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Journal of Arid Land
Journal of Arid Land  2021, Vol. 13 Issue (11): 1122-1141    DOI: 10.1007/s40333-021-0092-3
Research article     
Using statistical models and GIS to delimit the groundwater recharge potential areas and to estimate the infiltration rate: A case study of Nadhour-Sisseb-El Alem Basin, Tunisia
Ali SOUEI1,2,*(), Taher ZOUAGHI3
1Georesources Laboratory, Water Researches and Technologies Center (WRTC) of Borj Cedria, Soliman 8020, Tunisia
2Department of Geology, FST, University of Tunis El Manar, Tunis C P 2092, Tunisia
3Department of Geo-Exploration Techniques, Faculty of Earth Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Abstract  

The water resources of the Nadhour-Sisseb-El Alem Basin in Tunisia exhibit semi-arid and arid climatic conditions. This induces an excessive pumping of groundwater, which creates drops in water level ranging about 1-2 m/a. Indeed, these unfavorable conditions require interventions to rationalize integrated management in decision making. The aim of this study is to determine a water recharge index (WRI), delineate the potential groundwater recharge area and estimate the potential groundwater recharge rate based on the integration of statistical models resulted from remote sensing imagery, GIS digital data (e.g., lithology, soil, runoff), measured artificial recharge data, fuzzy set theory and multi-criteria decision making (MCDM) using the analytical hierarchy process (AHP). Eight factors affecting potential groundwater recharge were determined, namely lithology, soil, slope, topography, land cover/use, runoff, drainage and lineaments. The WRI is between 1.2 and 3.1, which is classified into five classes as poor, weak, moderate, good and very good sites of potential groundwater recharge area. The very good and good classes occupied respectively 27% and 44% of the study area. The potential groundwater recharge rate was 43% of total precipitation. According to the results of the study, river beds are favorable sites for groundwater recharge.

Key words： potential recharge      remote sensing      statistical models      MCDM      Nadhour-Sisseb-El Alem Basin     
Received: 20 January 2021      Published: 10 November 2021
Corresponding Authors: Ali SOUEI (E-mail: soueiali2014@gmail.com)
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Ali SOUEI, Taher ZOUAGHI. Using statistical models and GIS to delimit the groundwater recharge potential areas and to estimate the infiltration rate: A case study of Nadhour-Sisseb-El Alem Basin, Tunisia. Journal of Arid Land, 2021, 13(11): 1122-1141.

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http://jal.xjegi.com/10.1007/s40333-021-0092-3     OR     http://jal.xjegi.com/Y2021/V13/I11/1122

