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Published online 17 July 2007
Published in J Environ Qual 36:1310-1317 (2007)
DOI: 10.2134/jeq2006.0314
© 2007 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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TECHNICAL REPORTS

Surface Water Quality

Predicting Runoff of Suspended Solids and Particulate Phosphorus for Selected Louisiana Soils Using Simple Soil Tests

Theophilus K. Udeigwea, Jim J. Wanga,* and Hailin Zhangb

a School of Plant, Environmental, and Soil Sciences, Sturgis Hall, Louisiana State Univ. Agricultural Center, Baton Rouge, LA 70803
b Dep. of Plant and Soil Sciences, Oklahoma State Univ., Stillwater, OK 74078. Contribution of Louisiana Agric. Exp. Stn. Journal No. 06-14-0300 and is published with the approval of the Director

* Corresponding author (jjwang{at}agcenter.lsu.edu).

Received for publication August 11, 2006.

   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 1. Materials and Methods
 Results and Discussion
 Conclusions
 REFERENCES
 
This study was conducted to evaluate the relationships among total suspended solids (TSS) and particulate phosphorus (PP) in runoff and selected soil properties. Nine Louisiana soils were subjected to simulated rainfall events, and runoff collected and analyzed for various parameters. A highly significant relationship existed between runoff TSS and runoff turbidity. Both runoff TSS and turbidity were also significantly related to runoff PP, which on average accounted for more than 98% of total P (TP) in the runoff. Runoff TSS was closely and positively related to soil clay content in an exponential fashion (y = 0.10e0.01x, R2 = 0.91, P < 0.001) while it was inversely related to soil electrical conductivity (EC) (y = 0.02 x–3.95, R2 = 0.70, P < 0.01). A newly-devised laboratory test, termed "soil suspension turbidity" (SST) which measures turbidity in a 1:200 soil/water suspension, exhibited highly significant linear relationships with runoff TSS (y = 0.06x – 4.38, R2 = 0.82, P < 0.001) and PP (y = 0.04x + 2.68, R2 = 0.85, P < 0.001). In addition, SST alone yielded similar R2 value to that of combining soil clay content and EC in a multiple regression, suggesting that SST was able to account for the integrated effect of clay content and electrolytic background on runoff TSS. The SST test could be used for assessment and management of sediment and particulate nutrient losses in surface runoff.

Abbreviations: DP, dissolved phosphorus • EC, electrical conductivity • NTU, nephelometric turbidity unit • PP, particulate phosphorus • SST, soil suspension turbidity • TP, total phosphorus • TSS, total suspended solids


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
1. Materials and Methods
 Results and Discussion
 Conclusions
 REFERENCES
 
THE loss of suspended solids along with nutrients from agricultural fields has been considered one of the main causes for the impairment of water quality in many parts of the United States. In Louisiana, a total of 67 water body subsegments were impaired due to high levels of suspended solids (LDEQ, 2004). Suspended solids or sediments are insoluble solid particles that either float on the water surface or are in suspension, causing turbidity (Sammori et al., 2004). Turbidity is a function of both the concentration and the size of the suspended sediment. It is also related to the levels of pollutants because many nutrients and pollutants (e.g., P, pesticides, heavy metals, etc.) are attached to suspended particles (Sammori et al., 2004). Thus, an increase in soil particles washed into a water body results in an increase in other types of pollutants (Korsching and Nowak, 1983).

From an agronomic perspective, nutrient loss associated with suspended solids through surface runoff is the primary pathway of P loss from agricultural fields (Baker and Sanft, 1992; Vadas et al., 2004). Various studies have indicated that particulate phosphorus (PP) is the predominant form exported from agricultural lands (Vighi et al., 1991; Eghball and Gilley, 2001; Udawatta et al., 2004). In general, as much as 62 to 99% of total phosphorus (TP) has been found in the particulate-associated form in runoff waters from cultivated soils (Gillingham and Thorrold, 2000; Uusitalo et al., 2001; Daverede et al., 2003). Suspended solids also serve as a potential source of bioavailable P (Uusitalo et al., 2000, 2003). Therefore, it has been suggested that reducing sediment loss would be more effective in reducing total P as well as bioavailable P in runoff (Daverede et al., 2003).

