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Effects of bentonite on waterinfiltration in a loamy sand soilRezvan Talebnezhad a & Ali Reza Sepaskhah aa Irrigation Department , Shiraz University , Shiraz , IranAccepted author version posted online: 10 Jul 2012.Publishedonline: 06 Aug 2012.
To cite this article: Rezvan Talebnezhad & Ali Reza Sepaskhah (2013) Effects of bentonite on waterinfiltration in a loamy sand soil, Archives of Agronomy and Soil Science, 59:10, 1409-1418, DOI:10.1080/03650340.2012.708926
To link to this article: http://dx.doi.org/10.1080/03650340.2012.708926
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Effects of bentonite on water infiltration in a loamy sand soil
Rezvan Talebnezhad and Ali Reza Sepaskhah*
Irrigation Department, Shiraz University, Shiraz, Iran
(Received 26 March 2012; final version received 28 June 2012)
Water loss as deep percolation is considerable in furrow irrigation in light soilsdue to the high infiltration rate. Application of soil conditioners such as bentonitereduces the infiltration rate and improves irrigation application efficiency (Ea) inthese soils. The effects of bentonite application rates (BAR) of 0, 2, 4 and 6 g L71
on infiltration of a loamy sand soil were determined in a soil column in thelaboratory. The exponent of the Kostiakov infiltration equation was notinfluenced by BAR. Maximum reduction in infiltration equation coefficient andfinal infiltration rate (if) occurred with 2 g bentonite L71 and this reduction waslower on increasing BAR from 2 to 4 and 4 to 6 g L71 compared with control.The effect of 2 g L71 BAR on infiltration and its effect on the design of furrowirrigation in a field with a loamy sand soil indicated that in the first irrigation afterfield ploughing and seed planting, longer furrow length, lower deep percolationand higher Ea are obtained.
Keywords: infiltration rate; soil conditioners; furrow irrigation; irrigationapplication efficiency
Introduction
When water resources are scarce, water loss should be prevented. In this regard,irrigation application efficiency (Ea), especially in light-textured soils, and surfaceirrigation should be improved. In furrow irrigation in light soils, deep percolation ishigh due to the high infiltration rate (IR) and saturated hydraulic conductivity (Ks).Therefore, a short furrow length, which results in this condition, is not desirable infurrow irrigation design and nor is the use of farm machinery with a low Ea.
The design and efficiency of surface irrigation are dependent on the infiltrationequation (Walker and Skogerboe 1987). In surface irrigation, the inflow rate shouldbe greater than the infiltration rate for water advancing along the border or furrow.The water advance rate in surface irrigation in light-textured soils, especially in thefirst irrigation after field ploughing and seed planting, is slow due to the highinfiltration rate. Therefore, the application of soil conditioners that reduce theinfiltration rate of light-textured soils may result in a higher water advance rate.With the application of soil conditioners, the coefficient of infiltration equation ischanged such that there is an increase in furrow length and Ea.
Soil hydraulic properties are dependent on the particle size distribution, soilstructure, bulk density, organic matter and clay types (Mingorance et al. 2007).
*Corresponding author. Email: [email protected]
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Therefore, soil conditioners can be used to improve these properties and decrease theinfiltration rate (Ibrahim-Saeedi and Sepaskhah 2011; Gholizadeh-Sarabi andSepaskhah 2012).
The effect of a gel material (Jalma) on some physical properties of light-texturedsoils was studied by Al-Darby (1996). Al-Darby proposed that application of 0.4%Jalma can decrease Ks and deep percolation by a considerable amount. Lentz (2003)mixed polyacryamide (PAM) into the soil surface layer at a rate of 45 kg ha71 andmeasured the infiltration rate. Lentz showed a greater reduction in infiltration rate ina silt loam compared with loamy sand soil. Application of PAM also reducedseepage from the irrigation canal (Lentz and Freeborn 2007). Young et al. (2009)studied the effect of PAM on Ks of sandy soils and indicated that mixing PAM withthe soil surface layer resulted in a reduction in Ks.
