different geochemical tools, all groundwater types in this area seem to evolve more as in close pockets than along a flow path. This is consistent with groundwater head contour maps that do not reflect any groundwater flow directions, as groundwater bodies evolve in discontinuous or isolated units.

The limited extent of transfer and the predominance of natural phenomena contribute to explain the moderate level of groundwater contamination and the characteristics of surface water contamination by mining and metallurgy.

Introduction

The chemical and isotopic compositions of waters reflect the different natural processes that provide chemical elements to the dissolved load, i.e. mainly the weathering of rocks and soils, atmospheric inputs and anthropogenic disturbances [START_REF] Drever | The Geochemistry of Natural Waters[END_REF]. Detailed studies focused on the exogenic cycle of the elements were carried out on large-to medium-size river systems, including the Amazon, the Congo, the Ganga-Brahmaputra, the Indus, the Huanghe… [START_REF] Sarin | Major ion chemistry of the Ganga-Brahmaputra river system: weathering processes and fluxes to the Bay of Bengal[END_REF][START_REF] Ph | Erosion sources determined from inversion of major, trace element ratios and strontium isotopic ratio in riverwater: the Congo Basin case[END_REF][START_REF] Pande | The Indus river system (India-Pakistan): major ion chemistry, uranium and strontium isotopes[END_REF][START_REF] Gaillardet | Chemical and physical denudation in the Amazon river basin[END_REF][START_REF] Zhang | Drainage basin weathering and major element transport of two large Chinese rivers (Huanghe and Changjiang)[END_REF]. For small catchments, the application of geochemical tools may provide constraints on runoff, on the natural and anthropogenic end-members and on their respective contributions (Ben Othmann et al., 1997;[START_REF] Ph | Natural and anthropogenic budgets of a small watershed in the Massif Central (France): chemical and strontium isotopic characterization in water and sediments[END_REF],

In India, as in other fast developing countries, groundwater use for domestic, industrial and agricultural activities is fast growing. For example, the number of dug wells increased from around 4 up to 10 millions between 1952 and 1992 [START_REF] Ballukraya | Over exploitation and artificial recharge of Hard Rock aquifers of South India: issues and options[END_REF]. Ground water resource use needs to be concerted. The concept of sustainable use is quantitatively related to such factors as the volume of the existing resource, its recharge and environmental impacts. From the quality point of view, sustainability implies the prevention of deterioration of ground water quality beyond acceptable limits.

Groundwater flow and storage in hard rock areas has always been a major issue for both researchers and water managers [START_REF] Silva | Optimising the dimensions of agrowells in hard-rock aquifers in Sri Lanka[END_REF][START_REF] Krishnamurthy | Groundwater resources development in hard rock terrain -an approach using remote sensing and GIS techniques[END_REF][START_REF] Ballukraya | Over exploitation and artificial recharge of Hard Rock aquifers of South India: issues and options[END_REF] either with regards to water quantity [START_REF] Gupta | Flow regime associated with partially penetrating large-diameter wells in hard rocks[END_REF], water quality [START_REF] Robins | Hydrogeology and hydrogeochemistry of a small, hard-rock islandthe heavily stressed aquifer of Jersey[END_REF] as well as delimitation of resources and aquifers [START_REF] Singhal | Integrated approach to aquifer delineation in hard rock terrains -A case study from the Banda District, India[END_REF] and long-term sustainability [START_REF] Foster | Groundwater in rural development: facing the challenges of supply and resource sustainability[END_REF]. Pumping affects groundwater quality through salinity increase and heavy metal contamination, [START_REF] Kamra | Effect of pumping on temporal changes in groundwater quality[END_REF][START_REF] Singh | Hydrogeochemical exploration for unconformity-related uranium mineralization: example from Palnadu sub-basin, Cuddapah Basin, Andhra Pradesh, India[END_REF].

These issues are more complex in hard rocks terranes due to strong heterogeneity and anisotropy, with irregular distribution of pathways of groundwater flow.

-Groundwater accounts for over 80 per cent of the domestic water supply (…) and 50 per cent of irrigation requirements‖ [START_REF] Morris | Groundwater and its Susceptibility to Degradation: A Global Assessment of the Problem and Options for Management[END_REF]; -in weathered and fractured aquifers throughout India, shallow groundwater is widely used for small-scale irrigation and village potable supplies. Increasing abstraction from these low storage aquifers has resulted in severe seasonal water shortages in some areas.‖ (ibid). This paper uses geochemistry and isotope tracing to determine groundwater characteristics in a copper-mining region located in northeastern India. Data were collected in a larger surface and groundwater as well as soil and sediment monitoring program in the vicinity of mining and metallurgical industries along with extensive agricultural use of land [START_REF] Billaud | Impact assessment of mining activities in the Subarnarekha Basin[END_REF]. This paper investigates the recent hydrogeological and hydrogeochemical conditions of the site through the isotopic composition of strontium and oxygen and hydrogen in different groundwater types collected from a network of wells. Strontium isotope ratios are used to trace the degree of water-rock interaction and mixing processes in groundwater [START_REF] Ph | Strontium isotope systematics used to decipher the origin of groundwaters sampled from granitoids: the Vienne case (France)[END_REF][START_REF] Ph | Interaction between different groundwaters in Brittany catchments (France): characterizing multiple sources through strontium-and sulphur isotope tracing[END_REF] while stable isotopes provide an insight of the water origin [START_REF] Ph | Geochemistry of the Maroni River (French Guyana) during low water stage: Implications for water rock interaction and groundwater characteristics[END_REF].

General features of the catchment

The Subarnarekha river basin is located in north-eastern India, rising in southern Bihar state (Figure 1). The Subarnarekha river flows eastwards through the Singhbhum copper mining region. Continuing eastwards, it enters the Bay of Bengal after a 470-kilometre course.

The selected area is about 17 km long on 7 km wide, along the Subarnarekha River, with a mean altitude of 90 m. It is located around 40 km south-east of Jamshedpur (East Singhbhum district, Jharkhand state). It is underlain by folded and fractured Precambrian metasediments, mainly mica schists, locally with quartzite and hornblende schists [START_REF] Ghosh | Tectonic deformation of soft-sediment convolute folds[END_REF] and show dominant vertical fracturation (Fig. 1). Mineral resources, mainly copper (Cu) but also uranium (U), are associated with a Precambrian shear zone.

Three zones can be individualised:

-the southwesternmost zone is a hilly area belonging to the Singhbhum belt, reaching an altitude of 450 to 500 m. This area is covered by a fairly dense forest with scattered small settlements in the valleys and little paddy fields close to the settlements; -the area comprised between the bottom of the hills and the Subarnarekha River on its right bank is a 17 km long and 1.5 km to 3.5 km wide stripe. This area is almost flat with paddy fields, small forested areas, barren land on rock outcrops, and with important settlements in relation with the Cu or U mining sites; -the left bank of the Subarnarekha River is similar to the right bank, but it does not bear any mining activity. The Cu smelter was built close to the main agglomeration of the area (Ghatsila).

Only fissured aquifers were identified. Frequent quartzite outcrops in the river bed itself imply that alluvial formations are discontinuous and cannot host continuous alluvial aquifers.

Total annual rainfall is nearly 1300 mm, with around 300 mm per month during the monsoon season between mid-June and mid-SeptemberThe, and 50 mm per month between mid-September and mid-June. The temperature varies between 7°C and 36°C in winter and between 22°C and 45°C in summer. The Subarnarekha River discharge has a steep increase in response to monsoon rains (level up by 2 to 3 meters). This is enhanced because the upper catchment dams are cleared at the beginning of rains for safety.

However, monsoon rains do not cause an immediate increase in the tributaries (hereafter referred to as nallahs) flow rates, early precipitation being collected and stored in the paddy fields, or recharging the shallow aquifers.

Groundwater occurs under unconfined condition in the hard rock areas of the district. The potential aquifers comprise two units with thick weathered residuum and underlying fractured hard rock up to a depth of at least 100 m. Altered formations above metamorphic rocks usually behave as a seasonal water reservoir from which water is percolating to the fissured rock aquifer below. Areas with a thick alteration cover have better potential for groundwater than areas with exposed rock outcrops.

The altered layer is rather thin in the study area (usually less than 7 meters). Nevertheless, a large number of open dug-wells exist almost everywhere in the valley, with a typical depth of about 10 meters, with a few meters inside the fractured rock. Small diameter tube wells are also very frequent, with a typical depth of about 50 meters and usually equipped with Indian-type hand-pumps. This large number of wells shows that the area probably has a well-distributed fracturation network. However no lithological logs were available, and therefore no indication on the depth of the alteration, or on the depth of fracturation below. Water depletion in a well seems to affect little the level of the neighbouring ones, suggesting a poor interconnection of aquifers. Direct and roughly immediate correlation between rainfall events and groundwater raising is observed.

