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Journal of Arid Land
Journal of Arid Land  2023, Vol. 15 Issue (12): 1474-1489    DOI: 10.1007/s40333-023-0037-0
Research article     
Estimation and inter-comparison of infiltration models in the agricultural area of the Mitidja Plain, Algeria
Amina MAZIGHI1, Hind MEDDI1, Mohamed MEDDI1,*(), Ishak ABDI1,2, Giovanni RAVAZZANI3, Mouna FEKI3
1Higher National School of Hydraulics of Blida, Blida 09000, Algeria
2Department of Civil Engineering and Hydraulics, University of Jijel, Jijel 18000, Algeria
3Department of Civil and Environmental Engineering, Polytechnic University of Milan, Milan 20133, Italy
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Abstract  

Infiltration is an important part of the hydrological cycle, and it is one of the main abstractions accounted for in the rainfall-runoff modeling. The main purpose of this study is to compare the infiltration models that were used to assess the infiltration rate of the Mitidja Plain in Algeria. Field infiltration tests were conducted at 40 different sites using a double ring infiltrometer. Five statistical comparison criteria including root mean squared error (RMSE), normalized root mean squared error (NRMSE), coefficient of correlation (CC), Nash-Sutcliffe efficiency (NSE), and Kling-Gupta efficiency (KGE) were used to determine the best performing infiltration model and to confirm anomalies between predicted and observed values. Then we evaluated performance of five models (i.e., the Philip model, Kostiakov model, Modified Kostiakov model, Novel model, and Horton model) in simulating the infiltration process based on the adjusted performance parameters cited above. Results indicated that the Novel model had the best simulated water infiltration process in the Mitidja Plain in Algeria. However, the Philip model was the weakest to simulate the infiltration process. The conclusion of this study can be useful for estimating infiltration rate at various sites using a Novel model when measured infiltration data are not available and are useful for planning and managing water resources in the study area.

Key words： infiltration rate      infiltration model      double ring infiltrometer      Mitidja Plain      Novel model     
Received: 26 July 2023      Published: 31 December 2023
Corresponding Authors: *Mohamed MEDDI (E-mail: m.meddi@ensh.dz)
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Amina MAZIGHI
Hind MEDDI
Mohamed MEDDI
Ishak ABDI
Giovanni RAVAZZANI
Mouna FEKI
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Amina MAZIGHI, Hind MEDDI, Mohamed MEDDI, Ishak ABDI, Giovanni RAVAZZANI, Mouna FEKI. Estimation and inter-comparison of infiltration models in the agricultural area of the Mitidja Plain, Algeria. Journal of Arid Land, 2023, 15(12): 1474-1489.

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http://jal.xjegi.com/10.1007/s40333-023-0037-0     OR     http://jal.xjegi.com/Y2023/V15/I12/1474

Fig. 1 Study area with selected sites and soil texture (Boufekane et al., 2021; Bouziane et al., 2021)
Fig. 2 Double ring infiltrometer
Site Coarse silt (%) Fine silt (%) Clay (%) Fine sand (%) Coarse sand (%) Soil type Initial f(t) at t=
1 min (mm/h)		 Final/steady f(t) (mm/h)
P1 5.0 12.5 50.0 17.5 20.0 Sandy clay 240.0 30.4
