Groundwater modelling with limited data sets: the Chari–Logone area (Lake Chad Basin, Chad)

Abstract

One of the most important issues for water resource management is developing strategies for groundwater modelling that are adaptable to data scarcity. These strategies are particularly important in arid and semi-arid areas where access to data is poor and data collection is difficult, such as the Lake Chad Basin in Africa. In the present study, we establish a numerical groundwater flow model and evaluate the effects of dry and wet periods on groundwater recharge in the Chari-Logone area (96 000 km 2 ) of the Lake Chad Basin. Boundary conditions, flow direction, sources, and sinks for the Chari-Logone local model were obtained by revising and remodelling the Lake Chad Basin regional hydrogeological model (508 400 km 2 ) developed by the BRGM (Bureau de Recherches Géologiques et Minières) in the 1990s. The simulated aquifer water level showed good agreement with observed levels. Aquifer recharge is primarily determined by river-aquifer interactions and mostly occurs in the southern section of the study area. In wet years, groundwater recharge also occurs in the N'Djamena area. The approach we adopted provided relevant results and was useful as an initial step in more detailed modelling of the area. It also proved to be a useful method for groundwater modelling in large semi-arid and arid regions where available data are scarce.

Groundwater and Surface Water Interaction at the Regional-scale – A Review with Focus on Regional Integrated Models

“…Note the almost negligible extend of alluvial formations observations are usually focused in areas of particular interest, such as densely populated or intensely cultivated areas. Consequently, data are patchy in space, time, and with regard to the number and choice of observed parameters (Candela et al 2014). An additional issue is the heterogeneity of the data, which in many cases has been collected by different agencies, with different objectives, and over different periods and is consequently very inconsistent.…”

“…An additional issue is the heterogeneity of the data, which in many cases has been collected by different agencies, with different objectives, and over different periods and is consequently very inconsistent. Many authors define the relative scarcity of data as the main challenge for regional scale work (Candela et al 2014;Refsgaard et al 2010;. Looking at long time scales, it is often very difficult to judge whether data have been influenced by human activity (e.g.…”

Modelling the Influence of Groundwater Abstractions on the Water Level of Lake Naivasha, Kenya Under Data-Scarce Conditions

“…Second, through our methodology we aim to illustrate a possible strategy of going about modelling data-scarce regions. This study therefore contributes to contemporary discussions (as raised by e.g., Johnston and Smakhtin (2014) and Candela et al (2013)) concerning dealing with and reporting about data-scarce modelling efforts in water management.…”

“…Concerted data collection efforts usually lack in developing countries, especially when it comes to groundwater systems. Recent groundwater modelling studies with a focus on semi-arid basins encountered difficulties in estimating recharge (Candela et al 2013;Rödiger et al 2014), abstractions (Le Page et al 2012) and the effect of faults and fractures on hydrogeologically complex flow systems (Bense et al 2013) or in defining a plausible, appropriate conceptual model of the aquifer system at hand (Ayenew and Tilahun 2008).…”

“…Subsequently applied mainstream methods of dealing with model uncertaintysuch as Monte Carlo analyses or functional zoning (Li et al 2015;Zekri et al 2015) -may prove too sophisticated for data limited environments. Other options in modelling groundwater that are adaptable to data-scarcity need to be investigated too (Candela et al 2013).…”