water quality effects on soils and alfalfa: ii. soil physical and chemical properties
TRANSCRIPT
Water Quality Effects on Soils and Alfalfa: II. Soil Physical and Chemical PropertiesJ. L. Costa, Lyle Prunty,* B. R. Montgomery, J. L. Richardson, and R. S. Alessi
ABSTRACTSalt accumulation can occur in northern Great Plains soils during
irrigation with saline water. The objective of this study was to quan-tify effects of salinization produced in Barnes loam (fine-loamy,mixed Udic Haploboroll), Parshall loam (coarse-loamy, mixed Pach-ic Haploboroll), Svea loam (fine-loamy, mixed Pachic Haploboroll),and Williams loam (fine-loamy, mixed Typic Argiboroll) soils byirrigation with seven water qualities during 21 mo of greenhousealfalfa production in undisturbed columns. Eight physical and chem-ical soil properties were evaluated and related to soil, water quality,and depth in the soil. Saturation percentage (SP) of the soil increased0.2% for each unit increase in soil-extract sodium adsorption ratio(SARJ. Saturation-extract electrical conductivity (ECe) increasedwith depth, at rates dependent on water quality, to maximums of 1to 17 ds rrr1. Parshall was the soil most susceptible to dispersion asSAR. increased. From the surface to 15-cm depth, bulk density wasreduced 0.04 to 0.06 Mg nr3 by the water that resulted in the highestsoluble-Ca concentration. Significant regression models were devel-oped for SP, ECn SARe, and salt precipitation. Parshall, the mostirrigable soil, was the most detrimentally affected, as judged by dis-persion, ECe, and SAR,, indicating a need for further investigation.Barnes, Svea, and Williams soils proved more suited to irrigationthan previously believed.
SOIL PROPERTIES, physical and chemical, are affectedby water quality. In a 4-yr field study (Zartman
and Gichuru, 1984), hydraulic conductivity was re-duced, EC and SAR were increased, but bulk density(pb) and water retention were not changed by as muchas 1.3 m of saline water. Clay dispersion reduces hy-draulic conductivity by plugging pores when soils areirrigated with sodic waters (Frenkel et al., 1978). Alaboratory test for clay dispersion can quantify thepotential sodicity hazard of soils (Yousaf et al., 1987).
Swelling of a montmorillonite membrane has beencorrelated with reduction of hydraulic conductivity atexchangeable sodium percentage (ESP) values of 20 to50 (Shainberg and Caiserman, 1971). The ESPs <20however, reduced hydraulic conductivity when clayparticles were free to migrate in soil. Soil aggregatestability, slaking, and dispersion were related to SARand electrolyte concentration by Abu-Sharar et al.(1987). They concluded that aggregate breakdown andclay dispersion are concurrent processes. Emerson andBakker (1973) and Yousaf et al. (1987) found that, atequal aggregate ESP, more dispersion occurred if thecomplementary ion was Mg rather than Ca.
Exchangeable sodium percentage reflects the deg-radation potential for soil physical properties and canaffect plant growth. Precipitation of Ca and Mg saltsinfluences the Na hazard of salts remaining in solution,especially in sulfatic northern Great Plains soils(Timpson and Richardson, 1986; Arndt and Richard-son,}^).^_________________ __Dep. of Soil Science, North Dakota State Univ., P.O. Box 5638,Fargo, ND 58105. Contribution of the North Dakota Agric. Exp.Stn. Journal no. 1867. Received 2 Oct. 1989. "Corresponding author.
Published in Soil Sci. Soc. Am. J. 55:203-209 (1991).
Models of transient soil-solution concentrationscaused by irrigation with saline water show a transitionstage. Salt precipitation is enhanced in this stage andsolution concentrations remain less than calculated atequilibrium for up to 1600 d, for a 150-cm profile ata leaching fraction (LF) of 0.05 (Jury et al., 1978a).Transient and steady-state behavior differ, whichmakes good models of quantities influenced by water-uptake distribution difficult to construct (Jury et al.,1978b). Saline irrigation precipitated large quantitiesof salts, predominantly gypsum (Jury et al. 1978c).
