Investigating Groundwater Salinity in the Machile-Zambezi Basin (Zambia) with Hydrogeophysical Methods

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Investigating groundwater salinity in the Machile-Zambezi Basin (Zambia) with hydrogeophysical methods

Chongo, Mkhuzo

Publication date: 2015

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Investigating groundwater salinity in the Machile-Zambezi Basin (Zambia) with hydrogeophysical methods

Mkhuzo Chongo

PhD Thesis June 2015

Investigating groundwater salinity in the Machile-Zambezi Basin (Zambia) with hydrogeophysical methods

Mkhuzo Chongo

PhD Thesis June 2015

DTU Environment Department of Environmental Engineering Technical University of Denmark

Mkhuzo Chongo

Investigating groundwater salinity in the Machile-Zambezi Basin (Zambia) with hydrogeophysical methods

PhD Thesis, June 2015

The synopsis part of this thesis is available as a pdf-file for download from the DTU research database ORBIT: http://www.orbit.dtu.dk

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Cover: Torben Dolin Preface This PhD thesis is a presentation of the work conducted under the supervision of Associate Professor Peter Bauer-Gottwein between 1st December 2011 and 2nd March 2015 at the Technical University of Denmark (DTU) with extensive field work in the Machile-Zambezi Basin in south-western Zambia. The work was funded by the Danish Ministry of Foreign Affairs (DANIDA) under the programme for capacity building for the Zambian Water Sector - Phase II. Co supervisors included Anders Vest Christiansen, PhD (Associate Professor, Department of Geosciences, Aarhus University); Imasiku A. Nyambe, PhD (Professor, Geology Department, University of Zambia); and Flemming Larsen, PhD (Head of Department, Geological Survey of Denmark and Greenland). The first part of the thesis is a synopsis that puts into context the main findings of the PhD project. It is based on the second part which gives a detailed account of the work done in the form of three scientific papers referred to as papers I, II, and III. The titles of the three papers are:

I Chongo, M., Christiansen, A.V., Tembo, A., Banda, K.E., Nyambe, I.A., Larsen, F., and Bauer-Gottwein, P. 2014. Airborne and ground based transient electromagnetic mapping of groundwater salinity in the Machile-Zambezi Basin, south-western Zambia. Accepted for publication in Near Surface Geophysics Journal (in press).

II Chongo, M., Christiansen, A.V., Fiandaca, G., Nyambe, I.A., Larsen, F., and Bauer-Gottwein, P .2015. Mapping localized freshwater anomalies in the brackish Paleo-Lake sediments of the Machile- Zambezi Basin with transient electromagnetic sounding, geoelectrical imaging and induced polarization. Submitted to Journal of Applied Geophysics.

III Chongo, M., Nyambe, I.A., Larsen, F., and Bauer-Gottwein, P, 2015. Coupled hydrogeophysical inversion using a groundwater flow and transport model, and transient electromagnetic and direct current electrical resistivity data. Manuscript.

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iv Acknowledgements I wish to express my thanks and gratitude to all institutions and individuals that have been instrumental to the successful execution and completion of my PhD studies. It is not possible for me to list each and every one of them due to constraints of space on the paper except for a very select few; nevertheless I am truly grateful to all. I would like to thank the Danish Government for funding this research through its Ministry of Foreign Affairs and to the Zambian Government through the Department of Water Affairs under Phase II of the programme to build capacity in the Zambian Water Sector. I would also like to thank my principle supervisor Peter Bauer Gottwein (PhD) for the coaching, encouragement and guidance throughout this period. I am equally grateful to my co- supervisors Anders Vest Christiansen (PhD), Imasiku Anayawa Nyambe (PhD) and Flemming Larsen (PhD). A note of acknowledgement and thanks is also extended to the entire departmental and PhD administration at DTU-Environment and also to the Water Resources Engineering Section faculty members and colleagues. I would also like to appreciate the significant technical support from the Hydrogeophysics group at the Department of Geosciences, Aarhus University with respect to processing and inversion of various geophysical data. Finally, I would like to thank friends and colleagues who supported me by their companionship during my field work in Sesheke and Kazungula districts in Zambia. This also applies to the management and staff at the University of Zambia School of Mines. Last but not the least; I would like to thank my family for only they know how much water has gone under the bridge and the Lord God Almighty for all his goodness and tender mercies.

v Summary The importance of knowing the current state of groundwater resources cannot be over emphasized in rural areas in the developing countries with limited water resources. As such, innovative geophysical techniques are now part of the norm for quick and effective characterization of groundwater resources worldwide. This thesis presents the application of geo-electrical and electromagnetic methods for the investigation of groundwater salinity in the Machile-Zambezi Basin in south western Zambia, southern central Africa. Aerial and ground based transient electromagnetic measurenments were used to map the spatial distribution of apparent electrical resistivity on a regional scale in order to obtain a regional overview of groundwater salinization based on electrical resistivity correlation. Furthermore, ground based transient electromagnetic soundings and direct current and induced polarization measurements were used to investigate on a local scale, indications of surface water/ groundwater exchange from electrical resistivity anomalies coincident with alluvial fans and flood plains as deduced from the aerial electrical resistivity result. New and innovative geophysical data inversion schemes were also developed and used to gain a better explanation of the data collected. These include a new scheme for the joint inversion of direct current and induced polarization data, and transient electromagnetic data; and a new coupled hydrogeophysical inversion setup to allow for the first time the joint use of direct current and transient electromagnetic data in one optimization.

The result from the regional mapping with transient electromagnetic measurenments showed a spatial distribution of electrical resistivity that indicated block faulting in the Machile-Zambezi Basin. Saline groundwater was found to occur predominantly in the low lying graben areas that are essentially an extension of the Palaeo Lake Makgadikgadi system into south western Zambia. In addition, surface water from the Zambezi River was found to interact with saline aquifers to such an extent that the surficial physical form of alluvial fans and flood plains was visible in the spatial distribution of electrical resistivity from the aerial survey up to a depth of about 40 m.

Interpretation of direct current and induced polarization, and transient electromagnetic data using the new joint inversion scheme revealed a fresh water lens overlying the saline aquifer at Kasaya in Kazungula District, Zambia. The freshwater lens appeared to be in hydraulic contact with the

vi Zambezi River where it was thickest (60 m) and had the highest electrical resistivity values (about 200 Ωm) which steadily declined to about 30 Ωm whereas the thickness reduced to around 22 m at the end of the 6 600 m long transect line measured perpendicular to the Zambezi River towards the North. The distribution of chargeability along the Kasaya transect line was found to be correlated with the distribution of electrical resistivity thus giving a strong indication of the intrusion of fresh surface water into a pre-existing saline aquifer. It is postulated that the intrusion of fresh surface water in to the saline aquifer was driven by evapotranspiration. Finally, the new coupled hydrogeophysical inversion approach resulted in sharp estimates of hydrogeological model parameters. This was for a coupled flow and solute transport model setup for the Kasaya transect under the forcing of evapotranspiration. Performance of the coupled hydrogeophysical inversion was better with the inclusion of direct current data in comparison to the use of transient electromagnetic data alone.

The broader implications of these findings is that groundwater salinization in the Machile Zambezi Basin is now known to be strongly influenced by the tectonism of the Palaeo Lake Makgadikgadi system and is therefore not expected to increase over time. Rather, surface water tends to interact with the saline aquifers in places to create freshwater lenses that are an important source of clean drinking water. Therefore, the findings of this thesis will need to be augmented with data and further research from other geoscience disciplines such as surface water hydrology, geochemistry, petrology and meteorology in order to come up with sustainable water resources management practices that are applicable to arid and semi-arid sedimentary basins in general and the Machile-Zambezi Basin in particular within the broader context of the Kalahari Basin of southern Africa. This will make it possible to project the effects of climate variability and anthropogenic activities on the water resources with a view of disaster preparedness and mitigation for which this part of the world is particularly vulnerable.

vii Dansk sammenfatning Vigtigheden af et kendskab forekomsten af grundvandsressourcens kan ikke overvurderes i landområder i den tredje verden med begrænset vandressourcer. I forbindelse med beskrivelse forekomsten af vandressourcer, er anven- delsen af nye, hurtige og effektive geofysiske metoder et vigtigt element. I denne PhD afhandling præsenteres anvendelse af geoelektriske og elektromagnetiske metoder til undersøgelse saltforekomster i grundvandet i Machi- le-Zambezi bassinet i Zambia, i det sydlige Afrika. Den rumlige fordeling af jordlagenes tilsyneladende elektriske modstand er målt med anvendelse af luftbåren og landbaseret transient elektromagnetiske målinger med henblik på kortlægning af forekomsten af salt grundvand. Derudover er landbaseret elektromagnetiske sonderinger og elektrisk målinger, sammen med induceret polarisations, blevet anvendt på lokal skala med det formål at påvise overflade- grundvandsinteraktion. Nye og innovative metoder til inversion af geofysiske data er blevet udviklet, og anvendt til at opnå en bedre tolkning og anvendelse af indsamlede data. Dette omfatter blandt andet en ny metode for sammen- hængende inversion af elektriske data, induceret polarisations data og transient elektromagnetiske data; samt en ny koblet hydrogeofysisk inversionsmetode, der for første gang gør det muligt at foretage en samlet anvendelse af elektriske og elektromagnetiske data i en optimeringsrutine. Den regionale kortlægning med den transiente elektromagnetiske metode viser en rumlig fordeling af elektriske modstande, der indikerer blokforkastning i Machile-Zambezi bassinet. Salt grundvand forekommer hovedsagelig i lavt- liggende dele af grabenstrukturen, der er en forlængelse af Palaeo Makgadik- gadi søen ind i den sydlige del af Zambia. Det er blevet påvist, at interaktionen af overfladevand fra Zambezi floden med salt grundvand er så omfatten- de, at den kan registreres til 40 meters dybde med luftbårne opmålte elektriske modstand i alluvialfane og flodplan sedimenterne. Tolkningen af elektriske målinger, induceret polarisationsmålinger og elektromagnetiske data, med anvendelse af den nyudviklede koblerede inversionsmetode, viste, at fersk grundvand ligger over salt grundvand ved Kasaya i Kazaungula distriktet, Zambia. Hvor ferskvandslinsen er tykkest (60 m), ser den ud til at være i hydraulisk kontakt med Zambezi floden, og have maksi- male elektriske modstand (200 Ωm), som gradvist aftager til 30 Ωm, hvor tykkelsen af ferskvandslaget er reduceret til 22 m for enden af et 6600 m langt transekt, opmålt fra Zambezi floden og vinkelret mod nord. Fordelingen af sedimenterne kapacitet til elektrisk opladning langs Kasaya transektet kor-

viii relerer med dets fordeling af elektrisk modstand, og viser derved en stærk indikation på intrusion af fersk overfladevand ind i salt grundvand, hvor salt- dannelsen skyldes evapotranspiration. Endelig har den nyudviklede, koblede hydrogeofysiske inversionsmetode re- sulteret i en pålidelig bestemmelse af hydrogeologiske model parametre. Det- te blev påvist i en koblet strømnings- og transportmodel for Kansaya transektet, med klimatisk betinget forøgelse af evapotranspirationen. Med anvendelse af den koblede hydrogeofysiske inversionsrutine, blev resultaterne forbed- ret med indarbejdning af elektriske modstandsdata, sammenlignet med an- vendelsen af udelukkende transient elektromagnetiske data. Den overordnede betydning af disse resultater er den, at forekomsten af salt grundvand i høj grad er påvirket af tidligere tektoniske forhold i området, hvor Palaeo Makgadikgadi søens sedimenter forekommer, er det må derfor forventes, at saltforekomsterne ikke fremover vil blive mere udbredt i områ- det. Tværtimod synes interaktionen med overfaldevand at skabe en linse af ferskvand, der har stor betydning med henblik på etablering af drikkevands- forsyninger. Derfor bør resultaterne fra dette studie uddybes med nye data og yderligere forskning fra andre geovidenskabelig discipliner, såsom hydrologi, geokemi, petrologi og meteorologi for at tilvejebringe generelle, bæredygtige løsninger til god praksis til forvaltning af vandressourcer i aride og semi- aride områder, og især i Machile-Zambezi Bassinet og i Kalakari Bassinet i det sydlige Afrika. Dette vil gøre det muligt at belyse effekterne af klimafor- andringer og andre antropogene påvirkninger af vandressourcen med det for- mål at skabe beredskab og forebyggelse i forhold til sygdomsbekæmpelse for en befolkning, der især i denne del af verden, er sårbar.

x Table of contents Preface ...... iii Acknowledgements ...... v Summary ...... vi Dansk sammenfatning ...... viii Table of contents ...... xi 1 Introduction ...... 1 1.1 Motivation ...... 1 1.2 State of the art ...... 1 1.3 Research objectives ...... 2 1.4 Structure of the thesis ...... 3 2 Background and context ...... 5 2.1 TEM for groundwater applications ...... 5 2.2 DCIP for groundwater applications ...... 6 2.3 Hydrogeophysical inversion ...... 6 2.4 Hydrodynamic modelling ...... 7 3 The study area ...... 9 3.1 Geomorphological setting ...... 9 3.2 Geological setting ...... 10 3.3 Hydrological setting ...... 11 3.4 Socio-economic aspects ...... 11 3.5 Wildlife ...... 12 3.6 Data archive ...... 13 4 Materials and methods ...... 15 4.1 Airborne and ground based transient electromagnetic measurements ...... 15 4.2 Direct current and induced polarization measurements ...... 16 4.3 Processing and inversion of TEM and DCIP data ...... 18 4.3.1 Data processing ...... 18 4.3.2 Data inversion ...... 18 4.4 Coupled hydrogeophysical inversion ...... 19 5 Main findings...... 21 5.1 Regional electrical resistivity variations ...... 21 5.2 Localised freshwater/ groundwater interaction ...... 22 5.3 Freshwater intrusion into saline aquifer ...... 23 5.4 Utility of electrical and electromagnetic methods ...... 24 5.5 Coupled hydrogeophysical inversion with combined DC and TEM data ..... 24 6 Discussion ...... 27 7 Conclusion ...... 31 8 Outlook and Perspectives ...... 33 9 References ...... 35 10 APPENDIX: Inventory of electronic material ...... 43 11 Papers ...... 45

xi xii 1 Introduction The Earth is a very watery planet considering that about 70% of it is covered by water in addition to occurrences in the atmosphere and subsurface. How- ever, with respect to human habitat and environmental concerns, only a very small percentage is available as renewable freshwater reserves in the form of surface water and shallow groundwater Postel et al. (1996). The renewability of these fresh water resources (and hence their availability for continued sustained use) is very sensitive to climatic variability and anthropogenic activities (Srinivasan et al., 2012; Cassardo, 2014; Collet et al., 2014). Therefore in order to mitigate against the adverse effects of climate change or human socio-economic development on fresh water reserves such as groundwater, it is imperative that the condition of the respective water resources are constantly assessed and the impacts of the various stresses (such as reduced precipitation, pollution or abstraction) on the water resources themselves are quanti- fied. This would then form a basis upon which decision makers can make judgements about the best choices that would ensure sustainability of water resource utilization (Kinzelbach et al., 2003). 1.1 Motivation Arguably, nowhere is this more important and critical than in arid and semi- arid regions where much of the hydrological cycle oscillates between ex- tremes of precipitation (or flooding) and drought (Buytaert et al., 2012). As a result the dependence on groundwater is increased in such regions (Kinzelbach et al., 2003) like in the Kalahari Basin of southern Africa (McCarthy and Haddon, 2005; McCarthy, 2013). Thus for countries like An- gola, Botswana, Namibia and Zambia that have got significant territory and populations within the Kalahari Basin, knowledge of the properties and characteristics of the Kalahari aquifer system is absolutely crucial. Where available, such knowledge could then be used for important planning decisions such as the placement of water points in relation to human settlements or the zoning of new settlements based on the quality and quantity of groundwater reserves. 1.2 State of the art Various tools and methods have been developed and are still being developed that enable a relatively rapid and cost effective means of characterization of groundwater resources (Kinzelbach et al., 2003). These include ground based and airborne transient electromagnetics (TEM)(Auken et al., 2003;

1 Christiansen, 2003; Yan et al., 2009; Ezersky et al., 2011; Xue et al., 2012), direct current and induced polarization (DCIP)(Dahlin, 2001; Dahlin et al., 2002; Dahlin and Zhou, 2006; Loke et al., 2013), and hydrodynamic modelling(Rosbjerg and Madsen, 2005; Bauer et al., 2006a; Bauer et al., 2006b). The TEM methods are applied around the world on both regional and local scales and have been shown to be useful for investigation of regional trends on groundwater quality variations and detailed local scale site characterisation (Melloul and Goldenberg, 1997; Bauer-Gottwein et al., 2010; Chongo et al., 2011; Ezersky et al., 2011; Xue et al., 2012; Herckenrath et al., 2013b; Juanah et al., 2013; Podgorski, 2014). On the other hand, DCIP techniques are more suited for detailed local scale investigations since they can only be effectively deployed on ground based systems. However, recent innovations in data acquisition systems has given rise to DCIP instrumentation that com- bines the benefits of high spatial density, cost effectiveness and the integration of the measurement of both direct current and induced polarization in one field setting (Aristodemou and Thomas-Betts, 2000; Dahlin and Zhou, 2006; Poulsen et al., 2010; Gazoty et al., 2012; Loke et al., 2013). Therefore it is increasingly becoming common to design hydrogeological investigations that incorporate multiple types of geophysical data which can then be incorporated within the context of a hydrodynamic model (Ferré et al., 2009; Hinnell et al., 2010). This then has resulted in a powerful means of evaluating aquifer system behaviour under various stresses such as evapotranspiration and anthropogenic factors like contamination and water abstraction. 1.3 Research objectives The objectives of the research presented in this thesis were to:  Gain a better understanding of the occurrence of saline groundwater in the Machile-Zambezi Basin in south-western Zambia related to propagation of the Palaeo Lake Makgadikgadi system through the Okavango-Linyati fault system into Zambia;  Make a detailed local scale evaluation, at Kasaya in south western Zambia, of high electrical resistivity anomalies (> 100 Ωm) overlying a generally low electrical resistivity (< 13 Ωm) subsurface based on local scale DCIP and TEM measurements using a new DCIP-TEM joint inversion scheme. Areas with such high electrical resistivity anomalies were identified based on the results of the regional scale TEM mapping and appeared to be related to surface water groundwater exchange; and

2  Further develop a coupled hydro geophysical inversion framework for application to a river-aquifer solute transport problem under evapotranspiration to enable calibration with both DC and TEM data for the first time. 1.4 Structure of the thesis As mentioned above this thesis is divided into two parts. The first part is a synopsis that provides a background, context and overview of the research conducted at DTU Environment and extensive field campaigns in Kazungula and Sesheke districts of south western Zambia since December 2011 to date. The synopsis therefore comprises an introduction which briefly outlines the purpose and significance of the research (Chapter 1); a background and context which puts the thesis in the context of recent scientific developments and state of the art (Chapter 2); a description of the study area (Chapter 3); and a short overview of the methods used (Chapter 4). The main findings are presented in Chapter 5 whereas the discussion and conclusion are presented in chapters 6 and 7 respectively. The second part of the thesis comprises three papers which are a fulfilment of the three overall research objectives stated above respectively. To the best of our knowledge, this study has mapped for the first time the Palaeo Lake Makgadikgadi sediments in the Machile-Zambezi Basin using regional scale ground based and airborne TEM measurements. It has also demonstrated that TEM is effective for mapping groundwater quality (salinity) variations in a sedimentary setting such as that of the Machile-Zambezi Basin (Paper I). Re- gional scale TEM and local scale DCIP and TEM surveys give evidence of significant groundwater surface water interaction in the Machile-Zambezi Basin. Furthermore, the distribution of electrical resistivity and induced polarization at a study site at Kasaya in Kazungula District, Zambia indicatives recent intrusion of surface water into a pre-existing saline aquifer (Paper II). The intrusion of fresh surface water under evapotranspiration was evaluated using a new CHI that includes both DCIP and TEM data. The CHI showed the evapotranspiration does seem to be the main climatic excitation driving the surface water/ groundwater exchange given the simplifications and consequent limitations in the coupled flow and salinity transport model that was used. The CHI approach was thus shown to have tremendous potential as an effective and cost saving tool for hydrological model validation and geophysical data interpretation (Paper III).

