[pt] O objetivo deste trabalho é avaliar a contaminação da água subterrânea por metais pesados provenientes da Área de Disposição de Resíduos (ADR) do município de Resende, RJ. O escopo compreende um estudo preliminar com base em levantamento e mapeamento de dados espaciais; investigação in situ e em laboratório, incluindo a instalação de poços de monitoramento, amostragens e caracterização de solos, águas subterrâneas e chorume, ensaios de condutividade hidráulica, K; e modelagem da pluma de contaminação usando o programa MIKE SHE. Em geral, a caracterização apresentou argilas arenosas, siltes arenosos e, areias siltosas, cujos principais minerais foram quartzo, caulinita, e muscovita com presença de biotita e feldspato. Os valores de K variaram de 10(-5) a 10(-6) m/s; o pH entre 4,59 e 6,93 (água subterrânea) e 7,93 e 8,16 (chorume); a condutividade elétrica na água variou de 0,032 a 7,113 mS/cm, coerente com os sólidos totais dissolvidos e com maiores valores no chorume e no poço mais próximo a ADR. Análises detectaram 14 metais dissolvidos (Al, As, B, Ba, Cd, Co, Cr, Fe, Hg, Mn, Ni, Pb, Se e Zn) em concentrações acima do permissível por lei. A modelagem mostrou como a distribuição espacial e a anisotropia dos solos influenciam o fluxo e transporte do cloreto (advectivo) e do cromo (sorção). Quando são considerados solos anisotrópicos, a pluma de Cl- atinge o Rio Paraíba do Sul, à 2,5 km de distância, em 43 anos enquanto a pluma do Cr dista apenas 55 m da fonte. Embora os resultados experimentais não tenham sido claros em determinar se todos os metais encontrados são necessariamente da fonte de contaminação da ADR ou de origens naturais, as simulações deste modelo indicaram baixo impacto ambiental dos metais para o rio. / [en] The objective of this work is to evaluate the groundwater contamination due to heavy metals from the Waste Disposal Area (WDA) in the municipality of Resende, RJ. The scope consists of a preliminary assessment based on surveying and mapping spatial data; in situ and laboratory investigation, including the installation of monitoring wells, sampling and characterization of soils, groundwater and waste leachate, hydraulic conductivity tests, K; and contaminant plume modelling using the program MIKE SHE. Overall, the characterization revealed sandy clays, sandy silts and silty sands. The predominant minerals were quartz, kaolinite, and muscovite along with the presence of biotite and feldspar. The values of K varied from 10(-5) to 10(-6) m/s; the pH between 4.59 and 6.93 (groundwater) and 7.93 and 8.16 (leachate); the electrical conductivity in the water varied from 0.032 to 7.113 mS/cm, consistent with the total dissolved solids and with higher values attributed to the leachate and the well closest to the WDA. Analysis detected 14 dissolved metals (Al, As, B, Ba, Cd, Co, Cr, Fe, Hg, Mn, Ni, Pb, Se and Zn) with concentrations above the legal limit. The model illustrated how the soils spatial distribution and anisotropy influence the flow and transport of chloride (advective) and chromium (sorption). When considering anisotropic soils, the Clplume reached the Paraíba do Sul River, 2.5 km away, in 43 years while the Cr plume only moved 55 m from the source. Although the experimental results were not clear in determining whether all the metals found necessarily originated from the contaminant source from the WDA or from natural origins, the simulations of this model indicated a low environmental impact to the river.