Steady-state conditions, in contrast, have beenfound or presumed in numerous studies. Irrigation-water SAR (SARW) was a good estimator of steady-state ESP in the top 0.3 m of soil (Bingham et al.,1979). Steady-state SAR of drainage water was highlyrelated to LF, SARW, and the calculated pH of waterin equilibrium with CaCO3 (pHc) (Bower et al., 1968).A steady-state model (Oster and Rhoades, 1975) cal-culated expected drain-water compositions associatedwith western USA river waters. The minimum leach-ing requirement of the U.S. Salinity Laboratory Staff(1954, p. 43) presumed a steady-state salt balance.
This study evaluated the effects of irrigation-waterquality on selected physical and chemical propertiesof four potentially irrigable soils of the northern GreatPlains. Prunty et al. (1991) reported water-quality ef-fects on alfalfa growth and water use. This study ex-pands that work to include effects on soil properties.
MATERIALS AND METHODSDetailed information on water qualities WO to W6 and
the Barnes loam, Parshall loam, Svea loam and Williamsloam soils appear in Prunty et al. (1991). The experimentaldesign was completely random, split plot. Soil and waterquality were factorial main-plot treatments, with depth thesplit-plot treatment. All effects were considered fixed. Eval-uation of significant differences was based on F tests andLSD at a = 0.05. Henceforth, subscript w refers to irrigationwater and subscript e references saturation extract (e.g. ECeor ECW).
The large soil columns described in Prunty et al. (1991)were dried after the last quantified alfalfa harvest by allowingthe alfalfa to continue growth for 2 wk. Cylinders were care-fully cut open for sampling. The columns were sampled atdepth increments of 0 to 2.5, 2.5 to 7.6, 7.6 to 15.2, 15.2 to22.9, 22.9 to 30.5, 30.5 to 38.1, 38.1 to 45.7, 45.7 to 53.3,and 53.3 to 61.0 cm. Each depth was split, one-half for phys-ical analysis and one-half for chemical analysis. Chemical-analysis samples were crushed with a rolling pin to pass an8-mm sieve and air dried. Two 50- to 300-g clods were se-lected for PI, determination and stored moist, wrapped inwaxed paper. Soil for aggregate percentage (AP) was workedby hand to pass an 8-mm sieve, air dried, and stored inplastic containers.
Saturation percentage was determined as percent gravi-metric water in a subsample of the saturated paste. A stan-dard conductivity cell was used to determine ECe ofsaturated-paste extracts (Rhoades, 1984).
The degree of soil aggregation was determined by a mod-ification of the U.S. Salinity Laboratory Staffs Procedure42b (1954). Duplicate 20-g samples were dispersed, one
203
204 SOIL SCI. SOC. AM. J., VOL. 55, JANUARY-FEBRUARY 1991
chemically and one with water only. Further details of thedispersion procedure are in Prunty et al. (1984). Dispersedsamples were pipetted at 10-cm depth after settling for 1 hand 45 min (at 25 °C), or as corrected for other temperatures(Day, 1965, Table 43-1), and oven dried. The settling timepresupposed a soil particle density of 2.65 Mg nr3 and di-ameter of 4 nm, while U.S. Salinity Laboratory Staff (1954)used 50 urn. The 4-nm size resists breakdown due to handlingand storage operations and has been used in recent work(Dong et al., 1983).
Dispersion index (DI) was denned as the ratio of the dryweight of <4-jtm particles from the chemically dispersedsample to the dry weight of <4-/un particles from the water-dispersed sample. Aggregate percentage was calculated (U.S.Salinity Laboratory Staff, 1954) as
AP = 100(DI - 1.0)/DI.Thus, AP is the range of 0 to 100, with a highly aggregatedsoil having AP =100 and a highly dispersed soil having AP= 0. Samples from only depths 0 to 2.5 cm through 15.2 to22.9 cm were analyzed, due to the time-consuming natureof the measurement and the presupposition that major ef-fects (e.g., crusting) would be more likely in the near-surfacelayers.