4 2 Background and context Hydrogeophysics is a relatively young area of research often classified as a sub discipline of Hydrology even though it has its origins in the fields of mineral and petroleum exploration (Rubin and Hubbard, 2006; Auken et al., 2009a). The increasing interest in the use of geophysical methods as part of hydrological investigations probably stems from the need for a better understanding of how hydrological systems particularly groundwater resources re- spond to stresses such as climatic variability, pollution and long term abstraction. Furthermore, classical methods of groundwater investigation such as pumping tests, slug tests, core sample analysis and geophysical borehole logging can only be conducted as point measurements within a well or a borehole as and as a consequence will usually not be able to adequately capture lateral or spatial variations of hydrological parameters (Rubin and Hubbard, 2006). This lack of spatial data density and variability can potentially be ad- dressed by the incorporation of appropriate geophysical methods into hydrological investigations. Recent research efforts have therefore been directed at finding ways and means of using geophysical methods to provide accurate and reliable estimates of hydrological parameters such as hydraulic conductivity and porosity in addition to describing hydrological processes like groundwater flow and solute transport (Christiansen, 2010; Dafflon et al., 2010; Pollock and Cirpka, 2010; Christiansen et al., 2011; Busch et al., 2013; Herckenrath et al., 2013b). This has led to rapid developments in geophysical instrumentation, data handling and inversion. Transient electromagnetics (TEM) and direct current and induced polarization (DCIP), which are the main focus of this thesis, are two of the most commonly used geophysical methods for water resource or hydrogeological applications that have been extensively developed and improved in recent years. 2.1 TEM for groundwater applications TEM systems which are typically deployed as either ground based or airborne have seen the advent of instrumentation that is equally suited for traditional geological exploration as well as for hydrogeophysical applications using a high moment for deeper information and a low moment for shallow information. Furthermore, older instrumentation that is not equipped with the low moment-high moment concept can equally be used for hydrogeophysical applications provided it is calibrated with a just a few accurate ground based

5 TEM soundings from the survey area (Podgorski et al., 2013). Thus TEM has been successfully used for hydrogeological applications such as regional scale salinity mapping (Guerin et al., 2001; Chongo et al., 2011; Ezersky et al., 2011; Viezzoli et al., 2012)and aquifer characterization (Auken et al., 2003; Auken et al., 2009b; Siemon et al., 2009) and local scale salty water – freshwater interaction studies(Albouy et al., 2001; Bauer-Gottwein et al., 2010; Nenna et al., 2013). 2.2 DCIP for groundwater applications DC and IP have benefited from recent innovations that now make it possible to measure DC and IP in one field setup (hence the term DCIP) using multichannel instruments that not only greatly reduce the amount of time spent in the field but can at the same time increase the amount of data collected per field setting (Dahlin, 2001; Dahlin and Zhou, 2006; Loke et al., 2013; Singha et al., 2014). Examples of hydrogeological considerations to which DCIP has been applied include groundwater flow and solute transport, groundwater salinization (including salty water freshwater interaction in coastal and inland areas), surface water/ groundwater exchange and groundwater contamination or pollution at landfill or other sites (Aristodemou and Thomas-Betts, 2000; Nassir et al., 2000; Binley et al., 2002; Muller et al., 2005; Bauer et al., 2006c; Muller et al., 2010; Vaudelet et al., 2011; Fernandes et al., 2012; Gazoty et al., 2012; Singha et al., 2014; Van Dam et al., 2014). 2.3 Hydrogeophysical inversion CHI is one of three approaches that can be used to inform groundwater models with geophysical data. The other two are sequential hydrogeophysical inversion (SHI) in which a groundwater model is setup, parameterised and calibrated based on prior and independently inverted geophysical models; and joint hydrogeophysical inversion (JHI) in which geophysical and hydrological model parameters are inverted at the same time and related through petro physical relations (Herckenrath et al., 2013a). Thus SHI follows the traditional approach with which geophysical data has been used for hydrological purposes whereas CHI and JHI are relatively recent developments that run the geophysical and hydrological inversions simultaneously with exchange of information taking place both ways. Nevertheless they differ in the sense that CHI minimises the difference between hydrological state variables (e.g. solute concentration) and instrument responses through a petro physical trans- formation of the state variables and subsequent forward response calculation. JHI however inverts for both hydrological model parameters (e.g. hydraulic

6 conductivity) and geophysical model parameters (e.g. electrical resistivity) at the same time; with the hydrological and geophysical parameters being constrained by an appropriate petro physical relationship such as the log-linear relationship between hydraulic conductivity and electrical resistivity. 2.4 Hydrodynamic modelling Hydrodynamic modelling as applied to water resources in general and groundwater in particular provides an avenue through which scientific theo- ries about hydrological phenomenon and the interplay between different hydrological processes can be tested, validated or disproved. Thus in practice hydrodynamic modelling formulates required hydrological processes in a ge- neric mathematical/ numerical construct which can then be applied to specific hydrological conceptualizations and parameterizations (Rosbjerg and Madsen, 2005; Todini, 2007). Examples of standard mathematical/ numerical constructs applicable to groundwater include MODFLOW (Harbaugh, 2005 ; Hanson et al., 2014) for groundwater flow modelling, MT3DMS for reactive and solute transport modelling (Zheng and Wang, 1999) and SEWAT (Langevin et al., 2007) for coupled flow and reactive transport modelling. Thus any given model application is at best a parsimonious simplification of natural systems which explains to some degree observed processes and phenomenon. The performance of the model will therefore largely depend on the chosen conceptualization (e.g. layering of the subsurface and stresses in a groundwater model) and parametrizations (e.g. aquifer properties such as hydraulic conductivity and porosity). However there is often a great deal of uncertainty about some or all aspects of the conceptualization and model parameters. A standard approach of dealing with this uncertainty is through the use of in situ data to calibrate and validate the model (Rosbjerg and Madsen, 2005). Quite often the data is very sparsely distributed (e.g. point measurenments of hydraulic head and solute concentration from a limited number of boreholes in a wide geographic area) and because of this, model calibration efforts can often be unsatisfactory. However, geophysical measurenments overcome the limitations on data density since they can be more easily and cost effectively deployed on both local and regional scales. Thus the incorporation of geophysical data into classical and innovative model calibrations should lead to improvements in model parameter estimations and reduced uncertainty (Hinnell et al., 2010).

8 3 The study area The Machile-Zambezi Basin straddles Kazungula and Sesheke districts in the Southern and Western provinces of Zambia. It was hydrologically defined for purposes of this research as the catchment area with outlet on the Zambezi River at 17o 50.4’ S and 25o38’E but not exceeding the areal extent defined by latitude 16o - 17o 54’ S and longitude 24o 13’ – 26o 22’ E and within the Zambian territory. Thus it covers an area of about 26, 260 km2 which includes the northern extent of the Palaeo Lake Makgadikgadi Basin (Okavan- go-Linyati depression) and the catchment areas of three major streams called Loanja, Machile and Ngwezi. The location of the Machile Zambezi Basin is shown in Fig. 1.

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! 020 40 80 120 160 ! ! ! Km 22°30’0"E 24°0’0"E 25°30’0"E 27°0’0"E Fig. 1: Location of the Machile-Zambezi in Zambia, southern Africa in relation to the Lake Palaeo Makgadikgadi Basin. 3.1 Geomorphological setting The landforms and features of the Machile-Zambezi Basin are characteristic of a fluvial sedimentary environment with an intermittent - ephemeral river network that is prone to extensive flooding. This river network is entrenched onto a topography that is broadly divided into upland and low land areas. The upland areas or hilly belt with altitude between 950 – 1150 m above

9 mean sea level surround the low lying areas (935 -950 m above mean sea level) in form of an arc that stretches from the north western extent of the basin through the Machile-Kafue Watershed in the north east until the south eastern extent of the Basin. The Zambezi River forms the northwest to southeast boundary of the Basin into which many of the streams drain whereas others terminate into alluvial fans before reaching the Zambezi River. A topographic map of the Machile-Zambezi Basin which also depicts the surface geology is shown in Fig. 2.

N 200,000 250,000 300,000 350,000 400,000 450,000 WE

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Fig. 2: Topographic map of the Machile-Zambezi Basin also depicting the surface geology. 3.2 Geological setting The low lying areas occupy a position that appears to be a continuity in the form of a topographic depression that extends all the way down and across the Zambezi River then into the Okavango-Linyati depression (McCarthy, 2013). This depression, which is a remnant of the Palaeo Lake Makgadikgadi, is controlled by the Okavango-Linyati fault system whose genesis is the propagation of the East African Rift System through the Tanganyika-Mweru- Upemba-Kabopmbo Gorge axis (Moore et al., 2012) . The tectonic activity responsible for the creation of the Okavango-Linyati Depression is said to be still ongoing and has been responsible for evolution of landforms and drain-

10 age patterns in the entire Kalahari Basin (Moore et al., 2012). The low lying areas are thus underlain by sediments that have in-filled a graben structure often referred to as the Machili Graben or the Machili Basin (Main et al., 2008; Moore et al., 2012; McCarthy, 2013). The stratigraphy of the Machile-Zambezi Basin is a variant of the general stratigraphic setting of the entire Kalahari Basin and comprises a Kalahari Supergroup sand member as the uppermost unit. This in turn is typically underlain by a Kalahari Supergoup sandstone member or in its absence any sequence of stratification ranging from Karoo to Basement Complex. The blan- ket of sand varies in thickness from place to place and is generally thinnest on the outer northwest and southeast fringes of the basin particularly close to the Zambezi River where outcrops of Basalt and Basement Complex rocks respectively are clearly visible. A map depicting the surface geology of the Machile-Zambezi Basin is shown in Fig. 2. 3.3 Hydrological setting As has been mentioned above, the Machile-Zambezi Basin has three main streams of which the Machile and Ngwezi flow directly into the Zambezi River whereas the Loanja terminates in a seasonally flooded alluvial fan adjacent to the Zambezi. The upper reaches of the stream network originate in the forested hilly belt and are characterised by narrow flood plains and intermittent to perennial flow. On the other hand, the lower reaches traverse the low lying areas as they head towards the Zambezi River and are characterised by very wide flood plains and an ephemeral flow regime. Annual precipitation is around 808 mm whereas the actual and potential evapotranspiration are in the order of 616 and 1718 mm per annum (JICA/MEWD-B, 1995). Groundwater recharge has been estimated at 5 % of annual precipitation or around 40 mm per annum. The groundwater regime is predominantly characterised by unconsolidated sand and sandstone aquifer units that have a moderate yield of 3 – 10 l/s and hydraulic conductivities in the order of 1.05 m/day (Chenov, 1978; JICA/MEWD-D, 1995). 3.4 Socio-economic aspects The Machile-Zambezi Basin is a vast rural area with sparse population whose main centres are the towns of Kazungula and Sesheke. The main economic activity is trading with nearby towns like Livingstone in Zambia, Kasane in Botswana and Katima Mulilo in Namibia. Agricultural activity is mostly for subsistence (although some commercial agriculture does take place in the

11 Kazungla area) and involves staple crop production and animal husbandry. A thriving commercial timber industry used to exist in the area but this has now been reduced to small scale operators due to depletion of the timber stock over time. 3.5 Wildlife There exists a great variety of plant and animal species in the Machile- Zambezi Basin. The vast majority of the animal species are confined to the game management areas which are a buffer zone between the Kafue National Park in the northern fringes of the basin and human settlements in the central and southern areas. The Machile-Zambezi Basin also is home to the Machile and Simungoma Important Bird areas given the unique and diverse bird species that live there. Furthermore a new wildlife sanctuary has been estab- lished in the Machile Flats (the Machile Graben area) called Simalaha Com- munity Conservancy (SCC). It is an important wildlife sanctuary in the Ka- vango-Zambezi trans-frontier wildlife conservation area that seeks to re- establish wildlife populations and their migratory routes between the Chobe National Park in Botswana and the Kafue National Park in Zambia. SCC also aims at improving the economic outlook of the local people through tourism and wildlife development (Peace-Parks, 2015).

Fig. 3: Sable Antelope grazing in the dry season on the southern fringes of the Kafue Na- tional park interfacing with the northern areas of the Machile-Zambezi Basin.

12 The main vegetation types are deciduous tall canopy trees and flood plain and dambo grass. The major tree species include Mopane (Veenendaal et al., 2008; Smit, 2014) and Baikiaea plurijuga locally known as Mukusi or Zam- bezi Teak (Childes and Walker, 1987; Richer, 2008). The Mukusi is promi- nent in the hilly belt whereas the Mopane thrives in the low lying areas of the Basin that are close to the Zambezi River. The tall flood plain and dambo types of grass are primarily found in flood plains and dambos (local scale seasonally flooded pans) (Fanshawe, 2010 ).

(a) (b)

Fig. 4: (a) Typical vegetative cover during the rainy season in the low lying areas of the Machile-Zambezi Basin in south-western Zambia. (b) Vegetative cover in a typical flood plain in the Machile-Zambezi Basin in south western Zambia during the rainy season. In the background is the tree line denoting the beginning of the forested area shown in (a). 3.6 Data archive During the course of the research reported in this thesis, a large amount of old and new data was gathered and processed. This includes old ground based TEM data from Chongo et al. (2011) and new DCIP and TEM data (aerial and ground based) from this work. Furthermore, a large amount of new data was created in the form of intermediary TEM and DCIP data files required for inversion in addition to the final inverse models. A significant number of C++ and Matlab scripts were also produced or modified in order to support and implement the innovative inversion schemes herein described. Further- more, geospatial data for the study area was created and managed in two geographic information systems. These were:  ArcGIS (ESRI, 2015) for general spatial data processing and management; and  Aarhus Workbench (HGG, 2014) for processing and inversion of aerial TEM data and spatial visualization of aerial and ground based TEM inverse models.

13 This archive comprising raw data, processed data, programming scripts and geospatial databases is contained in an electronic appendix as out lined in Chapter 9 (Appendix). It may be accessed by contacting:

DTU Environment Technical University of Denmark Miljøvej, Building 113 2800 Kgs. Lyngby Denmark [email protected]

14 4 Materials and methods 4.1 Airborne and ground based transient electromagnetic measurements The TEM (Nabighian, 1988; Nabighian, 1991; Danielsen et al., 2003; Kirsch, 2006) method was used on both local and regional scale for mapping of electrical resistivity variations in the Machile-Zambezi Basin. The regional scale TEM was deployed on both airborne and ground based systems for mapping of the entire basin whereas the local scale TEM was conducted using only ground based TEM equipment on a 6.6 km transect line on the northern bank of the Zambezi River at Kasaya in south western Zambia. The instrumentation that was used for the airborne TEM measurements was the VTEM system from GEOTECH (GEOTECH, 2011) whereas the instrumentation for the ground based TEM comprised WalkTEM (ABEM(b), 2014) and ProTEM equipment. However, data from the ProTEM equipment is not discussed in this thesis. This is because more data was collected with the WalkTEM instrument. In addition, at locations where measurements were collected with both instruments, similar responses were obtained with slightly better measurements from the WalkTEM. The regional TEM survey was designed with two objectives in mind. These were:

 To cover as much area of the Machile-Zambezi Basin as possible given the constraints on time and resources; and  To capture as much geological variations as possible. Therefore with the constraint of 1000 line kilometers for the airborne measurements, the aerial survey was designed with two sets of four flight paths. One set was oriented northeast to southwest whereas another was oriented southeast to northwest. In order to extend the coverage of tem measurements beyond the 1000 line kilometers of the aerial survey, the regional ground based survey was designed to conduct spatially distributed TEM measurements at a spatial density of approximately 25 km2 taking into account the survey objectives mentioned above. The ground based survey was conducted only on the eastern half of the Machile-Zambezi Basin because spatially distributed TEM sounding on the western half of the basin were available from Chongo et al. (2011). The

15 locations of the flight paths and all TEM soundings considered in this thesis are shown in Fig. 5. Further details about the regional TEM mapping including calibration, processing and inversion of the airborne TEM data are given in Paper I. 200,000 250,000 300,000 350,000 400,000 N

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S UTM 35S O le X hi ac 1:2,000,000 .M 8,200,000 R 8,200,000 O O iX z O e b O lo O O O O O u .M RX X OO X X X O O O O X OX O XX X O O O X 8,150,000 lo 8,150,000 O fu X hi O X ic X X R O .S O X R . L X O o a O X n j O LEGEND O a X X X O O O X zi O OO e O e w Xl g Town O O O i N O h X . O c R OO O a X 8,100,000 O O X X 8,100,000 O OXXX O .M X O R Stream O O XXO O X O a O R.Za X Oy O mb XXO a ez OX s X X i a X VTEM Flight Path K . X Sesheke R XX XX WalkTEM 2013 X X 8,050,000 X Kazungula 8,050,000 R.Z X Chongo et. al (2011) ProTEM ambezi O Machile Zambezi Basin

025507510012.5

8,000,000 200,000 250,000 300,000 350,000 400,000 8,000,000 Km Fig. 5: Map showing the location of VTEM flight paths and ground based TEM soundings in the Machile-Zambezi Basin. The ground based TEM soundings coincident with the flight paths were used to calibrate the VTEM signal for amplitude and time shift error. The local scale TEM measurements were collected together with DCIP measurements on a transect line at Kasaya in the Machile Zambezi Basin as described in Section 4.2. Sixty-four TEM soundings were thus collected on the transect line at an approximate spacing of 100 m. 4.2 Direct current and induced polarization measurements DCIP (Binley and Kemna, 2006)measurements were conducted on a 6 600 m transect line across the Simalaha flood plain at Kasaya in the Machile- Zambezi Basin. The Terrameter LS (which is an innovative data acquisition system for self-potential, electrical resistivity and induced polarization) (ABEM(a), 2012) was used for the DCIP measurements in a roll along continuous vertical electrical sounding (CVES) setup (Loke, 1999; Loke et al.,

16 2013) with 5 m electrode spacing. The gradient array (Dahlin and Zhou, 2006) protocol was used in order to take advantage of the multi-channel ca- pabilities of the instrument. This resulted in significant reduction in the amount of time spent in the field but with data quality as good as traditional electrode configurations such as the Wenner and Schlumberger arrays (Dahlin and Zhou, 2004). Location of the Kasaya transect within the Machile-Zambezi Basin is shown in Fig. 6. The site was chosen based on electrical resistivity anomalies from the aerial TEM survey that were indicative of surface water groundwater exchange. Another site that showed similar traits is the Loanja alluvial fan. However this is not treated in this thesis.

24°40’0"E 24°50’0"E 25°0’0"E 25°10’0"E N WE

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ile ch a M . R R . Lo a n ja

17°22’30"S Lipumpu Village X Kasaya School X R a .Zam y be a zi s R.Z a LEGEND a K

m . be zi R X Borehole Simalaha Plain

17°33’0"S Kasaya Transect VTEM flight paths 24°40’0"E 24°50’0"E 25°0’0"E 02.5 5 10 15 20 Km Fig. 6: Location of the Kasaya Transect across the Simalaha Plan in the Machile-Zambezi Basin. Also note the termination of the Loanja River into an alluvial fan which was another area investigated but is not reported for purposes of this thesis. More information about the Kasaya Transect including details about how the data collected was processed in an innovative DCIP-TEM inversion scheme can be found in Paper II.

17 4.3 Processing and inversion of TEM and DCIP data 4.3.1 Data processing The electromagnetic data from the aerial survey was presented in the form of a geo-database by GEOTECH (GEOTECH, 2011). This was imported into the Aarhus Workbench (HGG, 2014) for processing and inversion. The aim of the processing was to remove data affected by coupling and systematic noise and to supress random noise by averaging of the electromagnetic data into soundings. The processing also comprised filtering and averaging of geographic position and altitude data and removal of soundings exceeding a roll or pith angle of 25 degrees. This was followed by visual inspection and editing where required (HGG, 2011). Calibration parameters (Sørensen et al., 2011; Podgorski et al., 2013) for correction of amplitude and time shift errors were added to the data at the processing stage. The calibration parameters (time shift and amplitude shift factor) were derived from calibration of the VTEM signal with corresponding ground based WalkTEM soundings (Paper I). Ground based TEM data was processed for removal of data points affected by noise and coupling using SiTEM-SEMDI (HGG, 2001) and sometimes manually with a text editor after download from the WalkTEM instrument. Unlike the airborne electromagnetic data, the ground based TEM data was processed on an individual sounding basis because the data was collected one sounding at a time at different locations. Finally DCIP data was also imported into the Workbench for automatic processing followed by visual inspection and manual editing (Paper II). 4.3.2 Data inversion Following processing, the airborne electromagnetic data was inverted in the Aarhus Workbench using the laterally constrained inversion (LCI) (Auken et al., 2005) approach on a flight line by flight line basis. This was followed by spatially constrained inversion(Christiansen, 2008; Viezzoli et al., 2009) of the whole aerial dataset in one inversion job. Ground based TEM data collected for the regional survey was inverted separately for each site using Aar- husInv (Auken et al., 2014). However the inverse models were imported into the Aarhus Workbench for synchronization with the aerial TEM inversion result. This facilitated the creation of mean horizontal electrical resistivity maps at various depth intervals for the Machile-Zambezi Basin (Paper I).

18 DCIP and TEM data collected for the Kasaya transect was inverted using AarhusInv under various schemes. These included separate LCIs of DCIP and TEM data; mutually and laterally constrained inversion (MCI)(Christiansen et al., 2007) of DC and TEM data; and finally an innovative MCI of DCIP and TEM data. Details about the inversion of DCIP and TEM data on the Ka- saya Transect are given in Paper II. 4.4 Coupled hydrogeophysical inversion Coupled hydro-geophysical inversion was performed using the Gauss- Marquardt-Levenberg parameter estimation approach (Doherty, 2005) for a simple coupled flow and solute transport model using TEM and DC data. The model was setup for a case of freshwater intrusion into a saline aquifer under evapotranspiration with a fixed river head boundary. SEAWAT (Langevin et al., 2007) was used to implement this hydro-dynamic model which was first calibrated using TEM data and then with an innovative combination of TEM and DC data. The PEST (Doherty, 2005) implementation of the Gauss- Marquardt-Levenberg algorithm (Marquardt, 1963) was used for the minimi- zation of square differences between transformations of simulated SEAWAT concentrations and apparent electrical resistivity from TEM and DC measurements. Thus Archie’s law (Archie, 1941) was used to transform the simulated concentrations into simulated electrical resistivities. The electrical resistivities were then sampled at locations corresponding to the location of respective geophysical data and used for calculation of forward instrument responses or apparent resistivities using AarhusInv (Auken et al., 2014). The optimization was thus performed on the SEAWAT model parameters (e.g. hydraulic conductivity and porosity) and petro-physical parameters (e.g. Archie’s exponent and cementation factor) but evaluated based on the sum of squared differences between the calculated forward responses and measured geophysical data. Further details about the calibration of the SEAWAT model with TEM and DC data are given in Paper III.

20 5 Main findings 5.1 Regional electrical resistivity variations Regional aerial and ground TEM electrical resistivity variations in the Machile-Zambezi Basin reflected the tectonic setting of the Okavango- Linyati fault system and Palaeo Lake Makgadikgadi extension into south- western Zambia. A regional graben-horst system with a northeast to southwest strike was outlined. The horst regions were characterized by resistivities values greater than 100 Ωm on the eastern and western flanges of the basin. However, the graben region was characterized by an area than can be considered to be a full graben in the low lying southern central portions of the basin and an expanse that dips into the full graben from the north east to the southwest. The full graben was found to be characterized by electrical resistivity values less than 13 Ωm whereas the dipping expanse had electrical resistivity values ranging between 10-100 Ωm. The low electrical resistivity values in the graben are attributed to the Palaeo Lake Makgadikgadi sediments. A map depicting the spatial distribution of electrical resistivity values for the deep sub subsurface(80-100 m) is shown in Fig. 7. 200,000 250,000 300,000 350,000 400,000 450,000 N

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UTM 35S ile ch 1:2,000,000 a i 8,200,000 M z 8,200,000 . e R e b il lo h u c .M a R .M a j R R n lo a .M 8,150,000 u 8,150,000 o if a h L c . c i

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i l R e LEGEND zi e w g Town 8,100,000 .N 8,100,000 R Sesheke R . Stream R Za .Za zi m mbe be zi VTEM Flight Path Kazungula

8,050,000 R 8,050,000 .Z am 010 20406080 bez i Km

8,000,000 200,000 250,000 300,000 350,000 400,000 450,000 Fig. 7: Mean horizontal electrical resistivity distribution at depth interval 80-100 m for the Machile-Zambezi Basin from aerial and ground TEM measurements.

