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1 Lake Chad Basin: Sustainable Water Management Groundwater Quality Investigations in the Lower Logone Floodplain in April – May 2013 Hanover, March 2014 On behalf of:
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Lake Chad Basin: Sustainable Water Management
Groundwater Quality Investigations in the Lower
Logone Floodplain in April – May 2013
Hanover, March 2014
On behalf of:
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Authors: Kristin Seeber, Djoret Daïra, Aminu Magaji Bala and Sara Vassolo
Commissioned by: Federal Ministry for Economic Cooperation and Development (Bundesministerium für wirtschaftliche Zusammenarbeit und Entwicklung, BMZ)
Project: Sustainable Water Management of the Lake Chad Basin
BMZ-No.: 2010.2274.8
BGR-No.: 05-2355
BGR-Archive No.:
ELVIS link: B4.1/B80123-09/2013-0005 Fachberichte
Date: March 2014
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Table of Content Summary ............................................................................................................................... 7
1 Introduction .................................................................................................................... 9
2 Study Area ....................................................................................................................10
2.1 Climate .......................................................................................................................10
2.2 Hydrology....................................................................................................................11
2.3 Flood Inundation Mapping with GIS Methods ..............................................................15
2.4 Soil, Vegetation, and Agriculture .................................................................................17
2.5 Geological Setting .......................................................................................................19
2.6 Hydrogeological Settings ............................................................................................19
3 Methodology ..................................................................................................................21
4 Results and Discussion .................................................................................................23
4.1 Groundwater Contours ................................................................................................23
4.2 Hydrogeochemistry .....................................................................................................25
4.2.1 Total Dissolved Solids ..........................................................................................25
4.2.2 Piper Diagram ......................................................................................................26
4.2.3 pH ........................................................................................................................27
4.2.4 Fluoride ................................................................................................................28
4.2.5 Nitrate ...................................................................................................................29
4.2.6 Sulphate ...............................................................................................................30
4.2.7 Barium ..................................................................................................................30
4.2.8 Irrigation Suitability ...............................................................................................31
4.3 Isotopic Analysis ....................................................................................................34
5 Conclusion and Recommendations ...............................................................................39
References ...........................................................................................................................40
Annexes ...............................................................................................................................42
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Table of Figures
Figure 1 Elevation model of the Lake Chad Basin, compiled using SRTM30 data (Vassolo, 2012) ....................................................................................................................................10
Figure 2 Study area inundation zone of the Lower Logone River, modified after (Vassolo, 2012). Red points indicate gauging stations .........................................................................10
Figure 3 Rainfall distribution in the study area. Green lines are long-term isohyets for the period 1973-2007 (Source: LCBC Data Base) ......................................................................11
Figure 4 Hydrological map of the study zone ........................................................................12
Figure 5 Discharge values in Bongor and Logone Gana for the period 2001-2008 ...............13
Figure 6 Outflow into the Yaéré and Naga plains relative to the discharge in Bongor ...........14
Figure 7 Outflow into the Yaéré and Naga plains relative discharge in Katoa .......................14
Figure 8 Mean daily discharge for the Logone River at Bongor for different periods of time .15
Figure 9 Variation of the Yaéré and Naga plains for 2011 (left) and 2012 (right) (Geerken et al., 2012) ..............................................................................................................................16
Figure 10 MODIS Land Surface Temperature (LST) maximum daytime images showing highest extend of the inundation zone in November 2011 (left) and November 2012 (right) .16
Figure 11 Naga plain near Dialo (~10.9°N 15.1°E) during dry season. Soils from shrinkage cracks (Foto: Djoret Daira, LCBC April 2013) .......................................................................17
Figure 12 Swampy landscape in the Naga floodplain near Logone Gana (11.55°N 15.19°E) (Photo: Aminu Magadji, LCBC Nov 2013) .............................................................................18
Figure 13 Grassy Naga plain near Yama (~11.20°N 15.20°E) during the dry season. (Photo: Djoret Daïra, LCBC April 2013) ............................................................................................18
Figure 14 Cattle breeding at Loumia River (tributary in the Naga plain 11.40°N 15.30°E) (Photo: Djoret Daïra, LCBC April 2013) ................................................................................18
Figure 15 Garden in Saka, Chad (10.38°N 15.35°E) (Photo: Djoret Daïra, LCBC April 2013) .............................................................................................................................................18
Figure 16 Fish channel constructed during the dry season, near Dialo, Chad (~10.90°N 15.10°E) (Photo: Djoret Daira, LCBC April 2013) ..................................................................18
Figure 17 Map of sample locations and well types ................................................................21
Figure 18 Record of water level in a piezometer, King King, Chad (11.50°N 15.20°E) (Photo: Djoret Daïra, LCBC April 2013) ............................................................................................22
Figure 19 Pumping through a flow cell and application of the WTW-Multi 3430 at Woulki (12.48°N 14.62°E) Cameroon (Photo: Djoret Daïra, LCBC May 2013) .................................22
Figure 20 Use of the COMET pump for sampling from an open well Biliam Oursi, Chad (10.55°N 15.23°E) (Photo: Djoret Daïra, LCBC April 2013) ..................................................22
Figure 21 Map of groundwater contours and sample points in the study area ......................24
Figure 22 Map of TDS distribution in the study area .............................................................25
Figure 23 Piper diagram for groundwater samples without considering nitrate .....................26
Figure 24 Piper diagram for surface water samples ..............................................................26
Figure 25 Stiff diagram for samples YC 22 and YC 25..........................................................27
Figure 26 Map of pH distribution in the study area ................................................................27
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Figure 27 Map of fluoride concentrations in the study area ...................................................28
Figure 28 Map of nitrate concentrations in the study area ....................................................29
Figure 29 Wilcox plot to evaluate groundwater suitability for irrigation ..................................31
Figure 30 SAR plot to evaluate the suitability of groundwater for irrigation ...........................32
Figure 31 Map of irrigation suitability of groundwater in the study area after Wilcox, SAR and MH indexes ..........................................................................................................................33
Figure 32 Results for δ18O and δ2H of groundwater, surface water and rain water ................35
Figure 33 Results for δ 18O and δ 2H of all groundwater samples ..........................................36
Figure 34 Map of measured δ 18O values in the study area ...................................................37
Figure 35 Map showing vegetation cycles in 2012 by means of MODIS satellite data (Geerken et al., 2012) and measured δ 18O values in the study area ....................................38
List of Tables Table 1 Irrigation Suitability Indexes .....................................................................................31
List of Annexes Annex 1 List of groundwater level sample points ..................................................................42
Annex 2 List of sample points ...............................................................................................44
Annex 3 Statistics of the measured parameters in groundwater samples .............................46
Annex 4 Statistic of parameters measured in surface water samples ...................................47
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Abbreviations
a.m.s.l. above mean sea level
ASTER Advanced Space Borne Thermal Emission and Reflection BGR Federal Institute for Geosciences and Natural Resources
BMZ Federal Ministry for Economic Cooperation and Development
DEM Digital Elevation Model
EPA Environmental Protection Agency
EU European Union
IAEA International Atomic Energy Agency
LCBC Lake Chad Basin Commission
LST Land Surface Temperature
MODIS Moderate Resolution Imaging Spectroradiometer
NDVI Normalized Difference Vegetation Index
DREM Water Resource and Meteorological Directory of the Hydrological Ministry of Chad
Q Discharge [m³/s]
GPS Global Positioning System
MH Magnesium Hazard Index
SAR Sodium Hazard Index of Irrigation Water
SD Standard Deviation
SEMRY Société d’expansion et de Modernisation de la Riziculture de Yagoua / Rice project in north Cameroon financed by World Bank
TDS Total Dissolved Solids [mg/l]
TU Tritium Unity
WHO World Health Organization
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Summary
Keywords: Lake Chad Basin, floodplain, wetland, Logone, Yaéré, Groundwater Quality Analysis, Isotopic Analysis
From March to May 2013, during the dry season, the BGR-LCBC project conducted groundwater quality investigations within the floodplain of the Lower Logone River, known as the Yaéré in Cameroon and Naga in Chad. The former BGR-LCBC project highlighted these wetland zones as an important groundwater recharge area for the Lake Chad basin, therefore the ongoing project decided to intensively study the groundwater origin, flow paths, the quality, as well as the interaction between the Logone River and the floodplain.
Field surveys comprising groundwater level measurements and in-situ parameter records as well as sampling for anion, cation and isotope analysis were conducted.
Groundwater contour lines were drawn using 55 groundwater level measurements and elevations from a digital model. They show groundwater flow from Bongor north-eastwards into the plain. However, a better distribution and more measurements are needed, to draw up a contour map for the whole study area.
The chemical analyses show that groundwater in the floodplain is in general of good quality. Throughout Piper diagrams of 76 groundwater samples, mainly two different types of groundwater can be distinguished: Firstly, water of bicarbonate calcium and magnesium type. This water is weakly mineralised, which is typical for groundwater encountered near the aquifer recharge area. The corresponding samples were taken in the north and northeast of Bongor and between Katoa and Logone Gana, hence in the floodplain of the Logone River. Secondly, older water of bicarbonate sodium and potassium type was encountered in the southern part of the study area at the foothills of the Mandara Mountains in Cameroon, along the Logone River and in the far north of Cameroon. This water is higher mineralised. Due to the fact that calcium has been replaced by sodium, it can be concluded that it was recharged relatively long ago and has flown a certain distance within the aquifer. It is assumed that groundwater northwest and south of the Maga Dam belongs to a different aquifer, which is probably recharged by water coming from the Mandara Mountains. For a clear understanding of the groundwater situation in the far north of Cameroon, more sample points have to be analysed. At the moment it is assumed that groundwater is a mixing of water of the Yaéré plain, the Logone and Chari River as well as the Lake Chad.