Bentonite contains smectite clay with 2:1 layers with a high specific surface areathat is expandable and absorbs a great amount of water. Chalermyanont andArrykul (2005) reported that a mixture of sand and bentonite of 5% reduced Ks byfour times compared with sand. An increase in the amount of bentonite in thebentonite–sand mixture did not decrease Ks further. Furthermore, Komine (2004)studied the effect of different mixtures of sand and bentonite (10, 20 and 30% ofbentonite) on Ks and expansion force. By increasing the percent of bentonite theexpansion force increased and resulted in smaller effective pores and Ks. Ibrahim-Saeedi and Sepaskhah (2011) studied the effect of irrigation water with differentbentonite concentrations on Ks of a loamy sand soil. Their results indicated thatbentonite concentration of 0.2% reduced Ks of the soil surface layer by 56% and theKs of the subsurface layer by 30%. Therefore, it was indicated that bentoniteapplication was more effective at Ks reduction in surface soil. Ebina et al. (2004) andYeo et al. (2005) reported that Ks of a mixture of sand and Na-bentonite was reducedto 1.0 6 1079 cm s71 and this reduction was lower for Ca-bentonite (Sivapullaiahet al. 2000; Sallfors and Oberg-Hogsta 2002; Abichou et al. 2002; Lee andShackelford 2005). Ameta and Wayal (2008) found that the lowest Ks value occurredin a 10% mixture of bentonite and sand.
According to the study of Ibrahim-Saeedi and Sepaskhah (2011), a bentonitemixture with water can reduce Ks of the soil surface. Application of this findingmight be used in water-loss reduction in irrigation channel construction in light soiltextures. However, the effect of a mixture of bentonite and water on the infiltrationrate and the coefficients of infiltration equation has not been investigated. Thefinding of such an investigation could be applied in surface irrigation design toimprove furrow length and water application efficiency in light-textured soils. Theobjectives of this study were to investigate: (1) the effects of different concentrationsof bentonite in water (0, 2, 4, and 6 g L71) on coefficients of the Kostiakovinfiltration equation in a loamy sand soil in a soil column in the laboratory; and (2)the effects of a modified infiltration equation on the design of furrow irrigation.
Material and methods
In this study, a loamy sand soil was used. The physical properties of the soil areshown in Table 1. Sodium bentonite was used and the chemical properties ofbentonite are presented in Table 2. The effect of bentonite on infiltration wasmeasured in soil columns. The column was made of a polyvinyl chloride (PVC) tubeof 85 mm i.d. and 470 mm height. A gravel filter with a thickness of 75 mm was
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placed in the bottom of the soil column. The bottom ends of these cylinders wereclosed by a layer of foam and equipped with a drain tube connected to the gravellayer (Figure 1). These columns were filled with soil to a height of 300 mm. Toprepare the soil columns, air-dried soil samples were passed through a large 2-mmsieve and a predetermined weight of air-dried soil was placed in the PVC column.Soil initial water content was determined by gravimetric method (Table 1). Soil waspoured into the column using a funnel with long stem to prevent non-uniform soilpacking. Then based on the weight and volume of soil in the column, the apparentbulk density of soil was determined (Table 1). The internal surface of the cylinderwall was lubricated with grease to prevent preferential lateral water flow in thecolumn. The experimental soil column set-up is showed in Figure 1.
The chemical composition of the fresh water is shown in Table 3. Differentbentonite–water mixtures were used with bentonite concentrations of 0, 2, 4 and6 g L71 in fresh water. Although the concentration of the bentonite–water mixtureseems low, bentonite is accumulated by continuous application in a thin near-surfacelayer of soil (*0.05 m) and a bentonite–soil mixture can reach *30% at aconcentration of *6 g L71.
The infiltration experiment was initiated by flowing water from the bentonitesolution reservoir to the soil surface and a height of 10 mm of water was establishedon the soil surface. Water was added to the soil column and the amounts of infiltratedwater at different elapsed times were determined by measuring the increased weight ofthe soil column using an electrical balance with a precision of+0.001 g (Figure 1). Toprevent bentonite sedimentation in the solution, an electrical mixer was used in thesolution reservoir. The infiltration experiment was continued until the infiltratedwater front reached the bottom of the soil column. The outflow of infiltrated waterwas measured. These measurements continued until steady-state infiltration wasreached. The steady-state condition was determined when the inflow rate of water wasequal to the outflow rate. At this point, the soil column was considered to be asaturated soil and the final infiltration rate was measured.
Table 1. Physical properties of the soil used in this study.
Soiltexture Sand (%) Silt (%) Clay (%)
Bulkdensity
(Mg m73)
Initial watercontent
(cm3 cm73)
Saturatedwater content(cm3 cm73)
Loamy sand 71 19 10 1.55 0.012 0.37
Table 2. X-ray diffraction analysis of the bentonite used in this study (Ibrahim-Saeedi andSepaskhah 2011).