Isopotential curves drawn from monthly measurements [START_REF] Billaud | Impact assessment of mining activities in the Subarnarekha Basin[END_REF] show that there is a complete recovery of the water table from one year to the other. The global water abstraction in the monitored wells, mainly for domestic uses, is not important compared to the aquifer recharge through precipitation. Annual rainfall is therefore sufficient to replenish the fissured aquifer with any excess discharging through the surface runoff network.

On the hill slopes, rice fields spreading over large areas are favourable features for the recharge of the fissured aquifer during the monsoon and the irrigation periods.

Groundwater is used mostly for domestic uses (drinking, washing, gardening), and for very limited industrial uses. Smelting and mining activities use surface water (mainly river water).

Geochemical sampling procedures and analytical methods

Sampling strategy

Surface water samples were collected from the river at two sites upstream and downstream of the study area, e.g. Subarnarekha Barrage and Subarnarekha Kanas. Small or medium-sized tributaries (nallahs) were also sampled over the study area and include Nallah Dhutra, Garra Nallah Barrage, Nallah Royam and Sankh Nallah. One sample was collected from a wastewater canal.

Groundwater samples were collected from tube wells used for drinking (plus one dug well). Sampling strategy was to take groundwater samples from the most used tube well in each village. This allows picking up water from a well renewed resource. Groundwater data will be grouped for detailed examination, based on the location of the wells on the right or left bank of the Subarnarekha River. This presentation is intended to highlight the possible effects of the mining activity, which is localised only on the right bank of the Subarnarekha River. The left bank is geologically similar but without any mining activity.

Sampling was carried out two times, during a low water stage in February 2001 and during a higher water stage in November 2001 (Figure 1).

Sampling procedure and field measurements

Master variables of each sample were measured on site, results are presented in Table 1.

Electrical conductivity (EC) and water temperature were measured using a WTW conductivity meter standardised to 25°C. EC data in the water samples collected during the low water stage are scattered between low EC values (115 µS/cm) and higher ones (~1400 µS/cm). The pH was measured on site using a WTW pH-meter calibrated using standard buffers, groundwaters display pH in the range 5.60-7.25, higher values are observed in surface waters (range 7.40-9.10) All water samples were collected in polyethylene bottles and filtered through precleaned 0.45µm acetate cellulose filters using a precleaned Nalgene filter apparatus. The filtrate was separated into three aliquots: 100 + 500 ml were acidified with suprapure nitric acid and stored in precleaned polyethylene bottles for major cations, trace elements analysis and strontium isotopes determination, 250 ml were stored in polyethylene bottles, unacidified, for anion determination.

Major-and trace-element determination, stable and strontium isotopic measurements

Chemical analyses of water samples were performed by atomic absorption spectrometry (Ca, Na, K), colorimetry (Si), ion chromatography (Cl, SO 4 , NO 3 ), inductively coupled plasma mass spectrometry (Mg, trace elements), HCl titration and Gran's method for HCO 3 . Precision was greater than ± 5% for the determination of major elements.

The deuterium and oxygen isotopic ratios are reported in per mil deviations from the international SMOW standard following  = [(R sample / R standard ) -1] x 1000 where R is the isotopic ratio of the heaviest isotope over the lighter (e.g. 18 O/ 16 O). The deuterium and oxygen isotopic ratios were analyzed using a Finnigan MAT 252 mass spectrometer. The average precision, based on multiple analyses of various samples and laboratory standards was  0.1 ‰ for  18 O and  0.8 ‰ for  2 H.

The standard procedure was adopted for the chemical separation and mass spectrometry of strontium [START_REF] Ph | Natural and anthropogenic budgets of a small watershed in the Massif Central (France): chemical and strontium isotopic characterization in water and sediments[END_REF]. After chemical separation, 1/5 of the sample was loaded onto a single tungsten filament and analysed using a Finnigan MAT 262 multiple collector mass spectrometer. The 87 Sr/ 86 Sr ratios were normalized to a 86 Sr/ 88 Sr ratio of 0.1194. The overall precision of the 87 Sr/ 86 Sr determination is approximately ± 10. 10 -6 (2 errors). The reproducibility of 87 Sr/ 86 Sr measurement was tested by duplicate analyses of the NBS 987 standard; the mean value obtained during the study was 0.710227 ± 17. 10 -6 (2, n = 70).

Results and Discussion

Surface-and ground waters geochemistry

Chemistry of the dissolved load

Total Dissolved Solid (TDS, mg/l, Table 1) is generally close to 300 mg/l in most surface waters, except nallah Royam (975 mg/l during the low water stage and 510 mg/l during the higher water stage). In the Subarnarekha River, the upstream sample is more saline during the higher period, whereas the downstream sample shows a similar salinity for both periods. In groundwater during the low water stage the TDS values ranged from 180 up to 1485 mg/l while during the higher water stage, the TDS ranged from 264 mg/l up to 1289 mg/l. The average TDS does not vary much between the two seasons despite the extreme discharge variations in the river (615 ± 341 mg/l and 687 ± 343 mg/l, respectively)

The range of total cationic charge ( + = Na + + K + + 2 Mg ++ + 2Ca ++, , expressed in µeq/l) in surface water samples is 3500 µeq/l to 5000 µeq/l, clearly higher than the ‗world average river water' (1200 µeq/l, [START_REF] Meybeck | Concentrations des eaux fluviales en éléments majeurs et apports en solution aux océans[END_REF]. In groundwater, the range of  + is large, (1000 to 15000 µeq/l, without any discrepancy between the right and left banks of the river). The charge imbalance, estimated by the Normalised Inorganic Charge Balance (NICB = 2{ -- + /  -+  + }* 100) is within the +5/-5% admissible interval for most chemical analyses. There is no evidence of any link between the NICB and the salinity of water, represented by  + . A minor deficit in negative charges suggests the presence of anions other than those analysed, such as organic anions.

The order of cation abundance in surface waters is Na > Ca or Mg > K during the low water stage and Ca > Na > Mg > K during the higher water stage. For anions, the order is HCO 3 > SO 4 or Cl > NO 3 during both the low and higher water stages. In groundwater, the order is Na or Ca > Mg > K and HCO 3 or Cl > SO 4 > NO 3 during both the low and higher water stages. Water types are often used in the characterisation of waters as a diagnostic tool [START_REF] Leybourne | Hydrogeochemical, isotopic, and rare earth element evidence for contrasting water-rock interactions at two undisturbed Zn-Pb massive sulphide deposits, Bathurst Mining Camp, N.B., Canada[END_REF][START_REF] Pitkänen | Hydrogeochemical interpretation of groundwater at Palmottu[END_REF]. Surface water samples are of the HCO 3-Ca type during both water stages, with the exception of the Royam nallah that plots within the field of Ca-SO 4 water type during the low water stage, and within the field HCO 3 -Ca during the higher water stage. Most groundwater samples are of Ca-SO 4 water type and HCO 3 -Ca water type, in agreement with the fresh and mined-water types defines by [START_REF] Sikdar | Geochemical evolution of groundwater in the Quaternary aquifer of Calcutta and Howrah, India[END_REF] in the Quaternary aquifer of Calcutta and Howrah (India).

However, two samples plot within the field HCO 3 -Na (TW4052 and 4033) during the higher water stage and their low water stage equivalents fall within the HCO 3 -Ca field, reflecting a higher Ca input during the low water stage.

Inter-element relationships

The chemical composition of the surface-and ground waters is efficiently examined through binary diagrams between two chemical species X and Y expressed in µmol/l. The seawater dilution line is classically added to the diagram as seasalt aerosols are often a source of chemicals in the dissolved load [START_REF] Krishnaswami | Strontium isotopes and rubidium in the Ganga-Brahmaputra river system: Weathering in the Himalaya, fluxes to the Bay of Bengal and contributions to the evolution of oceanic 87 Sr/ 86[END_REF][START_REF] Edmond | The fluvial geochemistry and denudation rate of the Guayana shield in Venezuela[END_REF][START_REF] Gaillardet | Chemical and physical denudation in the Amazon river basin[END_REF]. It is also generally agreed that Cl is used as reference element in such diagrams [START_REF] Leybourne | Hydrogeochemical, isotopic, and rare earth element evidence for contrasting water-rock interactions at two undisturbed Zn-Pb massive sulphide deposits, Bathurst Mining Camp, N.B., Canada[END_REF][START_REF] Ph | Interaction between different groundwaters in Brittany catchments (France): characterizing multiple sources through strontium-and sulphur isotope tracing[END_REF]Négrel et al., 2004). Unless evaporites occur in the catchment, Cl ions do not participate in weathering reactions and thus behave conservatively through the hydrological cycle. Cl originates from rain inputs (seasalts aerosols) and human activities.

