In arid and semi-arid regions, managing agricultural water for irrigation is essential to cope with water scarcity and maximize crop yields. In this study, an experiment was conducted on a potato crop in the Manouba region (lower valley of Medjerda, Tunisia). The experimental protocol consisted of four water treatments utilizing water-saving irrigation techniques: FI (Full Irrigation 100%): irrigation with 100% of crop water requirements. DI (Irrigation 75%): deficit irrigation with the application of 75% of crop water requirements. PRDRight (Irrigation 50% on the right side): Irrigation by partial root drying. PRDLeft (Irrigation 50% on the left side): Irrigation by partial root drying. Simulation of soil water profiles was carried out by the Hydrus-1D model. The soil hydraulic properties were calibrated according to the experimental conditions using an inverse modeling technique. According to the obtained results, simulated soil water profiles were close to those measured. Indeed, the calculated NRMSE values are low, indicating the reliability of Hydrus-1D as a decision support tool to optimize water irrigation management. These results were then used to investigate the effects of a 2 °C temperature increase on soil water loss, and it was determined that the impact was insignificant.

  • Arid and semi-arid need irrigation water saving techniques.

  • Deficit irrigation and partial root drying techniques can be a good alliterative to drip irrigation.

  • Simulation of water flow in the unsaturated soil allows the estimation of soil water storage.

  • Soil water loss under irrigation saving techniques is related to the applied irrigation doses.

  • The increase in temperature has no significant effect on deep percolation.

In the Mediterranean regions, especially in Tunisia, water is the main factor determining crop production. Continuous changes in climate conditions are characterized mainly by a decrease in water availability and an increase in temperature (IPCC 2021). By 2050, the amounts of precipitation in the countries of North Africa would be reduced by 20–50% compared to the current average values (Sarr 2012). In fact, Tunisia, with an average rainfall of less than 300 mm/year and an available water volume of less than 1,000 m3/inhabitant/year, is considered a country with limited water resources (Meddi & Eslamian 2021). To face this challenge, irrigation is not the only valid option, it is imperative to adopt appropriate agronomic management strategies that focus on improving the efficiency of agricultural water use (Sampathkumar et al. 2021).

Conventional irrigation, based on the maximum evapotranspiration requirements of crops (ETM), is used by farmers under conditions of limited or unrestricted water availability. This method of irrigation is now classified as a luxury water use that can be reduced with little or no drop in yield (Wanniarachchi & Sarukkalige 2022). Several irrigation water saving strategies have been used in recent years to improve water productivity such as supplemental irrigation (Satognon et al. 2021) and deficit irrigation (Elhani et al. 2019). Other scientific alternatives are also possible: the integration of antiperspirant products in the soil that can reduce the consumption of irrigation water, the limitation of the phenomena of percolations and water runoff by incorporating materials into the soil with high water retention ‘polymers’, and the use of drought-tolerant varieties (Wilson et al. 2009). With regard to this multitude of the aforementioned strategies, some researchers have oriented themselves through the knowledge base on the physiological and morphological mechanisms of the plant toward the development of the new technique ‘partial root zone drying’ (PRD) (Xie et al. 2012; Qin et al. 2018; Martínez-Romero et al. 2019).

In Tunisia, potato cultivation occupies an area of 25.6 thousand hectares, or 15% of the areas reserved for market gardening. It occupies the second place after tomato cultivation. The production of potatoes as a strategic crop in Tunisia requires more and more frequent use of water and therefore requires more efficient management of irrigation. PRD irrigation, which stands out for its potential to save water, its optimization is of major interest, especially in conditions of limited water availability.

Numerical modeling of the water storage in soils is a key factor in optimizing irrigation management (Kanzari et al. 2020). Among the modeling tools, the Hydrus-1D model (Šimůek et al. 2016) constitutes a promising software for managing the irrigation under different techniques such as drip irrigation (Yang et al. 2019) and deficit irrigation (González et al. 2015). However, a lack of research studies is noticed according to the use of the Hydrus-1D model in irrigation with the PRD technique (Nouna et al. 2016).

The objective of this study is to evaluate (i) the performance of the Hydrus-1D model for simulating water flow under irrigation saving techniques in the conditions of semi-arid Tunisia; (ii) the soil water storage and deep percolation and (iii) the effect of the increase of temperature on the soil water dynamics.