Anion and cation concentrations in the whole area are below the WHO drinking water limits. Only in peripheral regions, in the far north of Cameroon and in the west and south of the Maga Dam, concentrations of nitrate and fluoride above the respective WHO limits were measured. The elevated concentrations of fluoride are considered as geogenic and are linked to the presence of fluoride-rich minerals like mica and fluorapatite in the crystalline basement aquifer.
Within the study area, three samples in the north of Cameroon show nitrate concentrations above the WHO limit. Whether the pollution is caused by livestock watering directly from the borehole or due to the excessive use of nitrogenised fertilisers in the agriculture has not yet been clarified.
According to the SAR, Wilcox and MH indexes, the groundwater in the wetland zone is generally suitable for irrigation. Only in the peripheral region (north of Cameroon) irrigation suitability is questionable.
The isotopic analyses show that the groundwater in the Yaéré and Naga plains is recharged by surface water that has been exposed to evaporation, or in other words, by flooding water that rests three to five months in the plains before it flows back into the Logone River,
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infiltrates into the groundwater or evapotranspirates. Indications for direct recharge from the Logone River can be found in wells and boreholes north of Bongor.
Depleted groundwater appears in the deeper aquifer located in the southwest of the study area at the foothills of the Mandara Mountains indicating older water.
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1 Introduction
The project “Sustainable Water Management of the Lake Chad Basin” is a technical cooperation project between the Lake Chad Basin Commission (LCBC) and the German Federal Institute for Geosciences and Natural Resources (BGR) and is financed by the Federal Ministry for Economic Cooperation and Development. The main goal is to strengthen the analysis and monitoring functions of the LCBC regarding groundwater and surface water in the basin. The actual project started in September 2011 and is scheduled to end in August 2014.
The wetland zones within the Lake Chad Basin (Massenya and Salamat in the south of Chad, the inundation plain along the Lower Logone River, the Komadugu-Yobe at the border between Nigeria and Niger, and the Lake Chad itself) are of particular importance for the region, since they are known to contribute to the renewal of groundwater resources in the basin. Furthermore, they are major ecosystems supporting biodiversity and key economic activities such as fishery, livestock breeding and flood recession agriculture. Besides regional importance, these zones are of international significance in terms of ecology, botany, zoology, limnology or hydrology (Ramsar Sites).
During the project planning workshop carried out in November 2012 in N’Djamena, the participants (composed of: LCBC staff, hydrogeologists from the member countries and BGR staff) decided to intensify the groundwater research in one of the wetland zones of the Lake Chad Basin. Selected for more in depth research (pilot zone) was the inundation zone of the Lower Logone River known as the Yaéré in Cameroon and Naga in Chad, which supports more than 20 million people (Jung et al., 2011). Aim of the research is to intensively study groundwater origin and flow paths, the quality of the water resources, as well as the interaction between the Logone River and its floodplain.
The results of the first sampling survey which was conducted from April to May 2013, before the rainy season started, by the LCBC staff Djoret Daïra (hydrogeologist) and Aminu Magaji Bala (environment and wetland ecologist) are presented below. Within 27 field days a total of 83 water samples were collected, 49 in Chad and 34 in Cameroon. The samples were analysed at the BGR laboratory in Germany for complete anion and cation species, trace elements and the stable isotopes deuterium (2H) and oxygen-18 (18O). The parameters such as water temperature, pH and electrical conductivity were measured in-situ.
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2 Study Area
The study area extends from latitudes 10°00’0’’N to 12°50’0’’N and longitudes 14°20’0’’E to 15°50’0’’E (Figure 2) and comprises the Yaéré plain in north Cameroon, with an area of about 8000 km², and the Naga plain on the Chadian side with some 4500 km². The plains are periodically inundated by heavy rains and the overflow of the Lower Logone River between Bongor and N’Djamena and farther north, depending to a great degree on the intensity of the rainfall.
Figure 1 Elevation model of the Lake Chad Basin, compiled using SRTM30 data (Vassolo, 2012)
Figure 2 Study area inundation zone of the Lower Logone River, modified after (Vassolo, 2012). Red points indicate gauging stations
The inundation zones are limited in the north/northwest by surface water of the Lake Chad and to the east by the Chari River. In the south/southwest of the study area, it is the uprisings of the basement in the form of the Mandara Mountains that demarcate the inundation zone (Figure 1).
2.1 Climate
The climatic situation in the study area responds to two different climatic driving forces. A dry wind (harmattan) from the north and a wet wind from the south (West African monsoon) leading to a sudanian climate in the south and a sahelo-sudanian climate in the north.
The sudanian climate of the southern part of the study area is characterised by a rainy season of five months, from May to September, and a dry season of seven month from October to April. The annual average precipitation amounts to 800 mm (Figure 3).
The sahelo-sudanian climate in the northern part of the study area is characterised by a rainy season that begins about one month later in June to end in September, and a dry season that lasts from October to May. The annual average precipitation diminishes to 400 mm.
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Figure 3 Rainfall distribution in the study area. Green lines are long-term isohyets for the period 1973-2007 (Source: LCBC Data Base)
The average annual temperatures in the study area vary between 26°C and 28°C. The monthly average for April can reach up to 34°C (Ngounou Ngatcha et al., 2007). The average annual total evaporation (1987-1991) in Kousseri (located in Cameroon opposite to N’Djamena) is 3,944 mm and 2,614 mm in Yagoua (located in Cameroon opposite of Bongor, (Ngatcha, 1993). The monthly evaporation increases from October to March and is at its minima in August when rainfall is heaviest.
2.2 Hydrology
The Logone River, the major tributary of the Chari River, is a 1,000 km long perennial river which has its sources in the volcanic Adamawa Plateau located in western Central African Republic and northern Cameroon (see Figure 1). Its main tributaries are the Pendé, with headwaters at 1,400 m in the eastern part of the Plateau in Central African Republic that becomes the Logone oriental when entering Chad, and the Vina and Mbéré Rivers with sources at about 1,000 m in the northern part of the Adamawa Plateau in Cameroon, that confluence to form the Logone occidental. The Logone oriental and Logone occidental meet to originate the Logone River (Figure 1).
The course can be divided in three trenches: the Upper Logone between the confluence of Logone oriental and occidental and Laï, the Middle Logone between Laï and Bongor, and the Lower Logone from Bongor to N’Djamena, where the Logone joints the Chari River (Figure 4). The latter is of particular importance for the study area. The Logone/Chari River system accounts for approximately 90% of the Lake Chad water.
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The flatness of the study area (gradient ~0.6 m/km) impedes the formation of a hierarchical river network. However, several little sinuous channels appear during the rainy season, but usually disappear before they reach a more important affluent.
Figure 4 Hydrological map of the study zone
A major tributary is the Koulambou River, which has its source in the Naga floodplain and joins the Logone River in Logone Gana (Figure 4). The discharge measured during the rainy season in October 2013 accounts for 306 m³/s (Seeber, 2013). Water that bursts the Logone along the left banks flow into the Yaéré and is drained by effluents like Guerléou and Logomatya. The former one arises in the north of Yagoua and the latter between Pouss and Tekele. These rivers flow parallel to the Logone River. Most of these tributaries reflow into the Logone at Logone Gana (Ngatcha, 1993). The course of the Guerléou River was interrupted by the construction of Maga Dam in 1979 to create a 40,000 ha reservoir for rice irrigation northwards of the dam. The outlet of the Maga Dam (called Vrik Channel) was built to control the discharge of the Logomatya River northwards of the Dam that supports the
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Yaéré floodplain with water. Unfortunately, proper dam operation/management is a serious challenge at the moment.
The Yaéré and Naga plains are seasonally flooded during and short after the rainy season, usually from August until January, depending on the intensity of the rainfall and hence the discharge. The first rains in May/June saturate the soil and fill up the deepest depression. The overbank flow, which contributes the most to the inundation of the plains, starts to the east of the Logone River in September. The water level in the floodplain during inundation period varies between 0.7 m and 1.5 m above surface and is at its maximum at the end of October/beginning of November.
An analysis of the Logone River discharge for the period 2001-2008 (Figure 5) reveals an average monthly discharge value of 404 m³/s at Bongor and 265 m³/s at Logone Gana. Minimum discharge is reached in April during the dry season with an average value of 65 m³/s in Bongor and 14 m³/s in Logone Gana. Discharge flow increases rapidly during the rainy season from June to September. Discharge peaks are observed at the end of the rainy season, in late September with an average value of 1,525 m³/s at Bongor and one month later, in late October, with an average value of 765 m³/s at Logone Gana. The water loss between Bongor and Logone Gana is mainly caused by river water that bursts its banks and flows into the Yaéré or Naga plains (Seeber, 2013). The annual overbank flow reduces both the peak flows and total volumes of the water in the Logone River. Water stored in the floodplain either flows back into the Logone River during the recession period, is exposed to evaporation and evapotranspiration in the plains, infiltrates into the groundwater aquifer, or flows further north to form minor rivers that transport the water into the Lake Chad.