In the Na vs. Cl plot (Figure 2), the highest concentrated samples plot along the sea water dilution line while towards lower concentrations, the waters display Na enrichment generally related to silicate weathering. When plotted versus Cl in Figure 2, Ca, SO 4 (and K) also display enrichments that could be partly related to silicate weathering. Seasonal fluctuations can be best observed with individual sampling site variations of selected chemical elements (Figure 3). The upstream river sample shows a similar Cl (and Na) content during the dry and wet periods, which is not consistent with TDS variations.

The downstream river sample, which shows similar TDS for both periods, shows a higher Cl content during the dry period than during the wet one. The fluctuations between wet and dry periods for the Ca and SO 4 contents of surface waters suggest that the divergence in the TDS for the upstream sample is certainly due to the large increase in the Ca and SO 4 contents (Figure 3). This implies that at least one specific source of these two species is predominant during the wet period, the origin of which might be from agriculture and/or ore deposits weathering and/or mining activities.

For groundwater, the Cl graph (Figure 3, in log scale) evidences some enrichment during the wet period whereas only two samples show minor Cl enrichment during the dry period. A similar evolution is observed for Na. A larger scatter of Cl (and Na) variation is thus observed in surface water samples, whereas for many groundwater samples, there is no evidence of large fluctuations in the Cl contents even during the wet period. The good correlation observed between Cl and SO 4 (Figure 2) departs from the results of Leybourne et al. (1988) whom reported low Cl (0.1 -10 mg/l) associated with high SO 4 (up to 10 -100 mg/l) on groundwater at sulphide deposits. This suggests that fertilisers may be responsible of the correlation between Cl, SO 4 and Ca. Due to the absence of evaporites in the basin, part of the Cl input could be due to fertiliser application, this is further supported by the relationship between Cl and NO 3 , especially with regard to the highest concentrations. As no carbonate formations were recognised in the catchment, the large Ca contents could also be derived from agricultural inputs (Figure 2 and3).

Comparing Ca and SO 4 , most points display a Ca/SO 4 mole ratio close to 1.03, lower than that of the gypsum or anhydrite dissolution. Therefore, Ca seems depleted compared to SO 4 , suggesting that the additional source of SO 4 did not provide Ca to the water.

The higher Ca and SO 4 contents in the river sample upstream during the wet period are not accompanied by a significant increase in the NO 3 content. Conversely, the highest NO 3 content is observed during the dry period. It is therefore suggested that the source of Ca and SO 4 in surface waters is independent from that responsible of NO 3 inputs.

River chemistry variations during the wet period could be explained by a large input of water with a lower salinity (and therefore a lower content in chemical elements), hence the decrease in most elements in the river. The decrease in the contents downstream by a dilution scheme involving less concentrated waters (e.g. groundwater), is supported by the chemical composition of some groundwaters, all located donwstream. (e.g. Narsinghgarh, Patargorah and Deuli). On the other hand, during the dry period, most elements are almost constant downstream, excepted NO 3 that exhibits a decrease. The lack of variation seems to highlight the lack of groundwater input, and/or another influence that is not reflected by the geochemistry. This will be further investigated with the use of strontium isotopes. NO 3 enrichment is locally observed during the wet period, but most wells show identical values between the two periods. Much of Ca and SO 4 inputs in groundwater can therefore be related to agricultural practice.

The carbonate system and the origin of Ca and SO 4

The carbonate system in waters can be investigated by using calcium and bicarbonate which are the dominant ions. Samples plot above and below the Ca = HCO 3 equivalent line (calculated in µeq/l). The fact that points fall off this line implies that both cation(s) and anion(s) are necessary to reach the balance. This could be refined by comparing Ca + Mg as a function of HCO 3 + SO 4 (Figure 4) that shows a better scatter of the points around the 1:1 line [START_REF] Edmond | The fluvial geochemistry and denudation rate of the Guayana shield in Venezuela[END_REF]. This observation highlights the important role of calcium and sulphate in the Subarnarekha River system and induces that sulphate must be taken into consideration in the carbonate system equilibrium.

The PHREEQC geochemical code [START_REF] Parkhurst | User's guide to PHREEQC (version 2) -A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations[END_REF]; available at www.usgs.org) was used to compute the saturation indices on selected groundwater samples, covering the large Ca range. The saturation indices are hereafter referred as SI, a value of zero indicates equilibrium, a positive value indicates oversaturation and a negative value undersaturation. The values obtained for the relevant solid phases were used as criteria to determine the solids likely to precipitate under the measured physicochemical conditions. Among the main species available using PHREEQC, Table 2 summarises the SI for carbonate species (calcite and dolomite) and sulphate species (gypsum and celestite) on selected samples.

For the less Ca-concentrated samples carbonate and sulphate phases are generally undersaturated during both low and higher stages, implying that neither Ca nor SO 4 and Sr are controlled by solid phases. However, carbonate phases are undersaturated in one samples (Kesarpur) during the dry period (SI: -1.32 / -1.71) but surprisingly become oversaturated during the higher period (SI: 0.17 / 1/15). For the highest Ca-concentrated samples, SI values always indicate oversaturation for carbonate phases while sulphate phases are always undersaturated whatever the period is. These trends are more marked for the various species of dolomite.

With large and frequent oversaturation of carbonate phases, PHREEQC geochemical calculations confirm the large Ca and Mg contents in groundwaters, reflecting the role of the Ca and Mg source(s). However, the origin of this source remains in debate. Calcite saturation indices suggest that part of the Ca depletion compared to SO 4 can be linked with the precipitation of calcite; sulphate phases are never oversaturated. However, the relatively low SI with regard to calcite associated with the good linkage between Cl and Ca and the weaker linkage with SO 4 plead in favour of a common source for Cl and Ca and a specific one for SO 4 . The first source can be related to agricultural practices via fertiliser application and the second one can be related to mining activities.

 2 H and  18 O isotopic signature and origin of the waters

The stable isotopic signature in continental waters is mainly controlled by precipitation input, evaporation and mixing processes (IAEA, 1981). In the Subarnarekha River system, stable isotopes fall in the range 0.4 to -6.0‰ for  18 O and 10.4 to -39.0‰ for  2 H in surface waters, including sample WW2038 which contains a wastewater component.

For groundwaters, the range for  18 O is -3.3 to -6.8‰ and -28.5 to -45.5‰ for  2 H, including the sample DW2017 from Tentuldenga. All ranges are in accordance with values given by [START_REF] Stüber | Arsenic enrichment in groundwater of west Bengal, India: Geochemical evidence for mobilization of As under reducing conditions[END_REF], [START_REF] Majumdar | Seasonal variations in the isotopes of oxygen and hydrogen in geothermal waters from Bakreswar and Tantloi, Eastern India: implications for groundwater characterization[END_REF] and [START_REF] Gupta | Groundwater δ 18 O and δD from central Indian Peninsula: influence of the Arabian Sea and the Bay of Bengal branches of the summer monsoon[END_REF].

Stable isotope measurements in water are plotted in a classical  18 O vs.  2 H diagram (Figure 5). The global meteoric water line (GMWL,  2 H = 8  18 O + 10) is indicated, and the GNIP Database (from the Global Network for Isotopes in Precipitation, IAEA/WMO, 2001) allows drawing four significant local meteoric water lines over India (Allahabad, Hyderabad, Schillong, and Shiliguri stations) that fall either above or below the GMWL.

Many of the groundwater samples plot between the local and the global meteoric water line(s), reflecting a meteoric origin for the water without any major transformation, e.g. mainly evaporation. This suggests that the transfer from rainfall towards groundwater storage through soil and the non-saturated zone is fast, and that post-precipitation evaporation during the passage in soil is not an active process on the Subarnarekha River system. This is contrary to the observations of [START_REF] Majumdar | Seasonal variations in the isotopes of oxygen and hydrogen in geothermal waters from Bakreswar and Tantloi, Eastern India: implications for groundwater characterization[END_REF] and [START_REF] Gupta | Groundwater δ 18 O and δD from central Indian Peninsula: influence of the Arabian Sea and the Bay of Bengal branches of the summer monsoon[END_REF], but in agreement with the study by [START_REF] Stüber | Arsenic enrichment in groundwater of west Bengal, India: Geochemical evidence for mobilization of As under reducing conditions[END_REF] in West Bengal.