Bulk densities of oven-dry and moist clods were deter-mined by the saran method (Soil Conservation Service,1972) for each of the nine depths. Moist clods were equili-brated at 33.3 kPa in a pressure-extraction apparatus andthe moisture content determined.
The pH and soluble ions were determined from saturation-paste extracts. Soluble HCO3 and CO3 were determined bya potentiometric titration. Soluble Ca, Mg, Na, and K weredetermined by atomic-absorption spectrophotometry and Clby potentiometric titration with AgNO3. Sulfate was calcu-lated by the difference between total determined cations andanions (U.S. Salinity Laboratory Staff, 1954).
Calculation of salt precipitation (PPT) involved summingCa, Mg, Na, and K (mmolc L~') to obtain saturation-extractsoluble-cation concentration at each depth. Total soluble cat-ions for each depth increment were calculated as the productof the cation concentration, SP, pb, and the volume of soil.These were summed to obtain the total soluble cations percylinder (CTL). The total cations added per cylinder (CAD)was calculated from the total water added to each cylinderand its composition. Total cation uptake per cylinder byplants (CPL) was calculated using plant-analysis data anddry-matter yield (Prunty et al., 1991). Salt precipitation wasthen estimated by
PPT = (CAD - CTL - CPL)/MSL,where MSL is the soil mass.
Saturation-extract SAR was calculated for each depth asNa/[(Ca + Mg)/2]°-5 (U.S. Salinity Laboratory Staff, 1954).
Table 1. Analysis of variance F significance for saturation percent(SP), saturation-extract electrical conductivity (EC.), aggregatepercentage (AP), saturation-extract sodium adsorption ratio(SAR.), pH, and salt precipitation (PPT). Soils (S) and waterqualities (W) are factorial main effects and depths (D) are splitplots.
Source SP AP SAR. pH PPT
S
s x wDS X DW X DS X W X D
** NS *** * *** NS
Saturation index (SI) was calculated for each soil and watercombination with the computer program PCWATEQ (Rob-bins, 1988), using average saturation-extract concentrationsas input data.
RESULTS AND DISCUSSIONPhysical Properties
The saturation percentage was significantly affectedby all variables (Table 1). Saturation percentages, av-eraged over all water treatments and soil depths,ranged from 38.0 for Parshall to 50.0 for Barnes (Table2), which reflected a 15% sand and 5% clay differenceacross the range.
Electrical conductivity was significantly affected byall variables, except soil X water (SXW) interaction.The overall CV was 29.2. Oster (1984) reported CVvalues ranging from 35.7 to 57.0% for ECe in fieldexperiments. Barnes had the lowest ECe and Parshallthe highest, 35% greater (Table 2).
Increased irrigation-water salt concentration gen-erally tended to increase ECe. There was a general in-crease in ECe with soil depth (Table 2), except in the0- to 2.5-cm depth, because of evaporation at the soilsurface. Increased ECe with depth is the expected con-sequence of plant water uptake and a low LF (Osterand Schroer 1979). In all four soils ECe produced byW2 was usually one-half that produced by Wl (Fig.1), even though W2 had nearly identical ECW (2% low-er) and SARW (3% higher). This was probably the resultof CaCO3 precipitation. At equal salt concentration,but different Na levels (treatments W2 vs. W3 and W4vs. W5), irrigation waters with higher SARW increasedECe (Table 2). This was probably caused by higher Na
Table 2. Average values of saturation percent (SP), saturation-ex-tract electrical conductivity (ECe), and aggregate percent (AP) formain effects.
Treatment
SoilBarnesParshallSveaWilliamsLSD (0.05)
WaterfWOWlW2W3W4W5W6LSD (0.05)
Depth, cm0-2.5
2.5-7.67.6-15.2
15.2-22.922.9-30.530.5-38.138.1-45.745.7-53.353.3-61.0LSD (0.05)
SP%
50.038.048.449.70.9
43.545.246.146.547.949.546.6
1.21
46.7944.7944.7746.3145.4547.4547.9847.7347.330.99
EC,
dSnr1
4.546.145.274.890.63
0.753.631.604.278.71
10.047.270.85
2.992.523.574.514.836.506.817.447.840.42
AP
%
86.976.189.181.4
2.1
91.690.990.579.088.369.274.32.7
86.583.086.379.3
1.7,* ,««» significant at p = 0 05) O.ot, 0.001, respectively. NS
icant.not signif- t Represent typical electrical conductivity, Na absorption ratio, and residual
Na2CO3 range of North Dakota groundwater.
