An ASABE Meeting Presentation Paper Number: 083970
Estimating Preferential Flow to Agricultural Tile Drains Mohamed Chikhaoui Brace Center, McGill University, Montreal,
[email protected]
Chandra Madramootoo Brace Center, McGill University, Montreal,
[email protected]
Mark Eastman Brace Center, McGill University, Montreal,
[email protected]
Aubert Michaud IRDA, Quebec,
[email protected]
Written for presentation at the 2008 ASABE Annual International Meeting Sponsored by ASABE Rhode Island Convention Center Providence, Rhode Island June 29 – July 2, 2008
Abstract. The data used in this study were collected at two experimental fields located near Bedford, Quebec. These agricultural sites are characterized by different soil types and instrumented to monitor the surface and subsurface tile drain flows. The data collected include concentration of fours tracers (Mg2+, Ca2+, Na+, K+) in runoff and subsurface waters and electric conductivity (EC). The relationship between EC and tracers permitted estimation of the concentration of different tracers used in this study. The estimation of preferential flow to tile drains was based on the principle of conservation of mass. In this study, the data collected during the base flow corresponds to the matrix flow. The validation of the results was based on the particulate P loads in the subsurface drainage. The analysis and interpretation of collected data improve the understanding of the mechanism of P transport in the soil profile through preferential or matrix flow. Preliminary results indicate that the elements (Ca2+, Mg2+) satisfactorily predict the extent of preferential flow. Our results have also found a strong correlation between these two elements and the EC with a R2 ranging from 0.96 to 0.99 for Gagnon site. The study showed that the preferential flow through a fine soil is dominant (70%). 2
Keywords. Preferential flow, Matrix flow, Tile drain, Phosphorus, Electric conductivity, Quebec
Introduction Excessive phosphorus (P) loading into freshwater bodies has deteriorated water quality in many regions of the world (Buczko and Kuchenbuch, 2007). Intensive land use activities, such as agriculture, tend to drastically increase P loading into surface waters. Eutrophication has been identified as one of the leading threats to lake water quality worldwide (Harper, 1992). Negative effects of eutrophication include: dissolved oxygen depletion, increases in suspended solids, decreased light penetration, and reduction in aquatic flora and fauna species (Migliaccio et al., 2007). Eutrophication may cause algal mats to form at the surface, limiting the recreational use of the lake, and occasionally toxin producing cyanobacteria develop, which further pollute surface waters. This complicates the water treatment process, often rendering the lake water unsuitable for human consumption. Traditionally, it was believed that P loss from agricultural landscapes occurred primarily during surface runoff events and that very little was lost through subsurface drainage. However, many researchers are now observing significant P losses occurring through subsurface drainage systems under a wide range of soil characteristics and management practices (Gardner et al., 2002; Beauchemin et al., 2003). In a study performed by Heckrath et al. (1995), P concentrations of 2.75 mg total P L-1 were measured in subsurface drainage waters in an alkaline clay soil. P loss from fine textured soils predominately occurs as particulate phosphorus (PP). Uusitalo et al. (2001) reported that PP loss from a clay soil in Sweden represented 92% of the total phosphorus (TP) loss for both surface runoff and subsurface drainage. Extensive macropore development, common to heavy clay soils, allows the movement of sediment and therefore PP down through the soil profile, exiting the subsurface drainage system. P loss on coarse textured soils has also been observed. Recent studies have shown in Quebec that the P is mobile in the subsurface and ultimately to the degradation of water quality. The factors that may enhance the mobility of P in subsurface is preferential flow. Chikhaoui et al (2006) and Michaud and Laverdière (2004) showed that preferential flow may cause high total particulate phosphorus loads in tile drain from fields with fine soil texture, in combination with high P fertilization. Further, this mechanism of transport minimizes the interactions between soil particle and water fluxes. According to Enright and Madramootoo (2004), macropores associated with cracks in clay soils are the important type of preferential flow path. Estimating preferential flow contribution to tile drain facilitates understanding the mechanism of P transport through soil profile. The approach based on the subsurface hydrograph separation with a tracer appears an appropriate method (Stone and Wilson, 2006).