Figure 5 Discharge values in Bongor and Logone Gana for the period 2001-2008
The discharge rate in m³/s at which overflow takes place into the Yaéré and Naga plains at the stations Bongor and Katoa, respectively, was calculated in the former BGR-LCBC project (see Figure 6 and Figure 7 below).
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Figure 6 Outflow into the Yaéré and Naga plains relative to the discharge in Bongor
Figure 7 Outflow into the Yaéré and Naga plains relative discharge in Katoa
In Figure 6, the differences of the discharge values at Bongor and Katoa stations are shown plotted against the discharge value at Bongor station. The picture illustrates that the overflow into the Naga and Yaéré plains at Bongor takes place when the Logone River discharge exceeds 1,055 m³/s. A similar discharge of 1,100m³/s was reported by Ngounou Ngatcha et al. (2007). The same analysis can be done to estimate the discharge at which flood takes place in Katoa station. The overflow into the Yaéré and Naga plains starts when discharge surpasses 356 m³/s at Katoa station (Figure 7).
Olivry (1986) analysed the flow regime of the Logone for the period 1953 - 1973 and demonstrated a connection between discharge values in Bongor and the flow of the El Beid located in the far north of Cameroon Figure 4. He found that whenever the discharge in Bongor exceeded 1,500 m³/s, the Yaéré floodplain was heavily inundated and, from January to April, water of the plain was drained by the El Beid into the Lake Chad with a median value of 38.9 m³/s.
However, due to series of drought periods between 1972 and 1983, the flow regime in the area has changed (see Figure 8). While the mean daily discharge curve for the period 1953 - 1973 shows values above 1,500 m³/s over almost 2 months (from 4th September to the 21st October), the curve corresponding to the period 1974 - 1994 never reaches such a discharge. The green curve indicates that daily discharges have increased for the period 1995 - 2007 arriving at the long-term mean for the period 1953 - 2007, but not yet at the values of the 60’s. Mean daily discharges are now again above 1,500 m³/s, but only over a period of less than a month (from 2nd September to 11th October).
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Figure 8 Mean daily discharge for the Logone River at Bongor for different periods of time
2.3 Flood Inundation Mapping with GIS Methods
The growing availability of satellite data has increased the possibilities for mapping inundation areas in the floodplains. Different methods have been applied in the study area for this purpose. Jung et al. (2011) determined flooded areas using the short-wave infrared (SWIR) data with the application of an iterative self-organising data analysis clustering to differentiate open water. Using a series of 33 multi-temporal Landsat ETM+ images, they mapped the inundated areas of the plains for the years 2006 to 2008. Geerken et al. (2012) followed the vegetation cycle captured by MODIS satellite data, which allows distinguishing between rain-fed vegetation, irrigated vegetation and vegetation growing in flooded areas. By processing the MODIS satellite images of land surface temperature (LST) maximum daytime images, Bila (2013) mapped also the extension of inundated areas in the region. This method bases on the fact that evaporation from flooded areas is at its maximum during the highest daily temperatures. Thus, inundated areas are cooler than non-flooded areas and can easily be distinguished
Figure 9 below shows the extension of the inundation zones of the Lower Logone for 2011 and 2012 (Geerken et al., 2012). Vegetation is classified from annual Normalized Difference Vegetation Index (NVDI) time series according to the shape of the temporal vegetation cycle (Geerken, 2009). The dark blue areas in the Yaéré and Naga plains correspond to intensive seasonal flooding (open water surfaces), while the light blue areas are also seasonal flooded zones, but more intertwined with vegetation. The dark green colours represent vegetation in areas with high soil moisture, where the vegetation cycles are somehow longer than those to the normal rain-fed vegetation. The lightening of the green colour correlates with the shortening of the vegetation cycle. The shortest vegetation periods appear in the north of the study area. The red colour indicates irrigated areas, typically characterised by two vegetation cycles (two harvests) and the white colour visible in the Maga Lake shows surface water all over the year.
Figure 9 shows that in 2011 only minor inundation occurred compared to 2012.
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Figure 9 Variation of the Yaéré and Naga plains for 2011 (left) and 2012 (right) (Geerken et al., 2012)
MODIS satellite images of land surface temperature (LST) maximum daytime images were analysed for the period 1999-2012 by the remote sensing expert of the LCBC using 16 day composite images (Bila, 2013). The results for the years 2011 and 2012 are presented in Figure 10 showing again a much smaller inundation area in 2011 than in 2012.
Figure 10 MODIS Land Surface Temperature (LST) maximum daytime images showing highest extend of the inundation zone in November 2011 (left) and November 2012 (right)
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By comparing Figure 9 and Figure 10, especially the images of the year 2012, it can be concluded that the analysis of the NVDI allows to distinguish between open water, water mixed with vegetation and vegetation cover along with high soil moisture. In order to calculate the flooded area, all these three surfaces have to be summed up. In contrast, mapping the extent of the Yaéré and Naga plains with the help of the surface temperatures does not distinguish between areas of open water, vegetation under water and vegetation with high soil moisture. Nevertheless, it shows the areas where surface temperatures are cooler due to evaporation of free water surface and evapotranspiration from plants.
The different remote sensing methods contribute to a better understanding of the Logone floodplain dynamics, with details about the relationship between flooding area and water heights at the gauging stations, as well as spatial pattern and size of the flooded area. Furthermore, they allow for creating monthly probability maps of flooded areas. It has been shown that in September most of the flooded areas are located in the Naga plain. In October and November, the flooded areas spread out to both sides of the river moving from east to west. The maximum flooded area in late October 2008 reached up to 5,800 km². In December and January flood water moves to the north with decreasing size of the flooded area. The north of the Maga Dam is most of the time not flooded, even during the maximum discharge months of October and November, because of the safeguard from the embankment along the Logone River that was built to protect the rice fields as well as the Maga Dam against inundation (Jung et al., 2011).
2.4 Soil, Vegetation, and Agriculture The dominant soil types in the Yaéré plain are vertisols and black hydromorph clays (Brabant & Gavaud 1985). During the dry season, these soils form shrinkage cracks (Figure 11) in which water can penetrate at the beginning of the rainy season. The consequent swelling of the clays leads to a closing of the cracks and decreases the soil permeability and, thus, favours inundation of the area.
Vegetation in the Yaéré and Naga plains is season-depending. The region is characterised by a swampy landscape during the rainy season (Figure 12) and shrub savannah and grassy plains during the dry season (Figure 13).
Figure 11 Naga plain near Dialo (~10.9°N 15.1°E) during dry season. Soils from shrinkage cracks (Foto: Djoret Daira, LCBC April 2013)
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Figure 12 Swampy landscape in the Naga floodplain near Logone Gana (11.55°N 15.19°E) (Photo: Aminu Magadji, LCBC Nov 2013)
Figure 13 Grassy Naga plain near Yama (~11.20°N 15.20°E) during the dry season. (Photo: Djoret Daïra, LCBC April 2013)
Economically the inundation zone is mainly used for recessional agriculture such as sorghum and for cattle breeding. Furthermore rice, corn, peanuts and garden products are partly cultivated (Figure 14 and Figure 15). There are big irrigated rice fields around the Maga Dam with ~3,200 ha (SEMRY I and II projects) in Cameroon and ~800 ha north of Bongor in Chad (Casier B).
Figure 14 Cattle breeding at Loumia River (tributary in the Naga plain 11.40°N 15.30°E) (Photo: Djoret Daïra, LCBC April 2013)
Figure 15 Garden in Saka, Chad (10.38°N 15.35°E) (Photo: Djoret Daïra, LCBC April 2013)
During the flood period, the floodplain is also used for fishing with especially constructed fish channels that cut into the plains (Figure 16). They are about 70 m to 2,000 m long, 2 to 10 m bright, 1.5 m to 2.5 m deep (Sambo, 2010) and count up to more than 2,000. When recession starts (flow back), fishes living and breeding in the inundation zone look for their
Figure 16 Fish channel constructed during the dry season, near Dialo, Chad (~10.90°N 15.10°E) (Photo: Djoret Daira, LCBC April 2013)
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way back into the Logone River via these channels. Before their confluence with the Logone River, fish nets are spreaded across the channels and all fishes notwithstanding its age are captured. Unfortunately, this way of fishing is not sustainable and leads to a decline and disappearance of fish species. Although theoretically this type of fishing is prohibited in Cameroon, it is still wide practiced in Chad and Cameroon.
2.5 Geological Setting
The Logone-Chari floodplain lies at the edges of the Quaternary deposits in the Lake Chad Basin and is composed of recent and ancient Quaternary formations. The thickness can be very low, but generally varies between 50 m and 70 m (Schneider et al., 1992 and Biscaldi, 1970).
On the Cameroonian side of the Lower Logone deposits can be distinguished (Biscaldi, 1970):
• present alluvial sandy clay and loamy sand deposited by the Logone River, its tributaries, and the temporary rivers, which flow into the Lake Chad
• recent alluvial deposits in the Chad Basin with abundant mica • coarse grained alluvial deposits transported by rivers originated at the Mandara
Mountains (Cameroon) • lacustrine clays and loams of low thickness (in average 1.5 m in the Yaéré plain)
deposited by the Lake Chad during more humid climatic conditions, when the Lake level was at least 320 m a.m.s.l.