COSTA ET AL.: WATER QUALITY EFFECTS ON SOIL AND ALFALFA: II. 205
concentration, relative to Ca and Mg, in the high-SARwater, and the greater solubility of Na salts than of Caand Mg salts. The higher Ca and Mg concentration oftreatments W2 and W4 apparently resulted in moreprecipitation as carbonate and sulfate salts than fortreatments W3 and W5, respectively. This effect wasinfluenced by soil series and depth interaction in thecase of W4 and W5 (Fig. 1).
A dilution factor for the W6 treatment, based ontotal amounts of WO and W5 water applied (Pruntyet al., 1991), was calculated as Q.55. Using this factor,the chemical composition of the water produced bymixing W5 with WO (distilled water) was estimated(Prunty et al., 1991). The ECW for treatment W6 wasabout 40% higher than for Wl, W2, and W3, but theECe for treatment W6 was 100, 354, and 70% higherthan the ECe of Wl, W2, and W3, respectively. It is,therefore, implied that W6 (SAR = 14.5), which al-ternated W5 with WO, produced less salt precipitationthan Wl (SAR = 3.0), W2 (SAR = 3.1), and W3 (SAR= 9.2) because of the relative abundance of Na.
Aggregate percentage was significantly affected bysoil, water quality, depth, and their interactions (Table1). Parshall soil had the lowest AP (Table 2). Watertreatments with low SARW values (WO, Wl, and W2)had similar soil AP values. Irrigation waters W3, W5,and W6 (SARW values of 9, 19, and 14, respectively)significantly reduced AP. Treatment W4 reduced APonly slightly, compared with the low-SARw waters(WO, Wl, and W2). This was because of high salt con-centration, compared with SARW, i.e., ECW of 1.25 and2.98 dS m-1 for W3 and W4, respectively, while SARWvalues for W3 and W4 were nearly equal.
Only the oven-dry pb results are reported. Differ-ences due to soils series, irrigation-water treatment,and depth were significant for the top three layers (Ta-ble 3). Average pb for soils were 1.38 for Barnes, 1.47for Parshall, 1.39 for Svea, and 1.49 Mg m-3 for Wil-liams soil. Average pb by depth were 1.35, 1.42, 1.42,and 1.45 ± 0.02 Mg m-3 for the 0 to 2.5, 2.5 to 7.5,7.5 to 15 cm, and deeper depths, respectively.
From the surface to a depth of 15 cm, W4 producedlower pb than the average Ph produced by the otherwaters. The differences were 0.04, 0.06, and 0.06 forthe 0- to 2.5-, 2.5- to 7.6-, and 7.6- to 15-cm depths.For 2.5 to 7.6 and 7.6 to 15 cm, the differences ex-ceeded the LSD, which were 0.04 Mg m~3. For eachsoil to a depth of 15 cm, W4 was the treatment withthe highest Ca concentration. From the surface to 15cm, soluble Ca in W4-treated soil ranged from 6.3 toTable 3. Analysis of variance F statistic significance for bulk density
due to soil and water quality main effects.