With regard to the groundwater samples plotting along the GMWL (Figure 5), the ranges of 18 O and 2 H isotopes are narrow, e.g. from -5 to -7‰ for  18 O and -30 to -45‰ for  2 H. This suggests that groundwater recharge occurs during a limited period (i.e. the monsoon). Moreover, there is no evidence of stable isotopes variation with regard to the location of the samples or altitude, reflecting a similar input during the recharge period.

In accordance with the monsoon system, [START_REF] Deshpande | Distribution of oxygen and hydrogen isotopes in shallow groundwaters from Southern India: influence of a dual monsoon system[END_REF] evidenced a geographic distribution of the  2 H and  18 O isotopic signature in precipitations. Hence, groundwaters from southern India [START_REF] Deshpande | Distribution of oxygen and hydrogen isotopes in shallow groundwaters from Southern India: influence of a dual monsoon system[END_REF][START_REF] Ph | Stable isotope hydrogeology of the Maheshwaram watershed (Andra Pradesh, India)[END_REF] are strongly influenced by the different features in rain input, which is not the case in the Subarnarekha River system. Our values are depleted in heavy isotopes, like those of [START_REF] Gupta | Groundwater δ 18 O and δD from central Indian Peninsula: influence of the Arabian Sea and the Bay of Bengal branches of the summer monsoon[END_REF] in their study from the west to the east coast of India but further south. [START_REF] Gupta | Groundwater δ 18 O and δD from central Indian Peninsula: influence of the Arabian Sea and the Bay of Bengal branches of the summer monsoon[END_REF] showed an average  18 O in groundwater around 1 ± 1‰, but a decrease in  18 O up to -7‰ towards the northeast of their zone is clearly evidenced. They related these depleted values to atmospheric inputs marked by depressions and cyclonic storms originating from the Bay of Bengal.

A few of the surface-and groundwater samples show a significant shift of more than 1‰ to the right of the GMWL. Comparison of the  18 O in the surface-and ground-waters in the Subarnarekha River system between the wet and dry periods shows that all surface waters display  18 O enrichment more marked during the dry period (Table 1). These 18 O and 2 H enrichments in surface waters may be linked to evaporation processes in soils, to evapotranspiration or sometimes to surface evaporation from the river water masses (Negrel and Lachassagne, 2000). Some of the groundwaters are also shifted on the right of the GMWL in relation with either an evaporation processes linked with a poor isolation of the tube well or to water return flow with a depleted value as illustrated by [START_REF] Ph | Stable isotope hydrogeology of the Maheshwaram watershed (Andra Pradesh, India)[END_REF] in the Maheshwaram watershed (Andra Pradesh, India). However, most of the groundwater display similar  18 O between dry and wet periods reflecting few variations during the infiltration of recharge waters.

Strontium contents and Strontium isotope ratios

Variations in the concentrations and strontium isotopes

Strontium content varies greatly in groundwater samples and less in surface water samples. The range is between 1 and 2 µmol/l in surface waters, either in wet or dry periods. The observed range in surface water agrees with that found in rivers in the Ganga-Brahmaputra-Indus river system [START_REF] Krishnaswami | Strontium isotopes and rubidium in the Ganga-Brahmaputra river system: Weathering in the Himalaya, fluxes to the Bay of Bengal and contributions to the evolution of oceanic 87 Sr/ 86[END_REF][START_REF] Pande | The Indus river system (India-Pakistan): major ion chemistry, uranium and strontium isotopes[END_REF][START_REF] Singh | Chemical and Strontium, Oxygen, and Carbon Isotopic Compositions of Carbonates from the Lesser Himalaya: Implications to the Strontium Isotope Composition of the Source Waters of the Ganga, Ghaghara, and the Indus Rivers[END_REF] and Himalayan rivers [START_REF] Galy | The strontium isotopic budget of Himalayan rivers in Nepal and Bangladesh[END_REF]. However, Sr contents in groundwater vary by 2 order of magnitude from less than 0.4 up to 10 µmol/l on both banks of the Subarnarekha River. Few studies deal with the Sr content and Sr isotopes in India. The Sr content in the Subarnarekha hydrosystem agrees with that found by [START_REF] Dowling | The groundwater geochemistry of the Bengal Basin: Weathering, chemsorption, and trace metal flux to the oceans[END_REF] in groundwater near rivers of the Ganga-Brahmaputra floodplain in the Bengal Basin. They related the lowest values (around 1 µmol/l) to silicate weathering while the highest are related to carbonate inputs.

However, the fluctuations of the Sr contents in the Subarnarekha hydrosystem are correlated with those of Cl (Table 1). This relationship reflects that the source of chloride is also a potential source of Sr. On the other hand, the similar behaviour of Sr and Ca is widely recognised, due to their similar geochemical properties. The plot of Sr vs. Ca (Figure 6) shows different linear relationships, resulting from the weathering of shale, silicate and carbonate. Different Ca/Sr ratios reflect indicate the geological homogeneity of sub-watersheds draining single rock-type areas [START_REF] Meybeck | Composition chimique des ruisseaux non pollués en France[END_REF] as stated by [START_REF] Edmond | The fluvial geochemistry and denudation rate of the Guayana shield in Venezuela[END_REF] and [START_REF] Huh | The fluvial geochemistry of the rivers of Eastern Siberia: I. Tributaries of the Lena River draining the sedimentary platform of the Siberian craton[END_REF]. No points in the Subarnarekha River system were found along the shales weathering line. Most points are located on the "silicate line", while some of them are scattered closer to the carbonate one, either with low or high Ca and Sr contents. As most of the studied area is underlain by silicate rocks, the position of most points along the "silicate line" is consistent with the nature of the rocks. When comparing the Sr vs. Ca variations in some groundwater between dry and wet periods, an opposite behaviour can be observed. For example, the sample from Amdah is located on the "silicate line" during the wet period and shifts towards lower-Sr/higher-Ca during the dry period. Conversely, the sample from Sabisa plots on the "silicate line" during the dry period and shifts towards higher -Sr/ lower -Ca during the wet period.

Inasmuch as there is no carbonate outcrops, the shift of most points towards the "carbonate line" agrees and confirms Ca inputs from another source than weathering.

Such Ca inputs (and therefore Sr) could be related to (i) carbonate amendments used in agriculture and (ii) residues of ore processing.

Strontium isotopes display a wide variation both in the low and high water stages from 0.71844 to 0.80518 in surface waters and from 0.719997 to 0.76866 in ground waters.The observed range in surface-and groundwater, with relatively high 87 Sr/ 86 Sr ratios is similar to the range for rivers draining old cratons (Guyana Shield, [START_REF] Edmond | The fluvial geochemistry and denudation rate of the Guayana shield in Venezuela[END_REF]French Guiana, Négrel and Lachassagne, 2000;Lena River basin, Huh and Edmond, 1999) and for the Ganga-Brahmaputra -Indus River system [START_REF] Krishnaswami | Strontium isotopes and rubidium in the Ganga-Brahmaputra river system: Weathering in the Himalaya, fluxes to the Bay of Bengal and contributions to the evolution of oceanic 87 Sr/ 86[END_REF][START_REF] Pande | The Indus river system (India-Pakistan): major ion chemistry, uranium and strontium isotopes[END_REF][START_REF] Singh | Chemical and Strontium, Oxygen, and Carbon Isotopic Compositions of Carbonates from the Lesser Himalaya: Implications to the Strontium Isotope Composition of the Source Waters of the Ganga, Ghaghara, and the Indus Rivers[END_REF]. Similar ranges are observed in Himalayan rivers [START_REF] Galy | The strontium isotopic budget of Himalayan rivers in Nepal and Bangladesh[END_REF]. The 87 Sr/ 86 Sr ratios range given by [START_REF] Dowling | The groundwater geochemistry of the Bengal Basin: Weathering, chemsorption, and trace metal flux to the oceans[END_REF] in groundwater from rivers of the Ganga-Brahmaputra floodplain in the Bengal Basin are lower as water draining silicate displays 87 Sr/ 86 Sr ratios between 0.7143 and 0.724 while that draining carbonate displays 87 Sr/ 86 Sr ratios between 0.7155 and 0.7273. The time evolution of strontium and its isotopes shows show a good consistency between dry and wet period values as illustrated in Table 1.