• sandy deposits from arid periods • loamy sandy deposits with calcareous gravels with an average thickness of 10 to
20 m, very constant in the southern part of the Yaéré, but less continuous north of 12° parallel
• aeolian sands that form a chain of dunes called Limani-Yagoua (Cameroon)
2.6 Hydrogeological Settings
Former groundwater flow studies and hydrogeological settings of the aquifers located in the Yaéré plain can be found in the hydrogeological map 1/200,000 by Biscaldi (1970) and in the hydrogeological map by Detay et al. (1989) within the Atlas of the Extreme North province of Cameroon.
Sparse information about the Naga plain are presented in the hydrogeological maps 1/500,000 by Torrent (1966), which was later included in the Hydrogeological Map of Chad 1/1,500,000 by Schneider (1969).
The regional groundwater table within the Quaternary in the Yaéré varies between 320 m a.m.s.l in Yagoua and 265 m a.m.s.l in the extreme north. In the far north of Cameroon, towards the Lake Chad, three local groundwater depression zones have been detected. Ngounou (2007) studied a fourth groundwater depression located at the axe between Tagawa and Yagoua, north-eastwards of the chain of dunes. With the help of geological information, stable isotope analysis, tritium and hydro-chemical data, he identified a quaternary aquifer composed by two superposed layers. The ancient Quaternary is separated from the younger one by a loamy layer of average 2 m to 5 m thickness.
Within the SEMRY II project some sediment samples around Maga Dam were collected to evaluate permeabilities. A value of 10-8 m/s was observed for the loams, the loamy sands showed values between 4 to 5 x 10-6 m/s (Ngounou, 1993).
Biscaldi (1970) reported that the majority of the groundwater samples in the area are of bicarbonate calcium type, most of them correspond to shallow groundwater and, except for
20
some values in the far north near Lake Chad, they are suitable for irrigation. The average transmissivity is 3 to 4 x 10-5 m²/s.
In the Naga plain, groundwater table lies between 320 m a.m.s.l in Bongor to 280 m a.m.s.l. in N’Djamena. Schneider & Wolff (1992) reported that groundwater from the Quaternary aquifer in this region is generally low mineralised. Furthermore, they noted that the presence of sand lenses of 2 m to 15 m thickness results in local aquifers. These local aquifers where also mentioned by Ngounou (1993) for the Yaéré floodplain. A pumping test at a borehole from 1969 located in Bongor, which has a depth of 95 m, a filter length of 7.8 m from 83.2 m to 91 m, and captures the quaternary aquifer, yielded a transmissivity of 2.5 x 10-2 m²/s. Assuming an average thickness of 60 m for the Quaternary aquifer, this transmissivity is equivalent to a permeability value of 4 x 10-4 m/s and is thus quite high compared to the permeabilities measured around Maga Dam.
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3 Methodology
First investigations conducted by the former BGR-LCBC project show that the inundation zones of the Lower Logone River have a significant contribution to groundwater recharge (5 mm/a) within the Lake Chad Basin (Vassolo (2011) and Vassolo (2012)). Therefore it was decided to intensify the groundwater research in this zone in order to investigate groundwater origin and flow paths, the quality of the groundwater and surface water, as well as groundwater interaction between the Logone River and its floodplain.
The results of the first sampling campaign, conducted from April to May 2013 before the rainy season started, are presented below.
During a 27-day field campaign, a total of 83 water samples were collected. Out of 83 water samples, 76 belong to groundwater taken either from tube wells equipped with hand pumps (48), from open wells (26) or from piezometers (2). A list of sample points with location’s name and coordinates is given in Annex 1.
Although exact depths of the tube wells equipped with hand pumps are unknown, it can be assumed that they extract water from the Quaternary, since the thickness of this aquifer comprises 50 m to 70 m and the subjacent layer is composed of ~180 m impermeable Pliocene clays (refer to chapter 2). Yet, it is known that the Quaternary aquifer consists of layers of sand intercalated by lenses of clays, therefore it is difficult to establish a stratigraphic correlation between open wells and tube wells. The Logone River was sampled at Bongor and Katoa. Furthermore, the Koulambou River (tributary of the Logone River in the Naga plain) and four other streams located in the Yaéré and Naga plains were sampled (see Figure 17).
Figure 17 Map of sample locations and well types
22
During the field campaign water levels and total depths of open wells were recorded using a dipper (Figure 18). Coordinates of the sample points were collected by means of a Garmin GPS device.
In-situ parameters (temperature [°C], electrical conductivity [µS/cm], pH, oxygen [mg/l], redox potential [mV], and HCO3
- [mg/l]) were measured by means of a digital multi-sensor set (WTW-Multi 3430) and a titration apparatus. Water was pumped using a submersible pump (Set COMET-COMBI 12-4T) (Figure 20). When boreholes equipped with a hand pumps were sampled, a flow cell (Figure 19) was used in order to reach laminar flow and avoid contact of groundwater with oxygen.
Complete anion and cation species as well as trace elements and the stable isotopes δ18O and deuterium δ2H were measured in the BGR laboratory in Hannover.
Figure 18 Record of water level in a piezometer, King King, Chad (11.50°N 15.20°E) (Photo: Djoret Daïra, LCBC April 2013)
Figure 19 Pumping through a flow cell and application of the WTW-Multi 3430 at Woulki (12.48°N 14.62°E) Cameroon (Photo: Djoret Daïra, LCBC May 2013)
Figure 20 Use of the COMET pump for sampling from an open well Biliam Oursi, Chad (10.55°N 15.23°E) (Photo: Djoret Daïra, LCBC April 2013)
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4 Results and Discussion
4.1 Groundwater Contours Groundwater levels were measured at 56 shallow open wells and five piezometers (data listed in Annex 1). The open wells which are located in the floodplain are rarely developed. Very often just some 0.5 m to 1 m thick and 2 m to 4 m deep holes are hand dug into the ground by nomads. Firstly, this indicates that the floodplain is only sparse settled by villagers, due to the annually recurrent inundation, and secondly that a shallow groundwater aquifer can be encountered, which is directly recharged by flood water standing over three to five month in the plains.
The ASTER elevation model (resolution 30 m x 30 m) was used to estimate the heights of the open wells because they have not been measured. The water table heights range from 326 m a.m.s.l. in Marao near Bongor (15.27 E and 10.37 N) in the south of the study area to 265 m in Woulki (14.62 E and 12.48 N) close to the Lake Chad. The general groundwater flow is from south to the north following the surface gradient (Figure 21).
Due to an inhomogeneous distribution of the wells, large distances between the wells (sometimes >20 km), non-availability of elevation heights of the wells and the extreme flatness of the area (~0.6 m/km), it is very difficult to draw a contour map for the whole study zone. Furthermore the DEM used for estimating the surface elevations of the wells, has some errors (unnatural northeast-southwest stripes shown in Figure 21). Contour lines demonstrate groundwater flow from Bongor north-eastwards into the Naga plain following the direction of the river water outburst. According to the gradient, flow velocity seems to be elevated.
It is evident that more data in the Yaéré plain and in the north of Cameroon as well as around Logone Gana are necessary to be able to draw an adequate groundwater contour map. Furthermore it is important to measure the exact heights of the wells, since the DEM used for their assessment has a low resolution and thus only gives a raw estimation.
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Figure 21 Map of groundwater contours and sample points in the study area
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4.2 Hydrogeochemistry Water sampling was performed in 83 points (see Annex 2). Descriptive statistics like average, minimum, maximum and standard deviation of the analysed parameters of groundwater and surface water samples are reported in the Annex 3 and Annex 4. Additionally the World Health Organization drinking water standard limits are listed.
4.2.1 Total Dissolved Solids Total dissolved solids (TDS) are an indicator for the mineralisation of the water (total amount of mobile charged ions). Although higher TDS values do not seem to cause health problems, the WHO suggests drinking water (classified as fresh water) not to have more TDS than 1,500 mg/l. Water with TDS > 5,000 mg/l is too salty even to be used for livestock watering.
Within the study area, no TDS concentrations above 1,500 mg/l were detected (Figure 22). There is only one open well located in the north of Cameroon in Amfara (YC 25) with a TDS value of 1,470 mg/l (EC of 1,898 µS/cm) close to the suggested WHO limit.
In general, the values of TDS detected in the study area are relatively low (Figure 22) with an average concentration of 354 mg/l. The lowest TDS are measured in the inundation zones northeast of Bongor, and between Katoa and Logone Gana on both sides of the Logone River (average 279 mg/l). Higher values are found in the north of Cameroon (average 598 mg/l) and in the area adjacent to the Mandara Mountains in the south and northwest of Maga Lake (average 432 mg/l).
Figure 22 Map of TDS distribution in the study area
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4.2.2 Piper Diagram
A way of visualising the chemical composition (major anions) of the water samples is by means of a Piper diagram. This diagram enables to classify the type of water depending on its flow path from the recharge zones to discharge points mainly by three (four) zones of the diagram.
Three of the groundwater samples show concentrations of nitrate above 50 mg/l, one above 100 mg/l and further 4 above 10 mg/l. Considering that nitrate pollution is human induced and not naturally produced, this anion can be discarded. The resulting Piper diagram for the 76 groundwater samples without taking into consideration the nitrate concentration is presented in Figure 23, the one for the seven surface water samples in Figure 24.
Figure 23 Piper diagram for groundwater samples without considering nitrate
Figure 24 Piper diagram for surface water samples
Figure 23 shows that most of the samples (64%) are of bicarbonate calcium and magnesium type. This water is weakly mineralised, which is typical for groundwater encountered near the recharge area. The corresponding samples were taken in the areas north of Bongor and between Katoa and Logone Gana, where the Logone River bursts over its banks into the Yaéré and Naga plains. The low mineralisation in groundwater is the result of direct recharge from surface water.