Region, soil and irrigation water

This work was carried out during the 2021 season and conducted on an experimental plot belonging to the Potato and Artichoke Technical Center (CTPTA) located in ‘Saïda’. It belongs to the governorate of Manouba which is located in the lower valley of Medjerda (Lat: 37°N, Long: 10°E Alt: 24 m) 17 km from the capital (Figure 1). The plot is located in the temperate semi-arid bioclimatic stage, characterized by an average rainfall of about 450 mm/year. The prevailing wind direction is northwest with siroccos in summer. Frequent frosts during the December–March period make it impossible to grow early vegetables in the region of Saida. Climate data for this region was measured on 20 February 2021 (Planting date) until 28 May 2021 from the centrally located meteorological station. The soil is clay texture. It is, therefore, a heavy soil with a high water retention capacity. For this type of soil, water supply should be well controlled to avoid excess water (risk of asphyxiation). The average bulk density of the soil is 1.24 g/cm3. The plot is irrigated by water from the Canal du Nord (Majerda-Cap Bon) from the Laaroussia dam. The results of analysis showed that it is very rich in potassium, magnesium and calcium. The pH is around 7.2 and the salinity is 2 g/l.
Figure 1

Experimental site location in Tunisia.

Figure 1

Experimental site location in Tunisia.

Close modal

Experimental design and measurements

The choice of plant material was made on a seasonal potato variety ‘Spunta’. The planting of the potato is carried out on 20 February 2021, in a plot of 1,393.2 m2. The plot is divided into three blocks, each block has 10 experimental units, and each unit has an area of 46.44 m2. Inside the unit, we have six lines the spacing between them is 0.83 m, the length of a line is 9 m and the distance between the plants on the same line is 0.3 m so the density planting is 4.01 plants/m2. The used experimental design is the Complete Random Block with one main factor which is water regime with four levels of irrigation: FI (Full Irrigation 100%): irrigation with 100% of crop water requirements. DI (Irrigation 75% ETM): Regulated deficit irrigation with the application of 75% of water crop requirements from the tuberization stage. PRDRight (Irrigation 50% of water crop requirements on the right side): Irrigation by partial drying of the roots. PRDLeft (Irrigation 50% of water crop requirements on the left side): Irrigation by partial drying of the roots. Drip irrigation was used for all treatments to deliver the required amounts of irrigation water.

The experimental protocol began on 19 April 2021 (58 days after planting). This date corresponds to the initiation of the tuberization phase. Irrigation started 25 days after planting with a water regime of 100% ETM. From the start of tuberization, we began to apply the experimental protocol (Figure 2) while providing the necessary doses for each treatment (FI 100, RDI 75, PRDRight, PRDLeft). The calculation of the doses and the frequencies of the irrigations are carried out using the ‘MABIA-ETc’ software (Allani et al. 2019). This software is based on estimating the water balance at the root zone level according to the FAO model 56. It is a tool for calculating the water needs of crops and establishing an irrigation program according to the environmental conditions (soil and climate). The use of this software requires the input of data concerning the climate, the culture, the ground and the irrigation system, so that it can simulate the doses and the dates of irrigation. Figure 3 summarizes the different doses of irrigation water applied during the growing season. The water levels applied to the PRD underwent an alternation.
Figure 2

Schematic of the experimental design.

Figure 2

Schematic of the experimental design.

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Figure 3

Applied irrigation doses for each treatment in mm.

Figure 3

Applied irrigation doses for each treatment in mm.

Close modal

The gravimetric method allows the monitoring of the water stock in the soil. It consists of taking soil samples at different periods of the potato cycle and at different depths using an auger. This method was used to monitor the soil water dynamic by measuring the soil water profile in the corresponding dates for the calibration and the validation of the model in the next section.

Modeling approach by Hydrus-1D

Theory

Water flow
Variably saturated water flow in an unsaturated soil is commonly described using the Richards equation (1931):
(1)
where t is time and z is depth (positive upward), and h and (h) denote the volumetric water content and the soil water matric pressure head, respectively. The Richards equation can be solved numerically when the initial and boundary conditions are prescribed and two constitutive relations, i.e., the soil water retention, θ(h), and hydraulic conductivity, K(h), functions, are prescribed. The soil water retention curve is described using the van Genuchten analytical expression:
(2)
The hydraulic conductivity function is described using the capillary model of Mualem:
(3)
where θr and θs are the residual and saturated volumetric water contents, respectively; Se is the effective saturation, Ks is the saturated hydraulic conductivity, l is a pore connectivity coefficient, and α and n are shape parameters.
Parameter optimization

The approach of parameter estimation involves the minimization of an objective function that considers all deviations between the measured and simulated data, with the simulated results controlled by the adjustable parameters to be optimized. The parameter vector b includes the parameters α, n, θr, θs and Ks. Each inverse problem was restarted several times with different initial estimates of optimized parameters and the run with the lowest value of the objective function was assumed to represent the global minimum (Kanzari et al. 2021).