Site characterization is an important task in Geotechnical Engineering. In situ tests based on standard penetration test (SPT), cone penetration test (CPT) and shear wave velocity survey are popular among geotechnical engineers. Site characterization using any of these properties based on finite number of in-situ test data is an imperative task in probabilistic site characterization. These methods have been used to design future soil sampling programs for the site and to specify the soil stratification. It is never possible to know the geotechnical properties at every location beneath an actual site because, in order to do so, one would need to sample and/or test the entire subsurface profile. Therefore, the main objective of site characterization models is to predict the subsurface soil properties with minimum in-situ test data. The prediction of soil property is a difficult task due to the uncertainities. Spatial variability, measurement ‘noise’, measurement and model bias, and statistical error due to limited measurements are the sources of uncertainities. Liquefaction in soil is one of the other major problems in geotechnical earthquake engineering. It is defined as the transformation of a granular material from a solid to a liquefied state as a consequence of increased pore-water pressure and reduced effective stress. The generation of excess pore pressure under undrained loading conditions is a hallmark of all liquefaction phenomena. This phenomena was brought to the attention of engineers more so after Niigata(1964) and Alaska(1964) earthquakes. Liquefaction will cause building settlement or tipping, sand boils, ground cracks, landslides, dam instability, highway embankment failures, or other hazards. Such damages are generally of great concern to public safety and are of economic significance. Site-spefific evaluation of liquefaction susceptibility of sandy and silty soils is a first step in liquefaction hazard assessment. Many methods (intelligent models and simple methods as suggested by Seed and Idriss, 1971) have been suggested to evaluate liquefaction susceptibility based on the large data from the sites where soil has been liquefied / not liquefied. The rapid advance in information processing systems in recent decades directed engineering research towards the development of intelligent models that can model natural phenomena automatically. In intelligent model, a process of training is used to build up a model of the particular system, from which it is hoped to deduce responses of the system for situations that have yet to be observed. Intelligent models learn the input output relationship from the data itself. The quantity and quality of the data govern the performance of intelligent model. The objective of this study is to develop intelligent models [geostatistic, artificial neural network(ANN) and support vector machine(SVM)] to estimate corrected standard penetration test (SPT) value, Nc, in the three dimensional (3D) subsurface of Bangalore. The database consists of 766 boreholes spread over a 220 sq km area, with several SPT N values (uncorrected blow counts) in each of them. There are total 3015 N values in the 3D subsurface of Bangalore. To get the corrected blow counts, Nc, various corrections such as for overburden stress, size of borehole, type of sampler, hammer energy and length of connecting rod have been applied on the raw N values. Using a large database of Nc values in the 3D subsurface of Bangalore, three geostatistical models (simple kriging, ordinary kriging and disjunctive kriging) have been developed. Simple and ordinary kriging produces linear estimator whereas, disjunctive kriging produces nonlinear estimator. The knowledge of the semivariogram of the Nc data is used in the kriging theory to estimate the values at points in the subsurface of Bangalore where field measurements are not available. The capability of disjunctive kriging to be a nonlinear estimator and an estimator of the conditional probability is explored. A cross validation (Q1 and Q2) analysis is also done for the developed simple, ordinary and disjunctive kriging model. The result indicates that the performance of the disjunctive kriging model is better than simple as well as ordinary kriging model. This study also describes two ANN modelling techniques applied to predict Nc data at any point in the 3D subsurface of Bangalore. The first technique uses four layered feed-forward backpropagation (BP) model to approximate the function, Nc=f(x, y, z) where x, y, z are the coordinates of the 3D subsurface of Bangalore. The second technique uses generalized regression neural network (GRNN) that is trained with suitable spread(s) to approximate the function, Nc=f(x, y, z). In this BP model, the transfer function used in first and second hidden layer is tansig and logsig respectively. The logsig transfer function is used in the output layer. The maximum epoch has been set to 30000. A Levenberg-Marquardt algorithm has been used for BP model. The performance of the models obtained using both techniques is assessed in terms of prediction accuracy. BP ANN model outperforms GRNN model and all kriging models. SVM model, which is firmly based on the theory of statistical learning theory, uses regression technique by introducing -insensitive loss function has been also adopted to predict Nc data at any point in 3D subsurface of Bangalore. The SVM implements the structural risk minimization principle (SRMP), which has been shown to be superior to the more traditional empirical risk