The aim of this research was to investigate the effect of soil texture and structure on field hydrology and the mechanism of P transport in southern Québec and the estimation of preferential flow contributions to tile drains. The study was conducted in 2006 and 2007.
3
Materials and methods Site characteristics The study sites consisted of two single farm fields located approximately 5 km west of the town Bedford, Québec. Bedford lies 70 km southeast of Montreal and is located in the Pike River watershed (Figure 3.1). The Pike River watershed has an area of 630 km2 (243 mi2) and spans the Québec-Vermont border.
Pike River watershed
Lake Champlain
Field Sites
Missisquoi Bay
Figure 1. Map of the Pike River watershed and location of the field sites (LCBP, 2007) The two field sites were situated on privately owned lands and were approximately 3 km apart. Figure 1 displays the location of the field sites in the Pike River watershed. The field sites, commonly referred to as Gagnon and Marchand were established in 2000 and both had subsurface drainage installed. The subsurface drainage was installed with a trenchless plow in a systematic pattern with 11 cm diameter plastic corrugated laterals and 21 cm diameter outlets. The outlets were clay for Gagnon and corrugated plastic for Marchand. Lateral spacing was 10 m at Gagnon and 13 m at Marchand. The drains were installed at a depth of 1 m. The predominant soil type at Gagnon was Ste. Rosalie clay loam. The internal drainage of this soil is imperfect and it has a sand and clay content of 22% and 40%. This soil is characteristic of having a nuciform to massive structure (Cann et al., 1947) and very deep vertical cracks are common during the summer months when the soil is exposed to periods of extreme wetting and drying. The predominant soil types at Marchand was Rubicon sandy loam. The internal drainage of Rubicon sandy loam is fair and sand and clay contents are 59% and 10%. This soil is characteristic of having granular soil structure. Soil classification of the sites was obtained by local soil survey data. In addition, STP concentrations and P-Sat levels were calculated based on samples collected in early May 2007 and analyzed by the Mehlich-III procedure as described by Tran and Simard (1993). A complete list of the soil characteristics is available in Table 1.
4
Table 1. Field site characteristics Site
Surface Drainage Area
Subsurface Drainage Area
Soil Classification
Slope
STP
PSat
GAGNON
6.9 ha
7.8 ha
Suffield clay loam (21 %), Ste. Rosalie clay loam (70 %), Bedford sandy clay loam (9 %)
0.8%
145 kg -1 ha
7%
MARCHAND
5.2 ha
6.0 ha
Rubicon Sandy Loam
2.6%
289 kg -1 ha
17%
For Gagnon and Marchand the crops planted during the 2005-06 hydrologic year were soybeans under no-till management and alfalfa, respectively. A complete list of the crop characteristics is available in Table 2.
Table 2. Field site management practices Site GAGNON
Crop Practice
Tillage Practice
Fertilization Practice
2005: Corn
2005: Conventional
2005: 46 kg ha at planting
2006: Soybeans
2006: No-till
2006: No mineral P or manure addition
2005: Alfalfa
2005: Conventional
2005: 15 kg ha after 1 cut, 7 kg ha (manure) after rd 3 cut
2006: Alfalfa
2006: Conventional
2006: 15 kg ha after 1 cut, 7 kg ha (manure) after rd 3 cut
MARCHAND
-1
-1
st
-1
-1
st
-1
Topographic surveys were conducted on each field and digital elevation models (DEM) were created using ArcView GIS. Field drainage areas were obtained from the DEM using the autodelineation function within the ArcView-Soil and Water Assessment Tool interface. The surface drainage areas for Gagnon and Marchand are 6.9 and 5.2 ha, respectively. Subsurface drainage areas were based on the design of the tile drainage system and were 7.8 ha at Gagnon and 6.0 ha at Marchand.
Instrumentation and water analysis Both climatic and hydrologic measurements were made at each site. Precipitation was measured by tipping bucket rain gauges and air temperatures were measured with thermocouples. Measurements were checked for accuracy by comparing data with the Québec Ministry of Sustainable Development, Environment and Parks (MDDEP) Philipsburg weather station, which is approximately 9 km southwest of the sites. Surface runoff exited the fields through HS flumes. The water level in the flume was measured by two different sensors. The primary sensor was a Campbell Scientific SR50 ultrasonic depth sensor and the secondary sensor was a Keller 173 pressure transducer. Surface runoff volumes were calculated based on a rating curve, specific to the flume specifications at each site. Flowproportional, composite water samples were collected automatically by American Sigma water samplers. Grab samples were taken during large runoff events and results were compared to the composite samples for quality control purposes.
