<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">GEP</journal-id><journal-title-group><journal-title>Journal of Geoscience and Environment Protection</journal-title></journal-title-group><issn pub-type="epub">2327-4336</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/gep.2022.107014</article-id><article-id pub-id-type="publisher-id">GEP-118753</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Conceptual Model of Aquifers in the Bedrock Zone of the Marahou&#233; Watershed (Centre-West of Ivory Coast)
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kouassi</surname><given-names>Désiré Bouatrin</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Innocent</surname><given-names>Kouassi Kouame</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Aristide</surname><given-names>Gountôh Douagui</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kouamé</surname><given-names>Auguste Kouassi</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bi</surname><given-names>Tié Albert Goula</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Geosciences and Environment Laboratory, Department of Environmental Sciences and Management, Nangui University Abrogoua, Abidjan, Ivory Coast</addr-line></aff><pub-date pub-type="epub"><day>08</day><month>07</month><year>2022</year></pub-date><volume>10</volume><issue>07</issue><fpage>229</fpage><lpage>256</lpage><history><date date-type="received"><day>8,</day>	<month>April</month>	<year>2022</year></date><date date-type="rev-recd"><day>24,</day>	<month>July</month>	<year>2022</year>	</date><date date-type="accepted"><day>27,</day>	<month>July</month>	<year>2022</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Marahou&#233; watershed, located in the Center West of C
  &amp;#244;te d’Ivoire, has experienced significant population growth in recent decades. And a major economic boom linked to intense agricultural activity and the presence of certain industries. This population growth is also accompanied by seasonal water shortages. Hence 
  it
   need
  s
   to better manage the basin’s groundwater, which is a permanent resource and more resistant than surface water to climatic hazards. The objective of this study is therefore to propose a conceptual model of hydrogeological flow for the sustainable exploitation of groundwater resources in the Marahou&#233; watershed. The establishment of the conceptual model was carried out in two stages. The first step consisted in defining the stratigraphic units. For this purpose, three units have been defined. These are the layer of alterite, the useful fissured horizon and the sound basement. The thickness of the layer of alterite varies from 0 to 80 m with an average of 26 m. As for the useful fissured horizon, its thickness is between 43 and 46.5 with an average of 45 m. In addition, the roof of the basement presents a slightly uneven morphology with a North-West
  ,
   South-East dip and the altitudes are between 150 and 390 m. The second step corresponds to the phase of determining the hydrodynamic parameters. During this phase, the crack porosity, the transmissivity, the conductivity, the storage coefficient, the hydrological balance and the piezometric map were determined. Indeed, these parameters (the crack porosity, the transmissivity, the conductivity and the storage coefficient) confirm not only the heterogeneity of the medium but that the cracked horizon is sufficiently porous to be assimilated to an equivalent continuous medium during the simulation.
 
</p></abstract><kwd-group><kwd>Marahou&#233; Watershed</kwd><kwd> Conceptual Model</kwd><kwd> Ivory Coast</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>In Africa, particularly in West Africa, the decline in the level of rainfall, environmental degradation and population growth have caused a depletion of water resources (Baron &amp; Bonnassieu, 2011; Mah&#233; et al., 2001). One of the major consequences of the fall in rainfall is the increasing reduction in groundwater recharge (Ouedraogo, 2016). However, nearly half of Africa’s population relies on groundwater, which in many rural areas of sub-Saharan Africa is the only sustainable source of water for human consumption (Carter &amp; Parker, 2009) .</p><p>Marahou&#233; watershed, located in the center west of C&#244;te d’Ivoire in the basement zone (Bi&#233;mi, 1992; Akpo et al., 2016; Irie et al., 2015), is also affected by this drop in rainfall. The populations who live there frequently experience a shortage of drinking water during the dry seasons, accentuated by untimely water cuts by SODECI (Water Distribution Company in C&#244;te d’Ivoire) for up to two weeks or even a month or more in some localities. This shortage is accentuated in the villages and camps which lack village pumps. This problem can be attributed to the fact that there is a significant increase in bare soils/habitats and crops while the water reservoirs are strongly regressing (Irie et al., 2015). Also added is the fact that the productivity of boreholes is difficult to predict in the basement zone (Lachassagne et al., 2015; Ouedraogo, 2016; Yao, 2011). This causes several failures during the construction of hydraulic structures for groundwater catchment in particular (wells and boreholes), structures that are essential for the permanent supply of drinking water to the populations. Thus, the increasingly strong social demand makes it necessary to elucidate the major questions that arise for both researchers and managers in order to better understand the mechanisms conditioning the availability and distribution of groundwater for better management of this resource. We can only manage well what we know well.