minimization principle (ERMP) employed by many of the other modelling techniques. The present study also highlights the capability of SVM over the developed geostatistic models (simple kriging, ordinary kriging and disjunctive kriging) and ANN models. Further in this thesis, Liquefaction susceptibility is evaluated from SPT, CPT and Vs data using BP-ANN and SVM. Intelligent models (based on ANN and SVM) are developed for prediction of liquefaction susceptibility using SPT data from the 1999 Chi-Chi earthquake, Taiwan. Two models (MODEL I and MODEL II) are developed. The SPT data from the work of Hwang and Yang (2001) has been used for this purpose. In MODEL I, cyclic stress ratio (CSR) and corrected SPT values (N1)60 have been used for prediction of liquefaction susceptibility. In MODEL II, only peak ground acceleration (PGA) and (N1)60 have been used for prediction of liquefaction susceptibility. Further, the generalization capability of the MODEL II has been examined using different case histories available globally (global SPT data) from the work of Goh (1994). This study also examines the capabilities of ANN and SVM to predict the liquefaction susceptibility of soils from CPT data obtained from the 1999 Chi-Chi earthquake, Taiwan. For determination of liquefaction susceptibility, both ANN and SVM use the classification technique. The CPT data has been taken from the work of Ku et al.(2004). In MODEL I, cone tip resistance (qc) and CSR values have been used for prediction of liquefaction susceptibility (using both ANN and SVM). In MODEL II, only PGA and qc have been used for prediction of liquefaction susceptibility. Further, developed MODEL II has been also applied to different case histories available globally (global CPT data) from the work of Goh (1996). Intelligent models (ANN and SVM) have been also adopted for liquefaction susceptibility prediction based on shear wave velocity (Vs). The Vs data has been collected from the work of Andrus and Stokoe (1997). The same procedures (as in SPT and CPT) have been applied for Vs also. SVM outperforms ANN model for all three models based on SPT, CPT and Vs data. CPT method gives better result than SPT and Vs for both ANN and SVM models. For CPT and SPT, two input parameters {PGA and qc or (N1)60} are sufficient input parameters to determine the liquefaction susceptibility using SVM model. In this study, an attempt has also been made to evaluate geotechnical site characterization by carrying out in situ tests using different in situ techniques such as CPT, SPT and multi channel analysis of surface wave (MASW) techniques. For this purpose a typical site was selected wherein a man made homogeneous embankment and as well natural ground has been met. For this typical site, in situ tests (SPT, CPT and MASW) have been carried out in different ground conditions and the obtained test results are compared. Three CPT continuous test profiles, fifty-four SPT tests and nine MASW test profiles with depth have been carried out for the selected site covering both homogeneous embankment and natural ground. Relationships have been developed between Vs, (N1)60 and qc values for this specific site. From the limited test results, it was found that there is a good correlation between qc and Vs. Liquefaction susceptibility is evaluated using the in situ test data from (N1)60, qc and Vs using ANN and SVM models. It has been shown to compare well with “Idriss and Boulanger, 2004” approach based on SPT test data. SVM model has been also adopted to determine over consolidation ratio (OCR) based on piezocone data. Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. SVM model outperforms all the available methods for OCR prediction.

Die Uferfiltration (UF) ist eine potentielle Alternative zur konventionellen Oberflächenwasseraufbereitung in Indien, da Trübstoffe, pathogene Mikroorganismen und organische Wasserinhaltsstoffe effektiv entfernt werden. In dieser Arbeit wurde erstmals ein umfangreicher Überblick zu bestehenden UF-Anlagen in Indien erarbeitet. Für die Standorterkundung und -bewertung wurde ein Konzept erarbeitet, das an drei Standorten entlang des Ganges getestet und weiterentwickelt wurde. Das Konzept umfasst vier Stufen: Standortvorerkundung, Bestimmung von Grundwasserleiterparametern, Erfassung von hydraulischen und Beschaffenheits-parametern sowie numerische Grundwasser-strömungsmodellierung. Entlang des oberen Flusslaufes des Ganges (Haridwar und Srinagar) wurden günstige geohydraulische Verhältnisse identifiziert (kf = 10E-4 bis 10E-3 m/s, Grundwasser leitermächtigkeit 11 bis 20 m). Entlang des unteren Flusslaufes (Patna) gibt es in Abhängigkeit von der Mächtigkeit der Sedimentablagerungen im Ganges nur bei erhöhter Schleppkraft im Monsun eine gute hydraulische Verbindung zwischen dem Fluss und dem Grundwasserleiter. In Haridwar wurde der Uferfiltratanteil im Rohwasser mittels Isotopenanalysen (δ18O) und Leitfähigkeitsmessungen im Fluss- und Rohwasser ermittelt. Der Uferfiltratanteil in den auf einer Insel und südlich davon gelegenen Brunnen liegt bei bis zu 90%. An den untersuchten Standorten wird durch die UF eine effektive Entfernung von E. coli um 3,5 bis 4,4 Log10 und der Trübung bis >2 Log10 Einheiten erreicht. Eine Entfernung von 3 Log10 Einheiten wurde bereits bei einer Fließzeit des Uferfiltrats von zwei Tagen beobachtet. Die erhöhte Anzahl an Coliformen in einigen Brunnen am Standort Haridwar resultiert aus Verunreinigungen des landseitigen Grundwassers. Bei Hochwässern und Starkregenereignissen muss eine Kontamination