Fig. 1 Location (a) and Landsat image (resolution 30 m) (b) of the study area, Nadhour-Sisseb-El Alem Basin, Tunisia
Fig. 2 Hydrogeologic cross section of the aquifer system in Nadhour-Sisseb-El Alem Basin modified from Souei et al. (2018). S, south; N, north.
Fig. 3 Processing chain of making potential zone map for groundwater by using GIS and remote sensing SRTM (shuttle radar topography mission)
Fig. 4 Major and minor relationship among factors influencing the potential groundwater recharge
Factor Calculation process RW
Lithology (Li) 4×1+1×0.5 4.5
Soil (S) 4×1+1×0.5 4.5
Slope (Sl) 3×1+1×0.5 3.5
Topography (T) 3×1+1×0.5 3.5
Land cover/land use (LU/C) 2×1+3×0.5 3.5
Drainage density (Dd) 2×1+2×0.5 3.0
Lineaments density (Ld) 1×1+3×0.5 2.5
Runoff (Ru) 0×1+3×0.5 1.5
Table 1 Proposed relative weight (RW) obtained from the relationships among factors influencing the potential groundwater recharge
Factor Li S Sl T LU/C Dd Ld Ru W
Li 1.0 0.17
S 4.5 1.0 0.17
Sl 3.5 3.5 1.0 0.13
T 3.5 3.5 3.5 1.0 0.13
LU/C 3.5 3.5 3.5 3.5 1.0 0.13
Dd 3.0 3.0 3.0 3.0 3.0 1.0 0.11
Ld 2.5 2.5 2.5 2.5 2.5 2.5 1.0 0.10
Ru 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.0 0.06
Table 2 Comparison matrix obtained for eight factors for the analytic hierarchy process (AHP)
Factor Classes PR RW AR W Effective rate (ER)
Li Marls and sandy marls 0.15 4.5 0.68 0.17 0.11
Limestone and dolomites 0.43 1.94 0.33
Sand and sandstone 0.63 2.84 0.48
Alluviums and gravelly sand 1.00 4.50 0.76
S Building 0.07 4.5 0.32 0.17 0.05
Hydromorphic and allomorphic soils 0.15 0.68 0.11
Poor soil 0.52 2.34 0.40
Rendzine soil 0.83 3.74 0.63
Mineral soil and wadi beds 1.00 4.50 0.76
Sl 0.0-3.4 1.00 3.5 3.50 0.13 0.46
3.4-9.4 0.78 2.73 0.36
9.4-18.0 0.58 2.03 0.27
18.0-44.0 0.04 0.14 0.02
T 400-500 0.20 3.5 0.70 0,13 0.09
300-400 0.40 1.40 0.18
200-300 0.60 2.10 0.28
100-200 0.80 2.80 0.37
0-100 1.00 3.50 0.46
LU/C Building 0.06 3.5 0.21 0.13 0.03
Forest 0.24 0.84 0.11
Agricultural and waste land 0.65 2.28 0.30
Surface water body 1.00 3.50 0.46
Dd 0.00-0.62 1.00 3.0 3.00 0.11 0.34
0.62-1.25 0.50 1.50 0.17
1.25-1.87 0.20 0.60 0.07
1.87-2.50 0.02 0.06 0.01
Ld 0-10 0.22 2.5 0.60 0.10 0.06
10-30 0.66 1.65 0.16
30-45 1.00 2.50 0.24
Ru Building 0.07 1.5 0.11 0.06 0.01
Marls and clay 0.19 0.29 0.02
Limestone and dolomites with fractures 0.52 0.78 0.04
Sand and sandstone 0.65 0.98 0.06
Alluviums 0.81 1.22 0.07
Wadi beds 1.00 1.50 0.08
Table 3 Classes and ratings for determining potential groundwater recharge zones
Fig. 5 Lithology of the study area
Fig. 6 Soil of the study area
Fig. 7 Slope gradient map of the study area
Fig. 8 Topography of the study area
Fig. 9 Land cover/use of the study area
Fig. 10 Drainage density of the study area
Fig. 11 Lineament density of the study area
Fig. 12 Runoff of the study area
n 5 6 7 8 9 10 11 12
RI 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.54
Table 4 Arbitrary index based on the number of criteria (Saaty, 1980)
Factor Theoretical weight Effective weight
Value Proportion (%) Mean (%) Min (%) Max (%) SD (%)
Li 4.5 17 22 7 45 17
S 4.5 17 20 3 39 16
Sl 3.5 13 14 1 41 17
T 3.5 13 14 7 33 11
LU/C 3.5 13 12 3 51 22
Dd 3.0 11 8 1 56 24
Ld 2.5 9 8 12 53 21
Ru 1.5 6 2 2 31 11
Table 5 Single parameter sensitivity analysis
Fig. 13 Groundwater recharge potential areas. WRI, water recharge index.
Period 4 Feb-17 Aug 2004 11 Feb-4 Aug 2005 25 Feb-15 Aug 2006
Station S1 S2 S3 S4 S1 S2 S3 S4 S1 S2 S3 S4
NM 51 45 28 - 39 38 38 25 32 31 31 7
VM (×106 m3) 1.615 0.740 0.105 - 2.542 2.023 1.296 0.347 1.675 1.292 0.641 0.081
Reach - R1 R2 R3 - R1 R2 R3 - R1 R2 R3
VL (×106 m3) - 0.875 0.635 - - 0.519 0.727 0.949 - 0.383 0.651 0.560
PVL (%) - 54 86 - - 20 36 73 - 23 50 87
Table 6 Details of the three artificial recharge operations
Period Submersed bed area (×103 m2) Artificial recharge (×106 m3) PE
(mm) (×106 m3) (%)
Feb-Aug 2004 115 1.6 11.11 0.127 8
Feb-Aug 2005 2.5 1.19 0.136 5
Feb-Aug 2006 1.7 1.26 0.145 9
Table 7 Determination of the potential evaporation (PE) in Kairouan meteorological station
Groundwater recharge potential index Infiltration capacity Average precipitation for the period 1997-2013 (mm/a) Percentage of the area (%) Infiltration+PE (×106 m3/a) PE
(×106 m3/a)		 Infiltration (×106 m3/a)
Poor 0.04 364 1 3.64 0.25 3.39
Low 0.17 11 7.86 0.55 7.31
Moderate 0.31 17 20.30 1.42 18.88
Good 0.45 44 76.30 5.34 70.96
Very good 0.69 27 71.79 5.03 66.76
Total 100 179.89 12.59 167.30
Table 8 Determination of the infiltration rate
Fig. 14 Aquifer recharge and groundwater extraction (GWRD, 2013a) (a); temporal variation of the piezometric level (GWRD, 2012) (b); and average annual precipitation (c) (GWRD, 2013b).
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