21 5.2 Localised freshwater/ groundwater interaction The drainage network of the Machile-Zambezi Basin is such that streams originate in the high elevation areas on the north-western to north-eastern peripheries of the basin. As they flow southwardly towards the Zambezi river, they cross the low relief full graben area. At this stage, some of the streams form very wide flood plains whereas others terminate into alluvial fans. At several locations within the basin, the flood plains and alluvial fans make an imprint onto the electrical resistivity distribution in the shallow subsurface (0-40 m) by anomalously high resistivities (greater than 13.2 Ωm) that are coincident with these surface water features in an otherwise low electrical resistivity subsurface. This was indicative of intermediate to local scale surface water groundwater exchange. A satellite image showing the coincidence of an alluvial fan and flood plain with anomalously high electrical resistivity values in the Machile-Zambezi Basin is shown in Fig. 8.

240,000 250,000 260,000 270,000 280,000 290,000 300,000 310,000 N R .L WE oa nj a S

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ile h ac .M R

8,070,000 R.Zambezi a y i a ez s gw a N

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z R (a) i

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ile ch a .M R R.Zam a bezi y i a ez s gw a N

R.Z R. K a .

mbe z R (b) i 240,000 250,000 260,000 270,000 280,000 290,000 300,000 310,000 05102.5 UTM 35S Km Fig. 8: (a.) Alluvial fan and flood plain features for the Loanja River and the Kasaya River as it enters the Zambezi River respectively. (b.) Overlay of 0-20 m electrical resistivity map depicting the imprint of the alluvial fan and flood plain features onto the shallow subsurface.

22 5.3 Freshwater intrusion into saline aquifer Local scale evaluation of the anomalous superficial electrical resistivities mentioned in Section 5.2 using DCIP and TEM measurements at Kasaya, depicted a layer with variable high end electrical resistivity distributions and thickness. This layer exhibited electrical resistivity variations from about 200 Ωm at the beginning of the transect (at the edge of the Zambezi River) to about 30 Ωm at the end of the transect line (total distance 6,600 m). It in turn was overlain by a thin low resistivity layer (less than 12.6 Ωm) and underlain by the low electrical resistivity (3.59 Ωm) subsurface and was 60 m thick at the beginning and 22 m thick at the end. In addition, the spatial distribution of chargeability from joint inversion of DCIP and TEM data was more or less correlated to that of the electrical resistivity. This strong correlation between induced polarization and electrical resistivity is a strong indicator of freshwater intrusion into a pre-existing saline environment. The electrical resistivity and chargeability cross sections for the Kasaya Transect are shown in Fig. 9.

Elevation [m]

Fig. 9: (a.) Electrical resistivity cross section and (b.) chargeability cross section from DCIP-TEM joint inversion for DCIP and TEM data collected at Kasaya, Southern Prov- ince, Zambia. The mechanism governing the intrusion of freshwater from the Zambezi Riv- er into the salty aquifer at Kasaya is unknown. However, evapotranspiration seems to be a key process. Evaluation of the evapotranspiration hypothesis conducted using an innovative coupled hydro-geophysical inversion of a SEAWAT model with DC and TEM data added credence to the hypothesis. Nevertheless, processes such as seasonal recharge/ flooding, infiltration and percolation, and through flow could possibly have had an impact on the model outcome and could have helped to obtain a better explanation for the DCIP and TEM data.

23 5.4 Utility of electrical and electromagnetic methods TEM and DCIP are effective methods that can be used for quick characterization of groundwater resources particularly in sedimentary terrain. Major benefits can be drawn from innovations in instrumentation and data processing or inversion. Thus aerial TEM systems originally designed for mineral exploration such as the VTEM system can now be used for hydrogeological applications provided they are calibrated with accurate and precise ground based measurements. Similarly, innovative data processing schemes such as DCIP- TEM joint inversion can be used to take maximum advantage of recent and innovative data acquisition systems that enable the simultaneous collection of electrical resistivity and induced polarization measurements. Furthermore, TEM and DC data can now be jointly used to inform or calibrate coupled flow and solute transport models to such an extent that reliable estimates of parameters can be achieved as within sharp confidence intervals. 5.5 Coupled hydrogeophysical inversion with combined DC and TEM data An implementation framework for the calibration of hydrodynamic models (SEAWAT freshwater intrusion model in this case) was successfully developed. Model output in form of solute concentrations were transformed through a series of steps into simulated instrument responses and used in the parameter estimation process. Thus the Gauss-Marquardt-Levenberg algorithm implemented in PEST was used to minimise the difference between the simulated instrument responses and the measured TEM and DC data. This implementation approach has demonstrated the benefits of using multiple datasets in terms of both type and quantity by the improved sensitivities and reduced uncertainty in parameters and parameter estimates. In addition, the developed framework id flexible enough to incorporate any data type (hydrological or geophysical) for as long as it can be related to model variables (e.g. solute concentration and hydraulic head) using either direct or empirical rela- tionships). Qualitative evaluation of the CHI for a simple coupled flow and solute transport problem yielded a simulated electrical resistivity profile from the distribution of solute concentrations that is a close approximation of the electrical resistivity distribution obtained from joint inversion of DC and TEM data.

24 Simulated electrical resistivity x-section from SEAWAT model Wm 950 1000 900 100 850 10 800 1 Elevation [m] (a) 0 1000 2000 3000 4000 5000 6000 Proﬁle Coordinate [m]

Resistivity cross section from Joint DC-TEM Inversion Wm 950 1000 900 100 850 10 800 1 Elevation [m] (b) 0 1000 2000 3000 4000 5000 6000 Proﬁle Coordinate [m] Fig. 10: (a.) Simulated electrical resistivity cross section generated from solute concentration output of a SEAWAT excited by evapotranspiration at Kasaya, south-western Zambia. (b.) Electrical resistivity cross section from joint inversion of DC and TEM data. It is envisaged that the main limitations to the CHI is the simplicity of the hydrodynamic model that was used. Improved process descriptions and parameterizations in the model would lead to a closer match between the CHI resistivity cross section and the DC-TEM joint inversion cross section.

26 6 Discussion Electrical and electromagnetic methods are an effective means of evaluating groundwater resources particularly with respect to groundwater salinity variations and aquifer delineation in sedimentary basins. This is because of the sharp electrical resistivity contrasts between fresh groundwater and salty groundwater, and between aquifers and the background geology (Nobes, 1996; Albouy et al., 2001). Thus using a combination of both aerial and ground based deployment, regional trends in groundwater salinization can be cost effectively mapped. A typical regional survey would therefore begin with a ground based reconnaissance survey at appropriate sample spacing, followed by a more targeted aerial survey to gain finer resolution of regional features of interest as detected by the preliminary ground survey. In this way a balance can be struck between the need for high data density, reduced uncertainty in model interpretations, spatial coverage and costs associated with aerial surveys (Sapia et al., 2014). Furthermore, ground based measurements are more amenable to deployed for finer scale investigations such as site characterization and they can also be used for quality control checks and calibration of aerial measurements (Podgorski et al., 2013). Thus geophysical measurenments offer the possibilities of determining hydrological parameters for a broad range of scales(Rubin and Hubbard, 2006) particularly when used in conjunction with traditional means of hydrological exploration such as core recovery, pumping tests and groundwater sampling (Danielsen et al., 2003; Auken et al., 2009b; Ruggeri et al., 2014). However there are a number of significant challenges that hinder the use or incorporation of geophysical methods into hydrological investigations. These include terrain/geology specific suitability or appropriateness; requirement for sophisticated interpretation algorithms; general association of geophysical methods with mineral and petroleum industries; very high initial costs of instrumentation; and measurement of other physical earth properties than the hydrological parameters of interest (Rubin and Hubbard, 2006; Kirsch, 2009). Consequently, DCIP and TEM measurenments are not suitable for use in all geological environments. They are very effective in sedimentary systems because of the relatively high electrical resistivity contrasts between targets of interest and their host materials (e.g. clay lenses embedded in sand or fresh water lenses overlying salty aquifers) (Nassir et al., 2000; Guerin et al., 2001; Bauer et al., 2006c; Gazoty et al., 2012). This is in contrast to igneous or metamorphic geology in which groundwater occurs predominantly in the superficial weathered zone and in deeper fractures (Raju and Reddy, 1998)

27 which may not exhibit a sufficiently high electrical resistivity contrast to have a meaningful distinction between aquifers and their host environment. This is in addition to the high electrical resistivity nature of such environments which typically results in very low signal to noise ratios. Furthermore, geophysical datasets that are collected for surveys beyond a certain size (e.g. aerial surveys of more than a few 100 km2 or ground based transects of more than 1 km) often demand excessive computer memory and calculation speeds that cannot be met by ordinary computers. As a result, a significant invest- ment in appropriate computer technology and expertise is often required if DCIP and TEM data are to be interpreted and used in a meaningful way. This comes with the requirement for complicated data handling software and inversion algorithms that are often proprietary as a result of many years of ex- pensive research that go into their production. The fact that the same geophysical principles and methods as are used for hydrological applications can also be used for mineral and petroleum exploration does not help matters either. The mineral and petroleum industries are in general more willing and able to pay for geophysical instrumentation, data interpretation algorithms and the innovations thereof for as long as they can be shown to improve their operations and productivity. Therefore the laws of supply and demand dictate that the water and environmental sectors are at the losing end of the geophysical supply chain and would thus rather use alternative methods that fit their funding profiles in order to answer the pertinent hydrological questions. Many would go on to further argue that after all, geophysical methods do not measure the properties that are of most interest to hydrologists. For example, DCIP and TEM methods measure the chargeability or the electrical resistivity of the subsurface whereas hydrologists are interested in the aquifer properties such as porosity and hydraulic conductivity. There is no direct relationship between most geophysical parameters and hydrological parameters of interest except for the use of empirical relations such as Archie’s Law and hydrogeophysical inversion. Notwithstanding, the advantages of incorporating geophysical measurements into hydrological investigations are increasingly being recognised. A case in point is the characterisation of regional and local scale subsurface features in the Machile Zambezi Basin using DCIP and TEM measurenments. Standard aerial and ground based TEM measurenments were used to for the first time visualise the extent of the propagation of the Okavango-Linyati Fault System (OLFS) into the Machile-Zambezi Basin in south-western Zambia. The OLFS is considered to be an important structural control on the extent of groundwa-

28 ter salinization in the Machile-Zambezi Basin as it relates to the spatial extent of the Palaeo Lake Makgadikgadi sediments. Thus a block faulting system was inferred in the Machile-Zambezi Basin whose main feature is a northeast to southwest oriented graben structure which is deepest at its south western extent. Salinized groundwater was found to occur predominantly in this graben structure particularly at the deepest end in the southwest (Paper I). One implication of this is that saline groundwater was created at the time of deposition of the Palaeo Lake Makgadikgadi sediments and that as a consequence, further salinization of groundwater is not taking place (Banda et al., 2014). Indeed as indicated from the aerial TEM data, significant surface water\ groundwater exchange based on high electrical resistivity values that were found to be coincident with surface water features appears to be taking place, leading to the creation of freshwater lenses that are an important source of clean drinking water. A combination of DCIP and TEM measurements indicated that the high electrical resistivity anomalies were as a result of intrusion of fresh surface water into a pre-existing saline aquifer (Paper II). However a more detailed understanding of the surface water / groundwater exchange indicated by the geophysical data is still needed. This can only be achieved by conducting further research that will integrate geochemical, hydrological, petrological and meteorological data around the new knowledge that has been brought out by the geophysics as closely as possible under hydrogeophysical inversion approaches similar to those presented in Paper III. This will of no doubt be useful to water resource managers and planning authorities who have to weigh societal and environmental interests with respect to scarce freshwater resources particularly where decisions have to be made with the aid of groundwater models. Thus better estimates of pertinent hydrological parameters and processes can result from new formulations that incorporate as much geophysical data as is available in addition to data from other geoscience disciplines such as petrology, geochemistry, hydrology and meteorology. Furthermore, model outcomes will be more reliable and better able to predict system behaviour for as long as the model faithfully represents the natural system under consideration and this requires an integrated multi- disciplinary approach.

30 7 Conclusion The main conclusions that have been arrived at with respect to the research reported in this thesis are as follows:

 Saline groundwater in the Machile-Zambezi Basin in south-western Zam- bia was found to occur in a northeast to southwest oriented graben structure related to propagation of the Okavango-Linyati fault system stretching from Botswana in the south into south-western Zambia. The graben structure is deepest at its south-western extent where the observed low electrical resistivity values have been attributed to Palaeo Lake Makgadikgadi sediments and associated saline groundwater. This marks the first time that the northern extent of the Paleo Lake Makgadikgadi system (including the associated fault structures) extending into Zambia has been mapped using TEM methods;

 Considerable surface water/ groundwater exchange takes place in the Machile-Zambezi Basin as indicated by the coincidence of high electrical resistivity anomalies (> 100 Ωm) in a low electrical resistivity (< 13 Ωm) geological setting with surface water features such as alluvial fans and flood plains. One such feature, the Simalaha Flood Pain, was investigated at a local scale at Kasaya in Kazungula District, Zambia, using a combination of DCIP and TEM measurenments. Evaluation of the measurenments under a new DCIP-TEM inversion scheme revealed a freshwater lens with high electrical resistivity values (30-200 Ωm) overlying a Saline aquifer with electrical resistivity values 3.59 Ωm and below. The correlation of electrical resistivity and chargeability from the DCIP-TEM inversion result indicates intrusion of fresh surface water into a pre-existing saline environment; and

 An innovative coupled hydro geophysical inversion framework was developed to enable the calibration of a coupled flow and transport model with both DC and TEM data for the first time. When tested for a river-aquifer exchange problem under evapotranspiration for the Kasaya Transect in Kazungula District, Zambia, the CHI resulted in sharp parameter confidence intervals and reasonable estimates of parameter values. The estimated parameters also exhibited strong sensitivity with respect to model outcomes.

31  Finally, the practical relevance of the findings is that there is now new knowledge on a regional scale about the spatial distribution of saline groundwater in the Machile-Zambezi Basin including local scale surface water/ groundwater exchange in places. This knowledge will be useful in planning for new water points or human settlements taking into account the location of fresh and saline aquifers. Furthermore, these findings have an important impact on the management of the water resources not only of the Machile-Zambezi Basin, but of the entire Kalahari Basin in Southern Afri- ca and other similar semi-arid sedimentary settings around the world. This is because standard transient electromagnetic and geoelectrical (direct current and induced polarization) methods have been shown to be effective means of groundwater characterization in a semi-arid sedimentary environment. In addition, the findings have also shown that the data requirement for groundwater models which are an important water resources management tool and decision support can be effectively complimented by using geophysical data.

32 8 Outlook and Perspectives The hydrogeophysical characterization of groundwater salinization reported in this thesis is an important outcome for water resources management in arid and semi-arid environments particularly in the Machile-Zambezi Basin. However is does not represent the whole picture from the hydrogeological point of view because by and large the geophysical data was not integrated with other data such as geochemical (e.g. prevailing groundwater types and their evolution), petrological (e.g. laboratory determinations of rock and sediment properties like porosity and cementation) and hydrogeological (e.g. hydraulic conductivity and hydraulic head) data due to a lack of it. The few such data available in the study area were mostly not coincident with the geophysical data. Therefore there is still a strong need to conduct further geochemical, petrophysical, sedimentological, hydrological and hydrogeological research to generate data that can help to strengthen and or validate the outcomes from the hydrogeophysical investigation reported in this thesis. Furthermore, it is highly likely that given the nature of the propagation of the East African Rift Valley system into southern African, there could be other graben structures in the western parts of Zambia similar to the Machile graben that are hidden by the extensive Kalahari sand cover but nevertheless harbour salinized groundwater as a result of palaeo lake systems. One such palaeo lake system that could be investigated in the future is the area around the Barotse Flood plains which has been designated as Palaeo Lake Bulozi by Moore et al. (2012). The Barotse flood plains are an important wetland on the course of the Zambezi River and are protected under the Ramsar Conven- tion on conservation of wetlands of international importance. Thus in order to come up with measures that mitigate against the adverse effects of climate variability such as floods and droughts, and to develop water resource management and development practices that maintain the heritage status of the Barotse Flood plains whilst sustaining the requirements of the local people, the need for ongoing and integrated multi-disciplinary water resource related research cannot be over emphasised. Such research will need to integrate surface water and groundwater evaluation using multiple data from remote sens- ing and airborne geophysics to ground based geophysics and sedimentological, petrological, groundwater and geochemical sampling.

33 A recommended research strategy with respect to the Kalahari System of western Zambia would therefore be to:

 Use satellite data for a preliminary description of the hydrology of the Zambezi River system and design of a network of permanent hydrological monitoring stations;

 Conduct preliminary ground based TEM measurements in a 25 x 25 km grid in order to gain a regional perspective of ground water salinization based on electrical resistivity correlation. Geochemical sediment sampling could also be incorporated into the preliminary TEM survey in order to have an initial basis for relating geological mineralization to electrical resistivity variations;

 Design and develop a ground water monitoring network based on the preliminary TEM and geochemical sampling survey mentioned above with a rough spatial density of one monitoring borehole per 500 km2. The hydrogeological, petrological and geochemical data derived from these boreholes could then be integrated with the geophysical data using various geo- statistic and inversion approaches to interpolate and extrapolate parameters of interest. It is recommended that the monitoring boreholes should have a minimum depth of 500 m in order to capture all relevant geological history and not only that of the relatively recent Kalahari Supergroup;

 Design and conduct site specific airborne TEM surveys based on areas of interest identified by the preliminary ground based TEM and geochemical sampling surveys mentioned above, followed by detailed local scale surveys that integrate different geoscience disciplines in order to gain a com- prehensive picture about the ecosystem and water resources particularly with regards to the impact of climatic variability and anthropogenic activities; and

 Create an electronic and online database that integrates local and international multi-disciplinary data. This database should go together with coor- dinated environmental and water resources related research across the international boundaries of the southern African countries with significant territory in the Kalahari Basin.

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42 10 Appendix Inventory of electronic material Electronic materials associated with the production of this thesis are listed below. They could not be placed in a CD as is usually the practice due to the requirement for large storage space (63.9 gigabytes). The containing folder is called Chongo_Thesis_Electronic_Materials and maybe obtained by contacting the following: DTU Environment Technical University of Denmark Miljøvej, Building 113 2800 Kgs. Lyngby Denmark [email protected]

The contents of the electronic appendix are as follows: Raw data items  Geotech db/dt aerial data  Kasaya transect DCIP data  Kasaya transect differential GPS files  Kasaya transect TEM data  Kasaya CHI setup  Machile-Zambezi ground based TEM (raw and processed)

Processed data items  Machile-Zambezi Aarhus workbench workspace for aerial and ground based TEM data  Kasaya transect Aarhus workbench processed DCIP data files  Kasaya transect TEM data (.usf and .tem files)  Kasaya transect DCIP data (RES2DINV format and electrode coordi- nates)  DCIP_TEM_Joint (Folder containing the DCIP-TEM joint inversion scheme)  Joint_DC_TEM_Inversion (Folder containing the joint DC-TEM inversion scheme)

43 Databases  Sesheke GIS  Endnote references

Scripts  C++ CHI Scripts  Matlab CHI Scripts

Documents  Thesis  Papers I-III

44 11 Papers

The scientific papers that form the basis of this thesis are:

I Mkhuzo Chongo, Anders Vest Christiansen, Alice Tembo, Kawawa E. Banda, Imasiku A Nyambe, Flemming Larsen, Peter Bauer-Gottwein, 2015. Airborne and ground based transient electromagnetic mapping of groundwater salinity in the Machile-Zambezi Basin, south-western Zam- bia. Accepted for publication in Near Surface Geophysics Journal (in press).

II Mkhuzo Chongo, Anders Vest Christiansen, Gianluca Fiandaca, Imasiku A Nyambe, Flemming Larsen and Peter Bauer-Gottwein, 2015. Mapping localized freshwater anomalies in the brackish Paleo-Lake sediments of the Machile-Zambezi Basin with transient electromagnetic sounding, geoelectrical imaging and induced polarization. Submitted to Journal of Applied Geophysics.

III Mkhuzo Chongo., Nyambe, I.A., Larsen, F., and Peter Bauer-Gottwein, 2015. Coupled hydrogeophysical inversion using a groundwater flow and transport model, and transient electromagnetic and direct current electrical resistivity data.

Airborne and ground based transient electromagnetic mapping of groundwater salinity in the Machile-Zambezi Basin, south-western Zambia

Chongo, M., Christiansen, A.V., Tembo, A., Banda, K.E., Nyambe, I.A., Larsen, F., Bauer-Gottwein, P.

Accepted for publication in Near Surface Geophysics Journal (Manuscript ID: nsg-2014-1142.R1)

Airborne and ground based transient electromagnetic mapping of groundwater salinity in the Machile-Zambezi Basin, south-western Zambia.