durch den direkten Eintrag von Wasser durch undichte Brunnenabdeckungen, Risse in den Schächten bzw. unsachgemäßen Brunnenbau berücksichtigt werden. Die Anwendung des angepassten Untersuchungskonzepts an 15 weiteren UF-Standorten in Indien hat gezeigt, dass die niedrigen DOC-Konzentrationen im Flusswasser (0,9 bis 3,0 mg/L) und im Brunnenwasser (0,4 bis 2,3 mg/L) günstig für die Anwendung der UF sind. Bei erhöhten DOC-Konzentrationen (Vormonsun) im Flusswasser konnte in Delhi und Mathura im Monsun eine 50%ige Verminderung erreicht werden. Bei der Erkundung neuer UF-Standorte in bergigen Gebieten sind die Grundwasserleitermächtigkeit mit geophysikalischen Erkundungsverfahren, die Strömungsverhältnisse in den alluvialen Ablagerungen sowie lokale Hochwasserrisiken zu untersuchen. / Riverbank filtration or bank filtration (RBF / BF) is a potential alternative to the direct abstraction and conventional treatment of surface water by virtue of the effective removal of pathogens, turbidity, suspended particles and organic substances. A comprehensive overview of existing RBF systems in India has been compiled for the first time. To systematically select and investigate new and existing potential RBF sites in India, a methodological concept was developed and tested at three sites along the Ganga River. The four stages of the concept are: initial site-assessment, basic site-survey, monitoring of water quality and quantity parameters and determination of aquifer parameters and numerical groundwater flow modelling. Suitable geohydraulic conditions for RBF (hydraulic conductivity: 10E-4 to 10E-3 m/s, aquifer thickness: 11 to 20 m) exist along the upper course of the Ganga (Haridwar and Srinagar). Due to the presence of fine sediment layers beneath the river bed along the Ganga’s lower course (Patna), river-aquifer interaction occurs during increased shear stress on the riverbed in monsoon. The portion of bank filtrate abstracted by the wells in Haridwar was determined from isotope analyses (Oxygen 18) and electrical conductivity measurements of river and well water and is up to 90% for wells located on an island and between the river and a canal. The results were confirmed by groundwater flow modelling. A high removal of E. coli (3.5 to 4.4 Log10 units) and turbidity (>2 Log10 units) was observed at the investigated sites. An E. coli removal of 3 Log10 units was observed for short travel times of 2 days. Higher coliform counts in some wells occur due to contamination from landside groundwater. During floods and intense rainfall events, contamination of RBF wells from direct entry of flood water, seepage of surface runoff into the well through leaky covers, fissures in the well-heads / caissons and in-appropriately sealed well-bases has to be considered. The application of the adapted investigation concept to 15 other sites in India showed that the low DOC concentrations in river water (0.9 to 3.0 mg/L) and well-water (0.4 to 2.3 mg/L) are favourable for the application of RBF. A 50% decrease of the high (pre-monsoon) DOC concentration was observed during monsoon in Delhi and Mathura. For the exploration of new RBF sites in hilly / mountainous areas, investigations of the aquifer thickness using geophysical methods, subsurface flow conditions in the alluvial deposits and the risk from floods should be conducted.

Offshore developments for hydrocarbon resources have now progressed to water depths approaching 2500 m. Due to the difficulties and high cost in recovering high quality samples from deepwater site, there is increasing reliance on in situ tests such as piezocone and full-flow (i.e. T-bar and ball) penetration tests for determining the geotechnical design parameters. This research was undertaken in collaboration with the Norwegian Geotechnical Institute (NGI), as part of a joint industry project, to improve the reliability of in situ tests in determining design parameters and to improve offshore site investigation practice in deepwater soft sediments. In this research, a worldwide high quality database was assembled and used to correlate intact and remoulded shear strengths (measured from laboratory and vane shear tests) with penetration resistances measured by piezocone, T-bar and ball penetrometers. The overall statistics showed similar and low levels of variability of resistance factors for intact shear strength (N-factors) for all three types of penetrometer. In the correlation between the remoulded penetration resistance and remoulded shear strength, the resistance factors for remoulded shear strength (Nrem-factors) were found higher than the N-factors. As a result, the resistance sensitivity is less than the strength sensitivity. The correlations between the derived N-factors and specific soil characteristics indicated that the piezocone N-factors are more influenced by rigidity index than those for the T-bar and ball penetrometers. The effect of strength anisotropy is only apparent in respect of N-factors for the T-bar and ball penetrometers correlated to shear strengths measured in triaxial compression. On the other hand, the Nrem-factors showed slight tendency to increase with increasing strength sensitivity but were insensitive to soil index properties. These findings suggest that the full-flow penetrometers may be used to estimate remoulded shear strength and are potentially prove more reliable than the piezocone in estimating average or vane shear strength for intact soil but the reverse is probably true for the estimation of triaxial compression strength.