To develop appropriate management strategies for reducing the impact of surface runoff on water quality, an accurate and consistent assessment of potential risk associated with runoff from agricultural lands is necessary. Various efforts have been made to relate runoff of P from agricultural fields to soil test P (Pote et al., 1996; Gaston et al., 2003; Zhang et al., 2006). However, very little research has been done on relating sediment in runoff to soil test information, even though suspended solids are also a major contributor to the impairment of water quality of various water bodies in many areas across the country (USEPA, 1998).

The magnitude of soil particle loss in runoff appears to be greatly influenced by texture (Lado et al., 2004), type of clay (Curtin et al., 1994), organic carbon cementing agents (Rhoton and Tyler, 1990; Rhoton et al., 2003), interaction between soil salinity and sodicity (Shainberg, 1990; Ward and Carter, 2004), and soil surface characteristics (Udawatta et al., 2004). The relationship between soil salinity and its flocculating effects, and soil sodicity and its dispersive effects suggests that salinity measurements could be used to differentiate soils with respect to their potential loss of suspended solids through surface runoff.

In this study, we evaluated the relationships between suspended solids in surface runoff and soil characteristics determined by simple laboratory tests, especially soil suspendability and electrical conductivity (EC). These relationships could help in predicting the runoff of suspended solids from agricultural fields. Since particle loss in runoff influences nutrient loss, particularly P, these relationships could aid calibrating phosphorus loss indices to improve their reliability. The objective of this study was to evaluate the relationships between the total suspended solid (TSS) or PP losses in surface water runoff and selected soil characteristics using simple soil tests.


   1. Materials and Methods
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 1. Materials and Methods
Results and Discussion
 Conclusions
 REFERENCES
 
2.1 Soil Description and Characterization
A total of nine cultivated soils representative of major areas of agricultural production in Louisiana were selected for this study. The soils include a Baldwin (Fine, smectitic, hyperthermic Chromic Vertic Epiaqualfs; 29°57' N; 91°43' W), a Jeanerette (Fine-silty, mixed, superactive, thermic Typic Argiaquolls; 29°57' N; 91°55' W), a Latanier (Clayey over loamy, smectitic over mixed, superactive, thermic Oxyaquic Hapluderts; 31°10' N; 092°23' W), a Mer Rouge (Fine-silty, mixed, superactive, thermic Typic Argiudolls; 32°38' N; 91°50' W), a Mowata (Fine, smectitic, thermic Typic Glossaqualfs; 30°10' N; 92°21' W), a Norwood (Fine-silty, mixed, superactive, hyperthermic Fluventic Eutrudepts; 31°10' N; 92°24' W), a Sharkey (Very-fine, smectitic, thermic Chromic Epiaquerts; 30°21' N; 091°09' W), and two Commerce soils (Fine-silty, mixed, superactive, nonacid, thermic Fluvaquentic Endoaquepts). The Commerce soils include a Commerce (S) silty clay from St. Gabriel (30°15' N; 091°06' W) and a Commerce (E) silt loam from East Carroll (32°39' N; 91°13' W). These soils were in a conventional tillage with corn, sugarcane, or rice cropping system before being sampled.

Representative and composite surface soils (0–15 cm) were collected from each of the selected sites. Large clods were crushed to pass a 19-mm sieve and soil was thoroughly mixed and placed in a 100 cm by 55 cm by 20 cm plastic box with 19 6-mm drainage holes in the bottom (Davis et al., 2005). The same amount (75 kg) of soil was packed into each box. The height of the soil in each box was 15 cm from the bottom. A total of nine soil samples (nine boxes) were prepared, one from each of nine sites. All the samples in the boxes underwent a series of wetting and drying cycles for 3 mo before they were subjected to the rainfall simulation. These cycles were performed by saturating each soil to field capacity every 5 to 7 d and allowing to dry after each saturation in a greenhouse.