Furthermore 16 samples (21%) located near the Logone and within the floodplain are at the border between bicarbonate-calcium-magnesium type and bicarbonate-sodium-potassium type.
Nine samples (12%) lay in the bicarbonate sodium and potassium sector of the Piper diagram. This water is recharged relatively long ago and have flown a certain distance within the aquifer to allow for sodium to replace calcium. Samples were taken in Cameroon westwards and southwards of the Maga Dam (YC 3 Dama, YC 13 Badadaye, and YC 14 Andirni), along the Logone River near Logone Gana (YT 22 Logone Gana Hopital, YT 39 Douvoul), and in the extreme north of Cameroon (YC 27 Kiniboya, YC 30 Al-Krenic, YC 32 Al-Alak II).
The surface waters of the Logone River and Koulambou River as well as surface water within the Naga plain (see Figure 24) are of bicarbonate calcium and magnesium type with insignificant amounts of sodium and potassium. The surface water in the Yaéré plain differs from the other surface water samples since part of the calcium has been exchange by sodium. The reason for this exchange has to be investigated further.
27
One water sample (YC 25 Amfara) is of sulphate-bicarbonate-sodium-potassium type (see Figure 25) and corresponds to highly mineralised water in regions located far away from the recharge zone. Along the path in the underground ion exchange has taken place and calcium has been replaced by sodium while bicarbonate by sulphate.
There is also a sample (YC 22 Lacta) of sulphate-calcium type (see Figure 25) for which only bicarbonate has been changed by sulphate.
Figure 25 Stiff diagram for samples YC 22 and YC 25
4.2.3 pH According to the WHO norms, drinking water should have pH values between 6.5 and 9.5, although pH has no impact on consumers’ health (WHO, 2008).
The average pH values of groundwater and surface water samples are around neutrality. It ranges between 5.4 and 8 for groundwater and 7.2 to 8.2 for surface water. The lowest value of 5.4 was found in YC 3 an open well in Dama located south of Maga Dam in Cameroon. A total of 13 groundwater samples (26%) show pH values lower than 6.5, although only YC 3 a value below 6.
Figure 26 shows the pH distribution in the study area.
Figure 26 Map of pH distribution in the study area
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4.2.4 Fluoride Fluorine is required in small amounts (1 to 3 mg/day) for the prevention of dental caries and good bone development (WHO, 2008). Most of the fluorine is ingested as the dissociated fluoride ion in drinking water. However, high fluoride uptake is the cause for endemic diseases such as dental and skeletal fluorosis. Therefore, assuming that an adult consumes 2 l of drinking water per day, fluoride uptake should not exceed 3 mg/day (meaning that water should not have a concentration above 1.5 mg/l) (WHO, 2008).
As reported in previous studies Vassolo & Daïra (2012), elevated concentrations between 0.5 mg/l and 1.5 mg/l of fluorides in the Chadian basin have been observed, among others, along the Logone River (south of Bongor) and along the Chari River to the north of parallel 11° North. These elevated concentrations where explained by upwelling of basement water into the shallow quaternary aquifer, since the Logone River is known to flow along structural features.
Fantong et al. (2010) investigated fluoride concentration in groundwater in the Mayo Tsanaga River catchment, which is adjacent to the present study area. They found fluoride concentrations above the WHO limit in about 26.7% (n = 26) of the sampled wells, which were linked to the presence of fluoride-enriched minerals like mica and fluorapatite in the crystalline basement aquifer. Based on the fact that the drinking water consumption is higher in arid regions, Fantong et al. (2009) proposed for the Mayo Tsanaga River catchment with an average air temperature of 28.7 °C an optimal dose of fluoride in drinking water of 0.6 mg/l to 0.7 mg/l.
For more information on origin of fluoride in groundwater refer to Vassolo & Daïra (2012).
Except for three groundwater samples, fluoride concentrations measured in the study area are below the WHO limit (Figure 27). A value of 1.9 mg/l was detected in Cameroon in Badadaye (YC13). Values of 1.68 mg/l and 1.54 mg/l were found in Andirni (YC14) and in Dabloum (YT16), respectively. Nevertheless, concentrations above 0.5mg/l were detected in 31% of the groundwater samples.
Figure 27 Map of fluoride concentrations in the study area
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4.2.5 Nitrate
High nitrate concentrations in groundwater are generally an indicator for groundwater contamination by inadequate use of fertiliser, defect sanitation plants or direct waste water disposal or disposal of human and animal faeces. Yet, naturally-induced high concentrations of nitrate, due to mineralisation of soil organic matter accumulated during the wet periods in the past, have been reported from arid and semi-arid regions in Africa, too (Stadler et al., 2008).
High nitrate concentration is considered as carcinogenic for adult persons, if exposure is permanent. It is also known as the cause for the so called "blue baby disease”, due to the decreased oxygen carrying capacity of haemoglobin in babies that leads to asphyxia because of lack of oxygen in blood. For this reason, the upper limit accepted by the WHO norms is fixed at 50 mg/l (expressed as nitrate NO3
-). However, the EU norms consider a concentration of 25 mg/l as the figure from which measures of groundwater protection should be adopted (Vassolo & Daïra, 2012).
Previous BGR investigations reported different sources of nitrate contamination in the Chad Basin (Vassolo & Daïra 2012). Northwards of 12° latitude north, pollution is probably due to livestock watering directly from the well leading to accumulation of animal faeces close to the well. In the south of Chad, agriculture is the main activity, especially cultivation of cotton and rice. The high pollution there might be an effect of the excessive use of nitrogenised fertilisers.
Within the study zone only three samples show nitrate concentrations above the WHO limit (see Figure 28). They were found in the north of Cameroon YC28 (borehole in Woulki), YC31 (open well in Haran Goulmi) and YC23 (open well in Tilde). North of Bongor, close to the Casier B rice field, no elevated nitrate concentrations were detected. Unfortunately, no samples were taken in the irrigated agricultural areas close to the Maga Dam (SEMRY project area).
Figure 28 Map of nitrate concentrations in the study area
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4.2.6 Sulphate
Sulphate in water does not cause serious health problems, but concentrations of sulphate higher than 250 mg/l result in a bitter taste of water. Very high concentrations, over 1000 mg/l, might have laxative effects on unaccustomed users. The WHO has not set any limitation based on health effects for this anion, but a concentration of 500 mg/l is suggested as the upper limit.
Within this study elevated sulphate concentrations above 250 mg/l, but below 500 mg/l, were detected in two samples in the north of Cameroon (in a borehole YC22 Lacta and in an open well YC25 in Amfara). Both samples also show elevated concentrations of chloride and sodium.
In previous studies elevated sulphate concentrations in groundwater samples were among others found to the southeast and east of the Lake Chad, regions also characterised by elevated concentrations of chloride and sodium which is a result of a very low hydraulic conductivity of the aquifer that leads to very low flow velocity or very high residence time of groundwater in the aquifer (Vassolo & Daïra, 2012). Further studies are ongoing to identify the source of the high sulphate concentrations in these areas.
4.2.7 Barium
Barium in groundwater comes primarily from natural sources such as granite-like igneous rocks, alkaline igneous and volcanic rocks and manganese-rich rocks. The solubility of barium compounds increase with decreasing pH values. There is no evidence that barium is carcinogenic, but it has been shown to have a potential effect on human’s blood pressure at low concentration. Thus, a guideline value of 0.7 mg/l was derived by the WHO for drinking water (WHO 2008).
The analyses within this study reveal two samples with barium concentrations above the suggested WHO limit. One can be found in Malfana (YT46), which is located in the Naga plain eastwards of Logone Gana. The water of these open well also shows an elevated manganese concentration of 1.1 mg/l. The other value was detected in Tchede (YC10) a village located within the Yaéré plain.
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4.2.8 Irrigation Suitability
The quality aspects of water for irrigation purposes which deserve attention include the salt content, the sodium concentration, the presence and abundance of macro- and micro-nutrients and trace elements, the alkalinity, acidity, and hardness of the water (for more detailed information refer to Vassolo & Daïra, 2012).
To define the groundwater which is suitable for irrigation, three different indexes were used: Wilcox (Wilcox, 1948), Sodium Adsorption Ratio (SAR) (Richards, 1954) and Magnesium Hazard (MH) (Szabolcs & Darab, 1964). Table 1 Irrigation Suitability Indexes
Wilcox SAR MH
The percentage of sodium within the cations (as Na in percentage) is calculated and related to the EC in µS/cm.
The SAR evaluates the sodium hazard in relation to calcium and magnesium concentrations.
The MH evaluates the amount of magnesium compared to calcium
𝑁𝑎% = 𝑁𝑎+ + 𝐾+
𝐶𝑎2+ + 𝑀𝑔2+ + 𝑁𝑎+ + 𝐾+ ∗ 100 𝑆𝐴𝑅 = 𝑁𝑎+
�𝐶𝑎2+ + 𝑀𝑔2+
2
MH = Mg2+
Ca2+ + Mg2+∗ 100
S1 (0-10) low sodium hazard
S2 (10-18) high hazard on fine-textured soils
S3 (18-26) harmful effects in most soils
S4 (>26) unsatisfactory for irrigation
MH > 50 is considered harmful and unsuitable for irrigation use
Wilcox
Figure 29 Wilcox plot to evaluate groundwater suitability for irrigation
32
After the Wilcox irrigation hazard, 93.5% of the groundwater samples are excellent to permissible for irrigation purposes. Five samples are permissible to doubtful: YC 13 in Badadaye and YC 14 in Andirni on the foothills of the Mandara Mountains, as well as YC 25 in Amfara, YC 30 in Al-Krenic, and YC32 in Al-Alak II, all located in the extreme north of Cameroon close to the Lake Chad (Figure 29).