Mixing processes

The Sr isotope studies of rivers and lakes have shown that variations in 87 Sr/ 86 Sr and Sr contents are caused primarily by mixing of waters of various origins with different 87 Sr/ 86 Sr ratios and Sr contents, such as mixing between different water pools, each of them possibly reflecting water-rock interaction with different rock types [START_REF] Gaillardet | Chemical and physical denudation in the Amazon river basin[END_REF][START_REF] Bullen | Kinetic and mineralogic controls on the evolution of groundwater chemistry and 87 Sr/ 86 Sr in a sandy aquifer, northern Wisconsin, USA[END_REF][START_REF] Galy | The strontium isotopic budget of Himalayan rivers in Nepal and Bangladesh[END_REF]. A comparison of the 87 Sr/ 86 Sr vs. Sr contents shows that all the water samples from the Subarnarekha River system are largely scattered either with regard to Sr isotope and Sr contents. It is worth noting that (i) the large variation in the Sr contents corresponds to a relatively restricted range of the 87 Sr/ 86 Sr ratios and (ii) the highest 87 Sr/ 86 Sr ratios correspond to relatively low Sr contents. The 87 Sr/ 86 Sr ratios vs. 1/Sr diagram (Figure 7) is classically used to evaluate two-component mixing and end-member water compositions. The 1/Sr logarithmic scale is used for easier viewing [START_REF] Ph | Strontium isotope systematics used to decipher the origin of groundwaters sampled from granitoids: the Vienne case (France)[END_REF][START_REF] Ph | Comparison of the Sr isotopic signatures in brines of the Canadian and Fennoscandian Shields[END_REF]. The samples are scattered amongst 3 directions that suggest the existence of at least 3 end-member compositions [START_REF] Hogan | 87 Sr/ 86 Sr as a tracer of groundwater discharge and precipitation recharge in the Glacial Lake Agassiz, Peatlands, northern Minnesota[END_REF]. The most dilute end-member should be compatible with the rainwater inputs (hereafter referred to as rainwater) which characteristics are usually 87 Sr/ 86 Sr close to 0.720, Sr content around 0.1 µmol/l. The most mineralized endmember has very similar isotopic compositions, and Sr concentrations around 100 µmol/l.

It is believed to represent anthropogenic inputs, mainly agricultural in origin. The third end-member is characterized by a Sr content around 1 µmol/l and a more radiogenic signature ( 87 Sr/ 86 Sr > 0.760). This end-member is represented by Royam nallah, which drains a large area of mines tailings. This very high 87 Sr/ 86 Sr reflects the weathering of the Rb-rich minerals which are enriched in the tailings. This end-member reflects a natural background component, though enhanced by human activities.

Comparing the Sr isotope ratios and the chloride contents argues further in favour of these three end-members. Rainwater inputs display the lowest Cl contents while anthropogenic inputs shows the highest Cl contents, and the natural background has a low Cl content (around 100 µmol/l). These three end-members can also be observed by comparing Sr and SO 4 contents, 87 Sr/ 86 Sr ratios and SO 4 and 87 Sr/ 86 Sr ratios and Ca contents (all not shown).

In the case of water mixing, the mixture of two or more components and the end-member water compositions can be evaluated with the 87 Sr/ 86 Sr ratios vs. 1/Sr diagram [START_REF] Faure | Principles of Isotope Geology[END_REF][START_REF] Hogan | 87 Sr/ 86 Sr as a tracer of groundwater discharge and precipitation recharge in the Glacial Lake Agassiz, Peatlands, northern Minnesota[END_REF][START_REF] Grosbois | An overview of dissolved and suspended matter fluxes in the Loire river basin: natural and anthropogenic inputs[END_REF]. In the case of a multi-end member mix, several linear mixing lines have to be considered, and the main difficulty is the identification of the different end members [START_REF] Ph | Interaction between different groundwaters in Brittany catchments (France): characterizing multiple sources through strontium-and sulphur isotope tracing[END_REF][START_REF] Ph | Comparison of the Sr isotopic signatures in brines of the Canadian and Fennoscandian Shields[END_REF]. The isotope systematics of two-component mixtures, described in detail by [START_REF] Faure | Principles of Isotope Geology[END_REF], can be expressed as follows:

87 Sr/ 86 Sr m x [Sr] m =  ( 87 Sr/ 86 Sr 1 x [Sr] 1 ) + (1-) ( 87 Sr/ 86 Sr 2 x [Sr] 2 )

(1)

where 87 Sr/ 86 Sr m is the measured isotopic ratio in the mixture, 87 Sr/ 86 Sr 1 , 87 Sr/ 86 Sr 2 represent the isotopic ratios of the first and second end member, respectively. Different mixing trends exist between the end-members in Figure 7. The application of equation ( 1) allows the calculation of the mixing curves RW-NAT1 and RW-NAT2 on Figure 7 which end-members are rainwater (87 Sr/ 86 Sr = 0.720; Sr = 0.1µmol/l) and the two natural backgrounds NAT1, represented by Royam nallah ( 87 Sr/ 86 Sr = 0.80518; Sr = 1 µmol/l) and NAT2 ( 87 Sr/ 86 Sr = 0.77354; Sr content = 1 µmol/l).

The application of equation ( 1) allows the calculation of the second mixing curve RW-ANT on Figure 7 which end-members are rainwater ( 87 Sr/ 86 Sr = 0.720; Sr = 0.1µmol/l) and the anthropogenic end-member ( 87 Sr/ 86 Sr = 0.720; Sr = 30 µmol/l)., as well as that of the third mixing curves ANT-NAT1 and ANT-NAT2 on Figure 7 which end-members are the anthropogenic end-member ( 87 Sr/ 86 Sr = 0.720; Sr content = 30 µmol/l) and the two natural backgrounds NAT1and NAT2.

Considering the mixing diagram in Figure 7, it is worth noting that sample(s) lies directly on a mixing line reflecting binary mixing (one groundwater sample lying on the mixing lines RW-NAT2 and other samples on the mixing line RW-ANT). All other samples are located between the mixing lines, reflecting inputs from all end-members.

Groundwater circulation, existence of flow paths?

According to the piezometric levels, some areas can be focussed on for flow path investigations. Within the studied catchment, the most probable flow path area, located north, including Kesarpur, Bagalkora, Jarisa and Galudih wells, can be further detailed. The large increase in solutes in the Galudih samples, both during the dry and wet periods suggests anthropogenic inputs, along with the increased nitrate contents (not shown). Na displays a roughly similar behaviour to Cl (not shown). Sulphate contents seem to increase regularly from Kesarpur up to Galudih, whatever the period is. SO 4 contents, as well as numerous other chemical indicators not shown in Figure 8 (e.g. K, HCO 3 , …), do not show variations between dry and wet periods. Mg and Ca contents show similar trends to Cl, but with a supplementary increase in the Bagalkora samples.

Sr contents display the same trend along the possible flowpath as Ca and/or Mg, that is to say an increase in the Bagalkora samples compared to Kesarpur and Jarisa and a large increase in the Galudih samples, and very few differences between the dry and wet periods. Regarding the 87 Sr/ 86 Sr ratios, several features can be pointed out. First, the 0.724) than in Kesarpur samples. This reflects for Kesarpur a large homogeneity for the water resource, both for meteoric inputs and for water-rock interactions (i.e. no variations between dry and wet periods). For Galudih, this is true for meteoric inputs and for waterrock interactions, but also for anthropogenic activities. The 87 Sr/ 86 Sr ratios differ in Bagalkora and Jarisa samples between the dry and wet periods, the wet period ratio being higher. Overall, 87 Sr/ 86 Sr ratios increase from Kesarpur up to Jarisa, and therefore decrease up to Galudih.

As discussed previously on Figure 8 with further evidence on Figure 9 ( 87 Sr/ 86 Sr vs. 1/Sr ratios), Sr isotopes and Sr contents in Kesarpur and Galudih samples have similar values in dry and wet periods, which is not the case at Jarisa and Bagalkora. In Bagalkora, the main variation is an increase of the 87 Sr/ 86 Sr ratio during the higher water stage, while Sr remained similar. In Jarisa, the main variations are a decrease of the Sr content during the higher water stage, together with a slight but significant increase of the 87 Sr/ 86 Sr ratio.