</p><p>The models can thus serve as a basis for decision-making in a resource management framework. They are also a tool for improving the understanding of underground hydrodynamic phenomena (Jaunat, 2013). In addition, the conceptual model schematically describes the studied aquifer system (Kouam&#233;, 2007). It specifies the horizontal and vertical extension, details the succession of aquifers and aquitards, describes the lithology and the dominant hydrogeological characteristics, explains the hydraulic conditions at the limits of the system, evaluates the main components of the flows passing through it and identifies the zones of recharge and outlet (Barth&#233;lemy &amp; Seguin, 2016).</p><p>Indeed, basement aquifers are made up of crystalline rocks, of plutonic (granites) and metamorphic (gneiss, schists, micaschists, etc.) origin. Hydrogeologically, it is hard rock (“hard rock” in English) (Lachassagne et al., 2015). They thus exhibit, despite very diverse origins and compositions, a relatively homogeneous overall behavior and similar properties. They are mainly characterized by permeability of cracks and fractures. The aquifers they contain are therefore classically considered as discontinuous, due to the significant spatial variability of their hydrodynamic properties (Lachassagne et al., 2005). Between the sound impermeable rock and the surface alterites, there is an intermediate horizon called the fissured horizon. Unlike alterites, this environment has high permeability and forms the transmissive part of the aquifer (Duran, 2005). To this end, the knowledge, at the scale of the watershed, of the geometry (roof, wall) and of the hydrodynamic properties of the two main constituent horizons of the bedrock aquifer makes it possible to define its underground water reserve (Lachassagne et al., 2015). Thus, faced with this seasonal water shortage, a conceptual model of hydrogeological flows is required in the Marahou&#233; watershed.</p><p>It is in this context that this study was initiated, the objective of which is to propose a conceptual model of hydrogeological flow for the sustainable exploitation of groundwater resources in the Marahou&#233; watershed. This will first involve defining the stratigraphic units and then determining the hydrodynamic input parameters of the flow model.</p></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Study Zone</title><p>Marahou&#233; River watershed is a sub-basin of the Bandama River watershed which has an area of 97,000 km<sup>2</sup>, or about 30% of the area of C&#244;te d’Ivoire (Avenard et al., 1971; Kamagate et al., 2011). It is located between longitude 5˚31'80.0'' and 7˚1'80.0'' West and latitude 6˚45'60.0'' and 9˚27'0.0'' North. Its area is 24,300 km<sup>2</sup>. From an administrative point of view, the watershed of the marahou&#233; straddles six (6) regions (B&#233;r&#233;, Worodougou, Marahou&#233;, Bagou&#233;, Haut Sassandra and Kabadougou). 550 km long, the main river (the Marahou&#233;) is flanked by two tributaries: the B&#233;r&#233; to the east and the Yani or Bahoroni to the west (Irie et al., 2016; Bi&#233;mi, 1992). In fact, the Marahou&#233; watershed straddles two climatic regimes. In the north, we distinguish the subtropical regime (Sudanese climate) and in the south the humid tropical regime (Baoul&#233;an climate) (Goula et al., 2006). The subtropical regime is characterized by two seasons, a rainy season from May to October (6 months) and a dry season from November to April (6 months) which is accentuated by the harmattan with lower average annual rainfall (1977-2001) at 1200 mm. The humid tropical regime is distinguished by a four-season climatic regime and average annual rainfall (1977-2001) which varies on average between 1200 mm and 1600 mm. Namely, a long rainy season from March to June (4 months), a short dry season from July to August (2 months), a short rainy season starting in September and ending in October (2 months) and a great dry season from November to February (4 months) (Iri&#233;, 2019).</p><p>Geologically, several types of petrographic facies have been identified (<xref ref-type="fig" rid="fig1">Figure 1</xref>). These are fine-grained granite, porphyroid granite with biotite and dominant pink feldspar, biotite granite with migmatitic and gneissic past, granodiorite, migmatites, eyed gneiss, volcano-sedimentary and detrital rocks, vein complexes (Bi&#233;mi, 1992). These geological formations are grouped into two main entities: magmatic rocks and metamorphic rocks.</p></sec><sec id="s2_2"><title>2.2. Setting up the Conceptual Model</title><p>The purpose of setting up the conceptual model is to simplify the system to be modeled and to organize the associated data to take them into account in a numerical model (Koffi, 2004). According to Anderson and Woessner (1992), the essential steps in setting up the conceptual model are the definition of the hydrostratigraphic units and the preparation of the water balance.</p><sec id="s2_2_1"><title>2.2.1. Development of the Digital Terrain Model (DTM)</title><p>The DTM file of the Marahou&#233; watershed was set up using radar images captured from February 11 to 22, 2000 during the Shuttle Radar Topography Mission (SRTM) and published in September 2014. These are scenes n06_w006_1arc_v3, n06_w007_1arc_v3, n07_w006_1arc_v3, n07_w007_1arc_v3, n08_w006_1arc_v3, n08_w007_1arc_v3 n08_w008_1arc_v3, n09w007_1arc_v3. This SRTM 1 Arc-Second elevation data provides worldwide coverage with a resolution of one (1) arc second (30 meters) and provides the global dataset. Also, the DEM file was made in three (3) steps. The first step concerns the acquisition of the different scenes. Access to these data was possible thanks to the Earth Explorer software, developed by the USGS (United States Geological Survey). This application was used to search, preview and download SRTM 1 Arc-Second Global elevation data. After the downloads, the next step is the processing phase. This phase consisted of mosaicking the different scenes with the SNAP software. Finally, the last step was devoted to extracting the contour of the Marahou&#233; watershed from these different scenes and then coloring the different altitudes with the QGIS 3.16.2 software. This approach allowed the final implementation of the DTM of the basin.