SAR
Figure 30 SAR plot to evaluate the suitability of groundwater for irrigation
The calculated sodium adsorption ratio revealed that the groundwater in YC25 Amfara and YC 13 in Badadaye shows a medium sodium hazard (Figure 30).
Magnesium Hazard Only borehole YT40, located in Holom close to the Logone River, shows a MH value of 56 (Mg = 11.7 mg/l) and thus is considered as unsuitable for irrigation purposes.
Chloride and Boron The chloride concentrations of all groundwater samples analysed were found to be all lower than 150 mg/l and thus non toxic. Concentrations of boron are also below the toxic limit of 1 mg/l.
33
The Figure 31 presents a map of suitability of groundwater for irrigation taking into consideration all three parameters.
The light blue dots indicate water points where the water is suitable for irrigation for the three indices considered. The orange dots correspond to water points where the water is classified as unsuitable by one of the methods. The red dots show the water points classified as unsuitable by at least two of the methods.
Groundwater is only unsuitable for irrigation at Badadaye (YC13) and Amfara (YC 25).
Figure 31 Map of irrigation suitability of groundwater in the study area after Wilcox, SAR and MH indexes
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4.3 Isotopic Analysis
The composition of the environmental isotopes 18O and 2H in water is subjected to a modification (fractioning processes) by meteorological processes. Therefore recharge water in a particular environment has a characteristic isotopic signature which serves as natural tracer for the provenance of groundwater.
A water molecule is composed of two hydrogen atoms and one oxygen atom, generally written as H2O. Due to different numbers of neutrons in the nucleus of its hydrogen and oxygen atoms, the water molecule has different atomic weights or molecular mass. For example water composed of 2H2
16O has a mass of 20 and is heavier than a normal water molecule of 1H2
16O with a mass of 18.
Within the hydrological cycle, particularly in a precipitation event, generally the drops with heavier molecules tend to fall earlier while in contrast during evaporation, the lighter molecules tend to leave first. These effects can be used for defining evaporation influence in surface and groundwater.
As previously described in the report of Vassolo 2010 measurements of absolute ratio of isotopes requires sophisticated mass spectrometric equipment and measuring absolute values on a routine basis would lead to difficulties in the comparison of the results of different laboratories. That’s why the results are always expressed as the difference between the measured ratios for the given sample and that of a reference over the measured ratio of the reference (the same procedure is valid for hydrogen):
𝛿 𝑂18𝑠𝑎𝑚𝑝𝑙𝑒 =
� 𝑂18 𝑂16� �𝑠𝑎𝑚𝑝𝑙𝑒−� 𝑂18 𝑂16� �𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒� 𝑂18 𝑂16� �𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒
Eq. 1
The δ values are normally expressed as the parts per thousand (‰) differences from the reference, since fractioning processes do not reveal huge variations in isotopic concentrations (Clark & Fritz, 1997).
𝛿 𝑂18𝑠𝑎𝑚𝑝𝑙𝑒 = �
� 𝑂18 𝑂16� �𝑠𝑎𝑚𝑝𝑙𝑒� 𝑂18 𝑂16� �𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒
− 1� × 1000‰ 𝑉𝑆𝑀𝑂𝑉 Eq. 2
VSMOW stands for the Standard Mean Ocean Water, the reference which is used in this case. An δ18O value that is positive, e.g. +5‰ means it has 5 permil or 0.5 % more 18O than the reference or it is enriched by 5‰. A sample that is depleted from the reference by this amount would be expressed by δ18O = -5‰ VSMOV (Clark & Fritz 1997).
The results of the isotopic compositions of all groundwater and surface water samples are presented in the Figure 32 below. Further, the local water line corresponding to rainwater of N’Djamena provided by the International Atomic Energy Agency (IAEA) is presented. Additionally, the three isotopic compositions of at least four rainwater events from August to beginning of September 2013 in N’Djamena are added.
35
Figure 32 Results for δ18O and δ2H of groundwater, surface water and rain water
All groundwater data lie below the local water line (orange line) and the trend-line of the groundwater samples has a slope smaller than that of the local water line. This is an indication of water evaporation which takes place before rainwater recharges the groundwater. In the Yaéré and Naga plains, floodwater and rainwater rest over three months in the floodplain and are thus exposed to evaporation. Furthermore, it can be recognised that the surface water samples of the tributaries located within the floodplain have very enriched isotopic data (dark blue dots on the upper right corner of the graph), which is an indication of heavy evaporation processes. The isotopic compositions of the Logone River at Bongor and Katoa (light blue dots) as well as the Koulambou River in Logone Gana (orange dot) are enriched, although less than the tributaries, and also show evaporation impacts. The evaporation impact increases with increasing flow path of the Logone water.
The three rainwater samples from N’Djamena (red crosses) lie within the range of the rainwater samples taken from IAEA.
-55
-45
-35
-25
-15
-5
5
15
25
35
45
-8 -6 -4 -2 0 2 4 6 8 10 12
δ2H
[‰ v
s. S
MO
W]
δ 18O [‰ vs. SMOW]
Local Water Line (IAEA)
Rainwater N'Djamena (IAEA)
Rainfall N'Djamena (source BGR)
Logone River
Koulambou River
Tributaries Floodplain
Naga GW Data
Yaere GW Data
y= 6.3x + 4.53
y= 5.55x - 4.4
36
Figure 33 Results for δ 18O and δ 2H of all groundwater samples
The results for the δ 18O and δ 2H of the groundwater samples are presented in Figure 33. Depleted groundwater appears at YC13 Badadaye and YC14 Andirni in the southern part of the study area at the foothills of the Mandara Mountains indicating either immediate recharge from precipitation water or very old water. In a former study by Ngatcha et al., 2007 who studied the piezometric depression in the south of the Yaéré plain it was shown that the deeper groundwater of Andirni, located in the axe of the depression zone, belongs to old groundwater with tritium values below 4 TU. Whereby the water in the shallow aquifers on the border of the depression zone, for example in Guirvidig and Zina, shows tritium values above 4 TU, thus is recent water.
Furthermore it can be seen that the open wells lie along the trend-line and thus all receive recharge by water that has experienced evaporation before. Open wells within the plain have only a depth of about 2 m to 12 m and water analysed was probably recharged by water standing in the floodplain during the rainy season. In the case of the boreholes a combination of recharge with and without evaporated water can be observed, e.g. recharge without evaporated water can be found north of Bongor close to the Logone River (YT 10, YT 3, YT 5, YT 1 and YT6. Recharge by water experiencing evaporation is probably depending on the distance to the Rivers.
Furthermore enriched water could be detected in YC 7 Maga. Groundwater in Maga is surely recharged by Maga Lake which experiences evaporation due to open water surface.
The northern part of the study zone also shows enriched isotopic composition. Groundwater is probably a result of mixing water from the inundation plain, the Lake Chad and the Chari-Logone River. Unfortunately, neither lake water nor the area adjacent to the Lake Chad were sampled during the study period. Former studies identified enriched δ 18O values south of Lake Chad in the Chadian side (in Guirbe) which is probably a result of recharge from the Lake Chad into the aquifer.
37
For a better understanding of water sources in the extreme north of Cameroon more in depth studies have to be conducted.
Figure 34 shows the δ 18O values, hence water enriched (red) or depleted (blue) in δ 18O of all sample locations in the study area.
Big red dots representing surface water of the Logone River and its tributaries. Thus the Logone and its tributaries show enriched water during the dry season due to evaporation influence.
Small dark blue dots representing depleted water. They were measured in the piezometric depression zone adjacent to the Mandara Mountains indicating older water from deeper aquifers (see Ngatcha et al., 2007).
Furthermore water which is depleted in δ 18O could be detected in two open wells (YC3 Dama and YT 14 Bizimou), located around Katoa and indicating either immediate recharge from precipitation or very old water probably caused by upcoming water due to geological structures. The open well in YT 14 also shows high fluoride values which supports this assumption. Further investigations are necessary to draw a clear conclusion. The depleted sample in the extreme north of Cameroon could be also the reason of superposed aquifers and thus older water.
In the following Figure 35 the δ 18O values of the study area are presented together with the map of the temporal cycles of the vegetation gained by analysis of MODIS satellite data (refer to chapter 2).
Figure 34 Map of measured δ 18O values in the study area
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Figure 35 Map showing vegetation cycles in 2012 by means of MODIS satellite data (Geerken et al., 2012) and measured δ 18O values in the study area
From this figure, it can be seen that tube wells and open wells located in the floodplain northwards of Bongor show more depleted groundwater than those located in the floodplain between Katoa and Bongor. It is assumed that groundwater close to and northwards of Bongor is recharged by the first flooding in September/October, while groundwater between Katoa and Logone Gana receives recharge in October to November from surface water exposed to evaporation while standing in the floodplain.
Isotopic analyses demonstrate that the Logone River clearly interacts with the adjacent groundwater during the rainy season. In order to reveal a clear isotopic signal of the Logone water, sampling during the rainy season is necessary.