Die Uferfiltration (UF) ist eine potentielle Alternative zur konventionellen Oberflächenwasseraufbereitung in Indien, da Trübstoffe, pathogene Mikroorganismen und organische Wasserinhaltsstoffe effektiv entfernt werden. In dieser Arbeit wurde erstmals ein umfangreicher Überblick zu bestehenden UF-Anlagen in Indien erarbeitet. Für die Standorterkundung und -bewertung wurde ein Konzept erarbeitet, das an drei Standorten entlang des Ganges getestet und weiterentwickelt wurde. Das Konzept umfasst vier Stufen: Standortvorerkundung, Bestimmung von Grundwasserleiterparametern, Erfassung von hydraulischen und Beschaffenheits-parametern sowie numerische Grundwasser-strömungsmodellierung. Entlang des oberen Flusslaufes des Ganges (Haridwar und Srinagar) wurden günstige geohydraulische Verhältnisse identifiziert (kf = 10E-4 bis 10E-3 m/s, Grundwasser leitermächtigkeit 11 bis 20 m). Entlang des unteren Flusslaufes (Patna) gibt es in Abhängigkeit von der Mächtigkeit der Sedimentablagerungen im Ganges nur bei erhöhter Schleppkraft im Monsun eine gute hydraulische Verbindung zwischen dem Fluss und dem Grundwasserleiter. In Haridwar wurde der Uferfiltratanteil im Rohwasser mittels Isotopenanalysen (δ18O) und Leitfähigkeitsmessungen im Fluss- und Rohwasser ermittelt. Der Uferfiltratanteil in den auf einer Insel und südlich davon gelegenen Brunnen liegt bei bis zu 90%. An den untersuchten Standorten wird durch die UF eine effektive Entfernung von E. coli um 3,5 bis 4,4 Log10 und der Trübung bis >2 Log10 Einheiten erreicht. Eine Entfernung von 3 Log10 Einheiten wurde bereits bei einer Fließzeit des Uferfiltrats von zwei Tagen beobachtet. Die erhöhte Anzahl an Coliformen in einigen Brunnen am Standort Haridwar resultiert aus Verunreinigungen des landseitigen Grundwassers. Bei Hochwässern und Starkregenereignissen muss eine Kontamination durch den direkten Eintrag von Wasser durch undichte Brunnenabdeckungen, Risse in den Schächten bzw. unsachgemäßen Brunnenbau berücksichtigt werden. Die Anwendung des angepassten Untersuchungskonzepts an 15 weiteren UF-Standorten in Indien hat gezeigt, dass die niedrigen DOC-Konzentrationen im Flusswasser (0,9 bis 3,0 mg/L) und im Brunnenwasser (0,4 bis 2,3 mg/L) günstig für die Anwendung der UF sind. Bei erhöhten DOC-Konzentrationen (Vormonsun) im Flusswasser konnte in Delhi und Mathura im Monsun eine 50%ige Verminderung erreicht werden. Bei der Erkundung neuer UF-Standorte in bergigen Gebieten sind die Grundwasserleitermächtigkeit mit geophysikalischen Erkundungsverfahren, die Strömungsverhältnisse in den alluvialen Ablagerungen sowie lokale Hochwasserrisiken zu untersuchen.:Abstract i (Seitenzahl / page number) Acknowledgements iii Table of contents v List of tables viii List of figures ix Abbreviations and symbols xi 1 Introduction 1 1.1 Problem description 1 1.2 Riverbank filtration and its potential in India 2 1.3 Motivation 3 1.4 Aims 4 2 Bank filtration in context to India’s water resources 5 2.1 Water budget of India and the Ganga River catchment 5 2.1.1 Water budget 5 2.1.2 The Ganga River catchment 6 2.2 Problems of surface water abstraction for drinking water production 8 2.2.1 Effect of low surface flows on the quantity of raw water abstraction 8 2.2.2 Effect of the monsoon on conventional drinking water treatment plants using directly abstracted surface water 9 2.2.3 Quality of surface water 10 2.2.4 Treatment of directly abstracted surface water for drinking 11 2.3 Sustainability issues of groundwater abstraction 11 2.4 Drinking water consumption in India 12 2.5 Bank filtration for water supply 14 2.5.1 Geohydraulic, siting and design aspects of bank filtration systems 14 2.5.2 Water quality aspects 15 2.5.3 Water quality aspects for bank filtration in India 15 2.5.4 Risks to riverbank filtration sites from floods 16 2.6 Hypotheses favouring the use of bank filtration and the need for a concept to investigate potential RBF sites in India 17 3 Study areas 18 3.1 Choice of study areas 18 3.2 Case study site Haridwar 19 3.3 Case study site Patna 20 3.4 Case study site Srinagar in Uttarakhand 21 3.5 Hypotheses favouring RBF at the selected study sites 22 4 Methodology for the investigation of the case study sites 24 4.1 Overview of methodology for investigating the case-study sites 24 4.2 Investigations at the case study site of Haridwar 25 4.2.1 Initial site-assessment 25 4.2.2 Basic site-survey and establishing monitoring infrastructure 26 4.2.2.1 Identification of specific locations for monitoring wells 26 4.2.2.2 Geodetic survey and inventory