</p></sec><sec id="s2_2_2"><title>2.2.2. Layers Model Design</title><p>The design of the layer model was carried out from sections of boreholes collected in the various Territorial Directions of Hydraulics (DTH) of the Marahou&#233; watershed. These are the DTHs of Daloa; puffed up; Seguela; Mankono and Boundiali. Cross-checking of the geological profiles of the various boreholes at the longitudinal and transverse level, based on the analysis of the technical data sheets, made it possible to identify and describe the formations present. The last water inflows were considered as the lower limits of the different fissured horizons at the level of the boreholes. Boreholes F1 to F11 (<xref ref-type="fig" rid="fig2">Figure 2</xref>) respectively of M’Bia; Morondo; Manabri; Silakoro; Lenguekro 2; flash; gohitre; Drikouafla 2; Djessikro; Gobazra Dioula and Seitinfla were used for the realization of the longitudinal profile (the North-West, South-East direction). Similarly, boreholes F12 to F16 (<xref ref-type="fig" rid="fig3">Figure 3</xref>) respectively from Sanankoro; N’gokro; _ Meneni; Korosso; Brokodalah were used for the realization of the transverse profile (the East – West direction).</p></sec><sec id="s2_2_3"><title>2.2.3. Alterite Thickness Mapping</title><p>The weathering profiles manifested as two horizons, surface weathering and an underlying fissured horizon. If we assume that the thickness of the fissured horizon under the transition level with the alterites is almost constant spatially, we can then consider that it suffices to locate the contact zone of the alterites/fissured horizon to map the thicknesses of weathering profiles (Durand et al., 2015). Mapping the contact zone between the alterites and the fissured horizon consists in tracing the outline of the alterite outcrops as a lithological formation in itself. The mapping of the thickness of the alterites was carried out in two stages.</p><p>The first step consisted in subtracting the level of alterites from the altitude (Z) of the 300 boreholes used here as observation points of the interface alterites/fissured medium. These levels of alterites generated, made it possible to construct by kriging the map of the interface alterites/fissured medium thus representing the roof of the basement. Then, the second step was devoted to the deduction of the thickness of the alterites at all points of the Marahou&#233; watershed. To this end, it suffices to subtract the roof of the basement from the topographic altitude in the zones where the alterites are still in place to know the thickness of these at each point. For this, the DTM established is used under a Geographic Information System. On a new grid identical to that of the interpolation map, the value of the topographic altitude (DTM) removed from the altitude of the base of the alterites (roof of the base) is calculated using the raster tool ARCGIS 10.2 software calculator. Positive values, less than or equal to 80 m, are interpreted in terms of the thickness of the weathering layer. As for values greater than 80 m, they have been placed in the blank area of the map. In reality, beyond 80 m, the thickness of the layer of alterite coincides with the sectors where the slopes of the DTM were greater than 2%, which is higher than the limit commonly accepted by geologists as allowing the maintenance in place of altered formations on the plateaus (Mougin et al., 2015). With regard to the negative values (or the topographic surface which is located below the level of the base of the alterites), they give in absolute value the incised depth within the fissured horizon.</p></sec><sec id="s2_2_4"><title>2.2.4. Helpful Fissured Horizon Mapping</title><p>The thickness of the fissured horizon was determined from linear flow rates (Q/P'). By definition, the linear flow (Q/P') is the flow at the blowing of the boreholes (air lift flow noted Q) in relation to the depth (P) of the borehole (Equation (1)) under the base of the loose alterites (Lachassagne et al., 2015). The linear flows were calculated at the level of the three hundred (300) boreholes. Concretely, the method chosen for the determination of the thickness of the fissured horizon, is that which was developed by Courtois, entitled “80% percentile”. It consists of calculating a cumulative percentage of linear flow (Courtois et al., 2008). This percentage makes it possible to deduce two values:</p><p>&#173; First the thickness of the useful cracked horizon (L<sub>u</sub>) which corresponds to the thickness defined by the threshold of 80% of the cumulative percentage of linear flow.</p><p>&#173; Then the flow rate of this useful fissured horizon (Q<sub>Lu</sub>) obtained by multiplying the flow rate of the useful fissured medium (average of the linear flow rates not in relation to the total number of boreholes) (Q<sub>pl</sub>) and the thickness of the useful fissured horizon (Equations (2) and (3)).</p><p>The map of the thickness of the useful fissured horizon was carried out on the two geological formations, essential to the basin. That is to say on granites and schists. In total, 88.33% (i.e. 265) of the drillings were carried out on granites. The remaining 11.67% of the boreholes (i.e. 35 boreholes) were drilled on shales.