Mkhuzo Chongo1,*, Anders Vest Christiansen2, Alice Tembo3, Kawawa E. Banda1,4, Imasiku A Nyambe4, Flemming Larsen5, Peter Bauer- Gottwein1

1Technical University of Denmark, Department of Environmental Engi- neering, Miljøvej, Building 113, 2800 Kgs. Lyngby, Denmark 2Aarhus University, Department of Geoscience, C.F. Møllers Alle 4, 8000-Århus C, Denmark 3University of Zambia, School of Mines, Integrated Water Resources Management Centre, Great East Road Campus, P.O Box 32379, Lu- saka, Zambia 4University of Zambia, School of Mines, Department of Geology, Great East Road Campus, P.O Box 32379, Lusaka, Zambia 5 Geological Survey of Denmark and Greenland (GEUS), Geochemis- try, Øster Volgade 10, 1350 København K, Denmark

Accepted for publication in Near Surface Geophysics Journal (Manu- script ID: nsg-2014-1142.R1)

*Email: [email protected]; [email protected].

Abstract The geological and morphological evolution of the Kalahari Basin of South- ern Africa has given rise to a complex hydrogeological regime that is affected by water quality issues. Among these concerns is the occurrence of saline groundwater. Airborne and ground based electromagnetic surveying is an efficient tool for mapping groundwater quality variations and has been used extensively to explore the Kalahari sediments e.g. in Botswana and Namibia. Recently, airborne and ground based mapping of groundwater salinity was conducted in the Machile-Zambezi Basin, south-western Zambia using the VTEM and WalkTEM systems respectively, incorporating earlier ground based ProTEM 47D measurements. The data were inverted using the laterally constrained inversion technique followed by a separate spatially constrained inversion scheme. WalkTEM data was inverted as ordinary single site 1D inversions. The regional electrical resistivity signature of the Machile-Zambezi Basin was found to be characterised by high elevation (1,000-1,050 m amsl), high electrical resistivity (above 100 Ωm) areas that form the western and eastern boundaries of a low resistivity (below 13 Ωm) valley that extends south-westwards into the Makgadikgadi salt pans. The electrical resistivity distribution is indicative of a full graben related to the Okavango-Linyati Fault system as a result of propagation of the East African Rift Valley System into Southern Africa. The saline lacustrine sediments in- filling the Machile Graben are responsible for the low formation resistivity (below13 Ωm) and high salinity (above 7,000 µS/cm) observed in the groundwater and are probably related to the complex evolutionary history of palaeo Lake Makgadikgadi.

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1 Introduction The Kalahari sediments contain important groundwater resources throughout Southern Africa which however are constrained by a very variable water quality. Much effort has been made to characterize the sediments and groundwater resources of the Kalahari Basin (Worthington, 1977; Arad, 1984; Thomas and Shaw, 1993; Thomas and Shaw, 2002; McCarthy and Haddon, 2005; McCarthy, 2013), a basin which stretches from South Africa in the south into the Democratic Republic of Congo over a distance of 2200 km (McCarthy and Haddon, 2005) to form an extensive sea of sand (Thomas and Shaw, 1990). Geological events related to the breakup of Gondwana have had a major influence on the geological evolution and geomorphology of Southern Africa in general and the Kalahari Basin in particular (McCarthy, 2013). This has been characterised by a series of tectonic, volcanic, fluvial and aeolian processes over geological time scales. At the base of the simplified Kalahari stratigraphy is conglomerate sitting on pre-Kalahari formations. The conglomerate is in turn overlain by sandstone which in turn is overlain by the unconsolidated sands (Money, 1972; McCarthy and Haddon, 2005). The simplified stratigraphy exhibits local variations in terms of the presence or absence of lithological units. For example in places, the conglomerate is absent and sandstone overlain by aeolian sands rests directly on the bedrock whereas in others mudstones and siltstones overly the conglomerate before coarsening upwards into sandstone (McCarthy, 2013). Fig. 1 depicts the surface geology (un-consolidated sands) in the Okavango-Makgadikgadi- Machile area as being predominantly Cenozioic. One way of addressing water quality concerns is to use the transient electromagnetic (TEM) method to identify water quality variations in potential aquifers (Melloul and Goldenberg, 1997; Land et al., 2004; Ezersky et al., 2011). In the last few decades TEM has been developed and used extensively around the globe to identify fresh water aquifers, delineate salt water-freshwater interfaces and map the spatial extent of salty groundwater (Guerin et al., 2001; Auken et al., 2003; Danielsen et al., 2007; Levi et al., 2008; Boucher et al., 2009; Bauer-Gottwein et al., 2010; Herckenrath, 2012; Nenna et al., 2013). Large-scale airborne geophysical mapping in the Okavango Delta, conducted by the Government of Botswana, has played a major role in the understanding of the groundwater system of the Kalahari Basin (Campbell et al., 2006; Kgotlhang, 2008; Podgorski et al., 2013a).

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Fig. 1: Contour 945 m above mean sea level (amsl) corresponding to the palaeo Lake Makgadikgadi shoreline in southern Africa. In the background is the topography and Ce- nozoic surface geology corresponding to the extent of the unconsolidated Kalahari sediment. Also depicted are various faults in the Okavango-Machile depression here collective- ly referred to as the Okavango-Linyati Fault System (Persits et al., 2002; Jarvis et al., 2008; Moore et al., 2012; McCarthy, 2013; USGS, 2014) and the outline of the Machile- Zambezi Basin.

Airborne and follow-up ground based TEM data were used in these studies to map potential fresh water aquifers on the basis of their relatively high formation electrical resistivities. Such aquifers appeared as sinuous zones of moderate resistivity in an otherwise low resistivity environment. This reflected the wide spread distribution of saline groundwater and to a lesser extent clay rich units inter-bedded with the sands. The TEM data was used by Campbell et al. (2006) to set the lateral extent of potential freshwater aquifers as well as the fresh-saline water interface. Earlier work by Sattel and Kgotlhang (2004) in the Boteti area of Botswana used airborne TEM data collected with the TEMPEST system to map geological features that are consistent with the occurrence of fresh groundwater in the Lake Palaeo Makgadikgadi system (Burrough et al., 2009). From this they noted that freshwater occurred as recharge lenses above saline groundwater. Their correlation of TEM derived resistivity depth profiles with borehole data showed

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that the resistivity of the Kalahari Super-group lithology is defined by the level of clay content, amount of saturation and pore water salinity. Using a numerical modelling approach, Bauer et al. (2006) reproduced the salinity distribution in and around the Shashe River Valley in Botswana by modelling transpiration as a function of groundwater salinity. The model results were in agreement with airborne and ground based TEM data (including water level data and geochemical evaluation). The Airborne TEM data clearly outlined fresh groundwater lenses resulting from infiltration of fresh surface water along stream channels into a stagnant saline aquifer in the interfluves. In addition, profiling with ground based TEM across the Shashe River valley suggested the thickness of the freshwater lenses to be in the order of 60 m, and to be superficially embedded in a highly saline aquifer (formation electrical resistivity between 0.5 – 5 Ωm) with strong formation resistivity correlation to the total dissolved solids of the groundwater given the saturated conditions and relatively uniform sandy lithology (Bauer et al., 2006). In order to define the occurrence of salty groundwater in the Sesheke area in Zambia, Chongo et al. (2011) conducted single site ground based TEM measurements on a regional scale and showed that salty groundwater mainly occurs in a topographic depression east of Sesheke Town which is related to faulting associated with the East African Rift Valley System (EARS) (McCarthy, 2013). They further hypothesised that the origin of the salty groundwater was related to evapo-concentration of salts in inter-dune deposits and evaporation of the palaeo Lake Makgadikgadi. The general layered earth model from the TEM measurements indicated an unconfined freshwater aquifer with electrical resistivities in excess of 70 Ωm underlain by salty groundwater with resistivities below 35 Ωm. Podgorski et al. (2013a) describe the Okavango Delta as an alluvial mega-fan and used airborne TEM data constrained by ground based TEM, seismic data and borehole records to provide additional evidence for an ancient large scale alluvial fan complex underlying the Makgadikgadi sediments. Their airborne TEM data was a reprocessing of a commercially obtained VTEM dataset from the Okavango Delta affected by systematic errors and with large uncertainties regarding key system parameters. This was the same type of VTEM system used for the airborne TEM survey in the Machile-Zambezi Basin for this study and a number of steps were taken to retrieve the best possible results; given that the data collected was prone to contamination of early time gates by transmitter currents, noise in late time gates, and amplitude shifts between adjacent flight lines. Most importantly, accurate ground based TEM data were used to calibrate the VTEM data in order to eliminate absolute amplitude inaccuracies and timing errors between

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receiver and transmitter instrumentation (Podgorski et al., 2013b). Contami- nated early time and noisy late time gates were semi-automatically eliminated for each record. Late Palaeogene uplift along the Okavango-Kalahari-Zimbabwe axis and associated subsidence of the Kalahari Basin disrupted the south-westerly flow of the Palaeo Chambeshi-Kafue-Upper Zambezi (PCKU) into the Indian Ocean via the proto Limpopo River. This Palaeogene tectonism also resulted in the damming of the Cubango-Cuito (proto Okavango River system) and Cuando rivers to form a closed fluvial/ lacustrine Kalahari Basin (Moore et al., 2012). Headward erosion of the Mid-Zambezi led to the capture and di- version of the PCKU system to the Indian Ocean via the lower Zambezi (Main et al., 2008). This was marked by a significant decrease in sedimenta- tion in the Kalahari Basin between the Pliocene to Early Pleistocene (Moore et al., 2012). Secondary faulting related to the south-westerly development of the EARS through the Mweru-Tanganyika-Kabompo Gorge axis resulted in the Okavango-Linyati fault system responsible for formation of the Machile Graben bound to the north-west by the Sesheke fault and to the south-east by the Chobe/Mambova Fault (Fig. 1) (Moore et al., 2012; McCar- thy, 2013). Early Pleistocene uplift of the Chobe Horst and related subsidence of the Machile Graben re-directed the flow of the PCKU system into the endorheic Kalahari Basin to result in the highest lake stand - palaeo Lake De- ception. This was later reduced to the 945 m level corresponding to the palaeo Lake Makgadikgadi following loss of the palaeo Chambeshi River flow as a result of capture by the Luapula River initiated by 2.2-1.8 Ma uplift of the Congo-Zambezi Watershed (McCarthy, 2013). The palaeo Lake Makgadikgadi was maintained by flow from the Cubango- Cuito, Cuando and Upper Zambezi -proto Kafue rivers and associated climatic feedback (Moore et al., 2012). At this point the proto Kafue River still drained into the Upper Zambezi via the Machile Flats. Early to Mid- Pleistocene Uplift along the Machile-Kafue Watershed finally severed the link between the Upper Zambezi and the Proto Kafue with consequent con- traction of the palaeo Lake Makgadikgadi to the 936 m shoreline. Incision of the Chobe Horst initiated during high lake stands by over topping maintained some flow in the Middle-Zambezi which in turn sustained riverine erosion and lead to the final breach at Mambova (Fig. 1) to establish the modern course of the Zambezi River in the Mid-Pleistocene. In addition, tectonic events re-organised the Okavango and Cuando river systems resulting in reduced flow into the Palaeo Lake Makgadikgadi system which resulted in

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eventual drying up leaving behind remnants such as the Makgadikgadi Salt Pans (Main et al., 2008; Burrough et al., 2009; Moore et al., 2012; McCarthy, 2013). Thus endorheic conditions were initiated in the Kalahari Basin in the Late Palaeogene (approximately 25 Ma) with subsequent formation of palaeo Lake Makgadikgadi by Early Pleistocene (2.2 to 1.8 Ma). Early Mid- Pleistocene (more than 500 Ka) isolation of the proto-Kafue from the Upper Zambezi initiated desiccation of palaeo Lake Makgadikgadi until its final ex- tinction in the Mid-Late Pleistocene (100 Ka) to present (Moore et al., 2012). The objectives of this study were to map for the first time the paleo Lake Makgadikgadi sediments in the Machile flats of Zambia using airborne TEM methods; demonstrate the utility of TEM in the Machile-Zambezi geological setting for groundwater quality mapping; extend the regional coverage and spatial resolution of the work by Chongo et al. (2011) to encompass the entire Machile-Zambezi Basin using a combination of airborne and ground based TEM measurements; and to come up with a consistent conceptual explanation for the observed electrical resistivity variations. This was necessary in order to shed more light on and gain a better understanding of the Palaeo Lake Makgadikgadi system that extends into Zambia and in order to understand the occurrence of saline groundwater and how it relates to the geology. From a management perspective this was also important because it will lead to improved access to clean drinking water in rural and remote areas though a better understanding of the groundwater regime and quicker, efficient and cost effective means of evaluating groundwater for borehole placement.

2 Materials and methods 2.1 Description of the study area The Machile-Zambezi basin is located between latitude 16o - 17o 54’ S and longitude 24o 13’ – 26o 22’ E. It encompasses river basins for the three main northerly tributaries of the Zambezi namely, Loanja, Machile and Ngwezi, and a number of other smaller river basins. The outlet to the Machile- Zambezi Basin is defined at 17o 50.4’ S and 25o38’E (Fig. 2 ) and is therefore hydrologically defined but encompasses the northern tip of the Makgadikgadi Basin that extends into Zambia which is called the Machili Basin by Moore and Larkin (2001) (Fig. 2). The dominant surface geology is unconsolidated sediments of Cenozoic Era with outcrops of basaltic and basement rocks in places particularly in the eastern areas where the presence of basement complex rocks is significant. The topography is characterised by

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a valley that is widest in the south-central areas and narrows towards the north-east with elevations ranging between 800 -1200 m amsl (Fig. 2).

Fig. 2: The Study area map depicting aerial TEM survey flight lines and ground based TEM points. The surface geology is predominantly unconsolidated Cenozoic sediments with significant outcrop of the basement complex in the eastern region after Persits et al. (2002). Elevation data from Jarvis et al. (2008). The outline of the Machile Basin after Moore and Larkin (2001) is also contrasted with the outline of the Machile-Zambezi Basin. 2.2 Transient electromagnetic method Based on the principles of electromagnetism, secondary currents can be induced in the subsurface by a time-varying electromagnetic field. The secondary magnetic fields generated by the secondary currents can then be measured by appropriate electromagnetic receivers (Nabighian, 1988). The two main types of electromagnetic prospecting are frequency-domain electromagnetic (FEM) methods and time-domain (or transient) electromagnetic (TEM) methods (Nabighian, 1988; Nabighian, 1991; Kirsch, 2006). TEM methods were used for this research. These comprised both ground based and airborne measurements. Airborne TEM measurements were conducted with the helicopter-borne versatile time-domain electromagnetic (VTEM) system developed by GEOTECH Limited who were contracted by the Ministry of Energy and Water Development (MEWD) of the Republic of Zambia to conduct the

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survey (GEOTECH, 2011). Ground-based TEM measurements were carried out with the WalkTEM system (ABEM, 2014) developed by Aarhus Univer- sity and ABEM Instrument AB. In both cases a central loop configuration was used. The VTEM system had a nominal terrain clearance of 48 m and nominal flight speed of 90 km/h and a total of 1000 line kilometres were flown. This comprised two sets of four parallel lines as shown in Fig. 2. One set was southwest to northeast trending and the other northwest to southeast trending. In both instances the line separation was 2000 m. The 24 ground- based TEM soundings were conducted on the eastern side of the Machile River. These, together with the 66 TEM soundings conducted by Chongo et al. (2011) and the 27 soundings collected for calibration form the ground based TEM dataset for this paper (Fig. 2). The total number of TEM soundings collected for the Machile-Zambezi Basin was therefore 117 soundings over 26, 260 km2. Field schematics, transmitter waveform and system response of both the airborne and ground-based deployment are illustrated in Fig. 3. A central loop configuration was used for the VTEM setup with concentric transmitter and receiver coils. The outer loop in form of a 12 sided polygon acted as the transmitter loop with diameter 26 m and 4 turns transmitting a peak current of 240 A. The inner loop had a diameter of 1.2 m and 100 turns and acted as the receiver coil (GEOTECH, 2011) (Fig. 3a). The WalkTEM system also used the central loop configuration with a single turn 40 m by 40 m transmitter loop and a 0.5 m by 0.5 m receiver coil in the centre with 20 internal turns(ABEM, 2014) (Fig. 3b). The VTEM transmitter current waveform is 4.7 ms long with a peak at -1.646 ms. Receiver gates commence shortly after transmitter turn off at 0 ms with gate widths progressively increasing at later times. Gate centre times start at 21 µs and end at 10667 µs with a total of 45 gates (Fig. 3c). The WalkTEM system had two waveforms; a high-moment waveform transmitting a 10 ms 8 A pulse and a low- moment waveform of amplitude 1.0 A and duration 10 ms. Turn off time was 5.9 µs and 10.4 µs for low and high moments, respectively. The low-moment response was measured over 23 gates with the first gate centre time at 3.6 µs and the last gate centre time at 364 µs. The high moment response was measured over 37 time gates with the first gate centre time position at 3.6 µs and the last at 8850 µs. The low moment is optimised for early time gate measurements and thus near surface geological information whereas the high moment is optimised for later time gate measurements and thus deeper surface geological information (Fig. 3d).

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Fig. 3: Field Schematics, transmitter waveform and system response for the WalkTEM and VTEM systems: (a) VTEM Setup; (b) WalkTEM Setup; (c) VTEM waveform and system response; and (d) WalkTEM waveform and system response. 2.3 Aerial survey The instrumentation for the airborne survey was mounted on an AS 350 B3 helicopter equipped with a Terra TRA 3000/ TRI40 radar altimeter and a NoVatel wide area augmentation system (WAAS) enabled OEM4-G2-3151W GPS navigation system with a sampling interval of 0.2 s. The TEM transmitter and receiver loops were carried as a sling-load beneath the helicopter with sampling interval at 0.1s. The VTEM decay sampling scheme was configured for 45 time gates. The first gate centre time was at 21 µs and the last gate centre time was at 10.667 ms (GEOTECH, 2011). The transmitter current waveform and receiver time gates are illustrated in Fig. 3c. Electromagnetic data collected for the survey was presented as db/dt (time derivative of magnetic flux through the receiver coil). The data were imported into the Aarhus Workbench (HGG, 2014) where it was processed and inverted. The processing performed in the Workbench was on data that was already pre- processed by GEOTECH (2011) using an un-documented three stage digital

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filtering process to reject major broadband electromagnetic impulses or spherics caused by lightening events and to reduce system noise. The signal to noise ratio was further improved by the application of a low pass linear digital filter but the characteristics of this filter and its effects on the data were not documented by GEOTECH (2011). Thus the uncertainties about how the digital filtering was conducted by GEOTECH (2011) in addition to transmitter-receiver timing errors and amplitude shifts necessitated calibration of the airborne TEM dataset with accurate ground based TEM measurements (Podgorski et al., 2013b) in order to obtain a more reliable inversion and interpretation. Interpretation of resistivity data obtained from TEM measurements is described in more detail in the Discussion section. 2.4 Ground survey The ground based TEM dataset comprised data from both ProTEM and WalkTEM equipment. The ProTEM equipment was set to measure at three different repetition rates under 20 gate mode. The repetition rates were designated as u(237.5 Hz), v(62.5Hz) and H(25Hz) and the current was set at 3 A throughout with a standard square transmitter waveform characteristic of the ProTEM equipment. Thus for each location a complete sounding comprised one measurement for each of the three repetition rates. The gate times for the u repetition rate were optimised for early times whereas those for the H repetition rate were optimised for late times. The repetition rate v had an overlap between the gate times for the u and H repetition rates. The WalkTEM equipment used the concept of low moment and high moment. For each sounding, one measurement was made with the current setting at 1.0 A (low moment) and another with the current setting at 8.0 A (high moment). Fig. 3 (d) illustrates the concept of low and high moments used by the WalkTEM equipment. The low moment is optimised for early times and the high moment is optimised for late times. Characteristics of the transmitter waveforms and receiver gate times were all controlled through user defined script files. The location of the ground based TEM soundings for the Machile-Zambezi Basin are shown in Fig. 2. Each sounding was inverted individually using AarhusInv (Auken and Christiansen, 2007; Auken et al., 2014) and the best fit model with residuals below 1 that made geologic and physical sense was selected as the most appropriate at that location. 2.5 Inversion methodology Inversion of the airborne dataset from the time derivative of the secondary electromagnetic field (db/dt) passing through the receiver coil to resistivity

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layered earth models was done using two separate but similar techniques. These are laterally constrained inversion (LCI) (Auken et al., 2005) and spatially constrained inversion (SCI) (Viezzoli et al., 2008). Using the LCI technique, each of the eight flight lines was inverted individually segment by segment. A typical flight line comprised two or three segments and with the SCI technique, all flight lines were inverted together as one inversion job. In both cases tight constraints were set on a smooth or minimum structure starting model given the relatively homogenous sedimentary terrain. Thus a 29 fixed-layer starting model was setup such that the mean apparent resistivity for each sounding was used as the initial resistivity for each layer. No a priori information was added. The thickness of the first layer was 7 m and that of the last layer was 60 m; i.e. the thicknesses increased progressively with depth. Vertical and lateral reference constraints on resistivity values were set to 2.5 and 1.3, respectively. The reference distance for the reference constraints was set to 25 m with the with the power law factor (Christiansen et al., 2007) set to 0.5. 2.6 Calibration of the airborne dataset High quality ground based TEM soundings that were coincident with the airborne TEM data within a distance of 50 m were used for calibration, and in total these were 14 soundings. At each of the 14 sites, a forward response based on the layered earth model from inversion of the ground based TEM sounding was compared with the corresponding VTEM sounding at the same location. A manual calibration was then conducted by first shifting the VTEM sounding curve vertically upwards to get the level right and then hori- zontally to get the time shift right. The amount of vertical and horizontal shift comprised the calibration parameters designated as shift factor and time shift, respectively. The procedure and considerations used for processing and calibration of the airborne dataset are similar to those of Podgorski et al. (2013b) who report a final time shift of 30 µs and a final shift factor of 1.44. For this study the time shift was determined as -44.929 ± 10.05µs, and the shift factor was determined as 1.071 ± 0.112 based on averaging of the calibration results at 14 sites. The difference in sign between the time shift factor reported by Podgorski et al. (2013b) and the one determined in this study probably has to do with the amount of system drift experienced by the respective VTEM systems used each survey. The calibration was thus completed by subtracting 44.929 µs from all time gates and multiplying all raw data values (db/dt) with 1.071.