The increase of the 87 Sr/ 86 Sr ratios showed in Figure 8 between Kesarpur and Jarisa is not supported by a binary mixing trend between two end-members, as illustrated in the plot 87 Sr/ 86 Sr vs. 1/Sr ratios by the lack of any linear relationship (Figure 9). This suggests that all groundwaters evolved more as in close pockets than along a flow path. This could be related to a possible over exploitation of groundwater resources in hard rock aquifers. The shallower part of the aquifer is increasingly desaturated due to the large exploitation of groundwater resources for domestic, agricultural and mining activities, leading to the formation of exploited groundwater pockets. This can easily be related to the heterogeneous and anisotropic fractured rock aquifer system characteristics, in which flow is very significantly influenced by the fracture characteristics [START_REF] Gupta | Flow regime associated with partially penetrating large-diameter wells in hard rocks[END_REF][START_REF] Neretnieks | A stochastic multi-channel model for solute transport-analysis of tracer tests in fractured rock[END_REF]Talbot et al., 2003).

Conclusions

This study reports on the geochemistry of surface-and groundwaters along the Subarnarekha River system in the vicinity of the Singhbhum mining district, distinguishing between dry and wet seasons (low and high stages). The dedicated geochemical tools included major cations and anions, traces elements concentrations and isotopic tracing (stable isotopes of the water molecule, strontium isotopes) and this study comes to the following conclusions on the origin and the relationships between surfaceand groundwaters in the studied catchment.

A large range of salinities in surface-and groundwaters was observed in the system, both for dry or wet periods. On a TDS (mg/l) vs. Na/Na+Ca diagram, data from both surveys plot between the evaporation-crystallisation dominance and rock dominance fields, suggesting fluctuations between low-salinity and high-salinity water types.

Water characterisation can be done by using ternary diagrams. Surface water samples plot within the field HCO 3-Ca during both water stages. Most groundwater samples plot within the field of Ca-SO 4 water type and HCO 3 -Ca water type. This reflects the high Ca input in groundwaters.

In X vs. Cl diagrams (X being major ions), the most concentrated samples plot along the sea water dilution line while at lower concentrations water samples display enrichment, generally related to silicate weathering. However, in the absence of any evaporites, part of the Cl could come from fertiliser application, inducing part of the major ions vs Cl relationships.

With regards to stable isotopes of the water molecule ( 18 O and  2 H), many of the groundwater samples plot between the local meteoric water lines and the global meteoric water line, reflecting a meteoric origin for the water without any major transformation, e.g. mainly evaporation. This suggests a rapid transfer from rainfall towards groundwater through soils and the non-saturated zone.

Sr and Ca show different linear relationships resulting from the weathering of shale, silicate and carbonate. No sample of the Subarnarekha River system plotted along the line reflecting the weathering of shales. Most points are located closer to the "silicate line" with some of them being scattered towards the carbonate one, either with low or high Ca and Sr contents. Inasmuch as there is no carbonate outcrops, the shift of most points towards the "carbonate line" should reflect another source of Ca inputs than weathering. Such Ca inputs (and therefore Sr) could be related to (i) carbonate amendments used in agricultural practice or (ii) residues of mining treatment.

The scatter of 87 Sr/ 86 Sr signatures needs to be explained by at least 3 end-member compositions. The most dilute end-member should be compatible with rainwater inputs.

The most mineralised end-member has isotopic compositions very similar to the dilute one and is believed to represent anthropogenic inputs. The third end-member is characterised by an intermediate Sr content and a more radiogenic signature. It represents a natural background, but modified by human activities (e.g. drainage of tailings).

Potential flow paths were investigated north of the area. In the scope of the different geochemical tools used, all groundwaters in this area seem to evolve more as in close pockets than along a flow path.

These observations on groundwater and recharge explain the limited extent and irregularity of groundwater contamination. Groundwater plays a minor part in pollutant transfer. The observations on surface water chemistry show clearly the influence of human activities, but also the predominance of natural phenomena (mineral weathering and monsoon regime). The role of mining and metallurgy can be observed in sulphate and Sr behaviour, but it is not clearly greater than the role of agriculture. Table 1. Results of the master variables (EC in µS/cm, T in °C, pH), TDS (in mg/l, calculated by summing cation and anion contents), major ions (in µmol/l), total cationic and anionic charge (in µeq/l), Normalised Inorganic Charge Balance (NICB), Sr contents,

Figure Captions

  [Sr] m ,[Sr] 1 ,[Sr] 2 are the Sr content of the mixture, and of the first and second end members, respectively. The mixing parameter  derived from equation (1the proportion of the two components in the mixture.

Figure 8

 8 Figure 8 summarises the chemical indicators for the dry and wet periods with regards to their evolution along the suggested flowpath. The piezometric levels indicated a possible flowpath as indicated on the map in Figure 8. Along this possible flowpath, the chloride contents display a similar behaviour both between the samples and between the dry and wet period. The Cl contents fluctuate between 280 and 680 µmol/l in Kesarpur, Bagalkora and Jarisa and a larger value (up to 2200-2600µmol/l) is observed in Galudih.

Figure 1

 1 Figure 1 General setting of the studied site in the Subarnarekha River system

Figure 3 .

 3 Figure 3. Plot of Ca + Mg vs. HCO 3 + SO 4 (in µeql/l). The 1 : 1 line is calculated in µeq/l.

Figure 4 .

 4 Figure 4. Plot of Cl, Ca and SO 4 contents (expressed in µmol/l) between the dry and wet periods for surface-and groundwaters in the Subarnarekha River system.The Cl contents scale is expressed in logarithmic units for the groundwaters for easier viewing.

Figure 5 .

 5 Figure 5. Plot of the  18 O vs. the  2 H in rainwater (data are from the IAEA/WMO, 2001) and in the Subarnarekha River system. GMWL corresponds to the global meteoric water line ( 2 H = 8 18 O + 10).

Figure 6 .

 6 Figure 6. Plot of strontium vs. calcium contents (expressed in µmol/l) in the the Subarnarekha River system. The dashed lines correspond to the weathering of shales, silicate and carbonate, respectively.

Figure 7 .

 7 Figure 7. Plot of 87 Sr/ 86 Sr vs. 1/Sr (Sr concentration expressed in µmol/l) for the surface-and ground-waters samples during dry and wet periods in the Subarnarekha River system. The 1/Sr scale is reported in logarithmic units for easier viewing. Curves represent calculated mixing lines according to equation 1 (see text).

Figure 8 .

 8 Figure 8. Plot of selected chemical indicators (Cl, Ca, SO 4 , Sr, µmol/l) and Sr isotopes for the ground-waters samples during dry and wet periods in the supposed flowpath between Kesarpur and Galudih (North of the Subarnarekha River system).

Figure 9 .

 9 Figure 9. Plot of 87 Sr/ 86 Sr vs. 1/Sr contents (Sr concentration expressed in µmol/l) for the ground-waters samples during dry and wet periods in the supposed flowpath between Kesarpur and Galudih (North of the Subarnarekha River system).

(

  expressed in µmol/l), Sr isotope values ( 87 Sr/ 86 Sr ratios) and stable isotopes of the water molecule ( 18 O and  2 H) of water samples from the aquifers and surface waters from the Subarnarekha river basin. Samples SW refer to surface water, TW refer to groundwater collected by tubewells, DW refer to groundwater collected by dugwell. Low water stage corresponded to February 2001 and high water stage to November 2001.

Table 2 .

 2 Saturation indices on selected samples from the aquifers from the Subarnarekha river basin.

	Table 1

Table 2

 2

Sr/ 86 Sr ratio is identical for Kesarpur samples during the dry and wet periods, close to 0.720. This is also observed in Galudih samples, but the 87 Sr/ 86 Sr ratio is higher (e.g.

Acknowledgements

This study was carried out in the framework of a cooperation project on environmental technology transfer: the Subarnarekha Project, led in 1999-2003 by BRGM and the Geological Survey of India (GSI), and funded by the Indian and French governments. The isotopic studies were also supported by the research activities of BRGM, on behalf of the French Ministry of Education and Research. The study was granted by the total, constant and enthusiastic support of the GSI Eastern Region Project Managers, Officers and by GSI personnel, who ensured that we obtained all the necessary scientific and technical support on time and with quality, as well as hospitality. Most mineralogical, chemical and isotopic analyses were performed in the BRGM Laboratories, France, but analytical results obtained by GSI laboratories, Eastern Region Chemical Division were continuously available. Field analyses and sampling operations were performed first as teamwork between BRGM and GSI geoscientists, then by GSI teams with BRGM support as a result of capacity building.