Depth Soil Watercm0-2.5 "
2.5-7.67.6-15.2
15.2-22.922.9-30.530.5-38.138.1-45.745.7-53.353.3-61.0
******
NSNSNSNSNSNS
*,**,**» Significant at P = 0.05, 0.01, 0.001, respectively. NS •icant.
not signif-
0.UJQ
15
30
45
60
ECe(dSm8 12 16 20
BARNES
65 4
EC@(dS m )8 12 16 20
•' J31 /',36. '5
?!\ f ./&... PARSHALL
' ' '5
^ 5
5 '4'••• I
,6 54^
°\ \/7\'36 1
15
- 30Ii—Q.IllQ
45
60
(213 « 503' 3S* 5I.'! \\ \:\ \K \?\ ,\\ 5:
WILLIAMS
^ *\ ,
v, 1\ \ 'v.\ \- \U "
0 2 1 3 6 5 4
•'02 1 8'6 .5
?fl'f\ ^-?fl\4\"-^^021 3 N / (
I \ ! /0 213I i \? ? 3,
\'5-:?XI5-,
0 2 361/ \ ,-\ \0 2 6 3 1
Fig. 1. Depth distribution of saturation-extract electrical conductivity (ECe) for each soil after irrigating with different quality irrigation waters.Water qualities WO to W6 are designated by the corresponding numbers 0 to 6 at the plotted points.
206 SOIL SCI. SOC. AM. J., VOL. 55, JANUARY-FEBRUARY 1991
11.9 mmolc L-', 50 to 100% higher than the averageof all other treatments. Therefore, pb reduction withW4 water may be related to a high soluble-Ca con-centration. This agrees with Waldron et al. (1970), whoTable 4. Average values of saturation-extract sodium adsorption ra-
tio (SARJ, pH, and salt precipitation (PPT) for main effects.Treatment SAR, pH PPT
cmolc kg"1
SoilBarnesParshallSveaWilliamsLSD (0.05)
WaterfWOWlW2W3W4W5W6LSD (0.05)
Depth, cm0.0-2.52.5-7.67.6-15.2
15.2-22.922.9-30.530.5-38.138.1-45.745.7-53.353.3-61.0LSD (0.05)
13.6118.8414.2414.90
1.49
1.497.12
11.3519.8419.4230.3220.15
1.98
11.6514.5616.8216.7815.8218.1016.9115.1213.07
1.15
7.877.767.558.090.119
7.477.738.108.127.687.857.760.158
7.998.027.967.827.607.817.747.727.680.084
4.192.903.403.480.79
-1.653.484.913.218.116.95
-0.551.05
t Represents typical electrical conductivity, SAR, and residual Na2CO3 rangeof North Dakota groundwater.
10 20
SARe
30 40 50
Q.LUD
15
30
45
60
"°-1.f 6\\
\ 4,""5-
HA- ! \ 4
' \ \
BARNES
.9
IIQ.LUQ
0
15
30
45
60
p0
-f
I
oII•\̂0
"
12 4 3.6^._' 5.....'
| V^S^1 ? 4\ x'6' /3
K 4K /5;;-1 ? 6 N3* \ ' S \
1 2, SX 4 .5'
1 ffi *2 5 4i / v /1 1 \ /1 63 52 4
...5 WILLIAMS
''•5
..5
'.5
found a 5% increase in void ratio for soils permeatedwith solutions of CaCl2 vs. NaCl.
Chemical Properties and Salt BalanceAll main effects and interactions significantly influ-
enced SARe at the 0.05 level (Table 1) and all but SX Wwere significant at the 0.001 level. The overall CV was24.6, compared with a CV of 29.2% by Bingham et al.(1979). Average SARe was significantly higher in Par-shall than in the other three soils (Table 4).
Average SAR,, values by treatment across soil anddepth (Table 4) were consistent with SARW values pre-sented in Prunty et al (1991). The lowest SARe valuewas with WO (distilled water) and the highest with W5(highest SARW). Treatments W3 and W4 (same SAR,,,different ECe) produced similar SARe values but, inWl and W2 (same SARW and ECJ, SARe values dif-fered (7.12 vs. 11.35, respectively) due to higher car-bonates in W2. Greater CaCO3 precipitation with W2than with Wl increased the Na/(Ca + Mg) ratio, caus-ing SAR? to increase more in W2.