P2 12.0 13.5 40.0 12.6 32.5 Sandy clay 180.0 48.4
P3 5.3 2.2 50.0 17.0 30.3 Sandy clay 77.6 30.0
P4 12.5 2.5 55.0 37.5 7.5 Sandy clay 60.0 13.8
P5 12.0 15.0 40.0 12.3 26.3 Clay-limono 120.0 62.8
P6 15.0 12.5 41.5 18.3 22.8 Clay-limono 180.0 11.7
P7 50.0 5.0 34.5 7.5 7.5 Clay-limono 65.5 48.0
P8 20.0 20.0 55.0 13.9 14.8 Clay-limono 60.0 13.7
P9 15.0 15.0 10.0 51.0 22.6 Sandy loam 120.0 22.4
P10 1.0 4.5 35.0 12.0 65.0 Sandy loam 330.0 138.4
P11 10.0 55.5 25.0 6.2 7.7 Fine silt 90.0 61.2
P12 34.0 25.0 17.0 19.3 4.8 Fine silt 48.0 12.0
P13 3.6 70.0 5.8 13.2 11.8 Fine silt 90.0 51.0
P14 45.0 25.0 9.4 18.1 5.7 Fine silt 180.0 29.7
P15 15.0 56.5 15.0 11.2 5.3 Fine-clay-limono 180.0 29.6
P16 75.0 7.3 2.8 9.7 3.7 Fine-clay-limono 105.0 60.0
P17 35.0 35.0 20.0 10.8 7.3 Fine-clay-limono 120.0 15.5
P18 9.0 75.0 11.5 3.7 2.5 Fine-clay-limono 30.0 6.0
P19 5.0 15.0 42.5 16.2 32.2 Sandy clay-loam 180.0 15.0
P20 10.0 5.0 52.4 19.3 16.7 Sandy clay-loam 24.0 4.6
P21 7.0 10.0 41.5 15.2 26.8 Sandy clay-loam 36.0 4.4
P22 4.8 2.7 40.0 19.2 40.0 Sandy clay-loam 120.0 43.3
P23 5.0 7.5 75.0 8.4 12.1 Clay 180.0 38.0
P24 0.5 15.0 75.0 5.1 3.8 Clay 168.0 93.8
P25 30.0 5.0 55.0 4.9 14.2 Clay 60.0 14.4
P26 5.0 16.0 75.0 4.3 2.8 Clay 180.0 88.8
P27 9.0 9.0 63.0 7.6 20.6 Clay 11.7 6.0
P28 10.0 22.5 70.0 5.7 2.6 Clay 16.4 12.0
P29 20.0 10.0 45.0 22.3 4.5 Clay 120.0 56.7
P30 15.0 15.0 65.0 9.0 3.7 Fine-clay-loam 180.0 43.0
P31 35.0 10.0 40.0 5.5 10.4 Fine-clay-loam 60.0 9.6
P32 32.0 12.0 45.3 7.2 4.4 Fine-clay-loam 15.0 4.0
P33 20.0 14.0 50.6 7.7 8.4 Fine-clay-loam 60.0 3.7
P34 19.0 21.3 59.7 4.4 3.8 Clay-loam 60.0 48.0
P35 35.0 2.8 52.1 10.5 0.9 Clay-loam 120.0 34.8
P36 21.0 5.0 60.6 10.9 2.5 Clay-loam 60.0 5.9
P37 45.0 45.0 4.4 7.0 0.5 Very fine silt 80.0 55.4
P38 55.0 30.0 5.3 11.5 2.0 Very fine silt 60.0 26.7
P39 79.0 15.6 0.5 4.8 3.5 Very fine silt 27.3 8.9
P40 16.0 68.5 5.7 5.6 5.4 Very fine silt 60.0 20.8
Table 1 Details of the initial and final infiltration rates (f(t)), and soil properties of the study area
Site Philip Horton Kostiakov Modified Kosiakov Novel
K S f0 fc K ai bi ai bi fc ai bi c fc
P1 6.12 49.14 352.80 41.14 30.05 29.77 0.46 6.76 0.82 28.44 3.65 0.98 5.74 5.83
P2 38.76 47.40 158.99 54.54 3.37 60.79 0.29 60.79 0.29 2.3E-03 60.79 0.29 1.7E-05 4.61
P3 40.61 16.55 67.79 0.11 0.28 49.09 0.15 49.07 0.15 4.2E-04 49.08 0.15 10.90 6.3E-06
P4 12.66 15.72 41.31 8.31 0.97 20.50 0.28 20.50 0.28 8.6E-05 20.50 0.28 1.8E-05 1.36
P5 59.44 12.55 178.43 68.92 44.54 63.57 0.11 1.56 0.85 65.48 0.44 1.17 28.13 2.40
P6 3.6E-06 37.22 206.60 17.04 14.35 10.31 0.72 10.31 0.72 7.7E-05 10.31 0.72 6.9E-06 9.26
P7 53.64 7.16 66.29 28.01 0.30 56.95 0.07 56.96 0.07 2.1E-04 56.95 0.07 8.29 1.6E-05
P8 7.09 11.63 102.15 18.21 42.37 11.48 0.36 2.03 0.74 12.83 0.52 1.08 8.19 1.95
P9 9.31 37.69 120.40 26.07 5.14 27.64 0.41 27.65 0.41 1.6E-03 27.64 0.41 8.9E-05 1.83
P10 125.73 66.06 304.21 100.40 2.66 142.75 0.22 142.75 0.22 6.0E-04 142.75 0.22 5.3E-04 0.60
P11 61.96 11.72 90.01 55.15 1.74 64.99 0.11 65.00 0.11 1.8E-03 65.00 0.11 5.12 1.8E-05
P12 7.56 11.02 55.70 17.11 15.58 11.31 0.36 11.31 0.36 2.6E-03 11.31 0.36 1.04 8.8E-06
P13 53.89 12.20 77.66 50.25 1.14 59.41 0.10 59.41 0.10 1.6E-03 59.42 0.10 6.36 4.9E-05
P14 17.03 43.38 144.99 35.62 5.07 38.39 0.36 35.14 0.38 3.29 36.76 0.37 2.76 0.60