A soil sample from each box was collected and characterized for physical and chemical properties before the rainfall simulation. The collected soil samples were dried and ground to pass a 2-mm sieve before analysis. Soil EC was measured based on extracts of both saturated paste (SP) and 1:2 soil/water mixture (Rhoades, 1996), and sodium absorption ratio (SAR) was calculated based on Na, Ca, and Mg ion concentrations of these extracts. Soil pH was also determined in the 1:2 soil/water mixture. Soil test P was determined by Mehlich 3 procedure (Mehlich, 1984). Organic matter (OM) was determined by a modified loss-on-ignition (LOI) method (Ben-Dor and Banin, 1989). Cation exchange capacity (CEC) was determined by saturating the soil with 1 M NH4OAc at pH 7 followed by distillation and titration (Soil Survey Laboratory Methods Manual, 1996). Particle size analysis was conducted using a pipette method described by Gee and Bauder (1986), and soil mineralogy was characterized using X-ray diffraction (Bruker AXS Inc., Madison, WI) based on standard procedures (Moore and Reynolds, 1989).

A new and simple laboratory soil test measure, termed "soil suspension turbidity" (SST) was performed to assess soil suspendability and potential susceptibility to loss in surface runoff. The method involved suspending a 1-g subsample of each uniformly mixed soil in 200 mL deionized water in a 250 mL plastic bottle, which was then capped and shaken on a reciprocal shaker at a speed of 170 oscillations per minute for 1 or 24 h. Following shaking, the turbidity of the resulting suspension was determined either immediately or after a 7-h settling time using a turbidimeter based on a three-detector system (Model 2100N, Hach Co., Loveland, CO). The 7-h settling time was chosen on the basis that silt and sand fractions settled in a 10-cm water column at ambient temperature (Gee and Bauder, 1986). The 1:200 soil/water suspension was chosen based on preliminary runoff data obtained for these soils and was used to ensure turbidity values well within the instrument detection range. Duplicate SST tests for each soil were performed.

6.2 Rainfall Simulation and Runoff Analysis
The runoff experiment was conducted in packed soil boxes following a protocol developed for the National Research Project for Simulated Rainfall-Surface Runoff Studies (National Phosphorus Research Project, 2001) and modifications made by Davis et al. (2005). The simulation experiment over packed soil boxes was chosen for better controlled runoff conditions and it has shown to yield similar and consistent relations between runoff characteristics and soil properties as field plots (Kleinman et al., 2004). The rainfall simulator was based on the design of Miller (1987). It has a Teejet 1/2 HH SS 50 WSQ nozzle placed at the center of an aluminum frame with dimensions of 3.0 m by 2.3 m by 2.8 m. Boxes containing soils were placed on an inclined (5%) platform and runoff collected in a simulated rainfall event. The intensity of the rainfall was maintained at 75 mm h–1 using a control box with on and off spraying times of 1.5 and 0.6 s, respectively. Deionized water was used as the source for the rainfall simulation.

The soils in boxes were irrigated until saturation and the excess water was allowed to drain 24 h before rainfall simulation (Davis et al., 2005). All the soils were subjected to a 10-min initial runoff aimed at minimizing the effect of soil sampling from each box before the actual collection of runoff samples. Two consecutive runoff samples were collected (each for 25 min) from each soil box. Runoff was collected in preweighed plastic buckets and runoff volume determined by weight. Immediately after the rainfall simulation, the runoff samples were thoroughly mixed and a 1-L subsample was collected for laboratory analysis. Samples not analyzed immediately were stored at 4°C.

Total suspended solids and turbidity for each runoff sample were determined according to EPA Methods 160.2 and 180.0, respectively (USEPA, 1983a, 1993). Total P in the runoff sample was determined by the persulfate digestion procedure using USEPA Method 365.3 (USEPA, 1983b). Dissolved P was determined from aliquot of 20 mL from each runoff sample, which was centrifuged and filtered through a 0.45-µm membrane filter. All P and other element analyses were performed using an inductively coupled plasma (ICP) (SPECTRO CYRIOS, Spectro Analytical Instruments, Inc., Fitchburg, MA). Particulate P was calculated as the difference between TP and DP.

6.3 Statistical Analysis
Analyses were performed using the Statistical Analysis Software (SAS Institute, 2001). Both single and multiple linear regression analyses were performed using PROC REG to establish the relationship between runoff and soil parameters. The nonlinear relationships were determined using PROC MODEL in SAS.