Irrigation-water composition and soil influenced thedistribution of SARe with depth (Fig. 2). TreatmentsW3, W5, and W6 produced similar relative changesin SARe with depth. Treatments Wl, W2, and W4 alsoproduced similar SAR? changes. The W3, W5, and W6group produced maximum SARe a* shallower soildepths than Wl, W2, and W4. This behavior is mostevident for Parshall and Svea soils. Oster and Schroer(1979) reported the same response, concluding thatsteady state had not been reached and that furtherirrigation would have eventually raised the ESP in thelower one-half of the columns.
DEP
TH (
cm)
SARe
0 10 20 30 40 50
y<j 24' ' es^Ls..... 'PARSHALL0 i 2 4 ^"3^6"- 5
P \ \ V ^.-6XX3 5
"o' 1 \ ^43" .3X i1 ', \ V .-•-"9 \ 2v"S4\ 5-."0 V1 ̂ 3^2 N5
I SS / I I!0 3 1 X6 2 45
0 36 1 2 ' 45'
1 1,| 4^ 3-? ^-^ ' SVEA '
I \\ \ ^ - '̂ ••' 50, 1 2, 4 ^36X 5''
0 1 '2 '43X.6' 51 \ 1 A /0 1 2X6' 4i 5
°\ ^v^3/4-'-5r' C"? 45'/ f / //
G 3'1 2 4 5'
Fig. 2. Depth distribution of saturation-extract sodium adsorption ratio (SAR,) after growing alfalfa in the greenhouse under different qualityirrigation waters. Water qualities WO to W6 are designated by the corresponding numbers 0 to 6 at the plotted points.
COSTA ET AL.: WATER QUALITY EFFECTS ON SOIL AND ALFALFA: II. 207
As expected, because of their high residual sodiumcarbonate (RSC) values (Prunty et al., 1990), W2 andW3 generated the highest soil pH (Table 4). The highRSC of these water treatments indicate potential forfurther pH rise. Williams soil started and ended withthe highest pH.
Soils and water treatments significantly affected PPT(Table 1 and 4), but produced no significant interac-tion. All water treatments except WO and W6 precip-itated salt (Table 4). Similar results were reported bySchroer (1970) and Jury et al. (1978b). Jury et al.(1978b) found that 50% of the total salt added withirrigation precipitated after 500 d. Our results for treat-ment W5 indicated that 1.75 molc precipitated, out of3.6 molc added. Precipitation increased with salt con-centration, as seen by comparing treatments Wl, W2,and W3 vs. W4 and W5 (Table 4). At equal salt andNa concentration (Wl and W2), high-HCO3 water(W2) had more PPT than low-HCO3 water (Wl). Atequal salt concentration but different SARW (W2 vs.W3 and W4 vs. W5), increased SARW reduced PPT.Precipitation from W2 differed significantly from W3and PPT from W4 differed significantly from W5 (Ta-ble 4). The reduction of PPT with increasing SARWwas probably caused by the higher Na to Ca ion ratioof the high SAR water, since the higher solubility ofNa2SO4 prevented precipitation.
Using the chemical-divides-evaporite sequence out-lined by Hardie and Eugster (1970), we expected cal-cite and not gypsum to form with W2 and W3 becauseCO3 levels were higher than Ca levels (Prunty et al.,1990). Once calcite begins precipitating from suchwater, insufficient Ca remains to form gypsum. ForW4 and W5, however, ECW, Ca, and SO4 levels werehigh enough for gypsum precipitation (Doner andPratt, 1969; Steinwand and Richardson, 1989). Thechemical-divides concept also predicts, for W4 andW5, that, once calcite does begin to precipitate, Calevels will rise with respect to CO3, favoring gypsumprecipitation (Arndt and Richardson, 1989). Notethat, for W4 and W5, the average gypsum SI was great-er than —0.1 (Table 5), and gypsum did not super-saturate (SI > 0). In field soils, if SI is near zero (SI> —0.1), gypsum is nearly always observed. Calcite,
Table 5. Saturation index (SI) values generated by the geochemistryprogram PCWATEQ (Robbins, 1988) for calcite (CAL) and gyp-sum (GYP) based on average soluble ions in saturation extracts.