</p><p>Q / P ′ = Q P (1)</p><p>Q p l = ∑ i = 1 , ⋯ , n L u ( Q P ′ i ) / N f (2)</p><p>Q L u = Q p l &#215; L u (3)</p><p>With Q / P ′ the instantaneous linear flow and Nf the number of boreholes.</p></sec><sec id="s2_2_5"><title>2.2.5. Determination of Hydrodynamic Parameters</title><p>The data used to determine the porosities, transmissivities, hydraulic conductivities and storage coefficients are the data from the 106 pumping test sheets collected in the various Territorial Hydraulics Departments (DTH) in the basin. Thus, the model adopted for determining the porosity of cracks is the Warren and Root model, also called the Double porosity model (Thiery et al., 1982; Ko&#239;ta, 2010). According to Warren and Root the aquifer system is characterized by two factors. These are the ratio (F) and the interporosity flow parameter (ε). The ratio F is the ratio of the product of the porosity by the compressibility of the fractures compared to the product of the porosity by the compressibility of the system (Equation (4)). The ratio F (Equation (6)) is also determined by plotting the curve of the drawdowns as a function of time in semi-logarithmic coordinates. Then, one determines the porosity ( ϕ F ) after having chosen the Coefficient of compressibility of water and that of compressibility of the matrix (Faillat et al., 1998; Thiery et al., 1982). Thus the ratio F is established as follows:</p><p>F = ϕ F C e ϕ F C e + ( 1 − ϕ F ) C m a (4)</p><p>From Equation (4) we get the crack porosity ϕ F</p><p>ϕ F = F C m a C e + F C m a − F C e (5)</p><p>F = 10 − Δ S C (6)</p><p>With</p><p>ϕ F Porosity of fractures and connected pores;</p><p>C<sub>e</sub>: Water compressibility coefficient;</p><p>C<sub>ma</sub> Matrix compressibility coefficient.</p><p>Precise studies have made it possible to draw up the values of C<sub>ma</sub> according to the rock matrix and of C<sub>e</sub>according to the temperature of the water (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>). Under usual conditions, the temperature of water deposits is around 30˚C (Thiery et al., 1982). The corresponding coefficient of compressibility of water is close to C e = 4.6 &#215; 10 − 5 m 3 / m 3 / bar either C e = 4.508   m 2 / kg .</p><p>The transmissivities were determined using the Cooper-Jacob (1946) method. Indeed, the method of the rise of Cooper-Jacob allows the calculation of the transmissivity (T) by interpretation of the equation of THEIS -JACOB with the following data:</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref></label><caption><title> Values of the rock matrix compressibility coefficient used</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Nature of the rock matrix</th><th align="center" valign="middle" >C<sub>ma</sub> in m<sup>3</sup>/m<sup>3</sup>/bar</th><th align="center" valign="middle" >C<sub>ma</sub> in m<sup>2</sup>/kg</th></tr></thead><tr><td align="center" valign="middle" >granite</td><td align="center" valign="middle" >42 &#215; 10<sup>−7</sup></td><td align="center" valign="middle" >4.116 &#215; 10<sup>−10</sup></td></tr><tr><td align="center" valign="middle" >Sandstone</td><td align="center" valign="middle" >31 &#215; 10<sup>−7</sup></td><td align="center" valign="middle" >3.038 &#215; 10<sup>−10</sup></td></tr><tr><td align="center" valign="middle" >Shale</td><td align="center" valign="middle" >80 &#215; 10<sup>−7</sup></td><td align="center" valign="middle" >7.82 &#215; 10<sup>−10</sup></td></tr></tbody></table></table-wrap><p>&#173; t<sub>is</sub> time elapsed from the start of pumping until it stops;</p><p>&#173; t’ time counted after this stop;</p><p>&#173; s’ continuation of the recording of the drawdown in the control piezometer;</p><p>&#173; Q pumping flow rate value that created the initial drawdown.</p><p>The mathematical reasoning for determining the effects of stopping pumping is based on the principle of superposition. A “fictitious continuation” of the pumping at the initial flow rate Q is combined with a “fictitious injection” of water at the same flow rate, i.e. pumping at the flow rate −Q. The drawdown is measured in the observation piezometer. Jacob then becomes:</p><p>s ′ = 2.3 4 π ⋅ Q T ⋅ log ( 2.25 T ⋅ ( t a + t ′ ) r 2 S ) − 2.3 4 π ⋅ Q T ⋅ log ( 2.25 T ⋅ t ′ r 2 S ) (7)</p><p>s ′ = 2.3 4 π ⋅ Q T ⋅ log ( t a + t ′ t ′ ) (8)</p><p>The calculation is done on a semi-logarithmic graph. The experimental curve of the test is drawn with t a + t ′ t ′ (in fact log ( t a + t ′ t ′ ) ) in abscissa and ordinate (Assemian, 2014). Normally, all points tend to line up on a straight line. The slope of the line is obtained by doing:</p><p>d s d log ( t a + t ′ t ′ ) = Δ s ′ = 2.3 4 π ⋅ Q T (9)</p><p>with Δ s ′ slope. That is, the drawdown corresponding to one (1) logarithmic cycle.</p><p>We then obtain</p><p>T = 2.3 4 π ⋅ Q Δ s ′ (10)</p><p>The storage coefficient (S) is defined by Equation (11) (Thiery et al., 1982; Suski, 2006; Fouch&#233;, 2013):</p><p>S = ρ w ⋅ g ⋅ ( ϕ F C e + C m a ) &#215; e (11)</p><p>ϕ F : Porosity of fractures and connected pores;</p><p>C<sub>e</sub>: Water compressibility coefficient;</p><p>C<sub>ma</sub>: Coefficient of compressibility of the matrix (deduced starting from <xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>);</p><p>e: the thickness of the aquifer (m);</p><p>ρ w = density of water, 1000 kg/m<sup>3</sup>;</p><p>g = gravitational acceleration ≈ 10 m/s<sup>2</sup>.