Hydrus-1D applications and input parameters

The simulation period is 98 days, from 20 February 2021 until 28 May 2021. The dates of output are the 11th, 24th, 57th, 71st, 88th and 98th day. The profile is simulated up to a depth of 60 cm. Initial conditions can be expressed in terms of water content or pressure load and in terms of initial concentration. In our study, the initial state was expressed in terms of soil water content. Water content measurements were taken every 20 cm. The depth of 60 cm was simulated with a uniform intermodal space of 0.2 cm.

Climatic data (reference evapotranspiration and rainfall) are obtained from the climatic station located at the Potato and Artichoke Technical Center (CTPTA) in ‘Saïda’. The evapotranspiration values were estimated from the Mabia. ET0 software using the following parameters: temperatures (maximum and minimum in °C), relative humidity (maximum and minimum in %) and the wind speed (m/s).

For water flow, the boundary conditions are: at the upper boundary conditions, (Figure 4), atmospheric conditions ‘atmospheric BC with surface layer’ and at the lower boundary conditions, free drainage. After the simulation, the results of the soil water content are obtained in the form of graphs as a function of time and for each point of known coordinates.
Figure 4

Measured daily reference evapotranspiration and rainfall.

Figure 4

Measured daily reference evapotranspiration and rainfall.

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Statistical evaluation of the model

Simulation result was evaluated graphically and statistically. In the graphical method, the measured and simulated volumetric water content were plotted as a function of soil depth. The statistical approach involved the calculation of the normalized root mean square error (NRMSE).
(4)
where are the simulated values, are the measured values, is the average value of observed data and n is the number of observations.

Water dynamics

Figure 5 illustrates the soil water profiles measured for each date and for each irrigation treatment.
Figure 5

Measured soil water profiles for (a) full irrigation, (b) deficit irrigation, (c) PRDRight and (d) PRDLeft.

Figure 5

Measured soil water profiles for (a) full irrigation, (b) deficit irrigation, (c) PRDRight and (d) PRDLeft.

Close modal

The study of the variation in soil water content showed:

  • – An increase in soil moisture in the soil layer up to 30 cm in depth. The texture of the soil is more clayey and thus increases the retention of water.

  • – A common profile, that of 18 May 2021 and whose water content values are quite close to those of the average field capacity (37%). The measurement of this profile was carried out only 2 days after the irrigations. The soil remained quite moist except for the case of the PRDRight where the soil is in a drier state. The roots under water stress caused by the PRD irrigation strategy quickly absorbed the supplied amounts of water.

  • – That in the case of the FI, where 100% of the crop water requirements were applied for irrigation, the dynamics of soil water content reflected the cycles of saturation/drying out under the effect the irrigation doses, the evaporation and root water uptake without any stress. The soil dries out quickly after surface irrigation, while in the deepest layers, the soil humidity values showed less variation and revealed deep water percolation (Michot et al. 2003; Er-Raki et al. 2021).

  • – In the case of DI, where 75% of the crop water requirements were provided during irrigation, the water profiles showed a lower drying rate than that in the FI case and the soil retained more moisture, especially in the deepest layers. The reduction water quantities had the effect of reducing the infiltration beyond the root zone.

  • – In the case of the PRD irrigation strategies, the soil water profiles indicated a more significant state of drying due to the reduction in the doses of irrigation. In the case of PRDLeft, the value of the water content of the soil at the level up to 30 cm in depth did not vary. The root system of crops can be more developed on the left side and therefore water consumption is more optimal (Wu et al. 2022).

Simulation of soil water movement

Calibration and validation of Hydrus-1D

The calibration of Hydrus-1D was carried out over a total duration of 98 days with a daily time step (from 20 February 2021 to 28 May 2021). The times of the output files are the 11th, 24th, 57th, 71st, 88th and 98th day and correspond to the water profiles produced in the case of the FI irrigation treatment. The geometric domain is 60 cm in depth.

The hydraulic properties (α, n, θr, θs and Ks) were estimated by inverse modeling. During the optimization process, the values of these coefficients were adjusted so that the measured soil water content values were as close as possible to the simulated values. The calibrated soil hydraulic parameters are shown in Table 1.