Watertreatment!WO
Wl
W2
W3
W4
W5
W6
Soil
MineralCALGYPCALGYPCALGYPCALGYPCALGYPCALGYPCALGYP
Barnes0.70
-1.380.63
-0.310.26
-1.470.72
-0.790.38
-0.040.62
-0.151.14
-0.08
Parshall-0.74-0.12
0.51-0.34
0.88-1.11
1.06-0.30
0.250.010.530.000.02
-0.09
Svea-0.88-1.62-0.15-0.40
0.43-1.23
0.66-0.54-0.04-0.03
0.28-0.11-0.02-0.19
Williams0.57
-1.040.78
-0.270.81
-1.331.13
-0.380.77
-0.011.00
-0.101.07
-0.18
Mean-0.09-1.04
0.44-0.33
0.60-1.28
0.89-0.50
0.34-0.02
0.61-0.09
0.55-0.14
however, can easily supersaturate (Arndt and Rich-ardson, 1989). Gypsum apparently formed from W4and W5 (Table 5). It probably formed from W6 also,but redissolved with WO pulses.
ModelsThere was a trend toward increased SP with in-
creased adjusted SAR (SARadj). A stronger relation-ship,
SP = 43.6 + 0.198 SARe, R2 = 0.96***
(*** significant at P = 0.001) existed between averageSARe and SP values. Consistent with this, Bresler etal. (1982) pointed out that, at a given soil water ten-sion, water content increased as the Na/Ca1/2 ratio ofthe soil solution increased. Emerson and Bakker(1973) observed that water absorbed by Ca-Na aggre-gates or Mg-Na aggregates in excess of that adsorbedby Ca or Mg aggregates was a measure of the additionalswelling caused by Na.
By using multiple linear-regression models, wefound ECe to differ with soil depth (D) and three ir-rigation-water parameters: ECW, SARW, and alkalinity(COW). The best model wasECe = 1.73 + 0.155 SARW - 0.313 COW
+ 0.44 D ECW, -R2 = 0.89***where ECe and ECW are in dS rrr1, COW is in mmolcL~' and D is in cm. All regression coefficients in themodel differ from zero at P = 0.001. The regressorvariables were free of multicolinearity.
Electrolyte concentration and SAR^. are the principalfactors affecting clay dispersion in soil. A positive cor-relation (r = 0.68) between ECe and SARg preventedindependent analysis, thus only SARe was used inregression analysis of AP (Fig. 3).
Using the regression model appropriate for each soil(Fig. 3) and an SARe of 20, we estimated AP = 88 forSvea and AP = 75 for Parshall. This suggests thatParshall is more susceptible to dispersion at low SARe.Barnes and Williams AP estimates were 81 and 78,respectively.
The relationship between SARW and SARe dependson the nature of the soil cation-exchange complex andthe composition of the soil solution as affected by min-eral precipitation and dissolution processes. In prac-tical terms, these considerations are determined byevapotranspiration and irrigation-drainage manage-ment (Bower et al., 1968; Rhoades and Merrill, 1976).Rhoades and Merrill (1976) indicated that the SAR ofthe upper root zone (SARJ can be estimated by
SARU = SARW[1 + (8.4 + pHc)]. [1]
t Represents typical electrical conductivity, SAR, and residual Na2CO3 rangeof North Dakota groundwater.
The right side of Eq. [1] was used to calculate SARadj(Prunty et al., 1991). We regressed SARe against SARadjand SARW and found higher R2 values with SARadj(Table 6). The resulting equation was
SARe = 4.0 + 0.8 SARadj, R2 = 0.76*** [2]The dilution-factor method to calculate SARadj for
W6 (Prunty et al., 1991) was consistent with Eq. [2].
208 SOIL SCI. SOC. AM. J., VOL. 55, JANUARY-FEBRUARY 1991
a.<
100
80
60
40
BARNES
5 5
AP=94.76-0.73 SARe
R2= 0.45*"
PARSHALL
AP=96.68-1.09SARe
CL<
100
80
60
40
WILLIAMS
5 5
AP=94.21-0.87SARC
10 20 30SARe
40
SVEA
AP=96.10-0.44 SARe
R2= 0.76***
50 10 40 5020 30SARe
Fig. 3. Relation between aggregation percentage (AP) and saturation-extract sodium adsorption ratio (SARJ for each soil after irrigating withdifferent quality irrigation waters.