39
5 Conclusion and Recommendations
The groundwater research in the Yaéré and Naga plains was conducted to gain information about the groundwater origin and its flow paths, the quality of the groundwater and surface water, as well as groundwater interaction between the Logone River and its floodplain.
The hydrochemical analyses show that most of the samples are of bicarbonate-calcium type indicating groundwater which is located close to its recharge zone. Furthermore, hydrochemical and isotopic results, groundwater contour lines, and satellite information indicate that the Logone water directly recharges the region north of Bongor. It corresponds to the area where water bursts its bank and flows into the Naga plain.
Water of bicarbonate sodium and potassium type, and thus with a certain residence within the aquifer to allow for sodium to replace calcium, were detected in the extreme north of Cameroon, westwards and southwards of the Maga Dam and along the Logone River. It could be the result of superposed aquifers that are differently recharged, as published by Ngatcha et al. (2007) for an adjacent region.
Groundwater in the extreme north of Cameroon appears to be the result of mixing waters from the Chari/Logone River and the Lake Chad. In order to clearly identify the origin of the groundwater, more isotope and hydrogeological studies have to be conducted. It is necessary to gain more information on the geology of the study area to be able establish a stratigraphic correlation between the shallow groundwater extracted by open wells and the deeper groundwater extracted by boreholes.
The isotopic analysis show that most of the groundwater in the floodplain is recharged by surface water that rests for at least 3 month after the rainy season within the floodplain, where it experiences evaporation processes.
Furthermore, Quaternary groundwater in the Yaéré and Naga plains is of good quality. The Wilcox, MH and SAR index show that groundwater, except for six locations, is suitable for irrigation.
The majority of the samples show nitrate concentration under the WHO limit, although no samples along agricultural areas around the Maga Dam were taken.
It was found that open and tube wells are badly protected against human and animal pollution. It is recommended to sensitise the population about hygiene standards concerning the wells. In 26 of the visited villages not any borehole equipped with handpump was available and drinking water provided by open wells only. Furthermore, the village King King is equipped only with a piezometer and water for consumption has to be collected from a stream located in a distance of some 3 km.
Partly high concentrations of fluoride were detected along and close to the Logone River, Due to the fact that fluoride can cause serious health problems, it is recommended that other water consumption sources for these regions are used or filter units to reduce the fluoride content are installed.
In order to produce a map of groundwater contour lines for the whole Lower Logone inundation zone exact surface heights from boreholes and open wells have to be measured. Additionally to the already gained groundwater information in the Yaéré and Naga plains, it is recommended expanding research activities to include infiltration tests and water heights measurements in the floodplain.
Summarising, this report shows that the Lower Logone River actively interacts with the adjacent groundwater aquifer and thus, it is recommended to protect the Yaéré and Naga plains regarding its groundwater quality and quantity. The Logone River has to be preserved against pollution; and water abstraction by both member countries should be regulated in a sustainable manner.
40
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42
Annexes
Annex 1 List of groundwater level measurement points
ID Village X Y Depth [m]
Water level from top of casing [m] Stick up [m]
YT 7 Biliam Oursi 15.2323 10.5567 11 9.2 0.43 YT 9 Moga 15.3061 10.5287 8.8 0
YT 14 Bizimou 15.2695 10.8568 4 3.7 0 YT 15 Toul 15.2279 10.9146 4.5 3.8 0 YT 16 Dabloum 15.0790 10.9697 5.5 2.9 0 YT 17 Loutou Piezo 15.3781 10.7680 85 12.52 0.4 YT 19 Ouaye 15.2391 11.1240 3.1 2.4 0 YT 23 King King Piezo 15.2093 11.5689 62.3 6.2 0.5 YT 30 Yama 15.2700 11.2800 4.4 2.9 0 YT 31 Girli 15.2800 11.2400 4.5 4 0 YT 32 Kolomara 15.2800 11.2200 4.15 3.73 0 YT 33 Bayem 15.2600 11.2200 3.75 3.22 0 YT 34 Bogom 15.2400 11.2000 3.15 2.1 0 YT 35 Birim 15.2400 11.2600 4.73 4.18 0 YT 39 Douvoul 15.1100 11.4800 8.9 7 0.78 YT 43 Zoumka 15.1000 11.6800 4.9 4.7 0 YT 46 Malfana 15.1100 11.7700 11.7 8.45 0.7
1 Goulmoun Bassi 15.3376 10.3095 2.43 0 2 Saka 15.3536 10.3852 3.93 0 3 Dounou 15.2690 10.4411 4.83 0 4 Koumi 15.1966 10.5156 5.18 0 5 Magao 15.3513 10.6038 7.25 0 6 Mogodi 15.1683 10.6386 7.06 4 0.8 7 Ourkila 15.2137 10.6636 4.5 4.29 0 8 Gouaye 15.1160 10.7284 4.2 3.76 ? 9 Katoa 15.0743 10.8309 2.36 0
10 dialo 15.1385 10.9463 3 2.55 0 11 Djambal 15.0953 11.1399 3.95 3.5 0 12 Madoubou 15.3716 11.3019 12.8 11.24 0.74 13 Bougoumene 15.3339 11.4658 9.65 8.75 0.93 15 Logone gana 15.1479 11.5596 8.69 6.25 0.8 17 Bulaboulin 15.3528 11.2057 9.62 0.2 18 Balge 15.1947 11.4871 3.62 2.52 0 19 Holom 15.0684 11.3192 6.1 5 0.92 20 Ouldou Borno 15.1782 11.6580 12.83 9.92 0.82
YC 3 Dama 15.0900 10.5700 7.5 6.45 0.2 YC 4 Gaya 15.0800 10.7700 3.88 3.4 0.8 YC 5 Mazera 15.0400 11.1600 9.7 8.1 0.8 YC 7 Maga 14.9300 10.8400 4.5 3.95 0.75 YC 8 Guividig 14.8300 10.8800 13.8 12.92 0.84 YC 10 Tchede 14.8400 11.1900 9.32 8.4 0.9 YC 11 Zina 14.9700 11.2600 8.95 7.55 0.9 YC 12 Dafen 14.8900 11.0900 10 9.46 0 YC 23 Tilde 14.7400 12.1300 20.5 13.55 0.7 YC 25 Amfara 14.8500 12.2200 12.8 11.72 0.72 YC 31 Haran Goulmi 14.6300 12.2900 23.5 20.36 0.7
21 Marao 15.2760 10.3739 5.12 4.05 0.85 22 Dabai II 15.1948 10.4587 4.54 2.83 0.34 24 Mahe Piezo 14.9413 11.3934 7.93 6.82 0.89 25 Bourgouma Mouzgoum 15.0394 11.8869 8.6 8.45 0.65 26 Logone Birni 15.1039 11.7799 10.9 7.67 0.72 27 Merd? 14.9533 11.8783 8.8 7.85 0.32 28 Wourki 14.6224 12.4777 28 25.2 0.7 29 Zalat Nawara 14.7300 12.3564 15.8 15.12 0.68 31 Al-Alak 14.5451 12.3709 15.12 12.78 0.82
43
ID Village X Y Depth [m]
Water level from top of casing [m] Stick up [m]
32 Ngame II 14.7144 12.2179 17.53 0.7 33 Kousseri Ecole 15.0542 12.0517 8.7 7.64 0.43 23 Tschede Piezo 14.8407 11.1922 29.17 8.8 0.8 16 Matasi 15.3531 11.2057 ~1.34 1.27 0 30 Haran Goulmi Piezo 14.6250 12.2846 73.83 20.26 0.55
27A Goulfey 14.9014 12.4777 11.60 10.4 0.7
44
Annex 2 List of sample points
Sample-ID Village X Y Type of sample Depth [m] Date