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A qualitative assessment of the effect of calibration on the inversion was conducted by comparing the inversion result from an LCI with un-calibrated data (Fig. 4a) to that of a similar LCI with calibrated data (Fig. 4b) and another also with calibrated data but using SCI (Fig. 4c).

Fig. 4: Comparison of horizontal resistivity thematic maps over the Loanja Alluvial Fan at depth interval 0 to 20 m for a 29 layer smooth inversion using (a) LCI with un-calibrated data; (b) LCI with calibrated data; and (c) SCI with calibrated data. 3 Results The results from the airborne and ground based TEM survey are presented below as maps and cross sections. These are extractions from the Machile- Zambezi geophysical database produced and maintained in the Aarhus Work- bench (HGG, 2014). The mean horizontal electrical resistivity map (Fig. 5) at depth interval 0 – 20 m was superimposed over the topography in the Machile-Zambezi Basin and depicts low electrical resistivity values (1 – 10 Ωm) confined to the low lying south-central region. At higher elevation particularly in the north-eastern and north-western regions, the electrical resistivity values are very high in the range of 1000 Ωm. In between and surrounding the high and low electrical resistivity blocks are areas of moderate values (10 to 100 Ωm).

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Fig. 5: Mean horizontal electrical resistivity variations at depth interval 0 – 20 m.

The mean horizontal electrical resistivity map at 80-100 m (Fig. 6) is similar to that at 0 to 20 m (Fig. 5 above) except that the south-central low resistivity region is smaller in spatial extent and roughly coincides with the 945 m contour. In addition, the western and eastern areas with high resistivities are larger and elongated from south-west to north-east. North of the area with low electrical resistivity oriented towards the north east, is an elongated moderate resistivity region which together with the low resistivity block appear to be in valley structure between the western and eastern electrical resistivity blocks.

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Fig. 6: Mean horizontal electrical resistivity variations at depth interval 80 – 100 m.

The electrical resistivity structure along the northwest to southeast profile (Fig. 7a) indicates a low lying area with low electrical resistivity in the centre bound by an area with high electrical resistivity to the west (left hand side) and another area with high electrical resistivity to the east (right hand side) (Fig. 7a). The low electrical resistivities are interrupted in the shallow subsurface by moderate resistivity anomalies. Along the southwest to northeast profile line a low resistivity or high conductivity region shaped in form of a pot with a handle extends from south (left hand side) to north (right hand side) with the pot handle pinching out towards the north. Underlying the pot handle is the moderate resistivity region which crops out in the northern areas. The main low resistivity pot is interrupted in the southern shallow subsurface by moderate anomaly resistivity values ranging from 10 – 100 Ωm (Fig. 7b).

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(a.)

(b.)

Fig. 7: (a) - Northwest to southeast cross section along profile line NW_SE (Fig. 5). (b)-Southwest to northeast cross section along profile line SW-NE (Fig. 5). The depth of investigation is the top of the faded part of the electrical resistivity cross sections.

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Evaluation of borehole log data from various boreholes in the Sesheke area formed a basis of inferring groundwater salinity from the electrical resistivity mapped by TEM. An example borehole log at borehole RV31 (borehole number 1 in Table 1 below) is shown in Fig. 8 whereas the location of the borehole logs considered are shown in Fig. 5 and Fig. 6 above.

Natural Gamma Fluid Long [Counts/s] Conductivity[µS/cm] Conductivity[mS/cm] 0

Depth [m]

30 020406080 0 200 400 10024 10 10 Fig. 8: Example borehole log from borehole RV31

From the borehole logs, formation factors (Tsallis et al., 1992; Neretnieks et al., 2001) were determined using the pore water resistivity (which was measured as fluid conductivity with the borehole probe in µS/cm) and formation resistivity below the water table (which was measured as long conductivity in mS/m with an induction probe). The construction of most boreholes implemented a screen interval from the water table up to 3m above the bottom of the borehole. A single formation factor was thus assigned to each borehole by calculating the average formation factor from individual entries in the borehole log and the nominal formation resistivity around each borehole was defined as the product of the average pore water resistivity and the borehole formation factor. The formation factors and formation electrical resistivity values calculated for each borehole are shown in Table 1.

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Table 1: Pore water and formation resistivities, and formation factors derived from borehole logging in the Machile-Zambezi Basin. Locations of the boreholes are shown on figures 2, 5 and 6.

Location (UTM 35S) Pore Water Formation Resistivity Formation Nominal Formation Borehole Resistivity Threshold on non-saline General Lithology Factor Resistivity (Ωm) Northing (m) Easting (m) (Ωm) water (Ωm)

RV_31 8098183.40 237931.96 26.86 6.68 179.48 95.44 Sand

Clayey Sand and sand- RV_08 8099759.76 262479.77 17.31 5.74 99.31 81.97 stone

RV_29 8076339.01 211449.36 21.76 1.50 32.75 21.50 Sandstone/ Basalt

RV_12_02 8137425.81 299048.19 21.43 1.52 32.52 21.68 Sand/ Sandstone

RV_36 8068825.60 288165.00 15.72 1.54 24.19 21.98 Sand/ Sandstone

RV_01 8070051.34 231262.64 4.50 1.94 8.74 27.74 Sandy Clay

RV_26 8096066.40 289747.90 2.15 2.64 5.66 37.66 Clayey sand

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Also shown in Table 1 are formation resistivity thresholds of ground water salinity below which the groundwater is considered salty and above which it is considered fresh water or non-saline water. The formation resistivity thresh holds were calculated by multiplying the respective formation factor with the threshold for non-saline water which was taken as 700 µS/cm or 14.3 Ωm (FAO, 2014). Based on Table 2 the average formation electrical resistivity threshold for the Machile-Zambezi Basin is estimated as 44.0 ± 31.3 Ωm implying that in areas with very high clay content (i.e. high surface electrical conductivity), electrical resistivity values below 12.6 Ωm are indicative of salty groundwater whereas in areas with very little clay content the threshold is at 75.3 Ωm. This high degree of variability of formation factors is probably a consequence of the different geological domains from which the respective borehole logs were sampled but the values are typical of what can be expected in sedimentary terrain comprising mostly clay, sand and sandstone (Salem, 2001). Similarly the average formation factor for the Machile- Zambezi Basin is 3.08 ± 2.19.

4 Discussion

Overall, the resistivity structure mapped by TEM in the Machile-Zambezi Basin Fig. 6 is characterised by three southwest to northeast trending areas of distinct electrical resistivity. These are:  The westerly high electrical resistivity area with resistivity values greater than 100 Ωm;  The middle area with low to moderate electrical resistivity (with values less than 100 Ωm) which is further subdivided into the south central area with low electrical resistivity and the central, south west to north east trending area with moderate electrical resistivity area; and  The easterly high electrical resistivity area with resistivity values greater than 100 Ωm. The high resistivity structure of the westerly block is attributed to a typical Kalahari Basin stratigraphy (McCarthy and Haddon, 2005) of unconsolidated sands underlain by sandstone or basalt. A borehole profile at Munyeula (Kameyama, 2003) (Borehole 3 in Table 2) reveals a 12 m sequence of sand underlain by a 58 m succession of sandstone, which in turn overlies weathered and fractured Batoka Basalt. The electrical conductivity recorded in the

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Table 2: Selected borehole records in Machile-Zambezi Basin (Kameyama, 2003; Bäumle et al., 2007)

Borehole 1 Borehole 2 Borehole 3

Name Mbanga Name Kasaya Name Munyeula

Latitude 17.45241667 Latitude 17.45497222 Latitude 17.06072222

Longitude 24.96958333 Longitude 25.00333333 Longitude 24.66130556

EC (µS/cm) 7250 EC (µS/cm) 12180 EC (µS/cm) 263

Depth (m) Lithology Depth (m) Lithology Depth (m) Lithology

1 Fine sand 6 Clay 12 Fine sand

2 Clay 12 Fine sand 18 Sandstone

Clayed Fine Clayed fine 4 16 40 Sandstone sand sand Clayed fine 10 Fine sand 34 52 Sandstone sand Clayed Fine 14 50 Fine sand 58 Basalt sand Clayed fine 16 Clay 56 70 Basalt sand

22 Medium sand 60 Fine sand

Clayed Fine Clayed fine 26 62 sand sand

66 Fine sand 82 Fine sand

Borehole 4 Borehole 5 Borehole 6

Name Siamundele Name Sekute School Name Kamenyani

Latitude -17.17558 Latitude -17.65472 Latitude 17.06680556

Longitude 25.83619 Longitude 25.65889 Longitude 25.16697222

EC (µS/cm) - EC (µS/cm) - EC (µS/cm) 1932

Depth (m) Lithology Depth (m) Lithology Depth (m) Lithology

2 Top soil 6 Sand with clay 4 Fine sand

28 Granite 18 Sandstone 6 Clay

38 Granite 49 Basalt 22 Fine sand + silt

66 Granite 36 Sandstone

55 Quartz 68 Sandstone

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groundwater from this borehole is 263 µS/cm. This shows consistency between the formation resistivity measured by the TEM methods and the intrinsic high resistivity of the unconsolidated sands, sandstone, basalt and pore water at this location. The borehole record at Munyeula also shows the water table to be 4.4 m implying that a 4.4 m sequence of dry Kalahari sand sits on top of the water table and would typically register as a high resistivity layer with resistivity values greater than 500 Ωm. Below the water table, the resistivity values would be moderated down wards to below 100 Ωm until solid bed rock is encountered at which point they would also register high resistivity values in the 1000 Ωm order of magnitude. Similarly, the surface geology of the easterly block is defined in the northeast by a northeast to southwest trending basement complex (Pre Cambrian geology) region and in the southwest by what appears to be a basin filled with Kalahari sediments and bound to the northeast and southwest by Mesozoic igneous horsts (refer to Fig. 2 above) herein referred to as the Sekute Basin. A borehole record at Siamun- dele (Bäumle et al., 2007) (Borehole 4 in Table 2) indicates a granitic formation consistent with the high formation resistivity detected by the TEM methods. In addition, a borehole record at Sekute School (Bäumle et al., 2007) (Borehole 5 in Table 2) indicates that the stratigraphy of the Sekute Basin is characterised by sand and clay (6 m) on top of sandstone (18 m) which in turn is underlain by basalt, a lithology log similar to the borehole profile at Munyeula in the easterly block and a similar relationship to the formation resistivity measured by the TEM methods is thus inferred. A summary of selected borehole records in the Sesheke and Kazungula area of south western Zambia in the 3 resistivity blocks of the Machile-Zambezi Ba- sin is shown in Table 2. The electrical resistivity structure of the middle area as mentioned above has two sub divisions. The first one is the south and central low electrical resistivity area that has an extent closely following the 945 m contour synony- mous with the Palaeo Lake Makgadikgadi shoreline (Fig. 5 above). However, the spatial extent of the low electrical resistivity area is much larger at shallower depths (Fig. 4 above) and extends north-easterly beyond the 945 m contour by about 32 km with a vertical rise of about 20 m. The low resistivity block therefore overlies and thins out into the southwest to northeast trending moderate resistivity block northeast of the 945 m contour. The moderate resistivity block is abruptly truncated in the vicinity of the 945 m contour and has a gentle rise towards the northeast until it overlies the thinning out low electrical resistivity area (Fig. 6b above). Existence of the low resistivity

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block can be attributed to sediments related to the palaeo Lake Makgadikgadi with evidence of this correlation arising from the borehole profiles at Kasaya and Mbanga (Table 2). These depict alternating and mixed sequences of fine sand and clay with very high pore-water salinity; 7,250 and 12,180 µS/cm at Mbanga and Kasaya (boreholes 1 and 2 in Table 2). Milzow et al. (2009) observed a similar setting in the Okavango Delta and attributed the alternating and mixed sequences of clay and sand to alternating cycles of fluvial and lacustrine depositional setting. The work by Banda et al. (Technical University of Denmark/University of Zambia, Unpublished data, 2014) used borehole logging, sediment core characterization and geochemical analysis to postulate that palaeo Lake Makgadikgadi sediments were responsible for groundwater salinity in the Machile Basin (after Moore and Larkin (2001)) which is congruent with the low electrical resistivity area. Banda et al. (Technical Univer- sity of Denmark/University of Zambia, Unpublished data, 2014) thus describe a lithological setting of alternating and mixed sequences of silty-clay, clay and sand attributed to fluvial and lacustrine deposition associated with varying climatic conditions containing saline groundwater entrapped at the time of deposition of the lake sediments. In addition, the fact that the low electrical resistivity area closely follows the 945 m contour at the depth interval 80 -100 m is further supporting evidence of palaeo Lake Makgadikgadi sediments in the Machile-Zambezi Basin. However, this is in contrast to the extension of the low resistivity area beyond the 945 m contour towards the northeast for depth interval 0 to 20 m (refer to Fig. 5 above). A possible explanation for this is likely related to uplift along the Kafue-Machile Water- shed and associated closure of the palaeo-Kafue/Upper Zambezi link (McCar- thy, 2013). Alternatively this could also be as a result of shallow ground water related to the Palaeo Lake Makgadikgadi which was subjected to evapo- concentration. According to Moore et al. (2012) the palaeo Chambeshi River, which was a combination of the proto Kafue and proto Chambesh river systems, used to flow in to the Makgadikgadi Basin through the Machile Flats, where it would join the Upper Zambezi River. This south westerly flow of the palaeo Chambeshi was associated with deposition of Kalahari super group sediments (Moore and Larkin, 2001) which correlated with the Barotse sand member (Money, 1972). Thus the deposition of sandstone is believed to have occurred in braided streams (McCarthy and Haddon, 2005) indicative of low slope terrain which could have easily been below or at the level of the 945 m contour by the time the sands were fully deposited. Lake sediments would have then

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been deposited in a shallow stretch up to the present northern extent of the low resistivity block followed by uplift along the Kafue-Machile Watershed (Moore et al., 2012). This up-lift could have given rise to the gentle north easterly slope responsible for occurrence of part of the low resistivity block above the 945 m contour. However, Banda et al. (Technical University of Denmark/University of Zambia, Unpublished data, 2014) postulate that this was probably the result of evapo-concentration of shallow groundwater from the palaeo lake system. A borehole record at Kamenyani (Borehole 6 in Table 2) reveals an uppermost 4 m dine sand, overlying a 6 m sequence of clay, which again is underlain by a 22 m sequence of silt and sand suggestive of a lacustrine setting, overlying is a 4m layer of sand, probably as a result of recent deposition by aeolian processes. The silt and sand sequence is underlain by sandstone. One implication of this interpretation is that the moderate resistivity area could have had resistivity values as low as in the low electrical resistivity area. However uplift along the Kafue-Machile Watershed resulted in a net groundwater flow towards the southwest resulting in flushing of the system with fresh groundwater resulting in moderated electrical conductivity values such as the 1,932 µS/cm observed at Kamenyani compared to the 12,180 µS/cm observed at Kamenyani.

5 Conclusion The resistivity structure of the Machile-Zambezi Basin is characterised by three distinct southwest to northeast trending electrical resistivity areas. These are:

 The high electrical resistivity westerly area with resistivity values greater than 100 Ωm associated with a sand, sandstone and Basalt downward sequence;  The middle low to moderate electrical resistivity area with values less than 100 Ωm. This is further subdivided into the south and central low electrical resistivity area (with values less than 13 Ωm) and the south west to north east trending moderate electrical resistivity area (with values between 10 – 100 Ωm). The low electrical resistivity area is congruent with the northern tip of the palaeo Lake Makgadikgadi sediments extending into south- western Zambia and is filled with saline groundwater trapped at the time of deposition of the sediments ; and

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 The easterly high resistivity block with resistivity values greater than 100 Ωm associated with Basement Complex and Kalahari stratigraphic settings. The southwest to northeast orientation of the resistivity blocks is a clear indication of continuity of the Okavango-Linyati Fault System and associated palaeo Lake Makgadikgadi into south-western Zambia. The combination of ground based and airborne TEM methods was thus effective in mapping the regional electrical resistivity structure of the Machile- Zambezi Basin from which groundwater salinity variations could be inferred in addition to the regional tectonic structure or geological fault system. Cali- bration of VTEM data with accurate ground based WalkTEM data ensured a strong agreement between the airborne TEM inverted using an SCI scheme and ground based data inverted as single site 1D inversions.

6 Acknowledgements Gratitude is given to the governments of the Kingdom of Denmark and the Republic of Zambia for funding this research under the capacity building ini- tiative for the Zambian Water Sector through the University of Zambia Inte- grated Water Resources Management Centre. Thanks also go to the Hydro- geophysics group of Aarhus University for assistance in processing and inversion of the airborne dataset. Special thanks also go to colleagues and friends who assisted in field work especially Kebby Kapika (District Water Officer-Sesheke) and Mweemba Sinkombo (District Water Officer-Nalolo) who was then a Post-graduate diploma student at UNZA. Logistical support by Ms. Ingrid Mugamya Kawesha of UNZA IWRM Centre is also acknowl- edged.

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I - 27 II

Mapping localized freshwater anomalies in the brackish Paleo-Lake sediments of the Machile- Zambezi Basin with transient electromagnetic sounding, geoelectrical imaging and induced polarization

Chongo, M., Christiansen, A.V., Fiandaca, G., Nyambe, I.A., Larsen, F., and Bauer-Gottwein, P.

Submitted to Journal of Applied Geophysics (Manuscript No: - AP- PGEO3721)

Mapping localized freshwater anomalies in the brackish Paleo-Lake sediments of the Machile-Zambezi Basin with transient electromagnetic sounding, geoelectrical imaging and induced polarization

Mkhuzo Chongo1,*, Anders Vest Christiansen2, Gianluca Fiandaca2, Imasiku A Nyambe3, Flemming Larsen4 and Peter Bauer-Gottwein1

1Technical University of Denmark, Department of Environmental Engi- neering, Miljøvej, Building 113, 2800 Kgs. Lyngby, Denmark 2Aarhus University, Department of Geoscience, C.F. Møllers Alle 4, 8000-Århus C, Denmark 3University of Zambia, School of Mines, Department of Geology, Great East Road Campus, P.O Box 32379, Lusaka, Zambia 4 Geological Survey of Denmark and Greenland (GEUS), Geochemis- try, Øster Volgade 10, 1350 København K, Denmark

Submitted to Journal of Applied Geophysics (Manuscript No: - AP- PGEO3721)

*Email: [email protected]; [email protected].

Abstract A recent airborne TEM survey in the Machile-Zambezi Basin of south western Zambia revealed high electrical resistivity anomalies (around 100 Ωm) in a low electrical resistivity (below 13 Ωm) background. The near surface (0- 40 m depth range) electrical resistivity distribution of these anomalies appeared to be coincident with superficial features related to surface water such as alluvial fans and flood plains. This paper describes the application of transient electromagnetic soundings and multiple electrode profiling using geo- electrics and time domain induced polarization to evaluate a freshwater lens across a flood plain on the northern bank of the Zambezi River at Kasaya in south western Zambia. Coincident TEM and CVES measurements were conducted across the Simalaha Plain from the edge of the Zambezi River up to 6.6 km inland. The resulting TEM, direct current and induced polarization data sets were inverted using a new mutually and laterally constrained joint inversion scheme. The resulting inverse model sections depict a freshwater lens sitting on top of a regional saline aquifer. The fresh water lens is about 60 m thick at the boundary with the Zambezi River and gradually thins out and deteriorates in water quality further inland. It is postulated that the freshwater lens originated as a result of interaction between the Zambezi Riv- er and the salty aquifer under evapotranspiration. Similar high electrical resistivity features were also associated with other surface water features located in the airborne survey area.

II - 1 1 Introduction The interaction between surface water and groundwater has been studied extensively around the world (Winter, 1999; Sophocleous, 2002; Westbrook et al., 2005; Milosevic et al., 2012; Shanafield and Cook, 2014; Zhou et al., 2014) using different approaches, and increasingly geophysical methods are being incorporated into such studies. For example, Bauer et al. (2006) described the process of salt accumulation on islands within the Okavango Del- ta, related to the interaction between surface water and groundwater under evapo-concentration using a combination of electrical resistivity tomography (ERT) and hydrodynamic modelling. Sonkamble et al. (2014) evaluated the extent of aquifer pollution from industrial effluent across the flood plain of the Palar River at Ambur Town (India) using 1D and 2D geo-electrics correlated with in-situ water quality data and ground penetrating radar. They found that 60.4% of the study area (particularly in the shallow aquifers underlying the flood plain and valley fills) corresponding to a spatial extent of 33.4 km2 was polluted. Their criterion for pollution threshold was based on a formation electrical resistivity of less than 20 Ωm representing pore water electrical conductivity in the order of 15,345µS/cm. Shalem et al. (2014) studied the interaction of the Alexander River with groundwater as it cuts its way across a mostly sandy Quaternary coastal aquifer on the eastern coast of the Medi- terranean Sea. They accomplished this using a combination of 3 continuous vertical electrical sounding (CVES) transects of not more than a few 100 m each; single site transient electromagnetic (TEM) measurements; in-situ electrical conductivity, temperature and sediment sampling during borehole drilling; groundwater and stream level measurements; salinity and depth profiles along the river bed; and evaluation of regional water levels and chloride concentrations from databases of the Hydrological survey of Israel. From this they observed that sea encroachment resulted in a seasonal increase of river water salinity from which they could infer the extent to which the river interacted with the underlying aquifer. Aquifer salinization due to the river was found to be limited to several meters from the river bed and less than 5 m below ground level within 500 m from the coastline. However, about 1,800 m from the coast, the river salinized the aquifer more than 50 m away towards the north with fresh water occurring 120 m away at depths of 20-25 m. Thus geophysical measurements are well suited for gathering data at high spatial resolution and an overall assessment strategy using a combination of different geophysical methods can be advantageous (Brodie et al., 2007). In this regard, TEM (Harthill, 1976; Nabighian, 1991; Danielsen et al., 2003;

II - 2 Xue et al., 2012), direct current geo-electrics (DC) (Loke, 1999; Dahlin, 2001; Aizebeokhai, 2010; Loke et al., 2013) and induced polarization (IP) (Bertin and Loeb, 1969; Dahlin et al., 2002; Titov et al., 2002; Fiandaca et al., 2012; Fiandaca et al., 2013) techniques are quite suitable for environmental and hydro-geological investigations particularly in sedimentary terrain. Traditionally, TEM, DC and IP techniques have been deployed separately even for investigations at the same study site (Nassir et al., 2000; Guerin et al., 2001; Bauer et al., 2006; Ezersky et al., 2011; Vaudelet et al., 2011) although it is now common to have instrumentation that measures both DC and IP in the same field setup (Aristodemou and Thomas-Betts, 2000; Marescot et al., 2008). As a result, different types of datasets are quite often generated for the same physical or environmental phenomenon by inverting each type of dataset individually. Nevertheless, major benefits can be derived from joint inversion of different types of data that observe the same phenomenon and can lead to more accurate interpretations. Thus many studies have successfully used one form of joint inversion or another such as DC-TEM (Albouy et al., 2001; Christiansen et al., 2007; Danielsen et al., 2007), and MRS-TEM (Behroozmand et al., 2012; Vilhelmsen et al., 2014). Examples of DCIP joint inversions are scarce in the literature with the normal practice being to independently invert the DC and IP data either as separate inversion jobs or in one inversion job but without any of the datasets influencing the other during the inversion process. Furthermore, joint DCIP-TEM inversions have not been reported in the literature before. This paper therefore presents a first case study of joint inversion of DCIP-TEM data. The focus of this paper is on local scale electrical resistivity anomalies derived from interpreting high resolution regional scale TEM data in terms of surface water/ groundwater interaction in the Machile-Zambezi Basin. The objectives were to describe the occurrence of high electrical resistivity anomalies in the low electrical resistivity background environment of the Machile- Zambezi Basin; conduct high resolution local scale TEM and direct current- induced polarization (DCIP) CVES measurements along a transect cutting across an area exhibiting electrical resistivity anomalies; evaluate the benefits of joint inversion of the local scale TEM and DCIP data in comparison to separate inversions; and to evaluate the inverse resistivity section in terms of surface water groundwater interaction taking place at the local site.