</p><p>Permeability (or hydraulic conductivity) is the ability of a reservoir to allow water to pass through under the effect of a hydraulic gradient. It expresses the resistance of the environment to the flow of water passing through it. It is determined from the transmissivity formula (Savan&#233; et al., 1997; Assemian, 2014).</p><p>T = K ⋅ e (12)</p><p>With “K” the Hydraulic conductivity in m/s</p><p>“e” the thickness of the aquifer in m.</p><p>“K” then becomes:</p><p>K = T e (13)</p><p>The thickness of the fractured zone is assimilated to the length of the strainer if the borehole has a single water inlet. If the borehole has several water inlets, the thickness of the fractured zone is determined by making the difference between the first water inlet and the last (Kouassi et al., 2013). The permeability values are classified according to the table of Castany (1982).</p></sec><sec id="s2_2_6"><title>2.2.6. Determination of the Initial Piezometry of the Marahou&#233; Watershed</title><p>This choice is justified by the fact that it was during this year that there was a maximum of boreholes (20 boreholes) made in the middle of the dry season (<xref ref-type="fig" rid="fig4">Figure 4</xref>). In reality, during the dry season, the groundwater that flows through</p><p>the pores of the formation to the lower areas is not replaced by infiltrating rainwater. This promotes a better appreciation of the direction of groundwater flow in the basin (Soro, 2017). Piezometric levels are obtained from manually measured water depths according to Equation (14) (Yao et al., 2015)</p><p>N p = Z T N − N m e s u r e + H d (14)</p><p>With Np: the piezometric level (m) referring to the edge of the casing,</p><p>Z<sub>TN</sub>: the altitude (m) of the natural terrain at the location of the structure,</p><p>N<sub>mesure</sub>: the depth (m) of the water surface measured with the probe and</p><p>H<sub>d</sub>: the height (m) of the casing above ground.</p></sec><sec id="s2_2_7"><title>2.2.7. Establishment of the Hydrological Balance</title><p>NASA Power meteorological data from 1987 to 2017 were used to establish the water balance of the Marahou&#233; watershed. These data offer an advantage from the point of view of representativeness; spatiality and punctuality of measurements (Boudevillain, 2003). However, they require validation before any use. For this purpose, data from satellite measurement points close to the Bouafl&#233; rainfall stations; Mankono; S&#233;gu&#233;la and Boundiali were used. These data were compared to the terrestrial data of the cities mentioned above for the period from 1986 to 2000. Indeed, Laurent et al. (1998) proposed different statistical criteria to validate the quality of satellite data compared to field data. For a reference v i and estimation data set e i comprising n values with i = (1, n) whose mean is defined by v &#175; ( e &#175; ) and standard deviation by σ i ( σ e ) , the proposed criteria are the correlation coefficient, the bias, the RMSE (Root Mean Square Error) and the Nash index (<xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref>). Also, the index of Nash measures a relative distance between the estimate and the reference. If i = 1, the estimate is perfect and if i = 0, the estimate equals the mean of the reference values (Arvor et al. 2008).</p><p>After validation, potential evapotranspiration (ETP) and the real evapotranspiration (ETR) were determined using Thornthwaite’s method (Thornthwaite, 1954; Yao et al., 2015). The advantage of this method lies in the fact that it only asks for monthly temperatures and rainfall (N’Guessan Kouame et al., 2014). In this study, the reserve easily usable by plants (RFU) differs from north to south of the Marahou&#233; basin. It is equal to a fraction of the RU (useful reserve) which is estimated by the development of the rooting of the vegetation (Bi&#233;mi, 1992).</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref></label><caption><title> Statistical test for validation of satellite data</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Statistical criterion</th><th align="center" valign="middle" >Equation</th></tr></thead><tr><td align="center" valign="middle" >Correlation coefficient (R)</td><td align="center" valign="middle" >R = ∑ i = 1 n ( v i − v &#175; ) ( e i − e &#175; ) n σ i σ e</td></tr><tr><td align="center" valign="middle" >Bias (B)</td><td align="center" valign="middle" >B = e &#175; − v &#175;</td></tr><tr><td align="center" valign="middle" >RMSE (Root Mean Square Error)</td><td align="center" valign="middle" >R M S E = 1 n ∑ i = 1 n ( e i − v i ) 2</td></tr><tr><td align="center" valign="middle" >Nash index (I)</td><td align="center" valign="middle" >I = 1 − R M S E 2 σ v 2</td></tr></tbody></table></table-wrap><p>Since the Marahou&#233; watershed is densely vegetated with strongly rooted soil in general, the RFU was determined according to Equation (15) (Combres et al., 1999; Khechana et al., 2019).</p><p>R F U = 2 / 3 R U (15)</p><p>The work of Sodexam (2012) specifies the values of the RU according to the climatic zones. Thereby:</p><p>&#173; In the northern climatic zone, the RU = 30 mm (i.e. RFU = 20 mm), for the regions of Korhogo and Odienn&#233;;</p><p>&#173; In the central and southern interior climatic zone, the RU = 60 mm (i.e. RFU = 40 mm), for the regions of bondoukou, Bouak&#233;, Daloa, Man, Dimbokro, Yamoussoukro and Gagnoa;</p><p>&#173; In the South-coastal climatic zone, the RU = 100 mm (i.e. RFU = 66.67 mm), for the regions of Adiaqu&#233;, Abidjan, Sassandra, San-pedro and Tabou.</p><p>Therefore, from the area of S&#233;gu&#233;la and Mankono to Boundiali, we considered the RFU = 20 mm and from Bouafl&#233; to Zu&#233;noula the RFU = 40 mm. The month of November, which corresponds to the end of the rainy season in the basin, is taken as the starting point for the calculations.