   Results and Discussion
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 1. Materials and Methods
 Results and Discussion
Conclusions
 REFERENCES
 
8.1 Soil Characteristics
Selected soil chemical and physical properties are shown in Table 1. Soil test P (Mehlich 3) ranged from 13.4 to 32.9 mg kg–1. The soil pH ranged from 5.5 to 8.1 and soil OM from 11.2 to 56.0 mg kg–1. Soil EC ranged from 0.31 to 0.84 dS m–1 and SAR from 0.33 to 2.20 based on SP extract whereas EC and SAR ranged from 0.15 to 0.47 dS m–1 and 0.15 to 1.99 based on 1:2 soil/water extraction. The EC and SAR values from SP extracts were related to those determined from 1:2 soil/water extraction and can be expressed as y = 1.93x (R2 = 0.52, P < 0.05) and y = 0.97x (R2 = 0.61, P < 0.01), respectively where y represents SP extract data and x 1:2 soil/water extraction data. The result for EC relationship between the extracts of SP and 1:2 soil/water ratio was close to that reported by Hogg and Henry (1984) for medium- and heavy-textured soils.


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  		Table 1. Chemical and physical properties of selected Louisiana soils.{dagger}

 
Particle size analysis showed that silt was the dominant particle size among all the soils, ranging from 434 to 798 g kg–1. The clay fraction ranged from 111 to 438 g kg–1, and sand fraction ranged from 17 to 402 g kg–1. These particle size distributions represented a textural range of loam to silty clay, with silty clay loam and silty clay predominant. Soil CEC ranged from 1.0 to 22 cmol kg–1and was significantly correlated with clay content (R2 = 0.79, P < 0.01) but not with OM, suggesting that much of the CEC was due to permanent charge of soil clays. Overall six out of the nine soils were dominated by smectite with its content reaching as high as 86% in the clay fraction. Two soils were dominated by illite while one soil was dominated by kaolinite. These results were consistent with the properties of similar soils reported in other studies (Harrell and Wang, 2006). According to Barzegar et al. (1997), soils with stable soil structure, which are generally less susceptible to the aggregate breakdown and clay dispersion, are those with abundant organic matter and mixed clay mineralogy. In this study, the presence of one overwhelmingly dominant clay mineral in some low-OM soils could suggest relatively strong clay dispersion and, therefore, result in sediment runoff under a heavy rain event.

Runoff Characteristics
The results of the simulated rainfall runoff experiments are shown in Table 2. The data reported are average values of two successive rainfall simulations. This was based on our preliminary data which indicated that the samples collected from the initial two successive runoff simulations accounted for most of the variability in surface water runoff, when compared to the subsequent third and the fourth simulations. The runoff volume ranged from 11.6 to 16.7 L, TSS from 0.4 to 34.6 g L–1, and turbidity from 1480 to 42000 NTU. Relatively large standard errors were seen in these data especially for runoff TSS and turbidity. These situations were, however, not unexpected for the averages of two successive runoff events. Similar variations in TSS were reported for runoff experiments conducted over both field plots and packed soil boxes (Sharpley and Kleinman, 2003; Penn et al., 2004). Total P and PP concentrations in the runoff waters were from 5.4 to 28.4 mg L–1 and 5.3 to 27.9 mg L–1, respectively (Table 2). The TP and PP were found to be highly significantly related (y = 0.988x – 0.005, R2 = 0.99, P < 0.001). The PP accounted for more than 98% of TP, indicating that most of the P lost from these soils was in the particulate form. These results were similar to those reported by others for cultivated soils (Gillingham and Thorrold, 2000; Eghball and Gilley, 2001; Udawatta et al., 2004) but different from those for biosolids-impacted forage fields, which showed generally higher DP than PP (Edwards and Daniel, 1993; Sauer et al., 2000; Gaston et al., 2003). The TSS, TP, and PP in runoff water from each soil tended to decrease with consecutive simulated rainfall events (data not shown), a similar observation was also reported in other studies (Turner et al., 2004). In this study, the DP concentration in runoff water samples, ranging from 0.03 to 0.58 mg L–1 (Table 2), was slightly lower than that reported for biosolids-amended soils (Sharpley, 1995).


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  		Table 2. Runoff characteristics of selected Louisiana soils. Data presented are the averages (mean ± SE) of two successive runoff events.{dagger}

 
A highly significant relationship (y = 0.0008x + 0.11, R2 = 0.98, P < 0.001) was found between TSS and turbidity of runoff samples (Fig. 1). This relationship is stronger than that between suspended sediments and turbidity for river waters, R2 = 0.49 to 0.73 (Weigel, 1984). It has been shown that the relationships between suspended sediments and turbidity are likely stronger at higher turbidity levels (Grayson et al., 1996). These close relationships between stream turbidity and suspended solids have been used to indirectly estimate suspended solid concentrations in river streams (Grayson et al., 1996; Pavanelli and Bigi, 2005a, 2005b). Our results (Fig. 1) suggest that turbidity is also a reliable indicator of TSS in runoff water from these cultivated agricultural fields.