II - 3 2 Materials and methods 2.1 Study site The study area is in the southern central low lying areas of the Machile- Zambezi Basin on the northern banks of the Zambezi River. The area is drained by three main tributaries of the Zambezi namely Loanja, Machile (or Kasaya) and Ngwezi. The Machile and Ngwezi streams cut across flood plains before entering the Zambezi but the Loanja forms an inland delta or alluvial fan instead. The Loanja alluvial fan and the Simalaha flood plain (bound by Kasaya River to the west and the Zambezi River to the south) were the two local areas of interest for this study. However, the combined TEM/CVES transect is reported only for the Simalaha flood plain (Fig. 1).

Fig. 1: The study area depicting Loanja alluvial fan, Simalaha flood plain, Kasaya Tran- sect and TEM flight paths. Satellite image courtesy of ESRI (2014). Note that the Simalaha Profile is shorter than the Kasaya Transect since there is no more airborne electromagnetic data outside the flight lines, whereas the CVES and TEM data on the Kasaya Transect extend beyond the flight path where the Simalaha Profile ends up to the Zambezi River. 2.2 Data collection and pre-processing Airborne data was conducted along 8 flight lines totalling 1000 line kilometres using the VTEM system (GEOTECH, 2011). Four of the flight lines were oriented northeast to southwest whereas the other 4 were oriented from

II - 4 northwest to southeast (Fig. 1 in Section 2.1). Details about the airborne survey and about the processing, inversion and interpretation of the collected TEM data are given in Chongo et al. (in press, 2014). Cross sections of the airborne TEM data along the Loanja and Simalaha profiles (Fig. 1 in Section 2.1) are shown in Fig. 2 (a.) and (b.) respectively. These depict superficial electrical resistivity anomalies in an otherwise low electrical resistivity (saline environment) and were the basis of the detailed local scale study conducted on the Kasaya transect presented in this paper.

(a.)

(b.)

Fig. 2: (a) Electrical resistivity cross section along Loanja Profile (Fig. 1 in Section 2.1) from the airborne TEM data. (b) Interpolated electrical resistivity cross section along Simalaha Profile (Fig. 1 in Section 2.1) from the airborne TEM data. Note that Loanja and Simalaha profiles are not drawn to scale nor are they the same length since Loanja Profile (about 106 km long) is along a flight line whereas Simalaha Profile (about 5.7 km long) cuts across flight lines and as a result has a more limited data extent.

The detailed local scale geophysical investigation conducted across the Sima- laha Plain at Kasaya (Fig. 1 in Section 2.1) comprised:-

 6.6 km of CVES (Loke, 1999; Nassir et al., 2000; Loke et al., 2013) measurements at 5 m electrode spacing using the gradient array (Dahlin and Zhou, 2006) with 25,003 data points. The Terrameter LS (ABEM(a), 2012) was used for the CVES to measure both direct current electrical resistivity (DC) (Loke et al., 2013) and time domain induced polarization (IP)(Johnson, 1984) hence the term DCIP to denote the combination of DC and IP measurements in a roll along setup; and 64 single site TEM (Kirsch, 2006) soundings using the Aarhus Universi- ty/ABEM WalkTEM system; and another set of 64 central loop TEM soundings using the Geonics ProTEM 47D instrument (Geonics, 2006) at

II - 5 the same positions as the WalkTEM soundings. Thus the total number of TEM soundings along the transect line was 128 spaced at approximately 100 m along the 6.6 km transect line per pair of WalkTEM/ ProTEM 47D soundings. However data from the ProTEM instrument was not used for this paper. The DCIP data was pre-processed by removing all data points with negative electrical resistivity and data variations greater than 1.5 %. The data that was removed this way represented only 3.3 % of the original data i.e. 851 filtered out measurements from a total of 25, 857 DCIP measurements. The data was then imported into the Aarhus Workbench with the IP data gated into 10 channels. Data processing in the Workbench comprised semi-automatic removal of bad IP data by setting a maximum slope change for the IP decay curves followed by visual inspection of the DC and IP data points along the profile and consequent disabling of the outliers. The DCIP noise model was set to 1.03 uniform standard deviation (USTD) on DC and 1.15 USTD on IP whereas the threshold on voltage was set to 2.0 mV. For the WalkTEM data we used data from 77.6 µs to 2.84 ms, focusing on the deep information only. 2.3 Inversion methodology DC and TEM data were inverted separately using the 1D laterally constrained inversion (LCI) (Auken et al., 2005) scheme. Subsequently, a joint inversion using the mutually and laterally constrained inversion scheme of Christiansen et al. (2007) was conducted on the DC and TEM data as a single inversion. This was then extended to include IP data using the Cole-Cole model setup (Fiandaca et al., 2012; Gazoty et al., 2012b) so that the final inversion was a joint inversion of DCIP and TEM data. Thus the DCIP and TEM model parameters being modelled comprised (intrinsic chargeability (M0), frequency dependence constant (c), time constant (τ), formation electrical resistivity (ρ) and layer thicknesses). The inversion algorithm AarhusInv (Auken et al., 2014) was used for all inversions presented in this paper. As mentioned in Section 2.2, the interval of TEM soundings along the Ka- saya transect was approximately every 100 m whereas the DCIP data was collected with 5 m gradient array electrode spacing. The lateral constraints on the TEM models were setup such that each TEM model was constrained only to the adjacent TEM model on either side along the transect line. Similarly, each DCIP model was constrained only to the adjacent DCIP models. Treat- ment of mutual TEM/DCIP constraints is explained below.

II - 6 The reference lateral constraint on electrical resistivities was set to 0.3 and scaled according to: ∗ (1)

where Ci = lateral constraint on resistivity [dimensionless fraction]; Cr is the reference constraint [dimensionless fraction]; d is the distance between respective models [m]; and dr is the reference distance which was set to 10 m. Furthermore, the reference constraint on depths was set to 1 m and scaled according to depth so that the deeper layers had relatively tighter constraints. The constraint values mentioned above can be considered as medium for the resistivity values and tight for the depths. These were used because they were found to give a reasonable inversion result using trial and error. Lastly, mutual constraints were applied between the TEM and DCIP models using depths of layers to set the constraint width and scaled according to the power law given above (equation 1). Thus, the deeper layers had wider and tighter constraints between TEM and DCIP models because the constraints were only applied if the distance between respective TEM and DCIP models was less than or equal to the layer depth. The reference constraint between TEM and DCIP models was set to 0.1 but the reference depth was the same as for the lateral constraints (Christiansen et al., 2007). 2.4 Petro-physical considerations The petro physical relation for the Kasaya area was estimated using the following equations (Rhoades et al., 1989; Mualem and Friedman, 1991; Kirsch, 2009), ∗ (2) ∅

1000 ∗ 2.3 ∗ 0.021 (3)

where σo = bulk conductivity or formation conductivity [µS/cm]; σw = pore water conductivity [µS/cm]; θ = volumetric water content [dimensionless]; u = exponent on volumetric water content (reported as 2.5 by Kirsch (2009))

II - 7 ϕ = porosity [dimensionless]; σsfc = surface conductivity [µS/cm]; and C = volumetric clay content [dimensionless] (Kirsch, 2009). The constant 1000 is a unit conversion factor from mS/cm to µS/cm whereas the constants 2.3 and 0.021 are empirical factors as derived by Rhoades et al. (1989). For fully saturated conditions applicable to groundwater, the volumetric water content was taken to be the same as the porosity meaning that Equation 2 could be simplified as:

∅ (4)

where the porosity exponent, 1 (5)

The various parameters of equation 2 and 3 (porosity, porosity exponent and clay content) were adjusted in order to obtain the best curve fitting through the Kasaya pore water point and the unsaturated formation resistivity point Fig. 3 (a.). The Kasaya pore water point was defined by the pore water conductivity measured from the borehole fluid by Banda et al. (2014) using an electrical conductivity meter, and the formation electrical resistivity below the water table as measured by the TEM method. The layered earth model derived from 1D inversion of the TEM sounding at Kasaya was comparable to the induction borehole log of Banda et al. (2014) at the Kasaya School borehole Fig. 3 (b.). The TEM sounding was conducted using a 40 x 40 m central loop configuration with the centre of the loop coincident with the borehole. The unsaturated formation resistivity point was defined by a pore water electrical conductivity of 0 µS/cm, denoting absence of pore water, and the formation electrical resistivity above the water table as measured by the TEM method.

At present, a petro-physical relationship between IP parameters and hydrogeological parameters is difficult to define. However, Pelton et al. (1978) observed that chargeability (Cole-Cole parameter M0) and time constant (Cole- Cole parameter τ) were directly proportional to fluid concentration and that grain size was inversely proportional and directly proportional to M0 and τ respectively. On the other hand, Slater and Lesmes (2002) using an experi- mental laboratory freshwater intrusion into salty water model observed that

II - 8 the chargeability was directly proportional to the fluid resistivity i.e. inversely proportional to the fluid conductivity in contrast to observations by Pelton et al. (1978).

Kasaya curve x 104 3 C = 0.021 C = 0.5 2.5 C = 1 F = 0.10 2 F = 0.35 F = 0.60 1.5 u = 1 u = 2 1 u = 3 pore water at Kasaya 0.5 unsaturated formation resistivity pore water at Lipumpu

Pore water conductivity [µS/cm] 0 10-1 10 0 10 2 10 2 10 3 (a.) Formation resistivity [W /cm]

0 Induction log TEM model

100

Depth [m]

150

200 0 1020304050 (b.) Resistivity [W m] Fig. 3: (a.) Illustration of the variation of the petro-physical relation (Equation 1) for different parameters (porosity (ϕ), volumetric water content exponent (u) and clay content (C). Kasaya curve is the curve fitting the measured borehole fluid conductivity at Kasaya and the unsaturated formation resistivity measured by TEM at the same location. (b.) Vari- ation of electrical resistivity with depth from an induction log and TEM sounding at Ka- saya School in Machile-Zambezi Basin.

Furthermore, Slater and Lesmes (2002) could not find any clear correlation between chargeability and clay content for various mixtures of sand and ben- tonite clay. However, a correlation was found to exist between clay content and the product of fluid conductivity and chargeability. Given the observations by Slater and Lesmes (2002), the petro physical relation given by Equation (2) above (section 2.4) is assumed to hold for this

II - 9 study given that the electrical resistivity models produced from the joint DCIP-TEM inversion are informed or constrained by the chargeability models. Further research is required for better treatment of IP parameters with respect to hydrogeological considerations (Gazoty et al., 2012a; Gazoty et al., 2012b; Weller et al., 2013). 2.5 Depth of investigation The depth of investigation (DOI) (Roy and Apparao, 1971; Spies, 1989; Ol- denburg and Li, 1999; Christiansen and Auken, 2012)can be used as a way of evaluating the degree to which measured data and their associated uncertainty or noise level are able to resolve the parameters of an inverse layered earth model(Christiansen and Auken, 2012). This is because DOI estimation is based on recalculation of the Jacobian matrix of the final 1D model, taking into account the full system transfer function, system geometry, the data and the noise level on the data. From the Jacobian matrix, cumulated sensitivities are computed from which the DOI is deducted based on an empirical threshold value (Christiansen and Auken, 2012). For this paper, two threshold values were used: 0.75, for deeper estimation of DOI (or lower DOI) and 1.5, for shallower estimation of DOI (or upper DOI). The DOI is presented on the model cross sections in form of colour fading with the upper DOI having a slightly darker shade than the lower. Thus model parameters above the DOI can be said to be well resolved whereas those below it are not. In addition to DOI, data residuals are also typically used as a measure of the fit between the data and the model although the information contained in the data residuals is also implied in the DOI.

3 Results and discussion As mentioned in Section 2.2, the airborne survey results show electrical resistivity variations correlated with surface water features in both the Simalaha Plain and the Loanja Alluvial Fan (Fig. 1 and Fig. 2 in sections 2.1 and 2.2 respectively). However, only the results of the Simalaha Profile survey are tackled in this paper. 3.1 Separate inversions LCI of DC (Fig. 4 (a.)) data resulted in very high detail of electrical resistivity variations and clearly delineated a conductive layer about 5 m thick on top of a high electrical resistivity lens that thins out from left to right (i.e. south to north) with respective weakening of electrical resistivity values. The DOI

II - 10 could not go beyond the high resistivity lens especially where the lens was thick and the resistivities relatively very high but was able to penetrate com- paratively deeper where the high resistivity lens had thinned out. In addition, the DOI was very variable along the model cross section and was typically very shallow at both ends but mostly a few meters less or more than 40 m. The shallow DOI at both ends is a consequence of lack of data in the deeper parts as a result of the four electrode configuration which has a shallower penetration depth for shorter electrode spacing.

DC LCI Electrical resistivity cross section

TEM LCI Electrical resistivity cross section

TEM Residuals

Joint TEM ‐DC Electrical resistivity cross section

Joint TEM‐DC Residuals

Fig. 4: Inverse electrical resistivity cross sections and residual plots. (a.) – (b.), inverse electrical resistivity cross section and residual plot respectively for LCI of DC data; (c.) – (d.), inverse electrical resistivity cross section and residual plot respectively for LCI of TEM data; and (e.) – (f.), inverse electrical resistivity cross section and residual plot respectively for MCI-LCI (i.e. joint inversion) of DC and TEM data. On the residual plots, blue lines are for DC residuals whereas green lines are for TEM residuals.

II - 11 LCI of TEM (Fig. 4(c.)) data shows reduced detail of electrical resistivity variations but improved resolution of electrical resistivity interfaces at depth. The TEM data is able to look beyond the high resistivity lens with a much deeper DOI meaning that model parameters are resolved at larger depths with the TEM data. In addition, the DOI varies more uniformly being deeper at the beginning of the transect line (around 100 m) and shallower at the end (around 50 m). This variation of DOI is indicative of the sensitivity of the TEM method to conductive layers at depth. At the beginning of the transect line, the resistive lens is thicker and therefore the depth to the conductive layer is deeper than at the other end of the transect line where the resistive lens is thinner where the depth to the conductive layer is shallower. 3.2 Joint TEM-DC inversions Evaluation of the inversion result from joint inversion of DC and TEM data (Fig. 4 (e.) in Section 3.1) shows that major benefits can be derived when TEM and DC data are incorporated into the same inversion job. Variation of DOI for the DC models became much more uniform although it remained at more or less the same level as with the DC only LCI. However, the interface to resistivity contrasts showed a marked improvement in the DC models and indicates that the characteristic of TEM data to clearly determine layer interfaces at depth migrated into the CVES models during the inversion process. Furthermore the TEM inverse models from the joint inversion still showed a deeper DOI in addition to being in good agreement with the DC data in the upper parts of the section (Fig. 4 (e.) in Section 3.1). Thus CVES data was able to improve the resolution of TEM data in the shallow subsurface, whereas TEM data was able to improve the determination of depths, resistivities and thicknesses in the DC data throughout the transect line. 3.3 Joint TEM DCIP inversions The incorporation of IP data into the joint inversion appears to have improved the DOI estimation in the DC data resulting in similar DOIs for both the DC and TEM data (Fig. 5 and Fig. 6). The high resistivity or freshwater lens is also clearly delineated as lying in between a thin conductive layer at the top and the underlying conductive background below and constrained to the high chargeability section. Other additional parameters (τ and c) with the potential of further characterising the aquifer and sediments at Kasaya were also produced from the DCIP-TEM joint inversion. However these have not been presented in this paper since this would have required substantial additional research and analysis beyond the present scope of study.

II - 12 DCIP‐TEM Electrical resistivity cross section

DCIP‐TEM Chargeability cross section

DCIP‐TEM Residuals

Fig. 5: (a.) Inverse resistivity cross section, (b.) inverse chargeability cross section, and (c.) data residual plot from joint inversion of DCIP and TEM data. The green line is for TEM residuals whereas the blue and redlines are for DC and IP residuals respectively.

The chargeability along the Kasaya transect appears to be correlated to the electrical resistivity in a manner similar to the experiment of Slater and Lesmes (2002) in which chargeability increased with electrical resistivity as a sediment sample filled with saline water was flushed with freshwater. In the experiment of Slater and Lesmes (2002), a sample of de-aired sand was first saturated with pure water (electrical resistivity = 1000 Ωm) and then flushed with 33 pore volumes (25 l x porosity) of NaCl (electrical resistivity = 4.54 Ωm) followed by gradual reintroduction of 37 pore volumes (27 l x porosity) of pure water. Measurements of electrical resistivity and chargeability were performed during the initial introduction of NaCl solution and the reintroduction of pure water. From this Slater and Lesmes (2002) observed that the bulk or formation electrical resistivity reduced with the introduction of saline water and recovered with the reintroduction of pure water. They also noticed that the chargeability increased with fluid electrical resistivity in such a way that the chargeability curve was almost a mirror of the electrical resistivity curve. Thus the fact that the high chargeability distribution along the Kasaya transect appears to coincide more or less with the high electrical resistivity distribution suggests that processes similar to those modelled by Slater and Lesmes (2002) are at play in the Kasaya area. In other words, the high chargeability observed along the Kasaya transect has to more to do with the infiltration of fresh water into a pre-existing saline environment.

II - 13 DCIP‐TEM Electrical resistivity cross section

DCIP‐TEM Chargeability cross section

DCIP‐TEM Residuals

DCIP‐TEM Electrical resistivity cross section

DCIP‐TEM Chargeability cross section

DCIP‐TEM Residuals

Fig. 6: (a.) – (c.) zoom in inverse electrical resistivity cross section, inverse chargeability cross section, and data residual plot respectively from joint inversion of DCIP and TEM data for distance interval 0 – 1,000 m. (e.) – (f.) zoom in inverse electrical resistivity cross section, inverse chargeability cross section, and data residual plot respectively from joint inversion of DCIP and TEM data for distance interval 4,000 – 5,000 m.