</p><p>The runoff (R) was determined by the empirical Tix&#233;ront-Berkaloff formula (Equation (16)) which uses the rainfall and the potential evapotranspiration calculated by the method of Thornthwaite (N’Guessan Kouame et al., 2014).</p><p>R = P 3 3 E T P 2 (16)</p><p>R: runoff in mm;</p><p>P: average annual precipitation in mm;</p><p>ETP: average annual potential evapotranspiration calculated by the Thornthwaite method in mm.</p><p>Finally, the infiltration was determined from Equation (17) (Kouassi et al., 2007; N’Guessan Kouame et al., 2014).</p><p>I = P − ( E T P + R ) + Δ S (17)</p><p>With P: the depth of rain in millimeters (mm)</p><p>ETP: potential evapotranspiration (mm)</p><p>R: the stream of water (mm)</p><p>I: infiltration</p><p>∆S: change in water stock</p><p>In this study, the variations in water stock (∆S) are assumed to be zero. Because, on the scale of the annual hydrological cycle, the stock variations cancel each other out over a large basin (Mah&#233; et al., 2005).</p></sec></sec></sec><sec id="s3"><title>3. Results and Discussions</title><sec id="s3_1"><title>3.1. Conceptual Model of the Weathering Profile</title><sec id="s3_1_1"><title>3.1.1. Digital Terrain Model of the Marahou&#233; Watershed</title><p>Few things stand out from the landscape of the Marahou&#233; watershed. One notices, in fact, a uniqueness and a flatness of the whole basin. It presents only small formations of hills by place not exceeding in general the 400 m of altitude. Indeed, the altitude increases slightly from south to north from 147 to 807 m. The highest areas are above the 9<sup>th</sup> parallel. That is to say the entire area located north of the town of Morondo (<xref ref-type="fig" rid="fig5">Figure 5</xref>). Tiered plateaus with a flat surface (horizontal or sub-horizontal) are common in some localities. According to Bi&#233;mi (1992), this morphology promotes the formation of ponds, the infiltration of water and therefore the eventual recharge of the water tables.</p></sec><sec id="s3_1_2"><title>3.1.2. Alterite Thickness</title><p>The roof of the basement has a slighthly uneven morphology in the Marahou&#233; watershed. The dip of the basement is North-West, South-East and the altitudes are between 140 and 390 m (<xref ref-type="fig" rid="fig6">Figure 6</xref>). However, this dip of the basement roof does not seem to influence the distribution of the thickness of the alterites. It varies from place to place within the same area. Indeed, the analysis of the map of the thickness of the alterites obtained (<xref ref-type="fig" rid="fig7">Figure 7</xref>), shows that in the watershed of Marahou&#233;, the thickness of the alterites varies between 0 and 80 m with an average of 26.72 m according to card statistics. We can therefore say that the average thickness of the alterites is high in the basin according to the Inter-State Hydraulic Committee (CIEH, 1978). Most of the thicknesses are between 0 and 40 m. The white areas correspond to the uninformed sectors of the map. This map also shows that the alterite layer is not continuous.</p><p>The fact that most of the thicknesses are between 0 and 40 m represents a significant advantage for the good productivity of the boreholes. In fact, studies have shown that beyond 60 m of alterite thickness, the productivity of boreholes becomes increasingly low in the basement zone (Koudou et al., 2016; Ble et al., 2015). According to Soro et al. (2010), hydraulically active fractures tend to close with depth. They can become clogged if the arenas that cover them are clay.</p></sec><sec id="s3_1_3"><title>3.1.3. Evaluation of the Linear Flow According to the Depth of the Borehole under the Base of the Unconsolidated Alterites</title><p><xref ref-type="fig" rid="fig8">Figure 8</xref> presents the results of the analysis of linear flows as a function of the depth of the boreholes below the base of the unconsolidated alterites (value denoted P'). Analysis of this figure shows that the linear flows (Q/P') tend to decrease with depth. This is linked to the decrease in the number of cracks at depth. These results are consistent with the knowledge of basement hydrogeologists who have shown that the fissured horizon, located under the alterites, is the medium providing the best permeability of the subsoil and therefore the best instantaneous flows (Mougin et al., 2015). However, depending on the geological and hydrogeological environment, there is a depth beyond which the chances of finding an aquifer horizon decrease, particularly within altered basement rocks, due to the decrease in frequency and then the disappearance of permeable cracks (Dewandel et al., 2006).</p></sec><sec id="s3_1_4"><title>3.1.4. Thickness of the Cracked Medium Producing the Best Flow Rates</title><p>After analysis of the 300 boreholes in the Marahouh&#233; watershed (<xref ref-type="fig" rid="fig9">Figure 9</xref>), it appears that the thickness of the useful fissured horizon is 45 m with 8.45 m<sup>3</sup>/h (0.187807556 m<sup>3</sup>/h/m &#215; 45 m) as the flow rate of this fissured horizon useful.</p><p>This useful thickness is comparable to that obtained in Brittany (44 m), during the work at Mougin et al. (2015).