Table 1

Calibrated soil water hydraulic properties

Layer (cm)θr (cm3·cm−3)θs (cmcm−3)αnKs (cm·d−1)
0–60 0.0100 0.4000 0.0568 1.2145 28.39 
Layer (cm)θr (cm3·cm−3)θs (cmcm−3)αnKs (cm·d−1)
0–60 0.0100 0.4000 0.0568 1.2145 28.39 

Figure 6 shows the simulated and measured water profiles for each discharge date. The simulated soil moisture values are very close to the measured values for all output dates. An overestimation of soil water content values is observed. The graphical evaluation of the model is confirmed by the calculation of the NRMSE for each date. Indeed, according to Table 2, the NRMSE values showed the reliability of the Hydrus-1D model for the reproduction of water dynamics in the soil.
Table 2

NRMSE values for each output date in the calibration process of the Hydrus-1D model

Simulation dayNRMSE (%)
11 9.81 
24 19.25 
57 6.35 
71 6.04 
88 10.55 
98 9.12 
Simulation dayNRMSE (%)
11 9.81 
24 19.25 
57 6.35 
71 6.04 
88 10.55 
98 9.12 
Figure 6

Measured and simulated soil water profiles in the case of FI and for each output date.

Figure 6

Measured and simulated soil water profiles in the case of FI and for each output date.

Close modal
The same values of the input parameters of the model were kept during the validation except for the irrigation doses at the level of the upper boundary conditions, which were changed according to the case of each treatment. Figure 7 shows the measured and simulated water profiles for the final date and for each treatment. The measured soil moisture values are similar to the simulated values. The NRMSE values are also low and show the validity of the model for the simulation of water dynamics in the case of different used irrigation techniques.
Figure 7

Measured and simulated soil water profiles at the end of simulation for DI, PRDRight and PRDLeft treatments.

Figure 7

Measured and simulated soil water profiles at the end of simulation for DI, PRDRight and PRDLeft treatments.

Close modal

Soil water storage (SWS)

As a direct result of the successful calibration and validation, the Hydrus-1D model is able to provide soil water storage variations in the studied unsaturated zone of the soil (Figure 5).

According to Figure 8, the SWS did not vary during the first 59 days between treatments. Indeed, the beginning of the application of the protocol, which includes the irrigation regimes began after the 59th day and which corresponds to the date of the beginning of tuberization. After the beginning of the irrigations, the variation of the water stock in the soil followed the episodes of infiltrations/root water uptake. After each irrigation, a peak in SWS is reached, which gradually decreases with root extraction. This observation is noted for all the treatments with a higher peak (18 cm) for the FI and the lower for the PRDRight (14 cm).
Figure 8

Soil water storage for each irrigation technique.

Figure 8

Soil water storage for each irrigation technique.

Close modal

After tuberization (approximately 62 days), the variation in SWS for the PRDRight showed a shift in the level of the irrigation peaks compared to the other treatments. Root development on this side may be the cause.

Effect of temperature increase

Forecasts made by IPCC climate experts (IPCC 2021) show an increase in global warming of 1.5–2 °C between 2030 and 2052. To assess the effect of temperature increase, the average temperatures were raised by 2 °C. The evapotranspiration values were then adjusted at the upper boundary conditions accordingly. All other model parameters were retained. The soil water profiles showed a significant state of drying at the level of the superficial layer and which became less important in depth. Indeed, this state of drying is due to the increase in evaporation from the surface layer and the increase in crop evapotranspiration caused by rising temperatures (Figure 9).
Figure 9

Soil water profiles after the increase of temperature.

Figure 9

Soil water profiles after the increase of temperature.

Close modal

This effect is also studied according to the variation of the bottom cumulative fluxes in Figure 8.

According to Figure 10, a slight decrease in the water stock is noted and whose variation does not exceed 1 cm. The effect of this does not have a significant effect on the SWS.
Figure 10

Cumulative bottom flux of water in the case of (a) actual experiment and (b) scenario of temperature increase.

Figure 10

Cumulative bottom flux of water in the case of (a) actual experiment and (b) scenario of temperature increase.

Close modal

To deal with the problems of water scarcity in arid and semi-arid regions, the use of water saving techniques at the plot scale is an obligation in order to optimize crop yields by minimizing the irrigation water consumption and maximization of production. The Hydrus-1D model was able to simulate water dynamics, as indicated by the low calculated NRMSE values (Karlsson et al. 2015). The good correlation between the measured and simulated soil water content values shows that the inverse modeling succeeded in optimizing the hydrodynamic parameters. As a direct result of the successful calibration and validation of the Hydrus-1D model, variations in soil water storage in the unsaturated zone were investigated. The obtained showed results that after tuberization (approximately 62 days), the variation in the water stock for PRDRight showed a lag in the irrigation peaks compared to the other treatments. Root development on this side may be the cause. In addition, the study of the measured water profiles revealed the same result. However, to better understand the evolution of soil water under PRD irrigation technique, it is necessary to conduct in-depth study with a soil water movement modeling tool such as that of Hydrus-2D in order to understand the evolution of soil water dynamics under PRD irrigation technique.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