Using the dilution factor of 0.55 for W6, Eq. [2] pre-dicted SARe to within ± 10%. This has practical im-plications because of the importance of naturalprecipitation in the area where these soils occur (dry-subhumid continental climate).
Precipitation followed the multiple-regression equa-tion
PPT = -0.650 + 3.064 EQ, - 0.125 SARW
+ 0.227 COW, R2 = 0.88***
where PPT is in cmolc kg"1 and COW is the sum ofirrigation water CO3 and HCO3. Treatments WO andW6 were not included in this analysis because theyresulted in negative values of PPT.
Our yield (Y) models (Prunty et al., 1991) used cu-mulative salts applied as the independent variables.Because soil-salinity measurements were made only atthe end of the experiment, Y values at Time 4 (T4)only were modeled by ECe and SARe (Tables 2 and 4)as
Y = 1.400 - 0.008 ECe - 0.020 SARe, R2 = 0.996,a = 0.004.
This model was superior to a similar model (R2 =0.94, a = 0.06) using ECW and SARW. The above modeland the models of Prunty et al. (1991) are closely re-lated, because accumulated salts contributed to soilsalinity to the limits of solubility. Further yield mod-eling is beyond the scope of this work.
General DiscussionIncreases in ECW generally increased ECe, but, at
equal ECW, carbonates and divalent ions reduced ECedue to precipitation of calcite and gypsum. Aggrega-tion decreased as SAR,. increased (Fig. 3). Bulk den-sities were 0.04 to 0.06 Mg nr3 less in the surface 15cm of the W4 treatment, where relatively high soluble-Ca concentrations occurred. When estimating Na haz-ard in a subhumid to semiarid climatic region like thatof the northern Great Plains, the dilution effect of rainwater should be considered.
Salt-balance calculations indicated that salt precip-itated from all waters used, except WO and W6. Totalcation concentration, carbonate concentration, (COW)and SAR,, affected the quantities of precipitated salt.Such precipitation effects must be taken into accountin water-quality assessment relative to irrigation prac-tices. This is particularly important for water high inNa, Ca, SO4, CO3, or HCO3. Computer models areavailable to describe SARW and SARe relationships (Os-ter 1975), but Eq. [2] predicted SAR .̂ in this experiment.
Table 6. Determination coefficient (R2) for regression of saturation-extract sodium adsorption ratio (SAR,.) against irrigation-watersodium adsorption ratio (SAR,) and adjusted SAR (SAR^).
Soil SAR, SAR.4,BarnesParshallSveaWilliams
23242424
0.52***0.82***0.70"*0.83***
0.54***0.94***0.80***0.86***
" Significant at P = 0.05, 0.01, 0.001, respectively.
COSTA ET AL.: WATER QUALITY EFFECTS ON SOIL AND ALFALFA: II. 209
CONCLUSIONParshall soil had the highest ECe, lowest AP, highest
SAR,,, and the sharpest reduction in AP per unit in-crease in SARe. Alfalfa yields on Parshall also contin-ued to decrease when the other soils plateaued (Pruntyet al., 1991). The Soil Conservation Service (1977)however, lists it as irrigable and the other soils as con-ditional because of slow internal drainage and the haz-ard of salinization. Although irrigable, Parshall soil issensitive to mismanagement and could suffer rapiddegradation of physical and chemical properties withimproper irrigation management. Additional researchon these soils seems warranted to determine if, underfield conditions, Barnes, Svea, and Williams soils(combined area of 3.85 million ha) are more suitablefor irrigation, relative to Parshall soil (120000 ha),than indicated by current irrigability ratings.
Data Base AvailableThe data base for this study is available to the public
from the corresponding author.
ACKNOWLEDGMENTSPartial financial support for this study was provided by
the U.S. Department of Interior, Bureau of Reclamation,under Contract no. 9-07-60-V0025, Project 2.