The high chargeability section would therefore be an indicator of the physical extent of where salty water has been replaced by recent fresh water. This concept of fresh water groundwater replacing pre-existing saline groundwater water under through flow conditions is also supported by Banda et al. (2015) through their sediment dilution experiment in which 20 g of drill core sediment samples from the Machile-Zambezi Basin were placed in 50 ml centri-

II - 14 fuge tubes and filled with deionised water. They then placed the tubes in a mechanical shaker in order to dissolve mineral phases until equilibrium was reached after which deionised water kept being replaced in the centrifuge tubes until the electrical conductivity was almost zero, indicative of complete removal soluble salts. 3.4 Hydrogeological interpretation In general, the model cross sections from joint DCIP-TEM inversion (Fig. 5 and Fig. 6 in Section 3.3) show:  a low electrical resistivity layer about 5 m thick with electrical resistivity values ranging between 1 - 12.6 Ωm at the top;  a middle high electrical resistivity lens which is about 60 m in the south (left hand side) and thins out towards the north (right hand side) to about 22 m . An electrical resistivity gradient is observed from south to north with high electrical resistivity values in the south (around 200 Ωm) and moderate electrical resistivity values in the north of about 31 Ωm. The section between 0 to 1800 m from the beginning of the transect line or edge of the Zambezi River shows the highest electrical resistivity values. These range between about 200 Ωm (closest to the river) and about 60 Ωm further away. After about 1800 m, the high electrical resistivity lens begins to taper out and shows a mixed pattern of electrical resistivity values ranging between about 30 – 60 Ωm;  the high electrical resistivity lens underlain by a transition layer with thickness ranging between about 5 to 10 m and electrical resistivity values in the range of about 15 Ωm. This layer diminishes at about 4600 m from the beginning of the transect line.  formation resistivity of around 3.59 Ωm below the high electrical resistivity and transition layers.  an inverse chargeability model with three distinct layers in the first half of the section and a heterogeneous mix of chargeability in the second half. Between 0 to about 3,300 m from the start of the transect line, an approximately 5 m thick 23–40 mv/v chargeability layer overlies a 90 – 120 mv/v chargeability layer with variable thickness of about 20-40 m. This in turn is underlain by a 15-20 mv/v chargeability layer below which the chargeability values are about 7 mv/v. After about 3,300 m from the start of the transect line until the end, the chargeability section is more or less mixed or chequered and shows a lesser degree of layering. Chargeability values

II - 15 below the chequered section are about 10 mv/v. The distribution of chargeability appears to be an indication of the layering of the sediments along the transect. The high chargeability of the second layer could be due to fresh water infiltration from the Zambezi River taking into account the considerations by Slater and Lesmes (2002). The chargeability therefore has an added value of defining the stratification and zones where freshwater has infiltrated and replaced the salty groundwater. Available borehole records for the Kasaya area (Kameyama (2003) and Ban- da et. al. (unpublished data, Danish Technical University, 2014)) indicate that the main aquifer material is composed of mixed and alternating sequences of sand and clay. Nevertheless comparison of a coincident TEM sounding with the borehole record and induction log at Kasaya (Fig. 3 (b.) in Section 2.3) indicates that the alternating sequences of sand and clay below the water table are seen as one layer with average resistivity of 2.7 Ωm. Above the water table the formation resistivity of the unsaturated zone was determined as 43.6 Ωm (resistivity standard deviation factor = 1.07) from the TEM inverse layered earth model. The interface between the 43.6 Ωm layer and the 2.7 Ωm layer at 10.6 m (depth standard deviation factor = 1.01) was taken to represent the water table although the water level reading in the borehole record at Kasaya indicates the water table to be at 13.2 m. The difference in depth between the water table recorded in the Kasaya borehole record and the one inferred from the TEM sounding could be as the result of either systematic and random errors when the water table was measured or the effects of the capil- lary fringe or a combination of both factors. The induction log profile appears to be in agreement with the TEM sounding (Fig. 3 (b.) in Section 2.3) and given the low standard deviation factors on both the electrical resistivity and the depth, the 1D electrical resistivity model derived from the TEM is considered to be accurate and that the actual water table should be around 10 m below ground level. Rhoades et al. (1992) classified non saline water as having electrical conductivity (EC) of less than 700 µS/cm with anything above this threshold falling into one of five other degrees of salinity with the highest being the category of brines having EC greater than 45000 µS/cm. Therefore based on equation 2 (above), freshwater aquifers in the Kasaya area can be considered to have a formation resistivity of greater than or equal to 29.4 Ωm; 5.62 – 29.4 Ωm for slightly to moderately saline groundwater; and 5.62 Ωm or less for very saline ground water. This classification of aquifer salinity should be viewed as representing the order of magnitude since the petro-physical relation is bound

II - 16 to be site specific depending on the distribution of clay content and porosity from site to site as can be seen from the measured pore water conductivity at Lipumpu Village which falls at its own unique position different from the petro-physical considerations at Kasaya (Fig. 3 (a.) in Section 2.3). There- fore, the top 5 m layer with heterogeneous resistivity values ranging between 1 - 12.6 Ωm is probably a layer of moist top soil with varying degrees of porosity, clay content and water content; the localised lower electrical resistivity values being attributed to higher localised clay content compared to areas with higher localised electrical resistivity. In addition, the high electrical resistivity lens below the 5 m top soil layer shows resistivity values greater than the 43.6 Ωm threshold for non-conducting pore water within 1800 m from the edge of the Zambezi River. A possible explanation is that that most of the clay minerals have been leached out in this region thereby significantly reducing the surface conductivity component of equation 1 leading to a rise in formation conductivity above the 43.6 Ωm for non-conducting pore waters. Beyond 1800 m from the edge of the Zambezi River, the petro physical relation appears to hold with electrical resistivity values around 30 Ωm indicative of freshwater. Below the fresh water lens the petro-physical relation suggested by equation 1 also holds and with electrical resistivity values all below 3 Ωm; this part of the aquifer is expected to have pore water conductivity above 20,000 µS/cm. This distribution of electrical resistivity values along the Kasaya transect into three distinct zones indicates infiltration of fresh surface water into a pre-existing saline aquifer. The interaction of surface water and ground water as suggested by the geophysics is conceptualised in Fig. 7 and is probably driven by evapotranspiration and recharge from the Zambezi River. In addition, the separation of the chargeability section (Fig. 5 (b.) in Section 3.3) mid-way into a well layered part (0-3,300 m) and a chequered part (3,300.6,600 m) appears to correlate well with the extents of the plain and forest areas. The layered chargeability section is in the plain whereas the chequered chargeability section is in the forest. The reason for the high chargeability values and their distribution is unknown.

II - 17

Fig. 7: Conceptual model of surface water/ groundwater interaction in the Simalaha flood plain. The major drivers are conceptualised as seasonally varying water table in the Zam- bezi River, localised seasonal rainfall and flooding, overland flow and evapotranspiration. 3.5 Regional scale perspectives The landscape of the Machile-Zambezi Basin comprises a southern central low lying area (elevation between 900 – 950 m amsl) surrounded by moderate relief hilly areas from southeast to southwest in a clockwise direction. The drainage network is such that all streams flow from the hilly areas into the low lying area and either terminate into alluvial fans or eventually end up into the Zambezi River. It is therefore likely that the groundwater regime in the upper reaches of the stream network is dominated by local flow systems with influent streams (Sophocleous, 2002). From the transition between the hilly areas and the low lying area up to the Zambezi River the topography exhibits very low gradient. Consequently the groundwater flow is probably dominated by intermediate and regional flow systems. These interact with a seasonal flood cycle whereby the river system is influent during flooding and effluent during the dry season (Sophocleous, 2002; Main et al., 2008). Thus surface water / groundwater interaction in the Machile-Zambezi Basin can be said to be driven by recharge in the high elevation areas and a mix of seasonally alternating exfiltration and infiltration in the moderate to low relief areas.

II - 18 An evaluation of a satellite image encompassing the lower reaches of the Loanja River and the Kasaya area (Fig. 8 (a.)) shows the main channel of the Loanja River emerging from the high relief belt and broadening into an alluvial fan in the low relief region. Overlying the satellite image with a mean horizontal electrical resistivity map for depth interval 0-20 m from the airborne TEM (Fig. 8 (b.)) shows that the alluvial fan is coincident with the higher electrical resistivity. This suggests that surface water interaction with the aquifer is responsible for high electrical resistivity values in an otherwise low electrical resistivity terrain.

Fig.8: (a) Satellite imagery (ESRI worldly 2D) showing termination of Loanja River into an alluvial fan in the Sesheke area, south-western Zambia. (b) Superimposition of horizontal mean resistivity map for depth interval 0-20 m onto an ESRI worldly 2D Imagery.

4 Conclusion A combination of TEM and DCIP measurements processed under joint inversion provided insight into the nature of surface water / groundwater interaction on the northern bank of the Zambezi River at Kasaya in southern Zam- bia. To our knowledge, this is the first time that joint inversion of TEM and DCIP data has been conducted. The joint inversion showed a fresh water lens

II - 19 about 6.6 km in length from the edge of the Zambezi River. This was found to be about 60 m thick at the interface with the river and slowly thinned out further away from the river until it reached a thickness of about 22 m at the end of the transect line. The fresh water lens is postulated to have had been produced by a combination of river inter action with the aquifer and influenced by evapotranspiration. On a sub-regional scale, the hilly and higher elevation areas of the Machile Zambezi Basin act as recharge areas with influent streams whereas the low lying areas interact with a seasonal flood cycle whereby the river system is influent during flooding and effluent during the dry season. Finally, the combination of DCIP and TEM data in a single inversion run produced better inverse models with well resolved model parameters based on DOI considerations. As a standalone, the TEM method had better model parameter resolution especially at depth whereas the standalone DC LCI produced inverse models with resolved parameters in the shallower sub surface but could not resolve parameters at depth. It was, nevertheless, superior to the TEM method in terms of data density. The resultant inverse models from joint inversion of DCIP and TEM data are therefore preferred because they present very high spatial density coupled with well determined model parameters with additional information about the layering of the sub surface from IP data. Inclusion IP data in the inversion had the added value of indicating the stratification and zones where fresh surface water has infiltrated into the sub surface and replaced salty groundwater.

5 Acknowledgements We are grateful to the Governments of the Republic of Zambia and the King- dom of Denmark for sponsoring this research under the capacity building ini- tiative for the Zambian water sector though the University of Zambia. Special thanks also go to Dr. Chisengu Mdala, Lecturer in Geophysics at the Univer- sity of Zambia and proprietor of Azurite Water Resources (Ltd) for allowing his field technician James Zulu to accompany us if the field to collect the CVES and TEM data and to Ingrid Mugamya at the UNZA IWRM Centre for logistical support. Furthermore we are grateful to Erik Lange from DTU for facilitating the meeting with Kurt Sørensen of SkyTEM that enabled us to borrow their WalkTEM instrument for our fieldwork. We would also like to thank Kebby Kapika (District Water Officer –Sesheke, Western Province, Zambia), Mweemba Sinkombo (District Water Officer -Nalolo, Western

II - 20 Province, Zambia) and the community at Kasaya for moral and physical support during the field measurements. Finally we would like to thank the Hy- dro-geophysics group at Aarhus University for assistance during processing and inversion of the TEM and CVES datasets.

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II - 25 III

Coupled hydrogeophysical inversion using a groundwater flow and transport model, and transient electromagnetic and direct current electrical resistivity data

Chongo, M., Nyambe, I.A., Larsen, F., and Bauer-Gottwein, P.

Manuscript

Coupled hydrogeophysical inversion using a groundwater flow and transport model, and transient electromagnetic and direct current electrical resistivity data

Mkhuzo Chongo1,*, Imasiku A Nyambe2, Flemming Larsen3 and Peter Bauer-Gottwein1

1Technical University of Denmark, Department of Environmental Engi- neering, Miljøvej, Building 113, 2800 Kgs. Lyngby, Denmark

2University of Zambia, School of Mines, Department of Geology, Great East Road Campus, P.O Box 32379, Lusaka, Zambia

3 Geological Survey of Denmark and Greenland (GEUS), Geochemis- try, Øster Volgade 10, 1350 København K, Denmark

Manuscript

*Corresponding Author email: [email protected]; [email protected]

Abstract A challenge in applied groundwater modelling is how to automatically and objectively inform groundwater models with geophysical data. The current approaches that have been developed to allow for this include sequential, joint, and coupled hydrogeophysical inversions. The coupled approach is particularly indicated for freshwater/saltwater studies because of the direct relationship between simulated model state (solute concentration) and observed geophysical signals or instrument responses. An extensive geophysical dataset for a 6.6 km transect at Kasaya in south-western Zambia comprising direct current and induced polarization data at 5m electrode spacing and 64 transient electromagnetic soundings spaced at 100 m intervals was used to inform a groundwater model simulating the intrusion of fresh water into a saline aquifer. The groundwater model was set up using the multi species solute and heat transport simulation program SEAWAT with an evapotranspiration boundary and a fixed river head boundary condition for the simulation of solute concentration distributions in 2D along the transect line. Using the Gauss-Marquardt-Levenberg algorithm implemented in the parameter estimation program PEST, SEAWAT parameters (e.g. hydraulic conductivity and porosity) and Archie’s Law coefficient and cementation factor were updated iteratively by the joint use of direct current and transient electromagnetic data. This is the first time that both direct current and transient electromagnetic data have been used jointly in a coupled hydrogeophysical inversion. The final SEAWAT concentration profile was found to be in good agreement with the geophysical data whereas the direct current and transient electromagnetic data constrained the hydraulic and petrophysical parameters to reasonable values to yield sharp parameter estimates. Performance of the coupled hydrogeophysical inversion was superior with the joint use of direct current and transient electromagnetic data in comparison to the use of transient electromagnetic data alone.

III - 1 1 Introduction Hydrogeophysics can be regarded as the application of geophysical methods (traditionally applied to the mineral and petroleum industries) to solve hydrological problems. Thus it has to do with the use of geophysical measurements to characterize the shallow subsurface in terms of groundwater flow, solute transport and groundwater contamination (Rubin and Hubbard (2006). Typical examples of geophysical methods applied to water resource or hydrologic problems (Rubin and Hubbard, 2006; Kirsch, 2009) include direct current and induced polarization (DCIP, Marshall and Madden, 1959; Dahlin, 2001; Revil et al., 2012), transient electromagnetics (TEM)(Nabighian, 1988; Nabighian, 1991; Kirsch, 2009), magnetic resonance sounding (MRS) (Leg- chenko et al., 2004; Kirsch, 2009) and microgravity (MG) (Gabriel, 2009). Thus each geophysical technique makes some form of earth observations or measurements (data) from which the physical properties of the subsurface (i.e. an earth model such as the variation of electrical resistivity with depth) can be inferred. The process of inferring the relevant physical earth properties (model parameters) from geophysical observations or measurements (data) is referred to as inversion and is normally done iteratively until a set of parameters is found whose forward solution fits the observations. The forward solution in this case being a determination of observable entities for a given set of model parameters based on a physical theory that relates the measurements to the model parameters (Tarantola and Valette, 1982; Menke, 2012). Typically some form of implementation of numerical optimisation (Haber et al., 2000; Nocedal and Wright, 2006) is used to perform the inversion e.g. Loke and Barker (1996); Loke et al. (2003); Auken et al. (2005) and Schwarzbach and Haber (2013). Hydrogeophysical inversion, which by definition is the inversion of geophysical data for hydrologic concerns, can be considered to be of three types. These are sequential hydrogeophysical inversion (SHI, Ferré et al., 2009; Herckenrath et al., 2013a), joint hydrogeophysical inversion (JHI, Herckenrath et al., 2013a) and coupled hydro-geophysical inversion (CHI, Hinnell et al., 2010). SHI typically follows a traditional geophysical approach in which hydrological parameters do not play a part in the inversion. Instead hydrogeological parameters such as the stratification of the sub surface lithology are inferred on the basis of the inverse geophysical models using some form of correlation such as petro-physical relations, expert knowledge or experience (Ferré et al., 2009; Hinnell et al., 2010). The inferred hydrogeological parameters may then be independently used to e.g. set up a

III - 2 groundwater model (Ferré et al., 2009; Hinnell et al., 2010). JHI on the other hand operates on parameters from both the geophysical model and the groundwater model at the same time. The geophysical and hydrological parameters are connected through a predefined petrophysical relationship whose parameters act as the coupling constraints between the geophysical data and the groundwater model parameters (Herckenrath et al., 2013a). As with JHI, CHI also integrates a hydrological model into the inversion process but in such a way that the inversion operates on the hydrological (and petrophysical) parameters (e.g. hydraulic conductivity and porosity) but not on the geophysical parameters. However, the model output (e.g. hydraulic head and solute concentration) is compared with or calibrated against spatially and temporally related geophysical observations. This is typically done by calculating forward responses from model outputs for comparison with instrument responses using direct physics or empirical relations in a numerical optimization. In addition, actual hydrological observations such as measured heads and concentrations can also be included in the CHI as additional data or prior information (Ferré et al., 2009). However, CHI is a relatively new sub discipline with new developments having been recorded only in the last 5-6 years. The most common approach so far has been to use electrical resistivity as measured from either electromagnetic or direct current methods to evaluate a two dimensional groundwater flow and/or transport model (Hinnell et al., 2010; Pollock and Cirpka, 2010; Herckenrath et al., 2013b). Other approaches have used CHI with time lapse gravity data for groundwater model calibration (Christiansen et al., 2011), ground penetrating radar data (Busch et al., 2013) and time lapse magnetic resonance sounding (Herckenrath et al., 2012). This paper presents further development of the CHI approach by Herckenrath et al. (2013b) to include for the first time the combined use of both TEM and DC data in a CHI. This is tested using field data collected by Chongo et al. (2015) in the Machile-Zambezi Basin (Chongo et al., 2015; Chongo et al., in press, 2014) which is part of the Kalahari Basin of Southern Africa (Moore and Larkin, 2001; McCarthy and Haddon, 2005; McCarthy, 2013) . The CHI approach using TEM and DC data finds particular relevance to the Kalahari Basin because of the sensitivity of geo-electric and electromagnetic methods to groundwater salinity (Nassir et al., 2000; Levi et al., 2008; Ezersky et al., 2011) for which the Kalahari aquifers are prone (Bauer et al., 2006b; Bauer et al., 2006c; Campbell et al., 2006). The salinity of groundwater in the Kalahari Basin seems to be associated with fluctuating endorheic and semi-arid or arid

III - 3 conditions during the evolution of the Kalahari Basin (Worthington, 1977; Arad, 1984; Key and Ayres, 2000; Moore and Larkin, 2001; Sattel and Kgotlhang, 2004; McCarthy and Haddon, 2005; Campbell et al., 2006; Zim- mermann et al., 2006; Bauer-Gottwein et al., 2007; Eckardt et al., 2008; Mil- zow et al., 2009; Moore et al., 2012; McCarthy, 2013; Banda et al., 2014; Banda et al., 2015). In addition, surface water bodies have interacted with the salty aquifers under climatic stresses such as evapotranspiration to create freshwater lenses that can be an invaluable source of freshwater in an otherwise saline environment (Bauer et al., 2006a; Bauer et al., 2006b; Bauer- Gottwein et al., 2007).

2 Methods 2.1 The study site The Kasaya Transect is situated on the Zambian fringes of the Zambezi Wet- lands (locally known as the Simalaha flood plains) which are seasonally in- undated for at least 1-3 months in a year (Pricope, 2013). The wetlands stretch from Sesheke Town as the Zambezi River enters the Linyanti- Okavango Depression (Machile Flats or Machile Graben on the Zambian side) up to the Mambova Rapids (8-12 km upstream of Kazungula Town) where it overtops the Chobe Horst to exit the graben (Main et al., 2008; Moore et al., 2012; McCarthy, 2013). The horst forms a barrier to the east- ward flow of the Zambezi River such that a nearly permanent shallow lake stand is maintained in the wetlands (Riedel et al., 2013). During peak annual discharges between the months of February to June, the flooded extent of the Zambezi Wetlands includes large swaths of the Chobe Depression (in Namib- ia) and the Machile Flats (in Zambia) (Main et al., 2008; Pricope, 2013). Mean annual discharge of the Zambezi River at Sesheke Town (Katima Mulilo) is estimated at 1,144 m3 /s (Main et al., 2008). However, there are no discharge data for the Zambezi at either the Mambova Rapids or Kazungula Town. In fact, not much hydrological data exists for the Zambezi Wetlands since only very few studies have been conducted in this area (Pricope, 2013). During and after high rainfall events, rapidly flowing overland flow from the northern and forested catchment areas is slowed down as it enters and flows through the Simalaha Plain. This causes water to pond for several days after a major rainfall event during which time it is either consumed by evapotranspiration, infiltrates and percolates into the subsurface or eventually flows to the Zambezi River as overland flow at a reduced rate. This is in addition to the flood cycle of the Zambezi River in which it seasonally breaks its banks to

III - 4 establish a flooding front in the order of 10 km from its main channel at Ka- saya based on eye witness accounts of the local people. However, on average the rainfall days are 111 with average annual rainfall standing at 808 mm and average annual evapotranspiration at 1,574 mm. Therefore the area experi- ences a rainfall deficit and most of the surface water is consumed by evapotranspiration (JICA/MEWD-B, 1995). The Zambezi Wetlands are underlain by unconsolidated Palaeo Lake Makgadikgadi sediments (Moore et al., 2012; McCarthy, 2013; Banda et al., 2014). The sediments, which are around 95 m thick (Banda et al., 2014) have been reworked by fluvial and aeolian processes in the complex evolutionary history of the Kalahari Basin to give rise to intercalated successions of clay, sand and silt (Thomas and Shaw, 1990; McCarthy and Haddon, 2005; Milzow et al., 2009; Banda et al., 2014).

WE t c e l e i s R. Zambezi n S h a c r a T a M y . sa

R a K !

R. Loanj

a 0120.5 Sesheke Km

Za Wetlands mb ezi Kazungula R.Zambezi Chobe R.

012.5 255075100 Km Fig. 1: The study site. Depicted is the Kasaya transect abutting Zambezi Wetlands. 2.2 TEM and DC field methods TEM (Nabighian, 1988; Nabighian, 1991; Kirsch, 2009) and DCIP (Marshall and Madden, 1959; Bertin and Loeb, 1969; Loke et al., 2013) data were collected at a field site at Kasaya in the Machile-Zambezi Basin in south western Zambia. This comprised 6.6 km of continuous vertical electrical sounding

III - 5 (CVES) at 5 m electrode spacing with the Terrameter Lund System (LS) instrument (ABEM(a), 2012) and 64 single site TEM soundings placed 100 m apart using the WalkTEM instrument (ABEM(b), 2014). Details about the CVES/TEM transect at Kasaya which was constructed perpendicular from the edge of the Zambezi River are given by Chongo et al. (2015). However, a cross section from the TEM laterally constrained inversion (LCI) conducted by Chongo et al. (2015) is shown in Fig. 2 and depicts a freshwater lens sitting on top of a saline aquifer based on the distribution of electrical resistivity. Electrical resistivity values greater than 29.4 Ωm were indicative of fresh groundwater whereas those below 5.62 Ωm indicated very saline groundwater. In between these two values the groundwater was considered moderately saline to saline respectively (Chongo et al., 2015).

Electrical resistivity cross section from LCI of TEM data Wm 950 1000

900 100

850 10 Depth [m]

800 1 0 1000 2000 3000 4000 5000 6000 Proﬁle Coordinate [m] Fig. 2: Electrical resistivity cross section from the LCI of TEM data of Chongo et al. (2015). 2.3 Geophysical inversion techniques The TEM and DCIP data were inverted using a new joint inversion scheme in which DCIP and TEM data were combined in one setup using the mutually and laterally constrained inversion (MCI)(Auken et al., 2005; Christiansen et al., 2007) setup and AarhusInv(Auken et al., 2014) as the inversion algorithm. This was in addition to laterally constrained inversion (LCI) (Auken et al., 2005) of TEM data and joint inversion of TEM and DC data under the MCI setup. Details about the new DCIP-TEM joint inversion, the TEM LCI and the DC-TEM MCI are also given in Chongo et al. (2015). The final result from the TEM LCI and DC-TEM MCI of Chongo et al. (2015) was used to qualitatively evaluate the CHI performed in this paper. 2.4 Hydrodynamic modelling in SEAWAT A simple groundwater flow and solute transport model was constructed for the Kasaya Transect using SEAWAT (Langevin et al., 2007). This was designed based on the conceptual model shown in Fig. 3 in which the main

III - 6 stresses and boundary conditions are evapotranspiration and a fixed head in the Zambezi River respectively.