of existing on-site infrastructure 26 4.2.2.3 Construction of exploratory wells 27 4.2.3 Determination of hydrogeological parameters 27 4.2.3.1 Sediment analyses 27 4.2.3.2 Determination of hydraulic conductivity by pump tests on large-diameter wells 29 4.2.4 Water level and stable isotope measurements 30 4.2.4.1 Water level 30 4.2.4.2 Stable isotopes 31 4.2.5 Water quality monitoring 31 4.2.5.1 Initial investigations, screening and formulation of monitoring concept 31 4.2.5.2 Comprehensive and regular monitoring 2011 - 2013 33 4.3 Investigations at the case study site of Patna 34 4.3.1 Initial site-assessment, basic-site survey and monitoring 34 4.3.2 Sampling for water quality and isotope analyses 35 4.4 Investigations at the case study site of Srinagar in Uttarakhand 35 4.4.1 Basic site-survey and establishing monitoring infrastructure 35 4.4.1.1 Identification of a specific location for a new RBF well 35 4.4.1.2 Construction of production and monitoring wells and exploratory boreholes 37 4.4.2 Determination of hydrogeological parameters and monitoring 38 4.4.2.1 Sediment analyses and determination of hydraulic conductivity of the aquifer 38 4.4.3 Water quality monitoring 40 4.5 Column experiments to determine the removal of bacteriological indicators under field conditions 40 5 Characterisation of the RBF system in Haridwar 42 5.1 Site and design aspects 42 5.1.1 Location of RBF wells 42 5.1.2 Design of RBF wells 44 5.1.3 Quantity of drinking water produced by RBF 45 5.2 Aquifer characterisation 47 5.3 Numerical groundwater flow model of RBF well field in Haridwar 49 5.3.1 Model set-up 49 5.3.2 Model calibration 50 5.4 Origin of water and mean portion of bank filtrate abstracted by RBF wells 52 5.5 Water quality 53 5.6 Analysis of presence of thermotolerant coliforms in RBF wells 56 5.7 Impact of regulated Upper Ganga Canal on RBF wells on Pant Dweep 58 5.8 Summary of case study site Haridwar 60 5.8.1 Aspects related to water quality 60 5.8.2 Benefit of groundwater flow modelling 60 6 Evaluation of the potential for RBF in Patna 62 6.1 Physiography and hydrogeology 62 6.1.1 South Ganga Plain 62 6.1.2 Patna 63 6.2 Ground and surface water levels 65 6.3 Ganga River morphology 66 6.4 Water quality 67 6.5 Numerical groundwater flow model of case study site Patna 68 6.5.1 Model geometry and initial conditions 68 6.5.2 Boundary conditions 69 6.5.3 Steady-state flow modelling 70 6.6 Isotope analyses 71 6.7 Summary of case study site Patna 71 7 Evaluation of the potential for RBF in Srinagar 73 7.1 Drinking water production and overview of geomorphology 73 7.2 RBF site characterisation 74 7.2.1 Aquifer geometry and material 74 7.2.2 Water levels 75 7.2.3 Hydraulic conductivity 76 7.3 Numerical groundwater flow model of case study site Srinagar 77 7.3.1 Model geometry and calibration 77 7.3.2 Origin of bank filtrate and travel time 78 7.4 Water quality 79 7.5 Discussion and summary of case study site Srinagar 81 8 Assessment of risks from floods and insufficient sanitary measures to RBF wells in Haridwar and Srinagar 82 8.1 Flood-risk identification from field investigations 82 8.1.1 Description of an extreme flood event in Haridwar 82 8.1.2 Description of an extreme flood event in Srinagar 82 8.1.3 Summary of identifiable risks 83 8.2 Assessment of risks to RBF wells 84 8.2.1 Design of wells and direct contamination 84 8.2.2 Field investigations on the removal of bacteriological indicators 85 8.2.3 Removal of coliforms under field conditions by column experiments 87 8.3 Proposals to mitigate risks at RBF sites Haridwar and Srinagar 89 8.3.1 Operational and technical aspects for a general risk management plan 89 8.3.2 Health aspects for a general risk management plan 89 8.3.3 Criteria for flood protection measures of RBF wells 90 8.3.4 Sanitary sealing of RBF wells 90 9 Application of initial site-assessment to investigate other RBF sites in India 92 9.1 Hydrogeology and system-design 92 9.1.1 RBF systems for small and large-scale urban water supply 92 9.1.2 “Koop” well RBF systems for small-scale rural water supply 98 9.2 Water quality parameters 98 9.2.1 Removal of bacteriological indicators by RBF 98 9.2.2 Removal of dissolved organic carbon and organic micropollutants by RBF 101 9.2.3 Inorganic parameters 102 10 Conclusions, recommendations and propagation of RBF 105 10.1 Hydrogeological and system-design considerations 105 10.2 Aspects for improvement of the concept for RBF site investigations 106 10.3 Policy and planning aspects for the propagation of RBF in