Figure 1
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  		Fig. 1. Relationship between runoff total suspended solids (TSS) and runoff turbidity for selected Louisiana soils.

 
There was also a highly significant linear relationship (R2 = 0.95, P < 0.001) found between TP or PP and TSS in runoff (Fig. 2, only PP vs. TSS shown). As expected, similar relationships were also found between TP or PP and turbidity of runoff samples (data not shown). We did not observe any significant trend between DP and TSS or turbidity. These findings are consistent with those reported by others in that PP is the predominant form exported from most cultivated lands through surface water runoff (Gillingham and Thorrold, 2000; Daverede et al., 2003; Udawatta et al., 2004). The close relationships found between TSS or turbidity and TP or PP in runoff samples suggest that either a measure of TSS or turbidity of runoff sample could be a reliable indicator of the amount of total P or particulate P in runoff from cultivated soils.


Figure 2
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  		Fig. 2. Relationships between runoff particulate phosphorus (PP) and runoff total suspended solids (TSS) for selected Louisiana soils.

 
Relationships between Runoff Characteristics and Soil Properties
Both linear and nonlinear regression analysis were conducted to determine the relationships between runoff TSS/turbidity, TP/PP, and various soil properties. Highly significant and nonlinear relationships (R2 ≥ 0.89, P < 0.001) were found between soil clay content and runoff TSS as well as between soil clay content and runoff turbidity (Fig. 3a, 3b). The curvilinear relationships indicate that a rapid increase in runoff TSS and turbidity occurs at soil clay content of approximately 280 g kg–1. High soil loss with increasing clay content has been observed for various soils, especially in coarse to medium-textured soils due to easy detachment of soil particles from soil mass (Meyer and Harmon, 1984; Lado et al., 2004). On the other hand, soils with high clay content (e.g., 620 g kg–1) were shown to have lower erosion due to stronger formation of stable aggregates, cemented by a sufficient amount of clay (Ben-Hur et al., 1985; Mamedov et al., 2002; Lado et al., 2004). The soils used in this study contained between 111 and 438 g kg–1 clay, a common range for many Louisiana soils, and within this clay content range the loss of sediment in the runoff would be exponential (Fig. 3).


Figure 3
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  		Fig. 3. Relationships between runoff characteristics and soil clay content for selected Louisiana soils: (a) runoff total suspended solids (TSS) and soil clay content; (b) runoff turbidity and soil clay content.

 
The strong relationship between runoff TSS and soil clay content in Fig. 3a suggests that knowing soil clay content is important for predicting TSS in the runoff water for cultivated fields that tend to have soil surface exposed. On the other hand, other factors such as wetting rate, clay mineralogy, and soil solution ionic composition could also have an important effect on soil dispersion and erodibility (Lado et al., 2004; Ward and Carter, 2004). This implies that the suspendability of a soil could be the key for predicting the potential of sediment runoff. Since runoff turbidity is well related to soil clay content and runoff TSS (Fig. 1; Fig. 3b), we devised a "soil suspension turbidity" (SST) test to assess the potential suspendability and susceptibility of a soil to loss through surface runoff. The SST measured without settling gave much higher values than those after a 7-h settling time due to contribution of sand and silt. The SST measured after 24-h shaking and 7-h settling was most closely (y = 26.96e0.007x, R2 = 0.95, P < 0.001) related to soil clay content (Fig. 4). This strong relationship suggests that SST could be used to indirectly approximate soil clay content, a much easier approach than the traditionally used soil particle size analysis.


Figure 4
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  		Fig. 4. Relationship between soil suspension turbidity (SST) and soil clay content. The SST was measured based on 24 h shaking followed by 7 h settling.