Nesrine Khabou
email: nesrine.khabou@redcad.org

Ismael Bouassida Rodriguez

Towards a novel analysis approach for collaborative ubiquitous systems

Keywords: Ubiquitous computing, context awareness, adaptation, analysis techniques, tendency, peak

In ubiquitous computing systems, applications must be able to respond to dynamic context changes in order to maintain collaboration between entities. A promising solution consists of developing context aware applications which automatically change their behavior according to the user needs, the available resources and the surrounding environment. Furthermore, a context aware application is characterized by a closed feed back loop with four phases: Monitoring, Analysis, Planning and Execution. In this paper, we focus on the second phase and we propose an analysis approach of collaborative ubiquitous systems which aims at analyzing context information and detecting significant abnormal changes. The proposed approach relies on thresholds in order to track down context changes. Once relevant context changes occur, the context aware application will be notified to trigger its suitable process dynamically in order to deal with the changes.

I. INTRODUCTION

Nowadays, the tremendous development of wireless communication technologies and the widespread of devices such as laptops, sensors, RFID tags, etc, have led to the appearance of ubiquitous computing that takes place as the successor of mobile computing systems. This new paradigm brings new challenges to the traditional applications. In fact, the deployment of the heterogeneous devices will certainly face an environment full of changes. These changes are related for example to the availability of mobile devices resources, the devices joining or leaving the network, the network topology varying, the changing execution environment (temperature, pressure, noise, etc) and the application execution context (user location, device screen size). Hence, the application needs to be able to detect these changes in order to adapt its behavior to these varieties according to the corresponding context information. This ability to sense and to detect the environment changes is called "context awareness". Moreover, context awareness [START_REF] Abowd | Towards a better understanding of context and context-awareness[END_REF] is considered to be the key issue for making devices aware of the situation of their users and their environment.

As a result, the design and the implementation of context aware applications on top of ubiquitous environments is a challenging task. First, these applications need to manage context continuously, including the collection of a multitude of context information from different sources such as sensors, operating systems, etc. Second, a classification of context information into different categories should be performed in order to facilitate the context use. Then, the context aware applications analyze and interpret context information so that being able to detect the conditions under which adaptation actions are required. Finally, the context aware applications trigger adaptation actions when noticing context changes that can affect the application performance or functionalities.

In this paper, we propose a novel resource context classification taking into account the resource evolution behavior. Then, we introduce an approach that allows a collaborative application to detect the context changes, trigger notifications when necessary and adapt its functionalities to the current context. Our approach is based on thresholds in order to track down context changes. Moreover, thresholds are configured by domain experts or application designers and notifications are then raised by the corresponding entities in order to trigger appropriate reconfiguration actions.

The remainder of this paper is structured as follows: In section II, we introduce the context classification in ubiquitous environments followed by some research studies treating methods used for context changes detection in such environments. Section III presents the case study called "Entreprise hardware monitoring" that aims at monitoring resources state and raising appropriate notifications when resource violations are detected. In section IV, we introduce the proposed approach that allows for context classification and context changes analysis in collaborative ubiquitous systems using thresholds. In section V, we motivate and illustrate the feasibility of our approach through an illustrative scenario. The last section concludes the paper and gives some directions for future work.

II. RELATED WORK

We begin this section by introducing some research studies dealing with context classification. Then, we give an overview of studies which propose techniques to detect context changes.

A. Context and context classification

Dey et al [START_REF] Abowd | Towards a better understanding of context and context-awareness[END_REF] defined context as "any information that can be used to characterize the situation of an entity. An entity is a person, a place, or an object that is considered relevant to the interaction between a user and applications themselves". Due to the wide density of contextual data, many researchers have proposed several classifications of context into categories that are most suitable and meaningfull to their applications domain. These classifications are proposed in order to facilitate the context use. In fact, most of the studies made a classification into two categories [START_REF] Mitchell | Supporting the development of mobile contextaware computing[END_REF], [START_REF] Schmidt | Ubiquitous computing -computing in context[END_REF], [START_REF] Prekop | Activities, context and ubiquitous computing[END_REF]. On the one hand, Schmidt [START_REF] Schmidt | Ubiquitous computing -computing in context[END_REF] partitions context into two classes, such as "Physical environment" and "Human factors" as depicted in the Figure 1. On the other hand, Mitchell [START_REF] Mitchell | Supporting the development of mobile contextaware computing[END_REF] divides the context into two categories, a "personal environment" formed by the user's interest, the user's location and an "environmental context" formed by the weather forecast.

Other studies classify context to several categories like [START_REF] Rodden | Exploiting context in hci design for mobile systems[END_REF] and [START_REF] Schilit | Context-aware computing applications[END_REF]. In fact, Schilit et al [START_REF] Schilit | Context-aware computing applications[END_REF] define the context as the constantly changing execution environment. In fact, execution environment is the computing environment formed by the available processors, the network capacity, and the connectivity; the user environment which contains the user's location, his social situation. Finally, the physical environment. Brown et al [START_REF] Brown | Context-aware applications: from the laboratory to the marketplace[END_REF] proposed to add a fourth context category as the time context defined by the time of a day, week, month and the season of the year.

B. Context changes detection techniques in ubiquitous environments

In the context changes detection research direction, several techniques and models are proposed in order to reveal the context changes. In fact, in [START_REF] Cioara | A self-adapting algorithm for context aware systems[END_REF], Cioara et al propose to use the context entropy concept for detecting the context changes and determining the degree of fulfilling a predefined set of policies. Moreover, context situation entropy defines the level of the system's self and execution envionment disorder which is measured by evaluating the degree of respecting a set of policies. Hence, once the context entropy exceeds a fixed threshold, then the system is in a critical state and it must execute adaptation actions. Although this approach allows self adaptation following context changes, it does not consider many context parameters to study as it is restricted to external parameters such as temperature, humidity and light etc.

In other studies, context changes are picked up by comparing a context value saved in a repository with a new context value. In fact, in The proposed middleware enables to save the scare resources. In fact, the component deployment is performed "just-in-time". However, this middleware does not specify context information to take into account. Another approach for dynamic context management is proposed in [START_REF] Taconet | Ca3m: A runtime model and a middleware for dynamic context management[END_REF]. Indeed, Taconet et al [START_REF] Taconet | Ca3m: A runtime model and a middleware for dynamic context management[END_REF] present CA3M, a context aware middleware, which enables applications to adapt their behavior by dynamically taking into account context changes.

They model the application by "entities", which represent a physical or logical phenomenon (person, concept, etc.) and "observable", which defines something to observe. For instance, a mobile device state is an example of an observable which may take a finite number of values (e.g low battery, almost low battery or normal battery). They consider that the change of an "observable" state or even the observation goes past a given threshold from the last notified value leads to a different application behavior.

In [START_REF] Rodriguez | A model-driven adaptive approach for collaborative ubiquitous systems[END_REF], Bouassida et al proposed a model driven approach for collaborative ubiquitous systems. In order to detect context changes, they specify predefined thresholds. Then, once context values remain below/under the threshold values, a notification is raised. Although this approach enables to detect instantly context changes, it may cause false detections as well as missing alarms by using fixed thresholds.

III. CASE STUDY: ENTREPRISE HARDWARE MONITORING

In order to illustrate the usability of our approach, we introduce an example of an M2M application named "Entreprise hardware monitoring" denoted in the Figure 2 which aims at enhancing security and detecting undesirable effects. In this case study, we focus on some context parameters such as battery level, available bandwidth and available memory such as the RAM. The application involves three kinds of participants as denoted in the Figure 2: Controlling M2M servers, M2MSrv1 and M2MSrv2, gateways such as GW1 and GW2, some meters used for monitoring and devices connected to the gateways. The M2M servers implement analysis algorithms, and process monitored data received from meters in order to analyze them. Once results are obtained, the corresponding M2M servers notify the device and/or act to reconfigure the architecture by switching or disabling the affected device(s).

For example, the M2M servers send requests to the power meter connected to the gateway GW1 in order to monitor the available battery level of some devices. Another bandwidth meter is used to calculate the connection speed between the different devices. In fact, the bandwidth meter is able to perform the bandwidth measurement. On the other hand, at the operating system level, a probe can measure the state of hardware resources such as the available RAM. Thus, the corresponding device can send a report to the appropriate M2M controlling server in order to notify it about its current state as well as its emergency degree.

IV. THE PROPOSED APPROACH

We propose a distributed approach which aims at detecting context changes and raising notifications when context changes occur in order to adapt the application behavior accordingly.

Furthermore, in order to adapt an application to the changing context, the application should perform the following steps. It should collect information, analyzes contextual data and finally triggers the decided adaptation actions. Our approach depicted in Figure 3 is structured around this issue. In fact, it involves two main components: a component First, the context collecting from different sources. This task is performed by the "Context Collector". Second, the context interpretation which aims at processing context information and computing high level observations. Once achieved, processed context information are stored in a "Context Database" which is used finally by the "Context Analyzer" in order to analyze stored context information and detect context changes.