India 108 References 110 Annexes 121 / Riverbank filtration or bank filtration (RBF / BF) is a potential alternative to the direct abstraction and conventional treatment of surface water by virtue of the effective removal of pathogens, turbidity, suspended particles and organic substances. A comprehensive overview of existing RBF systems in India has been compiled for the first time. To systematically select and investigate new and existing potential RBF sites in India, a methodological concept was developed and tested at three sites along the Ganga River. The four stages of the concept are: initial site-assessment, basic site-survey, monitoring of water quality and quantity parameters and determination of aquifer parameters and numerical groundwater flow modelling. Suitable geohydraulic conditions for RBF (hydraulic conductivity: 10E-4 to 10E-3 m/s, aquifer thickness: 11 to 20 m) exist along the upper course of the Ganga (Haridwar and Srinagar). Due to the presence of fine sediment layers beneath the river bed along the Ganga’s lower course (Patna), river-aquifer interaction occurs during increased shear stress on the riverbed in monsoon. The portion of bank filtrate abstracted by the wells in Haridwar was determined from isotope analyses (Oxygen 18) and electrical conductivity measurements of river and well water and is up to 90% for wells located on an island and between the river and a canal. The results were confirmed by groundwater flow modelling. A high removal of E. coli (3.5 to 4.4 Log10 units) and turbidity (>2 Log10 units) was observed at the investigated sites. An E. coli removal of 3 Log10 units was observed for short travel times of 2 days. Higher coliform counts in some wells occur due to contamination from landside groundwater. During floods and intense rainfall events, contamination of RBF wells from direct entry of flood water, seepage of surface runoff into the well through leaky covers, fissures in the well-heads / caissons and in-appropriately sealed well-bases has to be considered. The application of the adapted investigation concept to 15 other sites in India showed that the low DOC concentrations in river water (0.9 to 3.0 mg/L) and well-water (0.4 to 2.3 mg/L) are favourable for the application of RBF. A 50% decrease of the high (pre-monsoon) DOC concentration was observed during monsoon in Delhi and Mathura. For the exploration of new RBF sites in hilly / mountainous areas, investigations of the aquifer thickness using geophysical methods, subsurface flow conditions in the alluvial deposits and the risk from floods should be conducted.:Abstract i (Seitenzahl / page number) Acknowledgements iii Table of contents v List of tables viii List of figures ix Abbreviations and symbols xi 1 Introduction 1 1.1 Problem description 1 1.2 Riverbank filtration and its potential in India 2 1.3 Motivation 3 1.4 Aims 4 2 Bank filtration in context to India’s water resources 5 2.1 Water budget of India and the Ganga River catchment 5 2.1.1 Water budget 5 2.1.2 The Ganga River catchment 6 2.2 Problems of surface water abstraction for drinking water production 8 2.2.1 Effect of low surface flows on the quantity of raw water abstraction 8 2.2.2 Effect of the monsoon on conventional drinking water treatment plants using directly abstracted surface water 9 2.2.3 Quality of surface water 10 2.2.4 Treatment of directly abstracted surface water for drinking 11 2.3 Sustainability issues of groundwater abstraction 11 2.4 Drinking water consumption in India 12 2.5 Bank filtration for water supply 14 2.5.1 Geohydraulic, siting and design aspects of bank filtration systems 14 2.5.2 Water quality aspects 15 2.5.3 Water quality aspects for bank filtration in India 15 2.5.4 Risks to riverbank filtration sites from floods 16 2.6 Hypotheses favouring the use of bank filtration and the need for a concept to investigate potential RBF sites in India 17 3 Study areas 18 3.1 Choice of study areas 18 3.2 Case study site Haridwar 19 3.3 Case study site Patna 20 3.4 Case study site Srinagar in Uttarakhand 21 3.5 Hypotheses favouring RBF at the selected study sites 22 4 Methodology for the investigation of the case study sites 24 4.1 Overview of methodology for investigating the case-study sites 24 4.2 Investigations at the case study site of Haridwar 25 4.2.1 Initial site-assessment 25 4.2.2 Basic site-survey and establishing monitoring infrastructure 26 4.2.2.1 Identification of specific locations for monitoring wells 26 4.2.2.2 Geodetic survey and inventory of existing on-site infrastructure 