YT 1 Goulmoun Bassi 15.3411 10.3076 tubewell (hand pump) 09.04.13 YT 2 Saka 15.3541 10.3848 tubewell (hand pump) 09.04.13 YT 3 Ogol 15.3021 10.3695 tubewell (hand pump) 09.04.13 YT 4 Télémé 15.3241 10.4249 tubewell (hand pump) 09.04.13 YT 5 Dounou 15.2689 10.4420 tubewell (hand pump) 10.04.13 YT 6 Koumi 15.1961 10.5161 tubewell (hand pump) 10.04.13 YT 7 Biliam Oursi 15.2323 10.5567 open well 11 10.04.13 YT 8 Magao 15.3532 10.6023 tubewell (hand pump) 10.04.13 YT 9 Moga 15.3061 10.5287 open well not measured 10.04.13 YT 10 Mogodi 15.1665 10.6376 tubewell (hand pump) 11.04.13 YT 11 Ourkila 15.2349 10.6774 tubewell (hand pump) 11.04.13 YT 12 Gouaye 15.1163 10.7290 tubewell (hand pump) 11.04.13 YT 13 Katoa 15.0682 10.8268 tubewell (hand pump) 11.04.13 YT 14 Bizimou 15.2695 10.8568 open well 4 12.04.13 YT 15 Toul 15.2279 10.9146 open well 4.5 12.04.13 YT 16 Dabloum 15.0790 10.9697 open well 5.5 12.04.13 YT 17 Loutou 15.3781 10.7680 Piezometer 85 13.04.13 YT 18 Guiao 2 15.3331 10.8913 tubewell (hand pump) 13.04.13 YT 19 Ouaye 15.2391 11.1240 open well 3.1 14.04.13 YT 20 Madoubou 15.3710 11.3024 tubewell (hand pump) 14.04.13 YT 21 Bougoumene 15.3358 11.4683 tubewell (hand pump) 14.04.13 YT 22 Logone gana Hôpital 15.1478 11.5645 tubewell (hand pump) 15.04.13 YT 23 King King 15.2093 11.5689 Piezometer 62.3 15.04.13 YT24 Bongor 15.3688 10.2690 Logone River 10.04.13 YT25 Katoa 15.0729 10.8304 Logone River 11.04.13 YT 26 Logone Gana 15.1461 11.5602 Kouloumbou River 15.04.13 YT 27 Loumia 15.3278 11.4146 River 14.04.13 YT 28 Djoungotoli 15.2885 11.5461 tubewell (hand pump) 29.04.13 YT 29 Matasi 15.3566 11.2044 tubewell (hand pump) 29.04.13 YT 30 Yama 15.2667 11.2832 open well 4.4 30.04.13 YT 31 Girli 15.2794 11.2367 open well 4.5 30.04.13 YT 32 Kolomara 15.2810 11.2153 open well 4.15 30.04.13 YT 33 Bayem 15.2581 11.2210 open well 3.75 30.04.13 YT 34 Bogom 15.2408 11.2016 open well 3.15 30.04.13 YT 35 Birim 15.2423 11.2583 open well 4.73 30.04.13 YT 36 Oudiya 15.2232 11.4923 tubewell (hand pump) 01.05.13 YT 37 Yaouri 15.1813 11.4806 River 01.05.13 YT 38 Dogofe 15.1443 11.4602 tubewell (hand pump) 01.05.13 YT 39 Douvoul 15.1059 11.4847 open well 8.9 01.05.13 YT 40 Holom 15.0731 11.3318 tubewell (hand pump) 01.05.13 YT 41 Gofa 15.0677 11.4142 tubewell (hand pump) 01.05.13 YT 42 Aouri 15.1042 11.6072 tubewell (hand pump) 02.05.13 YT 43 Zoumka 15.1042 11.6755 open well 4.9 02.05.13 YT 44 Mouzoul kotoko 15.1463 11.7044 tubewell (hand pump) 02.05.13 YT 45 Ouldou Arabe 15.1726 11.6810 tubewell (hand pump) 02.05.13 YT 46 Malfana 15.1110 11.7722 open well 11.7 03.05.13 YT 47 Hille Ziki 15.1506 11.7635 tubewell (hand pump) 03.05.13 YT 48 Goni 15.1426 11.8040 tubewell (hand pump) 03.05.13 YT 49 Kolomata 15.1419 11.8036 River 03.05.13 YC 1 Marao 15.2760 10.3739 tubewell (hand pump) 16.05.13 YC 2 Dabai II 15.1941 10.4600 tubewell (hand pump) 16.05.13
45
Sample-ID Village X Y Type of sample Depth [m] Date
YC 3 Dama 15.0909 10.5748 open well 7.5 16.05.13 YC 4 Gaya 15.0807 10.7703 open well 3.88 16.05.13 YC 5 Mazera 15.0404 11.1573 open well 9.7 17.05.13 YC 6 Arainaba 15.0419 11.0329 tubewell (hand pump) 17.05.13 YC 7 Maga 14.9333 10.8414 open well 4.5 17.05.13 YC 8 Guividig 14.8288 10.8811 open well 13.8 17.05.13 YC 9 Zina Blang 14.7987 11.0119 tubewell (hand pump) 18.05.13
YC 10 Tchede 14.8404 11.1919 open well 9.32 18.05.13 YC 11 Zina 14.9653 11.2638 open well 8.95 18.05.13 YC 12 Dafen 14.8861 11.0905 open well 10 19.05.13 YC 13 Badadaye 14.5743 11.0949 tubewell (hand pump) 19.05.13 YC 14 Andirni 14.7000 11.0622 tubewell (hand pump) 19.05.13 YC 15 Boromo 14.9614 11.2605 River 20.05.13 YC 16 Mahe kotoko 14.9409 11.3933 tubewell (hand pump) 20.05.13 YC 17 Hinale 14.9930 11.5869 tubewell (hand pump) 20.05.13 YC 18 Bourgouma Mouzgoum 15.0398 11.8863 tubewell (hand pump) 22.05.13 YC 19 Nbekle 14.9721 11.7539 tubewell (hand pump) 22.05.13 YC 20 Merdé 14.9531 11.8775 tubewell (hand pump) 22.05.13 YC 21 Ouaditouna 14.9622 12.0360 tubewell (hand pump) 22.05.13 YC 22 Lacta 14.8795 12.1049 tubewell (hand pump) 23.05.13 YC 23 Tilde 14.7421 12.1253 open well 20.5 23.05.13 YC 24 Sahaba 14.7977 12.0356 tubewell (hand pump) 23.05.13 YC 25 Amfara 14.8468 12.2191 open well 12.8 24.05.13 YC 26 Goulfey 14.9022 12.3839 tubewell (hand pump) 24.05.13 YC 27 Kiniboya 14.7711 12.4536 tubewell (hand pump) 24.05.13 YC 28 Wourki 14.6236 12.4797 tubewell (hand pump) 24.05.13 YC 29 Zalat Nawara 14.7298 12.3569 tubewell (hand pump) 25.05.13 YC 30 Al-krenic 14.5728 12.5902 tubewell (hand pump) 25.05.13 YC 31 Haran Goulmi 14.6255 12.2871 open well 23.5 26.05.13 YC 32 Al-Alak II 14.5451 12.3709 tubewell (hand pump) 26.05.13 YC 33 Ngame II 14.7153 12.2176 tubewell (hand pump) 26.05.13 YC 34 Kousseri Ecole 15.0544 12.0528 tubewell (hand pump) 27.05.13
46
Annex 3 Statistics of the measured chemical parameters in groundwater samples
Parameter Unit WHO limit Average Min Max SD
pH >6.5<8.5 7.0 5.4 8.0 0.5
EC µS/cm <1500 382.8 55.0 1898.0 309.1
T °C 30.4 27.3 32.7 1.2
K mg/l 8.2 0.9 101.0 15.5
Na mg/l 31.5 4.4 270.0 44.3
Mg mg/l 8.4 0.5 32.2 6.1
Ca mg/l 33.0 2.2 121.0 23.9
Cl mg/l 5.2 0.1 80.4 13.7
SO4 mg/l 500 18.1 0.0 448.0 69.0
HCO3 mg/l 207.3 22.2 650.0 129.9
NO3 mg/l 50 5.1 0.0 101.0 15.7
NH4 mg/l 0.1 0.0 1.1 0.2
NO2 mg/l 3 0.1 0.0 1.4 0.2
PO4 mg/l 7.8 0.0 7.8 7.8
F mg/l 1.5 0.5 0.1 1.9 0.4
Fe(II) mg/l 0.5 0.0 10.7 1.6
Al mg/l 0.9 0.0 0.0 0.6 0.1
Mn mg/l 0.2 0.0 1.6 0.3
Cu mg/l 0.2 0.0 0.0 0.1 0.0
Br mg/l 0.0 0.0 0.4 0.1
As mg/l 0.01 0.00 0.00 0.00 0.00
Sr mg/l 0.2 0.0 1.1 0.3
Cd mg/l 0.003 0.000 0.000 0.000 0.000
Ni mg/l 0.07 0.00 0.00 0.00 0.00
Pb mg/l 0.01 0.00 0.00 0.00 0.00
Ba mg/l 0.7 0.2 0.0 0.9 0.2
Zn mg/l 0.1 0.0 1.6 0.2
SiO2 mg/l 64.0 29.3 106.0 22.0
47
Annex 4 Statistic of chemical parameters measured in surface water samples
Parameter Unit WHO limit Average Min Max SD
pH >6.5<8.5 7.7 7.2 8.2 0.3
EC µS/cm 160.1 64.0 307.0 98.3
T °C 29.0 24.1 33.1 2.7
K mg/l 5.9 2.2 10.8 3.5
Na mg/l 11.6 3.5 29.5 9.9
Mg mg/l 4.7 2.3 9.4 2.7
Ca mg/l 12.1 5.0 25.3 7.7
Cl mg/l 1.0 0.3 2.1 0.6
SO4 mg/l 500 0.1 0.0 0.2 0.1
HCO3 mg/l 97.6 37.5 193.0 62.0
NO3 mg/l 50 0.2 0.0 0.8 0.3
NH4 mg/l 0.1 0.0 0.6 0.2
NO2 mg/l 3 0.5 0.0 1.8 0.8
PO4 mg/l 0.09 0.03 0.15 0.04
F mg/l 1.5 0.4 0.1 0.9 0.3
Fe(II) mg/l 0.2 0.1 0.4 0.1
Al mg/l 0.9 0.1 0.0 0.3 0.1
Mn mg/l 0.03 0.00 0.14 0.05
Cu mg/l 0.2 0.02 0.00 0.04 0.02
Br mg/l 0.003 0.000 0.005 0.003
As mg/l 0.01 0.00 0.00 0.00 0.00
Sr mg/l 0.15 0.07 0.29 0.09
Cd mg/l 0.003 0.000 0.000 0.000 0.000
Ni mg/l 0.07 0.00 0.00 0.00 0.00
Pb mg/l 0.01 0.00 0.00 0.00 0.00
Ba mg/l 0.7 0.1 0.1 0.2 0.1
Zn mg/l 0.004 0.000 0.006 0.002
SiO2 mg/l 26.9 21.3 40.8 8.1