Intermediate water table Evapotranspiration river induced potentiometric surface

fresh water /salty water interface

Lake sediments

river induced fresh water aquifer

Saline aquifer

Fig.3: A simple conceptual model of freshwater infiltration from the Zambezi River into the saline aquifer at Kasaya in south western Zambia. The main stress was considered to be evapotranspiration with a fixed head boundary in the Zambezi River.

The conceptual model is one possible hypothesis to explain the occurrence of a freshwater lens on top of a saline aquifer given the similar hydrological, hydrogeological and geological stresses and settings as reported by Bauer et al. (2006a; 2006b; 2006c) in the Okavango Delta. The freshwater lens was inferred from interpretation of geophysical data for the Kasaya Transect (Chongo et al., 2015). Evapotranspiration was considered as the main hydrological forcing because the study area is in a rainfall deficit region whereby potential evapotranspiration is significantly higher than precipitation. In addition, the actual rainfall days, with extremely variable precipitation, are less than 4 months between the December to May rainy season (JICA/MEWD-B, 1995). Therefore, the effects of seasonal processes such as overland flow, infiltration and percolation, and through flow were assumed to be negligible. Furthermore, it was considered reasonable to have a fixed head in the Zambe- zi River because of the near permanent shallow lake stand in the Zambezi Wetlands to which the Kasaya Transect abuts. The main aquifer material at Kasaya was considered to be the Palaeo Lake Makgadikgadi sediments which are known to be stratified by intercalations of clay, sand and silt as mentioned

III - 7 above. However, the geophysical result of Chongo et al. (2015) suggests two basic units; the superficial high electrical resistivity (freshwater lens) upper layer and the underlying saline water domain. Thus for purposes of this study the two basic units were hydrologically distinguished by different horizontal hydraulic conductivities. The upper unit was assigned higher values whereas the lower unit was assigned lower values because it was assumed that the saline water domain could have had higher levels of cementation (i.e. calcreti- zation and silcretization) and compaction on account of very high solute concentration (i.e. very low electrical resistivities) and depth respectively. The numerical setup comprised a 2D grid with 1000 columns and 10 rows for a domain extent and depth of 6,500 and 100 m respectively. The columns represented discretization along the transect line whereas the rows represented discretization in the vertical direction and were thus the numerical layers of the groundwater model. Thus in order to reflect the two unit nature of the aquifer at Kasaya, the first few layers were assigned a relatively higher hydraulic conductivity which was allowed to vary as required. And conversely, the last layers were assigned a relatively lower hydraulic conductivity which was fixed at 0.01 m/day. The initial interface between the upper and lower units was set at 50 m depth and is one of the model parameters that entered the calibration as mentioned below. The numerical implementation of the evapotranspiration conceptual model shown in Fig. 3 is illustrated by Fig. 4 whereas the initial parameter values for the SEAWAT model are given in Table 1.

Fig. 4: Numerical model schematic for the Kasaya SEAWAT model

III - 8 Table 1: Initial parameter values for setup of a simple SEAWAT model for Kasaya Tran- sect

Parameter Initial value Unit Grid (layers, rows, columns) 10, 1, 1000 [-] Model extent (length, depth) 6500, 100 [m] Simulation time 10000 [years] Horizontal hydraulic conductivity (upper, lower)1 1, 0.01 [m/day] Vertical hydraulic conductivity2 0.01 [m/day] Maximum evapotranspiration3 4.3 [mm/day] Porosity 0.1 [-] Initial concentration (river, aquifer) 0.2, 15.611 [kg/m3] Longitudinal dispersivity 10 [m] Hydraulic conductivity interface (m) 50 [-] Fixed concentration interface (m) 90 [-] 1 The hydraulic conductivity was separated into two zones. The first zone comprised the first top layers above the interface depth whereas the second zone comprised the layers below the interface depth.

2 Same considerations as for 1 but with respect to concentration. This was implemented by setting layers below the fixed concentration interface to a fixed concentration that could not change throughout the simulation.

Thus using the initial parameters given in Table 1, the SEAWAT model con- ceptualized and parameterized by figures 3 and 4 respectively was run in transient mode for a simulation period of 10 000 years in order to evaluate model convergence with time. Using the 95 % quantile difference approach between successive time steps, the 10 000 year transient simulation was found to reach steady state after 8 000 years of simulation as illustrated in Fig. 5. It was thus considered to be completely in steady state at the end of the 10 000 year simulation. Thus given the time frame for evolution of the transient simulation in the order of thousands of years consistent with the evolution of the Makgadikgadi Basin (Bauer et al., 2006; Moore et al., 2012; McCarthy, 2013), it was not possible to acquire geophysical observations da- ting back thousands of years. Therefore the DCIP and TEM data that was obtained represents the current state of the aquifer at Kasaya in an evolution that has been taking place over geologic time scales. Therefore the CHI was performed on a steady state model rather than a transient one. Hence the simulated concentrations and hydraulic heads at the end of the 10 000th year were used as the initial conditions for the final SEAWAT model setup used in the CHI. This final SEAWAT model setup was nevertheless run in transient

III - 9 mode for a simulation period of 2 000 years in order to determine if steady state conditions were still being maintained during the CHI. The 95 % quantile difference evaluation of the final SEAWAT model at the end of TEM data only CHI (CHI-TEM) and combined TEM and DC data CHI (CHI-DC & TEM) indicated that steady state conditions were maintained and remained valid throughout the optimization. Consequently, the effect of using the steady state model as described above in the CHI was a significant reduction in both computational burden and time.

14 Initial run CHI-TEM 12 CHI-DC & TEM

4 95% Quantile difference 2

0 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 Period [years] Fig. 5: Ninety-five percent (95%) quantile difference for determination of the time when the transient SEWAT simulation reaches quasi steady state. For the Kasaya SEAWAT simulation, the model was in steady state by 8 000 years of simulation. 2.5 Model calibration with TEM and DC data The CHI for this paper was formulated as a Gauss-Marquardt-Levenberg parameter estimation problem for the SEWAT model mentioned above using geophysical data (Marquardt, 1963; Doherty, 2005; Herckenrath et al., 2013b). The SEAWAT model was first calibrated with TEM data and then the CHI setup was expanded to allow for an innovative use of both TEM and DC data in one optimization. PEST which implements the Gauss-Marquardt- Levenberg algorithm (Doherty, 2005) was used for running the optimization algorithm whereas forward model calculation was performed using Aar- husInv. The forward calculations were used to translate the electrical resistivity profiles derived from the concentration profiles into simulated instrument responses for comparison with the respective field datasets (TEM and DC in this case).

III - 10 Thus given a function or model description F such that

(1)

where 1,2,… i.e. model outcomes; and

1,2,… i.e. model parameters, and given a small change

in model parameters such that

∆ (2)

where ∆ = small change vector for the initial parameter vector , using the Taylor Series expansion equation 1 may be expressed as

(3)

where m and mo are model outcomes corresponding to parameter vectors p and po respectively; and J = the Jacobian matrix of partial derivatives of model outcomes with respect to model parameters.

If there exists a set of observations or data given by d= (d1,d2,…dm) (or x number of multiple sets of different types of data such that d=(d1,d2,…dx) which can be compared to model outcomes, then a set of model parameters (p) for which model generated outputs (m)are as close as possible to the data (d) can be obtained by minimising the objective function φ which is given as

′ 1 Φ (4)

‐1 where e = the square matrix whose diagonal elements (eii)are the squared inverses on the data standard deviations (σ) i.e. 1 2 (Doherty, 2005).

III - 11 Simulated solute concentration values were converted into simulated formation electrical resistivity values using Archie’s law in the form: 10 (5)

where, ∅ (6) = formation factor;

ρf = formation electrical resistivity; a = Archie’s exponent; Ф = porosity; m = cementation factor; k = conversion factor from solute concentration

[mg/l] to pore water electrical conductivity [µS/cm]; Cs = simulated solute concentration; and 10 = conversion constant from mg/l to kg/m3 (Archie, 1941; Walton, 1989; Tsallis et al., 1992). Thus using equation (5) the concentration profile was converted into an electrical resistivity profile from which forward models of the resistivity profile were generated at places corresponding to the locations of DC and TEM data using AarhusInv. The model parameters comprised hydrological parameters and petrophysical parameters. Hydrological parameters included hydraulic conductivity, interface layer between the upper and lower hydrological units and specific yield. On the other hand, the petro physical parameters comprised the Archie’s exponent and cementation factor of Equation 6. Porosity was a common parameter belonging to both the hydrological and petrophysical parameter sets. An overview of the CHI implementation presented in this paper is shown in Fig. 6.

III - 12

Fig. 6: Overview of CHI methodology used in this paper.

III - 13 3 Results The results of the CHI described above are outlined here in form of figures and tables. Thus, Fig. 7 shows the simulation results of the SEAWAT Model described above for different combinations of model parameters. The model was run under different parameter settings which were adjusted manually in order to make a judgement about the sensitivity of model outputs with respect to changes in model parameters. Thus, it is observed from Fig. 7 that different combinations of model parameters result in different spatial distributions of solute concentration on the 2D cross section. This was considered an indication of satisfactory parameter sensitivity to enable success of the CHI. For example, with all other parameters kept constant, a reduction in porosity from 0.25 to 0.09 resulted in faster travel times for the freshwater plume such that after 100 years of simulation (Fig. 7 (b)), the freshwater lens was much more developed in comparison to the case of 10 000 years of simulation with porosity at 0.25 (Fig. 7 (c)). Similarly, a hydraulic conductivity of 100 m/ day results in near complete flushing of the saline water from the first 50 m of the aquifer at the end of 10 000 years of simulation (Fig. 7 (d)). This is in contrast to the partial development of a freshwater lens at the end of 10 000 years of simulation with hydraulic conductivity equal to 1.05 m/ day (Fig. 7 (c)).

SEAWAT simulation output for various parameter settings

No HK interface but same as (c) Kg/m3 Porosity =0.09, HK = 1.05 m/day Kg/m3 950 15.6 950 15.6 900 4.2 900 4.2 850 1.1 850 1.1 800 0.3 800 0.3

Elevation [m] 0 2000 4000 6000 Elevation [m] 0 2000 4000 6000 Proﬁle Coordinate [m] Proﬁle Coordinate [m] (a)Simulation period: 10000years (b)Simulation period: 100years

Porosity = 0.25, HK = 1.05 m/day Kg/m3 Porosity = 0.25, HK = 100 m/day Kg/m3 950 15.6 950 15.6 900 4.2 900 4.2 850 1.1 850 1.1 800 0.3 800 0.3

Elevation [m] 0 2000 4000 6000 Elevation [m] 0 2000 4000 6000 Proﬁle Coordinate [m] Proﬁle Coordinate [m] (c)Simulation period: 10000years (d)Simulation period: 10000years

Fig. 7: Simulated temporal variation of solute concentration along the Kasaya Transect for various parameter settings ((a) to (d)). The model was setup with a fixed head river boundary condition and evapotranspiration hydrological forcing.

The result of the CHI with TEM data only is shown in Fig. 8 as concentration and electrical resistivity cross sections and in Table 2 as estimated parameter

III - 14 values. Similarly the result of the CHI with combined DC and TEM data is shown in Fig. 9 and Table 3. SEAWAT concentration proﬁle Kg/m3 950 15.6 900 4.2 850 1.1

Elevation [m] 0.3 800 0 1000 2000 3000 4000 5000 6000 (a) Proﬁle Coordinate [m]

Simulated electrical resistivity x-section Wm 950 1000

900 100

850 10

Elevation [m] 800 1 0 1000 2000 3000 4000 5000 6000 (b) Proﬁle Coordinate [m]

Resistivity cross section from LCI of TEM data Wm 950 1000

900 100

850 10

Elevation [m] 800 1 0 1000 2000 3000 4000 5000 6000 (c) Proﬁle Coordinate [m]

Fig. 8: (a) SEAWAT concentration cross section and (b) electrical resistivity cross section derived from the concentration cross section using Archie’s Law (Archie, 1941) for Kasaya Transect. (c) Electrical resistivity cross section form LCI of TEM data by Chongo et al. (2015). The SEAWAT model output is from a CHI run with TEM data only.

Table 2: Estimated parameters from the CHI with only TEM data for the Kasaya Transect Model

Initial Estimated 95 % confidence Sensitivity Parameter value value interval [-] Hydraulic conductivity 1.00 2.53 1.78 to 3.60 0.42 [m/day]

Porosity [-] 0.10 0.248 0.164 to 0.374 1.35

Cementation factor (m) [-] 1.92 1.485 -12.10 to 15.07 0.500

Top layer resistivity (Ωm) 10.00 12.48 11.81 to 13.19 0.953

Archie’s exponent (a) [-] 0.80 0.41 -10.47 to 11.28 0.65

Depth interface (m) 50 48.0 43.0 to 54.0 0.042

Note: For this CHI, specific yield was tied to porosity 1:1 whereas vertical hydraulic conductivity was tied to horizontal hydraulic conductivity 0.01:1 respectively. In addition the concentration interface was fixed at 90 m.

III - 15

SEAWAT concentration proﬁle Kg/m3 950 15.6

900 4.2

850 1.1 0.3 Elevation [m] 800 0 1000 2000 3000 4000 5000 6000 (a) Proﬁle Coordinate [m]

Simulated electrical resistivity x-section Wm 950 1000

900 100

850 10

Elevation [m] 800 1 0 1000 2000 3000 4000 5000 6000 (b) Proﬁle Coordinate [m]

Resistivity cross section from Joint DC-TEM Inversion Wm 950 1000

900 100

850 10

Elevation [m] 800 1 0 1000 2000 3000 4000 5000 6000 (c) Proﬁle Coordinate [m] Fig. 9: (a) SEAWAT concentration cross section and (b) electrical resistivity cross section derived from the concentration cross section using Archie’s Law for Kasaya Transect. (c) Electrical resistivity cross section from the joint inversion of DC and TEM data conducted by Chongo et al. (2015). This cross section plots both the DC and TEM models together. The SEAWAT model output is from a CHI run with both DC and TEM data.

Table 3: Estimated parameters from the CHI with both TEM and DC data for the Kasaya Transect Model Initial Estimated 95 % confidence Sensitivity Parameter value value interval [-] Hydraulic conductivity 1.00 1.36 1.26 to 1.46 5.99 [m/day]

Porosity [-] 0.10 0.21 0.190 to 0.234 23.66

Cementation factor (m) [-] 1.92 1.69 1.00 to 2.38 9.63

Top layer resistivity (Ωm) 10.00 12.0 11.85 to 12.15 23.67

Archie’s exponent (a) [-] 0.80 0.60 -0.34 to 1.54 7.91

Depth interface (m) 50 49.4 48.2 to 50.6 0.63

III - 16 4 Discussion CHI brings into play the benefits that can be derived from spatially dense data such as a more realistic representation of the spatial heterogeneity of hydraulic parameters like porosity, hydraulic conductivity and specific yield normally inherent from geophysical data sets such as TEM and DC (Rubin and Hubbard, 2006; Ferré et al., 2009; Busch et al., 2013). This in turn can have a significant impact on the accuracy and validity of model outcomes which may then be important for the decision making process. The CHI formulation therefore offers a framework within which hydrological models can be validated against spatially (and possibly temporally) dense earth observations in the form of geophysical measurements. The geophysical observations could then be used either alone (where no other type of data is available) or in combination with other types of data such as measured hydraulic heads and pore water concentration where available. Thus the CHI acts as a kind of reg- ularization in which the inversion is constrained by the physics of the hydrological model as opposed to arbitrary constraints in an ordinary geophysical inversion. Therefore for as long as the hydrological model faithfully simu- lates the pertinent natural processes, an accurate interpretation of the geophysical data can be obtained (Hinnell et al., 2010). This is in addition to the effect of constraining the model parameter estimations to narrow confidence intervals as a result of using the geophysical data. However, in order to gain the confidence of conventional hydrologists and geophysicist, and in order to have a more qualified basis upon which to base decisions, some form of qualitative evaluation such as the fit between the final forward simulation and measured data (or residual) would need to be used (Hinnell et al., 2010). And this is where the main disadvantage with CHI lies. In order for the calibrated hydrological model forward simulations to be an exact match of the geophysical instrument responses, the hydrological model will first of all need to capture all the pertinent hydrological processes very accurately, something which is usually not possible with standard model development on account of the simplifications and generalizations that are often required for successful numerical implementation. Secondly, the hydrological model would need to have degrees of freedom comparable to geophysical earth property models (e.g. layered electrical resistivity models). However this would require a very complex hydrological model implementation with a computational requirement that would be difficult to meet in terms of computational resources and time. There is thus need for innovative numerical implementation approaches for hydrological models that would

III - 17 allow for greater model complexity and degrees of freedom at reduced computational cost. 4.1 Data value of TEM and DC Inspection of the result from DC-TEM CHI and TEM only CHI reveals that the DC-TEM CHI has higher parameter sensitivities and narrower (95 %) confidence intervals. This is an indication of better performance of the optimization run under DC-TEM CHI compared to TEM only CHI. This is because lower parameter sensitivity tends to undermine the parameter estimation process with a consequent increase in parameter uncertainty. Therefore, the narrower (95 %) confidence intervals with the DC-TEM CHI suggest that addition of DC data in the model calibration helped to greatly reduce the uncertainty of the estimated parameters. Parameter uncertainties and sensitivities for the respective CHIs are given in Table 4.

Table 4: Comparison of parameter uncertainty and sensitivity for TEM CHI and DC-TEM CHI.

TEM Only CHI DC-TEM CHI

Parameter Width of 95 Sensi- Sensi- Initial Estimated Estimat- Width of 95 % confidence tivity tivity value value ed value % confidence interval [-] interval [-] Hydraulic conductivity 1 2.53 1.82 0.420 1.36 0.2 5.99 [m/day]

Porosity [-] 0.1 0.248 0.21 1.350 0.21 0.044 23.66

Cementation 1.92 1.485 27.17 0.500 1.69 1.38 9.63 factor (m) [-] Top layer resistivity 10 12.48 1.38 0.953 12 0.3 23.67 (Ωm) Archie’s exponent (a) 0.8 0.41 21.75 0.650 0.6 1.88 7.91 [-] Depth inter- 50 48.0 11.0 0.042 49.4 2.4 0.63 face (m)

This paper presents only a qualitative evaluation of the CHI result because the scope of works was to evaluate the feasibility of CHI on a larger local scale and also the feasibility of the inclusion of DC data in a combined DC and TEM CHI formulation. As expected, the SEAWAT simulation does indicate infiltration of fresh water from the Zambezi River into the adjacent sa-

III - 18 line aquifer at Kasaya. However the fresh water lens is not created to the same extent as suggested by the joint inversion result particularly in the last half of the transect line where the freshwater lens begins to thin out (Fig. 8 and Fig. 9). In the electrical resistivity profiles from the SEAWAT simulations, the freshwater lens is barely visible beyond profile coordinate 5 000 m whereas the inverse electrical resistivity cross sections of Fig. 8 and Fig. 9 depict a freshwater lens till the end of the transect line. Nevertheless the lens is considerably thinner and deeper in the subsurface towards the end of the transect line. Note that the fresh water lens in this context is used only qualitatively to denote groundwater with a water quality that is distinct from the underlying aquifer as indicated by the electrical resistivity distribution. Thus the simulation result from the CHI is not a perfect fit when compared to the joint inversion result (Fig. 8 and Fig. 9). The main reason of this is the over simplification of the SEWAT model which does not take into account some important hydrological processes. Processes that may not have been be taken into account include overland flow, through flow, seasonal flooding and infiltration or local recharge which may be different in the plain and in the forest areas of the transect line. The way forward would therefore be to develop a more realistic but simple coupled flow and salinity transport model that takes all possible processes into account but this was beyond the scope of the present paper.

5 Conclusions A CHI formulation involving the joint use of TEM and DC data in one optimization was successfully implemented for the first time as a proof of concept method development. The performance of the CHI was considered satisfactory based on qualitative evaluation of the simulated electrical resistivity cross section from the CHI calibrated SEAWAT model in comparison to TEM and DC-TEM inverse electrical resistivity sections for the same transect line. However, improved performance of the CHI was limited by the model simplicity which probably did not capture all relevant hydrological processes in addition to restricted degrees of freedom. It is expected that a more ad- vanced hydrological model that captures all the relevant hydrological processes at play at the Kasaya area (such as through flow and local rainfall/ flood recharge) would result in a better performance of the CHI that would then lend itself to qualitative evaluation.

III - 19 6 Acknowledgements This research was financially supported by the Danish International Devel- opment Agency (DANIDA) in the framework of the project, “Programme to support capacity building in the Water Sector for Zambia”, Phase II through the Ministry of Energy and Water Development for which we are grateful. The project was undertaken by the University of Zambia (UNZA) Integrated Water Resources Management Centre (IWRM) with collaboration and technical assistance from the Technical University of Denmark (DTU) and the Geological Survey of Greenland and Denmark (GEUS). We would also like to acknowledge the logistical support from Ms Ingrid Mugamya Kawesha (of the UNZA IWRM Centre) during field campaigns in Zambia. Furthermore we are grateful to colleagues (like Dr. Chisengu Mdala (UNZA); James Zulu (Azurite Water Resources,); Kebby Kapika (Department of Water Affairs- Sesheke, Zambia); and Mweemba Sinkombo (Department of Water Affairs – Nalolo, Zambia)) and the community at Kasaya for physical support during the field campaign. Finally, we are also grateful to the Hydrogeophysics group at the Department of Geosciences, Aarhus University for technical support in processing and inversion of the various geophysical datasets.

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