Statistical and Geostatistical Analysis of Lineaments Network Mapped in The Precambrian Basement: Case of Divo-Oume Region (Southern Cote d’Ivoire)

Abstract

The high populated and dense agricultural region of Divo-Oumé, in the southern part of Côte d’Ivoire, periodically faces drinking water scarcity and lack of reliable water resources management tools. This study presents a statistical and geostatistical analysis of lineaments network, conducted in Divo-Oumé region, in order to contribute to a better understanding of local Precambrian basement aquifer. Fractures network has been characterized through the analysis of the attributes of lineaments derived from conjoint Radarsat and Asar images. The average length of lineaments is 2.15 km and around this value, high dispersion is observed (CV = 133%). A total of 3,559 cross-points (CP) are identified and most of spacing values (84.3%) are less than 2 km. The statistical distribution of lineaments lengths, cross-points and spacing follow power law, highlighting the fractal nature of fractures network. Also, the variation coefficient (CV = 51%) of lineaments spacing and the characteristic exponent of power law in the case of lineament lengths (α = 2.55) would indicate respectively, fracturing process is intense in the region and fracture network reach a mature stage of development. The geostatistical analysis showed that the variograms of lineaments cumulative lengths (CL) and cross-points (CP) are structured. These variograms have the same behavior, reflecting the intrinsic character of CL and CP. However, the correlation ranges of CL are higher than those of CP. These results could be useful for understanding groundwater flow and the establishment of water resource management tools.

Fracture aquifers identification in the Zou basin (West Africa) using remote sensing and GIS

“…The spatial distribution across the basin depicts a repetitive pattern of longer fractures being broken in smaller one which is one of the reasons why the PALSAR fracture map count is higher. Whatever the visible (0.8 to 15.8 km), infrared (0.3 to 21.2 km) or PALSAR fracture map (0.15 to 11.2 km) is, the interval of length is in consistency with past studies (Tagnon & al., 2016;Jourda, 2005;Baka, 2012;Lasm & al., 2014;Koudou & al., 2013;Koudou & al., 2014;Oussou & al., 2019;and Akokponhoué & al., 2019). For the cumulative length adjustment, the calculated for the visible and PALSAR fracture maps (61.46 and 37.07) are greater than the theoretical revealing that there is a significant relationship between the cumulative length and class frequency.…”

“…The cumulative length (CL) of each fracture map is adjusted to the power law, which has been used in the past works (Jourda, 2005, Koudou & al., 2013and Tagnon & al., 2016. Short fracture lengths (less than 1.28 km) are affected by the problem of ''Truncation '' effect and the longer one (greater than 13.04 km) by ''censoring '' effects (Ackermann &Zazoun, 2008).…”

“…This type of analysis is useful to find out major fracture populated area for high flow aquifers identification in hard rocks areas (Tran, 2004). A cross-point (CP) is the point of intersection between fractures where groundwater flow occurrence might be very interesting for water supply (Tagnon et al, 2016). The open source software QGIS tool '' Line intersection '' is used to generate the cross-points.…”

“…Aquifers are geological formations capable of bearing significant underground water flow depending on their geometric and hydrodynamic properties. The basement aquifers from the surface to the bottom consist of weathered layer and a bottom fractured layer that concentrates most of the groundwater (Biemi, 1992;Savané, 1997;al., 2004 andal., 2011 cited by Tagnon & al., 2016). For the management and monitoring of these resources, Remote sensing data offer an appropriate spectral and spatial resolution for better hydrogeological surveys (Bruning, & al., 2009).…”

“…Lineaments extraction through Remote sensing technics has been recognized as an efficient way toward hydrogeological knowledge improvement because of the possibility to exhibit geological fractures that shelter groundwater (Das, 1990) and even more structural elements A c c e p t e d M a n u s c r i p t enhancement from satellite images lead to a better geological accidents mapping (Youan Ta & al., 2008). Therefore, in bedrock areas, for example, different type of satellite images and aerial photographs have been used for multiple purposes such as groundwater potential evaluation and fractures network identification (Boukari, 1982;Kouamé & al., 2009;Yao & al., 2014;Ndong & al., 2014;Assatse & al., 2016;Tagnon & al., 2016, Oussou & al., 2019. Furthermore, Remote sensing satellite observations such as Landsat 7 ETM+ have been successfully used in the eastern Tauride belt (SE Turkey) to isolate hydrothermally altered rocks by applying the Crosta techniques (Aydal et al, 2007).…”