</p></sec><sec id="s3_1_5"><title>3.1.5. Spatial Distribution of the Thickness of the Useful Fissured Horizon over the Basin</title><p>After statistical analysis of the boreholes carried out on these two geological formations (granites and shales), it appears that the thickness of the useful fissured horizon is 46.5 m, of which 9.42 m<sup>3</sup>/h as flow at the level of the granites and 43 m with 6.42 m<sup>3</sup>/h as useful flow associated with the level of the shales. This gives a useful, fairly small fissured horizon thickness range of between 43 and 47 m (<xref ref-type="fig" rid="fig1">Figure 1</xref>0). Therefore, beyond these values, it is not useful to drill because of the high cost and the low throughput gain. This suggests that the “useful thickness” (at least as defined with the proposed method) is quite equivalent for the different lithologies in the Marahou&#233; watershed. This range of useful thickness is greater than that obtained at the level of 27 geological formations in Burkina Faso, which varies between 25 m and 37 m (Courtois et al., 2008). On the other hand, it is lower than that obtained in Brittany (out of 83 geological formations) which varies from 19 to 65.7 m (Mougin et al., 2015).</p></sec><sec id="s3_1_6"><title>3.1.6. Weathering Profile Layer Model</title><p>The different stratigraphic units were established from observations made during drilling. The longitudinal and transverse sections of the Marahou&#233; watershed show that the different lithological horizons are not homogeneous throughout the basin (<xref ref-type="fig" rid="fig1">Figure 1</xref>1 and <xref ref-type="fig" rid="fig1">Figure 1</xref>2). There is also a strong accumulation of alterites in the valleys, while these tend to disappear on the slopes. The fissured horizon remains substantially unchanged over the entire basin and outcrops in places.</p></sec></sec><sec id="s3_2"><title>3.2. Hydrodynamic Parameters of the Marahou&#233; Watershed</title><p>The porosities determined at the Marahou&#233; watershed are relatively low. They vary from 0.16% to 5.37%, the maximum of which is reached in the village of S&#233;itinfla near Bouafl&#233;. The maximum value of the porosity obtained in the basin</p><p>is higher than that encountered in the literature (2% at the level of fissured granites and schists) (Fouch&#233;, 2013). However, it demonstrates that certain areas of the basin are sufficiently fractured and therefore capable of being assimilated to a homogeneous medium (Thiery et al., 1982).</p><p>The majority of transmissivities are moderately high (59.62%). In addition, 78.85% of the transmissivity belong to the middle and strong classes. The highest transmissivity (3.3110E−03 m<sup>2</sup>/s) in the Marahou&#233; basin was obtained in the village of Drikouafla 2 in the sub-prefecture of Zuenoula. However, the lowest transmissivity (2.3242E−06 m<sup>2</sup>/s) was recorded at Gb&#233;nan in the S&#233;gu&#233;la sub-prefecture. We deduce from this analysis that the transmissivity of at the level of the Marahou&#233; watershed is clearly good (CIEH, 1978).</p><p>The permeabilities obtained vary from 6.640 &#215; 10<sup>−08</sup> to 2.255 &#215; 10<sup>−04</sup> m/s with an average of 8.95493 &#215; 10<sup>−06</sup> m/s. This means that the permeability at the level of the marahou&#233; watershed is of poor quality. Thus, the aquifers crossed by the various boreholes are semi-permeable types (Castany, 1982). Finally, the determined storage coefficients vary between 4.51 &#215; 10<sup>−05</sup> at 2.93 &#215; 10<sup>−03</sup>. The maximum was obtained at Manabri in the Kani sub-prefecture. Indeed, the minimum storage coefficient is less than 10<sup>−02</sup>, which means that the aquifers crossed by the various boreholes are confined or semi-confined (Soro, 2017).</p></sec><sec id="s3_3"><title>3.3. Piezometric Analysis</title><p>The piezometric map (<xref ref-type="fig" rid="fig1">Figure 1</xref>3) gives an overview of groundwater flow dynamics from fissured aquifers in the Marahou&#233; watershed. In general, all groundwater flows towards the basin outlet. That is to say the North-West – South-East direction. There are areas of possible recharge of the basin’s aquifers in places. These zones are factors for good borehole productivity because confined and semi-confined aquifer systems usually have specific recharge zones where the aquifer outcrops (Soro, 2017).</p></sec><sec id="s3_4"><title>3.4. Validation of Satellite Data</title><p>There is a very strong correlation between terrestrial data and satellite data (<xref ref-type="fig" rid="fig1">Figure 1</xref>4 and <xref ref-type="table" rid="table3"><xref ref-type="table" rid="table">Table </xref>3</xref>). This correlation varies from 0.94 to 0.98. The Nash index also varies from 0.64 to 0.85. These values indicate that the NASA-power estimates are good. Therefore, these satellite data are likely to be used for the calculation of the hydrological balance. These good correlations are in line with the results of several authors in West Africa and Brazil (Guillo, 1996; Arvor et al., 2008; Gascon, 2016). These authors demonstrated that there is good spatial coherence of interannual rainfall at monthly and seasonal time steps.</p></sec><sec id="s3_5"><title>3.5. Hydrological Balance of the Marahoue Watershed</title><p>Marahou&#233; watershed corresponds to the zone where the infiltration is the highest. The infiltration rate in this area during the period 1986 to 2017 varies between 250 and 460 mm (<xref ref-type="fig" rid="fig1">Figure 1</xref>5). The Bouafl&#233; sector, located at the outlet of the basin, recorded the lowest amount of infiltrated water (250 mm on average, or 19.92% of the amount of precipitated water). This low infiltration obtained at Bouafl&#233; is greater than that obtained at Yamoussokro from 1975 to 2001 (70 mm or 6.15% of the precipitated water layer) (N’Guessan Kouame et al., 2014). These results are substantially equal to those of the work of Iri&#233; (2019).</p></sec><sec id="s3_6"><title>3.6. 