Parameter Quantity (%)
Montmorillonite, (Na, Ca)0.3(Al, Mg)2Si4O10(OH)2,nH2O 55.00Gypsum, CaSO4 5.00Muscovite, KAl2Si3AlO10(OH)2 4.00SiO2 24.00CaCO3 7.00NaCl 3.00Fe2O3 2.00
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Measured cumulative infiltration was fitted to the Kostiakov equation as follows:
Z ¼ ktm ð1Þ
where Z is the cumulative infiltration (CI) in cm, t is the elapsed time in min and kand m are constants. Furthermore, the Lewis–Kostiakov equation was fitted to themeasured CI as follows:
Table 3. Chemical analysis of the fresh water used in this study.
Parameter Unit Quantity
Electrical conductivity dS m71 0.710pH – 7.160Cl7 mmolc L
71 0.056HCO3
7 mmolc L71 5.200
Naþ mmolc L71 0.690
Ca2þ mmolc L71 3.000
Mg2þ mmolc L71 4.120
Kþ mmolc L71 0.049
Figure 1. Experimental set-up for infiltration measurement.
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Z ¼ k0tm0 þ ift ð2Þ
where if is the final infiltration rate and k0 and m0 are constants.
Results and discussion
CI as a function of elapsed time at different bentonite application concentrations isshown in Figure 2. Fitted constants of Equation (1) are shown in Table 4. Values ofmare not influenced by bentonite concentration and its mean value is 0.485. The valueof k was reduced by 36% at a bentonite concentration of 2 g L71, by 27% at 4 g L71
with respect to 2 g L71 and by 29% at 6 g L71 with respect to 4 g L71 (Table 4).As shown in Figure 2, CI decreased with increasing bentonite solution
concentration. The relationship between k and the bentonite concentration (Figure 3)is as follows:
k ¼ 2:839 exp �0:183bð Þ ð3Þ
R2 ¼ 0:99; n ¼ 4; SE ¼ 0:0461; p < 0:003 ð4Þ
Table 4. Mean values of the Kostiakov infiltration coefficient (k), Lewis–Kostiakovinfiltration coefficient (k0) and final infiltration rate (if) at different bentonite concentrations.
Bentonite concentration (g L71) k (cm min7m) k0 (cm min7m0) if (cm min71)
0 2.940a* 2.894a 0.207a2 1.869b 1.909b 0.085b4 1.364c 1.416c 0.048c6 0.964d 1.048c 0.032d
Note: Means followed by the same letter are not significantly different at the 5% level of probability usingDuncan’s multiple range test.
Figure 2. Cumulative infiltration as a function of elapsed time at different bentoniteconcentrations.
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where k is the constant of Kostiakov equation in cm min7m and b is theconcentration of bentonite in irrigation water in g L71. Equation (3) can be usedto estimate the value of k for bentonite concentrations other than those used in thisexperiment.
Addition of bentonite to the soil led to a decrease in the infiltration rate due tothe blockage of soil pores by bentonite particles. With further application of abentonite solution to the soil column, a thin layer of bentonite is formed on the soilsurface, similar to a crust, and reduces if. Values of if are given in Table 4. The valueof if decreased by *59% with a bentonite solution of 2 g L71 and by *43.5 and33.5% on increasing the bentonite solution to 4 and 6 g L71, respectively. Therelationship between if and the bentonite solution concentration (Figure 4) is shownas follows:
if ¼ 0:182 exp �0:309bð Þ ð4Þ
R2 ¼ 0:97; n ¼ 4; SE ¼ 0:173; p < 0:015
where if is the final infiltration rate in cm min71.Equation (4) can be used to estimate the value of if for bentonite concentrations
other those used in this experiment. The reduction in if was 46% on increasing thebentonite concentration from 2 to 4 g L71 and from 4 to 6 g L71 due to fittingEquation (4) to the measured data in Table 4 which showed scattering around thefitted curve in Figure 4.
Figure 3. Kostiakov infiltration equation coefficient (k) as a function of bentoniteconcentration.
Figure 4. Final infiltration rate (if) as a function of bentonite concentration.
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By using if (Table 4) in Equation (2), the constants of the Lewis–Kostiakovinfiltration equation were determined. It was shown that the exponent of t (m0) doesnot vary and its value is 0.39. However, k0 varied at different bentoniteconcentrations (Table 4). The value of k0 was reduced by 34% at a bentoniteconcentration of 2 g L71, and by 26% at 4 g L71 compared with 2 g L71 andat 6 g L71 compared with 4 g L71 (Table 4). The relationship between k0 and b(Figure 5) is as follows:
k0 ¼ 2:775exp �0:166bð Þ ð5Þ
R2 ¼ 0:99; n ¼ 4; SE ¼ 0:0408; p < 0:003
For bentonite concentrations other than those used in this experiment,Equations (4) and (5) can be used to estimate the values of if and k0 for theLewis–Kostiakov infiltration equation.