26 4.2.2.3 Construction of exploratory wells 27 4.2.3 Determination of hydrogeological parameters 27 4.2.3.1 Sediment analyses 27 4.2.3.2 Determination of hydraulic conductivity by pump tests on large-diameter wells 29 4.2.4 Water level and stable isotope measurements 30 4.2.4.1 Water level 30 4.2.4.2 Stable isotopes 31 4.2.5 Water quality monitoring 31 4.2.5.1 Initial investigations, screening and formulation of monitoring concept 31 4.2.5.2 Comprehensive and regular monitoring 2011 - 2013 33 4.3 Investigations at the case study site of Patna 34 4.3.1 Initial site-assessment, basic-site survey and monitoring 34 4.3.2 Sampling for water quality and isotope analyses 35 4.4 Investigations at the case study site of Srinagar in Uttarakhand 35 4.4.1 Basic site-survey and establishing monitoring infrastructure 35 4.4.1.1 Identification of a specific location for a new RBF well 35 4.4.1.2 Construction of production and monitoring wells and exploratory boreholes 37 4.4.2 Determination of hydrogeological parameters and monitoring 38 4.4.2.1 Sediment analyses and determination of hydraulic conductivity of the aquifer 38 4.4.3 Water quality monitoring 40 4.5 Column experiments to determine the removal of bacteriological indicators under field conditions 40 5 Characterisation of the RBF system in Haridwar 42 5.1 Site and design aspects 42 5.1.1 Location of RBF wells 42 5.1.2 Design of RBF wells 44 5.1.3 Quantity of drinking water produced by RBF 45 5.2 Aquifer characterisation 47 5.3 Numerical groundwater flow model of RBF well field in Haridwar 49 5.3.1 Model set-up 49 5.3.2 Model calibration 50 5.4 Origin of water and mean portion of bank filtrate abstracted by RBF wells 52 5.5 Water quality 53 5.6 Analysis of presence of thermotolerant coliforms in RBF wells 56 5.7 Impact of regulated Upper Ganga Canal on RBF wells on Pant Dweep 58 5.8 Summary of case study site Haridwar 60 5.8.1 Aspects related to water quality 60 5.8.2 Benefit of groundwater flow modelling 60 6 Evaluation of the potential for RBF in Patna 62 6.1 Physiography and hydrogeology 62 6.1.1 South Ganga Plain 62 6.1.2 Patna 63 6.2 Ground and surface water levels 65 6.3 Ganga River morphology 66 6.4 Water quality 67 6.5 Numerical groundwater flow model of case study site Patna 68 6.5.1 Model geometry and initial conditions 68 6.5.2 Boundary conditions 69 6.5.3 Steady-state flow modelling 70 6.6 Isotope analyses 71 6.7 Summary of case study site Patna 71 7 Evaluation of the potential for RBF in Srinagar 73 7.1 Drinking water production and overview of geomorphology 73 7.2 RBF site characterisation 74 7.2.1 Aquifer geometry and material 74 7.2.2 Water levels 75 7.2.3 Hydraulic conductivity 76 7.3 Numerical groundwater flow model of case study site Srinagar 77 7.3.1 Model geometry and calibration 77 7.3.2 Origin of bank filtrate and travel time 78 7.4 Water quality 79 7.5 Discussion and summary of case study site Srinagar 81 8 Assessment of risks from floods and insufficient sanitary measures to RBF wells in Haridwar and Srinagar 82 8.1 Flood-risk identification from field investigations 82 8.1.1 Description of an extreme flood event in Haridwar 82 8.1.2 Description of an extreme flood event in Srinagar 82 8.1.3 Summary of identifiable risks 83 8.2 Assessment of risks to RBF wells 84 8.2.1 Design of wells and direct contamination 84 8.2.2 Field investigations on the removal of bacteriological indicators 85 8.2.3 Removal of coliforms under field conditions by column experiments 87 8.3 Proposals to mitigate risks at RBF sites Haridwar and Srinagar 89 8.3.1 Operational and technical aspects for a general risk management plan 89 8.3.2 Health aspects for a general risk management plan 89 8.3.3 Criteria for flood protection measures of RBF wells 90 8.3.4 Sanitary sealing of RBF wells 90 9 Application of initial site-assessment to investigate other RBF sites in India 92 9.1 Hydrogeology and system-design 92 9.1.1 RBF systems for small and large-scale urban water supply 92 9.1.2 “Koop” well RBF systems for small-scale rural water supply 98 9.2 Water quality parameters 98 9.2.1 Removal of bacteriological indicators by RBF 98 9.2.2 Removal of dissolved organic carbon and organic micropollutants by RBF 101 9.2.3 Inorganic parameters 102 10 Conclusions, recommendations and propagation of RBF 105 10.1 Hydrogeological and system-design considerations 105 10.2 Aspects for improvement of the concept for RBF site investigations 106 10.3 Policy and planning aspects for the propagation of RBF in India 108 References 110 Annexes 121