Allani
M.
,
Mezzi
R.
,
Zouabi
A.
,
Béji
R.
,
Joumade-Mansouri
F.
,
Hamza
M. E.
&
Sahli
A.
2019
Impact of future climate change on water supply and irrigation demand in a small Mediterranean catchment. Case study: Nebhana dam system, Tunisia
.
J. Water Clim.
11
,
1724
1747
.
Er-Raki
S.
,
Ezzahar
J.
,
Merlin
O.
,
Amazirh
A.
,
Hssaine
B. A.
,
Kharrou
M. H.
,
Khabba
S.
&
Chehbouni
A.
2021
Performance of the HYDRUS-1D model for water balance components assessment of irrigated winter wheat under different water managements in semi-arid region of Morocco
.
Agric. Water Manage.
244
,
106546
.
González
M. G.
,
Ramos
T. B.
,
Carlesso
R.
,
Paredes
P.
,
Petry
M. T.
,
Martins
J. D.
,
Aires
N. P.
&
Pereira
L. S.
2015
Modelling soil water dynamics of full and deficit drip irrigated maize cultivated under a rain shelter
.
Biosyst. Eng.
132
,
1
18
.
IPCC
2021
Climate change 2021: the physical science basis
. In:
Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
(
Masson-Delmotte
V.
,
Zhai
P.
,
Pirani
A.
,
Connors
S. L.
,
Péan
C.
,
Berger
S.
,
Caud
N.
,
Chen
Y.
,
Goldfarb
L.
,
Gomis
M. I.
,
Huang
M.
,
Leitzell
K.
,
Lonnoy
E.
,
Matthews
J. B. R.
,
Maycock
T. K.
,
Waterfield
T.
,
Yelekçi
O.
,
Yu
R.
&
Zhou
B.
, eds).
Cambridge University Press
,
Cambridge
,
UK
;
New York, NY, USA (In press)
.
Kanzari
S.
,
Daghari
I.
,
Šimůnek
J.
,
Younes
A.
,
Ilahy
R.
,
Ben Mariem
S.
,
Rezig
M.
,
Ben Nouna
B.
,
Bahrouni
H.
&
Ben Abdallah
M. A.
2020
Simulation of water and salt dynamics in the soil profile in the semi-arid region of Tunisia – evaluation of the irrigation method for a tomato crop
.
Water
12
,
1594
.
Karlsson
S. C.
,
Langergraber
G.
,
Pell
M.
,
Dalahmeh
S.
,
Vinnerås
B.
&
Jönsson
H.
2015
Simulation and verification of hydraulic properties and organic matter degradation in sand filters for greywater treatment
.
Water Sci. Technol.
71
,
426
433
.
Meddi
M.
,
Eslamian
S.
,
2021
Uncertainties in rainfall and water resources in Maghreb countries under climate change
. In:
African Handbook of Climate Change Adaptation
(
Oguge
N.
,
Ayal
D.
,
Adeleke
L.
&
da Silva
I.
, eds).
Springer International Publishing
,
Cham
, pp.
1967
2003
.
Sampathkumar
K. M.
,
Ramasamy
S.
,
Ramasubbu
B.
,
Karuppanan
S.
&
Lakshminarayanan
B.
2021
Hybrid optimization model for conjunctive use of surface and groundwater resources in water deficit irrigation system
.
Water Sci. Technol.
84
,
3055
3071
.
Šimůnek
J.
,
van Genuchten
M. T.
&
Šejna
M.
2016
Recent developments and applications of the HYDRUS computer software packages
.
VZJ
15
,
vzj2016.04.0033
.
Wilson
M. L.
,
Rosen
C. J.
&
Moncrief
J. F.
2009
Potato response to a polymer-coated urea on an irrigated, coarse-textured soil
.
J. Agron.
101
,
897
905
.
Xie
K.
,
Wang
X.-X.
,
Zhang
R.
,
Gong
X.
,
Zhang
S.
,
Mares
V.
,
Gavilán
C.
,
Posadas
A.
&
Quiroz
R.
2012
Partial root-zone drying irrigation and water utilization efficiency by the potato crop in semi-arid regions in China
.
Sci. Hortic.
134
,
20
25
.
Yang
T.
,
Šimůnek
J.
,
Mo
M.
,
Mccullough-Sanden
B.
,
Shahrokhnia
H.
,
Cherchian
S.
&
Wu
L.
2019
Assessing salinity leaching efficiency in three soils by the HYDRUS-1D and -2D simulations
.
Soil Tillage Res.
194
,
104342
.
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