3D Model of the Weathering Profile</title><p>In sum, the conceptual model of the weathering profile takes into account three stratigraphic units with different properties (<xref ref-type="fig" rid="fig1">Figure 1</xref>6). The first layer corresponds</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3"><xref ref-type="table" rid="table">Table </xref>3</xref></label><caption><title> Validation of satellite data</title></caption><table><tbody><thead><tr><th align="center" valign="middle" ></th><th align="center" valign="middle" >MUFFLE</th><th align="center" valign="middle" >BOUNDIALI</th><th align="center" valign="middle" >MANKONO</th><th align="center" valign="middle" >SEGUELA</th></tr></thead><tr><td align="center" valign="middle" >R</td><td align="center" valign="middle" >0.96</td><td align="center" valign="middle" >0.94</td><td align="center" valign="middle" >0.98</td><td align="center" valign="middle" >0.97</td></tr><tr><td align="center" valign="middle" >RMSE</td><td align="center" valign="middle" >30.40</td><td align="center" valign="middle" >43.23</td><td align="center" valign="middle" >31.79</td><td align="center" valign="middle" >29.16</td></tr><tr><td align="center" valign="middle" >Deviation</td><td align="center" valign="middle" >50.56</td><td align="center" valign="middle" >111.87</td><td align="center" valign="middle" >61.98</td><td align="center" valign="middle" >63.65</td></tr><tr><td align="center" valign="middle" >Nash</td><td align="center" valign="middle" >0.64</td><td align="center" valign="middle" >0.85</td><td align="center" valign="middle" >0.74</td><td align="center" valign="middle" >0.79</td></tr></tbody></table></table-wrap><p>to alterites. It varies from 0 to 80 m. It can be noted that this thickness is not specific to a geographical area of the basin. Indeed, due to their clay content, alterites are characterized by low water permeability (2.4 &#215; 10<sup>−7</sup> m/s on average at basin level). Nevertheless, they have significant storage capacities. Their piezometric levels drop significantly in the dry season and rise again in the rainy season (Bi&#233;mi, 1992). This causes wells to dry up during dry seasons. The second layer is that of the fissured horizon. Its thickness varies from 43 to 47 m according to the geological layers with an average equal to 45 m. Beyond these values, the chance of obtaining hydraulically active fractures decreases. In addition, this part encloses the hydraulically active fissures of the basin. The frequency of these cracks decreases steadily from top to bottom (Yao, 2011). According to Dewandel et al. (2006), most of the permeability of basement aquifers comes from the lower part of the weathering profile (the stratiform fissured horizon) which is located under the unconsolidated alterites (when these have not been eroded). The last layer corresponds to the sound base. This is unweathered bedrock. Apart from fractures of tectonic origin that may exist locally, this bedrock offers only a very low underground water storage capacity (Lachassagne et al., 2005). Given its infinite nature, it was limited to an altitude of 80 m during the design of the model.</p></sec></sec><sec id="s4"><title>4. Conclusion</title><p>The implementation of the conceptual model of groundwater flows in the Marahou&#233; watershed has made it possible to characterize the weathering profile. This profile consists of three stratigraphic layers (alterites, fissured horizon and sound basement). The thickness of the alterites varies from 0 to 80 m. That of the useful fissured horizon is between 43 and 47 m. Then, the analysis of the hydrodynamic parameters made it possible to know that the different aquifers are confined or semi-confined. Groundwater generally flows towards the outlet of the basin, i.e. in the North-West - South-East direction. This work has contributed to the improvement of knowledge of fissured aquifers by proposing a multidisciplinary method, adaptable to any analogous system, and offering valuable assistance for a reasoned management of groundwater resources. However, further research is needed to best facilitate the exploitation of this resource. Thus, in the future, it will be necessary to carry out a steady-state simulation to better understand the direction of groundwater flow. Then perform a transient simulation to determine the influence of climate variability and abstraction on flows, the relationship between aquifers and surface water. In addition, set up a global management model for groundwater resources for its quantitative and qualitative sustainability at the level of the marahou&#233; watershed.</p></sec><sec id="s5"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s6"><title>Cite this paper</title><p>Bouatrin, K. D., Kouame, I. K., Douagui, A. G., Kouassi, K. A., &amp; Goula, B. T. A. (2022). Conceptual Model of Aquifers in the Bedrock Zone of the Marahou&#233; Watershed (Centre-West of Ivory Coast). Journal of Geoscience and Environment Protection, 10, 229-256. https://doi.org/10.4236/gep.2022.107014</p></sec><sec id="s7"><title>Annex</title><p><xref ref-type="table" rid="table">Table </xref>of symbols and their meanings</p></sec></body><back><ref-list><title>References</title><ref id="scirp.118753-ref1"><label>1</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Akpo</surname><given-names> K. S.</given-names></name>,<name name-style="western"><surname> Coulibaly</surname><given-names> L. S.</given-names></name>,<name name-style="western"><surname> Coulibaly</surname><given-names> L.</given-names></name>,<name name-style="western"><surname> &amp; Savane</surname><given-names> I. </given-names></name>,<etal>et al</etal>. (<year>2016</year>)<article-title>. 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