Infiltration equation application in furrow design
Furrow length is one of the parameters in furrow design. According to the designprocedure proposed by Soil Conservation Service of the USA (Walker andSkogerboe 1987), the furrow length is determined by taking the advance time asone quarter of the infiltration opportunity time for a net irrigation water depth of130 mm (Tn). Because Tn is determined using the infiltration equation for a given netirrigation water depth, it is influenced by the bentonite concentration. According toWalker and Skogerboe (1987), the furrow length is determined as follows:
Ta ¼ x=fð Þexp gxð Þ= QS0:5� �� �
ð6Þ
L ¼ fTn=4ð Þ exp gLð Þ= QS0:5� �� ��1 ð7Þ
where Ta is the advance time, x is the advance distance, Q is the inflow rate, S is thefurrow bed slope, L is the furrow length, Tn is the infiltration opportunity time for
Figure 5. Lewis–Kostiakov infiltration equation coefficient (k0) as a function of bentoniteconcentration.
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the infiltration of net irrigation water depth, and f and g are constants that aredependent on the soil final infiltration rate.
The estimated furrow lengths at different bentonite concentrations are presentedin Figure 6. In general, application of irrigation water with 2 g L71 of bentoniteincreased the furrow length 1.9 times compared with control. This increase was 2.97and 4.63 times compared with control in 4 and 6 g L71 treatments, respectively. Itshould be noted that the optimum bentonite concentration should be determinedbased on economic analysis.
The effects of bentonite concentration on the furrow length at different inflowrates in furrow irrigation (0.6, 0.8, and 0.95 L s71) are shown in Figure 6. Themaximum non-erosive inflow rate for loamy sand soil is 0.95 L s71. It is shown thatfurrow length increased with increasing bentonite concentrations at different inflowrates. For all inflow rates, application of 2 g L71 of bentonite increased the furrowlength by 87%. This value was 56% on increasing the bentonite concentration from2 to 4 g L71 and from 4 to 6 g L71, respectively. It is shown that the maximumincrease in furrow length was reached by application of 2 g L71 of bentonite,therefore this application rate is desirable for increasing furrow length, the efficiencyof farm machinery use and Ea in loamy sand soil.
Our infiltration equation was obtained in soils with low initial volumetric watercontent (i.e. 1.2%), which is similar to the conditions during the first irrigation afterfield ploughing and seed planting. Therefore, the effect of bentonite application onfurrow irrigation is considered for this condition at which irrigation efficiency andfurrow length are low due to the high infiltration rate. By applying bentonite at thefirst irrigation, a thin layer of bentonite is deposited on the soil surface layer and thislayer may decrease the infiltration rate, even on irrigation with fresh water after firstirrigation with bentonite solution, provided there have been no tillage operations inthe meantime.
It is well known that the viscosity of water is highly dependent on temperatureand this should be taken into account in infiltration studies, at least in the transfer oflaboratory results to the field, especially under arid and semi-arid conditions inwhich temperature may vary widely from day-to-day and season-to-season. A fieldrecirculating furrow infiltrometer experiment was conducted by Lentz andBjorneberg (2002) to determine the effect of irrigation water temperature on
Figure 6. Furrow length as a function of bentonite concentration at different inflow rates (Q)in furrow irrigation.
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infiltration rate in a silt loam soil. They observed an increase of 2.0 to 2.9% per 8C ininfiltration rate in the soil used. Therefore, when transferring the laboratory resultsobtained under an air temperature of 23 + 28C to field conditions, the increase intemperature in in arid and semi-arid conditions (*358C) should be taken intoconsideration.
Conclusions
Application of bentonite with irrigation water did not affect the exponent coefficient inthe Kostiakov or Lewis–Kostiakov equation in loamy sand soil, however, thecoefficients of these equations and the final infiltration rate were reduced considerablyby 2 g L71 of bentonite compared with control. Additional reductions were lower withthe application of bentonite at 4 and 6 g L71 compared with 2 g L71 bentonite. Using2 g L71 bentonite, the furrow length can be doubled compared with no bentoniteapplication at the first irrigation after field ploughing and seed planting in a loamy sandsoil which may result in a greater efficiency in farm machinery use and irrigationapplication. It is indicated that the optimum bentonite concentration is more aneconomic issue and should be clearly expressed by economic analysis.
Acknowledgements
This research was supported in part by Grant no. 91-GR-AGR-42 of Shiraz UniversityResearch Council, Drought National Research Institute, and Center of Excellence on FarmWater Management.
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