P15 4.03 43.71 239.41 33.61 19.55 25.92 0.46 7.73 0.76 21.43 6.66 0.80 6.02 3.82
P16 81.23 14.41 112.55 8.9E-04 0.39 85.99 0.10 86.02 0.10 6.9E-04 86.00 0.10 7.9E-05 0.01
P17 1.8E-04 35.98 135.59 20.06 9.28 16.51 0.53 16.51 0.53 9.2E-05 16.51 0.53 9.9E-06 0.97
P18 4.05 9.83 27.94 7.18 3.02 8.91 0.36 8.91 0.36 2.3E-04 8.91 0.36 3.4E-06 1.14
P19 7.4E-06 47.38 190.14 20.59 8.86 17.55 0.61 17.55 0.61 3.4E-05 17.55 0.61 0.61 1.7E-05
P20 1.71 6.16 34.99 6.87 23.05 4.45 0.42 4.15 0.43 0.36 4.45 0.42 1.56 1.4E-05
P21 3.2E-05 11.05 34.63 4.20 5.73 5.04 0.53 5.04 0.53 5.5E-05 5.04 0.53 9.7E-07 0.20
P22 35.07 23.69 133.99 49.10 11.71 45.27 0.22 9.16 0.56 38.12 9.13 0.56 1.44 26.45
P23 29.86 35.79 162.58 47.80 8.62 47.29 0.28 18.78 0.49 28.91 16.62 0.52 9.34 3.34
P24 98.32 31.31 170.33 60.20 1.21 107.97 0.15 107.99 0.15 3.2E-04 107.97 0.15 0.01 9.1E-05
P25 12.95 8.46 77.16 16.22 25.17 17.83 0.17 0.87 0.95 15.56 0.78 0.98 5.97 2.62
P26 91.15 25.56 159.85 96.29 3.53 98.41 0.14 98.40 0.14 1.4E-03 98.39 0.14 2.47 1.3E-04
P27 8.35 1.94 11.13 6.74 0.37 9.50 0.09 9.50 0.09 2.1E-05 9.50 0.09 1.4E-05 6.22
P28 12.75 2.51 16.65 6.51 0.26 14.14 0.08 14.14 0.08 1.1E-04 14.15 0.08 0.12 3.9E-05
P29 56.29 15.76 101.44 63.08 4.77 62.45 0.13 25.38 0.25 37.77 14.23 0.37 9.12 5.41
P30 28.13 51.71 167.76 47.58 4.01 51.83 0.34 51.83 0.34 5.3E-05 51.83 0.34 7.4E-05 2.34
P31 1.2E-04 13.65 110.15 14.47 44.32 6.49 0.51 2.43 0.74 6.65 0.75 1.02 2.42 4.43
P32 2.68 3.83 17.21 4.76 9.32 4.48 0.31 2.63 0.42 1.92 2.63 0.42 0.97 1.98
P33 1.1E-05 11.56 94.09 6.43 30.41 7.61 0.38 1.96 0.80 3.47 1.47 0.88 1.04 3.92
P34 48.28 4.90 61.83 28.67 1.09 48.08 0.07 48.09 0.07 3.7E-04 48.08 0.07 3.2E-05 2.96
P35 27.85 24.97 105.82 40.37 6.09 38.05 0.27 32.78 0.29 5.54 32.78 0.29 2.76 2.01
P36 3.72 10.57 85.78 7.53 25.26 9.57 0.34 2.19 0.76 6.06 1.91 0.80 3.81 1.64
P37 46.37 48.22 175.34 64.38 3.92 67.98 0.28 67.98 0.28 8.0E-05 67.99 0.28 5.47 6.5E-05
P38 22.93 15.93 65.68 29.08 3.99 30.30 0.22 30.30 0.22 1.4E-04 30.30 0.22 1.1E-04 2.53
P39 6.94 5.93 28.89 11.07 11.03 8.60 0.29 8.59 0.29 1.2E-04 8.60 0.29 4.97 1.7E-05
P40 17.73 8.68 69.42 22.18 19.95 22.14 0.16 2.56 0.64 19.62 1.04 0.88 17.76 1.18
Table 2 Parameters of estimated infiltration models
Fig. 3 Comparison of observed infiltration rate with estimated infiltration rate from various models in different sites. (a), P1 site; (b), P6 site; (c), P9 site; (d), P12 site; (e), P15 site; (f), P20 site; (g), P25 site; (h), P33 site; (i), P36 site; (i), P39 site.
Fig. 4 Comparision of infiltration models based on KGE (a), NSE (b), CC (c), and NRMSE (d) statistics. Boxes indicate the IQR (interquartile range, 75th to 25th of the data). The median value is shown as a line within the box. Outlier is shown as circle. Lines extend to the most extreme value within 1.5×IQR. KGE, Kling-Gupta efficiency; NSE, Nash-Sutcliffe efficiency; CC, coefficient of correlation; NRMSE, normalized root mean squared error; M-Kostiakov, modified Kostiakov model.
Fig. 5 Distribution of PBIAS (percent bias) of different infiltration models. (a), Horton model; (b), Kostiakov model; (c), Philip model; (d), M-Kostiakov (modified Kostiakov) model; (e), Novel model.
Table 3 Performance evaluation parameters from different infiltration models
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