In this paper, we focus on context information analysis performed by the "Context Analyzer". The "Context Analyzer" retrieves context information from the context database, analyzes it and tracks down the context changes using thresholds. Afterwards, the "Context Analyzer" notifies the application in order to execute the appropriate adaptation actions.

In our work, we consider computing context called resource context. Resource context constitutes the constraints imposed by the surrounding environment. For instance, the battery level, the available memory, the CPU load are examples of resource context.

A. Resource context classification

The diversity and the heterogeneity of devices and the network connectivity that ubiquitous environments provide, open the door to different resource context classification methods where context resources are combined in different ways to exploit.

A first classification divides resource context into two categories: Resource context related to the devices and resource context related to the network communication.

• Resource context related to the device

This category corresponds to the resources which characterize the device such as the available memory, the CPU frequency, the CPU load and the battery level. • Resource context related to the network communication This category deals with the resources that characterize the network communications as the network bandwidth, the network connectivity, the communication link load , the loss rate and the latency. Despite the simplicity and the ease of this classification, it remains inappropriate to use. In fact, this classification doesn't take into account the resource behavior which is necessary especially in such systems that are characterized by an important evolution of the resource behavior. Second, we recall that our purpose is to define an approach that aims to detect context changes based on thresholds.

As a result, our idea consists on classifying resource context according to the resource evolution behavior.

This classification divides the resource context into two families: Resources whose behavior is characterized by a tendency and resources whose behavior is characterized by peaks. In the following, we present each family separately.

1) Resources with behavior characterized by a tendency: This family concerns resources whose model roughly coincides to a trendline as denoted in the Figure 4. In this class, we are interested to the tendency. This class includes resources whose behavior evolves (increase, decrease) in a constant way within time.

The battery level mentioned in the case study detailed previously is an example of this category. The available memory, the latency belong also to this class resource context classification.

B. Threshold calculation

We have proposed a resource context classification which takes into account the resource evolution behavior.

Since we base our approach on thresholds for detecting context changes, we present the threshold calculation for each resource class.

We propose to attribute for each resource parameter belonging to a category, n thresholds and for each threshold, we assign a notification or a signal. This notification, defined by an expert, corresponds to an emergency degree or a need for adaptation that depends on the need of the expert or the application itself. The thresholds can be either predefined or adaptive ones.

Afterwards, we give some elements about threshold calculation for each category detailed previously.

1) Threshold calculation for the resources whose evolution behavior is characterized by a tendency: For this category, we remind that the resource evolution behavior is described by a tendency. In order to avoid false detections as well as missing alarms, we need to define thresholds which are uncorrelated with the resource tendency evolution behavior. Thus, a notification is raised whenever the tendency curve crosses the threshold one. Different kinds of thresholds can be applied for this class, such as fixed thresholds, adaptive thresholds and step function thresholds.

For instance, fixed thresholds may be defined by the application designer according to the resource characteristic. Then, a notification is raised once the resource crosses the threshold as depicted in the Figure 6(a).

For the adaptive threshold denoted in the Figure 6(b), mathematical methods can be applied in order to update threshold values at runtime such as the Exponential Weighted Moving Average technique used in [START_REF] Lahyani | Qos monitoring and analysis approach for publish/subscribe systems deployed on manet[END_REF]. However, for this kind of resource context characterized by a tendency, adaptive threshold must be uncorrelated with the resource evolution behavior in order to avoid false detections and missing alarms. Finally, for the step function threshold described in the Figure 6(c), thresholds are defined per period and notifications are raised when the resource behavior crosses the thresholds.

Let's consider the example of the battery level depicted in the previous section. In this example, whenever the battery level values remain under the threshold, a notification is raised. In the Figure 6(c), we use the thresholds modeled as a step function. Hence, we raise different level depending on the battery state. For example, in Figure 6(a), Figure 6(b), when the battery level values decrease until reaching a critical value under the threshold, an alarm is forwarded to the M2M server in order to switch the corresponding device.

2) Threshold calculation for the resources whose evolution behavior is characterized by peaks: In the second category of resource context whose evolution behavior is characterized by abrupt changes, specifying adaptive thresholds that are correlated with the resource evolution behavior tendency is an appropriate method for setting thresholds. Indeed, in this family, peaks characterize sudden changes form a normal behavior to an abnormal one. For that reason, adaptive thresholds correlated with the resource evolution behavior remain under the resource shape. Furthermore, a violation of the threshold reveals a context change. We illustrate the feasibility of our approach through a remote hardware maintenance application. This scenario shows how the application behavior is updated according to context changes and highlights the need for context modification at runtime. A computer company buys new devices such as laptops, desktop computers, PDAs, routers, etc. Furthermore, each new device embeds an analysis entity that implements our approach in order to detect resource context changes such as Battery level, available bandwidth, etc. Eric, the manager of the company decides to control daily the devices state as well as the communication links reliability. Bob is the employee selected to perform this work. To achieve this task, every day, Bob brings his PDA which contains a notebook application, equipped with a logical sensor, running a sender and a receiver program and connected to a power meter enabling him to monitor the battery state of his device as well as the other devices in the company. He starts then supervising the company hardware state. First of all, Bob broadcasts periodic messages through the network to monitor the devices state (ON, OFF), but also to check the network connectivity. Once a timestamp is elapsed without receiving a signal from the devices, in that case, Bob is notified that there is either lossy links or faulty devices or both. The bandwidth meter connected to Bob's PDA as depicted in the Figure 2 starts monitoring the communication links. At each moment, Bob notes in its mobile device the message number through the corresponding link. By using the analysis approach, Bob decides that the link is overloaded, so that the bandwidth is in a critical state which engenders lossy links. Afterwards, Bob decides to monitor his mobile device state. So he starts by supervising the battery level and he initiates this task by applying threshold for this resource. In fact, since the battery level belongs to the first category detailed in section IV, Bob chooses three thresholds. Each one corresponds to an emergency degree: "Normal Battery", "Almost Low Battery" and "Low Battery". So when the power meter attached to his mobile device detects that the battery level of his mobile device reaches the "Low Battery" state, hence, the PDA switches to a poor mode omitting pictures and reducing contrast. After plugging his device, the PDA returns to its normal mode.

The scenario justifies the context awareness of the application in order to cope with different resources constraints and to adapt its behavior accordingly.

VI. CONCLUSION AND FUTURE WORK

In this paper, we have proposed an approach for the context changes detection in collaborative ubiquitous environments. Our approach is composed of two major components. A "Context Provider" and a "Context Manager". The "Context Provider" is out of the scope of this paper. In fact, we focus on the "Context Manager". The latter is divided into four components such as a "Context Collector", a "Context Interpreter", a "Context Database" and a "Context Analyzer". The "Context Analyzer" is the key component of our approach. Indeed, it is responsible for analyzing context information, detecting the context changes and forwarding notifications to the application when necessary. The "Context Analyzer" relies on thresholds in order to detect context changes. In our work, we have considered computing context to deal with as we have focused on resource context. Furthermore, we have presented a bi-classification of resource context according to the resource evolution behavior. A first category deals with resources whose behavior is modeled by a trendline. A second category concerns resources whose behavior is characterized by abrupt changes.

As future work, we plan to implement our analysis approach and to integrate it into the framework FACUS [START_REF] Sancho | Adaptation d'architectures logicielles collaboratives dans les environnements ubiquitaires. contribution l'interoprabilit par la smantique[END_REF]. Then we intend to use ontologies in order to model context information.

Figure 1 .

 1 Figure 1. Context classification

  [9], Zheng et al have addressed the issue of context change detection by proposing a contextaware middleware which conforms to the CORBA component model. The proposed middleware is composed of context aware services such as a context collector, a context interpreter, a context repository and a context analyzer. The latter is in charge of filtering and analyzing context information to determine relevant context changes and notifies the application afterwards. Furthermore, context filtering is based on a comparison of the context values saved in the context repository with the new context value in order to detect context changes.

Figure 2 .

 2 Figure 2. Entreprise monitoring use case

Figure 3 .

 3 Figure 3. The proposed approach

Figure 4 .

 4 Figure 4. Battery level evolution within time

Figure 5 .

 5 Figure 5. Latency evolution within time

Figure 6 .

 6 Figure 6. Threshold calculation for the resource whose evolution behavior is characterized by a tendency

Figure 7 .

 7 Figure 7. Threshold calculation for the resources whose evolution behavior is characterized by a peak

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ACKNOWLEDGMENT

This research is supported by the ITEA2's A2NETS (Autonomic Services in M2M Networks) project 1 .