 
The inclusion of the 7-h settling time after shaking generally yielded the best correlations of SST with suspended solids in runoff (Fig. 5). Overall, the SST determined with 24-h shaking and 7-h settling exhibited the strongest linear relationship (y = 0.06x – 4.38, R2 = 0.82, P < 0.01) with TSS in runoff (Fig. 5d). Similarly, soil SST values were also highly correlated (y = 73.73x – 5442.53, R2 = 0.84, P < 0.001) with turbidity values of runoff samples (Fig. 6). As expected, the SST was also significantly and linearly correlated with runoff PP and accounted for 85% of variability in runoff PP (Table 3). The good fit of these linear relationships between SST and runoff TSS, turbidity, or PP suggests that the SST test could be used to indirectly predict the potential loss of sediment and PP in surface runoff from cultivated soils.


Figure 5
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  		Fig. 5. Relationship between runoff total suspended solids (TSS) and soil suspension turbidity (SST) measured after: (a) 1 h shaking, no settling; (b) 1 h shaking, 7 h settling; (c) 24 h shaking, no settling (d); 24 h shaking, 7 h settling.

 

Figure 6
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  		Fig. 6. Relationship between runoff turbidity and soil suspension turbidity (SST). The SST was measured after 24 h shaking followed by 7 h settling.

 

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  		Table 3. Linear and nonlinear regression equations and coefficients (R2) for the relationships between runoff total suspended solids (TSS)/turbidity/particulate phosphorus (PP) and soil property variables. SST, soil suspension turbidity.{dagger}

 
The relationships between runoff characteristics and soil properties were further evaluated by investigating the relationships between runoff TSS and soil EC. The importance of electrolyte concentration in controlling soil dispersion and aggregate stability has been studied, especially in management of irrigated or saline soils (Abu-Sharar et al., 1987; Ward and Carter, 2004), but has not been thoroughly evaluated in relation to sediment runoff in low EC soils, such as those in this study. The regression analysis showed that runoff characteristics were equally predicted by soil EC as measured in either SP or 1:2 soil/water extracts. Due to the fact that these two methods were significantly correlated and the EC measurements in 1:2 soil/water extracts are easier, only the relationships between the runoff characteristics and soil EC/SAR measured in 1:2 soil/water extracts are reported herein unless otherwise indicated.

As shown in Fig. 7, the TSS was negatively related (R2 = 0.70, P < 0.01) to the soil EC. The negative relationships of soil EC with runoff TSS as well as turbidity were generally better described by a curvilinear regression (Table 3). These negative relationships were expected from diffuse double layer (DDL) theory (Evangelou, 1998). Higher ionic strength (higher electrolyte concentration) would generally lead to compressed double layer, causing flocculation, increased particle aggregation, improved permeability and enhanced infiltration, thus reducing the susceptibility of particles to runoff (Agassi et al., 1981). Since ionic strength of a soil solution can be empirically approximated from EC (Griffin and Jurinak, 1973), soil EC can also be used to evaluate the susceptibility of soil solids to runoff. For the soils used in this study, soil EC accounted for 70% of the variability associated with runoff TSS and 65% with runoff water turbidity. In addition, soil EC was also negatively related to runoff PP, but only accounted for 54% of its variability (Fig. 8). The generally smaller regression coefficients of soil EC with runoff TSS, turbidity, and PP than those of soil SST indicate that SST would be more sensitive than soil EC in predicting sediment and PP losses in runoff. The latter could be due to the fact that other influencing factors, such as clay mineralogy and solution composition, rather than just soil clay content, were likely integrated and accounted for in soil SST measurements as opposed to soil EC determinations.


Figure 7
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  		Fig. 7. Relationship between runoff total suspended solids (TSS) and soil electrical conductivity (EC). Soil EC was measured in 1:2 soil/water mixture.

 

Figure 8
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  		Fig. 8. Relationship between runoff particulate phosphorus (PP) and soil electrical conductivity (EC). Soil EC was measured in 1:2 soil/water mixture.

 
Besides soil EC, SAR is often used to evaluate soil dispersion in sodic soils. The SAR values for selected soils in this study were less than 2.20 with the majority less than 1.00 based on measurements in both SP and 1:2 soil/water extracts (Table 1). This small range of SAR (low sodium impact) could be the reason that no relationship was observed between SAR and runoff TSS, turbidity, or PP (Table 3). Previous research, however, suggested that at low SAR values (e.g., close to 0), soils with electrolytic concentration less than approximately 3.0 to 5.0 mmolc L–1, depending on the aggregate size, began to exhibit clay dispersion as soil aggregates broke down (Abu-Sharar et al., 1987; Curtin et al., 1994). For soils with a SAR of 10, the electrolyte concentration of approximately 10 mmolc L–1 was found to be the threshold below which significant dispersion of clays would likely occur (Curtin et al., 1994). In this study, the plot of runoff TSS and the electrolyte concentration for all nine soils also indicated that substantial TSS in runoff occurred at electrolyte concentration less than 10 mmolc L–1 (data not shown). As shown in Fig. 7, this critical electrolyte concentration corresponded to a soil EC of approximately 0.3 dS m–1 based on 1:2 soil/water mixture (equivalent to 0.6 dS m–1 based on saturated paste extracts). Clearly, our results appeared to be consistent with soil structural stability and clay dispersion phenomena reported in the literature. There was no significant relationship (R2 ≤ 0.20) between any runoff parameter and soil pH or OM. We did find significant nonlinear relations between runoff TSS and soil CEC (R2 = 0.55, P < 0.05) as well as between runoff PP and soil CEC (R2 = 0.72, P < 0.01), which would be expected because soil CEC was primarily related to soil clay content and mineralogy in these generally low OM soils.

Multivariate regression analyses of the relationships between major runoff properties and selected soil properties were also conducted and compared (Table 3). Among the four soil properties, SST, clay content, EC, and SAR, the SST was clearly the single most dominant parameter relating to runoff TSS, turbidity, and PP in a linear fashion. Linear combination of clay content and soil EC yielded the similar R2 values as SST alone, suggesting that SST may indeed account for the integrated impact of clay and EC on runoff TSS and other parameters. The inclusion of SAR in the multivariate regression offered little improvement. Another noteworthy point is that the linear relationships between runoff parameters and SST were only slightly better than nonlinear regressions whereas runoff parameters were clearly better linked to soil clay content or EC in a curvilinear fashion. Overall, approximately 80 to 91% of the variability associated with runoff TSS, turbidity, and PP could be explained by SST alone or in combination with soil clay content and EC linearly or nonlinearly.


   Conclusions
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 1. Materials and Methods
 Results and Discussion
 Conclusions
REFERENCES
 
The study demonstrated the interrelationships among major runoff parameters and the effects of selected soil properties, especially soil clay content, EC, and suspendability. For these nine Louisiana cultivated agricultural soils with a clay content range of 111 to 438 g kg–1, highly significant and positive linear correlations existed between runoff TSS and turbidity as well as between runoff TSS and PP and between runoff turbidity and PP. Runoff parameters were clearly impacted by soil properties. Higher clay contents resulted in higher sediment concentrations in the runoff waters and their relationship could be best described by an exponential relationship (TSS = 0.10e0.01(Clay), R2 = 0.91, P < 0.001) for these loam to silty clay soils. Soil EC inversely related to runoff TSS whereas the newly devised SST test, a measure of soil suspendability, showed strong correlations with runoff TSS (y = 0.06x – 4.38, R2 = 0.82, P < 0.01), turbidity (y = 73.73x – 5442.53, R2 = 0.84, P < 0.001), and PP (y = 0.04x + 2.68, R2 = 0.85, P < 0.001). The SST was able to account for the integrated effect of soil clay content and electrolytic background on runoff TSS. The good fit of linear relationships between soil SST and runoff TSS or PP suggests that the SST test could be used to indirectly predict the potential loss of sediment and PP through surface runoff from these cultivated soils.

Although losses of sediment and nutrients from packed boxes are generally consistent with losses from field plots (Kleinman et al., 2004), the relationships derived in this study may represent a worst case scenario because the soil was bare and aggregate stability somewhat diminished compared to in situ soil. Future work is needed to validate these relationships for cultivated field soils and uncultivated soils such as pasture, for which runoff loss of P is often dominated by DP rather than PP. Successful prediction of sediment and PP in runoff could improve P indices since the latter also contributes to the bioavailable pool of P.


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ABSTRACT
 INTRODUCTION
 1. Materials and Methods
 Results and Discussion
 Conclusions
 REFERENCES
 
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   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 1. Materials and Methods
 Results and Discussion
 Conclusions
 REFERENCES
 





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The SCI Journals Agronomy Journal Crop Science
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