5
The subsurface drainage systems were modified to record discharge. Two sensors were installed at both sites. The primary sensor was an Endress and Hauser ProSonic DMU 93 ultrasonic flow meter and the secondary sensor was a Global Water, fixed, insertion flow meter. Similar to the surface runoff water sampling strategy; flow-proportional water samples were collected automatically by Global Water samplers from the tile drainage outlet, which lay 1 m below the soil surface. The sampler was activated for every 1 mm of subsurface drainage, and samples were collected in the composite form. Periodically, grab samples were taken and compared to composite samples for quality control purposes. Both grab and automatic samples were collected in contaminant-free 500 ml sample bottles. Immediately after collection, the samples were cooled to 4ºC and stored in the dark. Analysis of the water samples was performed by the Institut de Recherché et de Developpement en Agroenvironnement (IRDA) in Sainte-Foy, Québec. Suspended sediment concentrations were quantified by filtration through a 0.45 µm cellulose filter. Once filtered, the samples were exposed to persulfate mineralization to determine ortho-phosphate and total water-borne P by automated colorimetry, as described by Murphy and Riley (1962).
Estimation of preferential flow To estimate the preferential flow, we compare the concentration of four cation tracers (Mg2+, Ca2+, Na+, K+) in surface runoff and in base flow with corresponding concentration in tile drain discharge at the same storm. According to Steenhuis et al. (1994), the preferential flow water reflects the chemistry of water of runoff, while matrix flow water reflects the chemistry of water that has more contact time with soil. In our conditions, we consider that the water in tile drain during base flow conditions was matrix flow. In order to estimate the contribution of preferential flow to tile drain, we assume that the tile drain discharge is the combination of matrix flow and preferential flow. Based on the conservation of mass equations (Eq. 1) and the total solute flux in tile drain (Eq. 2), we estimated both type of flow (Stone and Wilson, 2006). It should be noted that evaluating the contribution of preferential flow to tile drain was done during two events.
Qd = Qm + Q p
(Eq.1)
Qd Cd = Qm Cm + Q p C p
(Eq.2)
Where, Qd = tile drain flow; Cd = concentration of tracer in drainage discharge; Cm = concentration of tracer in matrix flow; Cp = concentration of tracer in preferential flow. Based on Eq. 1 and Eq. 2, the contributions of preferential and matrix flow to tile drain can be estimated from Eq 3 and Eq 4.
Qp=
Qm =
Qd (Cd − Cm ) (C p − Cm ) Qd (Cd − C p ) (Cm − C p )
(Eq.3)
(Eq.4)
However, relationships were developed through regression analysis between electric conductivity (EC) data and the concentration of cation tracers. Those relationships were used to estimate the concentration of tracer in tile drain. 6
Results and discussion Hydrology Field scale hydrology was measured continuously during the 2005-06 hydrologic year at both Gagnon and Marchand sites. During the year, an average of 1134 mm of precipitation accumulated on-site. Of the 1134 mm, 220 and 79 mm left the sites through surface runoff at Gagnon and Marchand, respectively. In addition, 737 and 528 mm of subsurface drainage occurred. It was expected that Gagnon would produce more surface runoff than Marchand due to a higher clay content, but it was not expected to see more subsurface drainage at Gagnon than Marchand. Traditionally, it has been believed that fine textured soils lead to increased surface runoff because drainage is poor, which should result in a reduction in subsurface drainage. In order to explain this phenomenon, attention was paid to the differences in soil structure. As a result, it was determined that Gagnon, which had a high clay content was prone to soil cracking and these cracks allowed surface waters to rapidly infiltrate the soil profile down to the subsurface drains and exiting the field very quickly. This form of flow is often referred to as preferential flow. In comparison, Marchand which has a low clay content had very little soil cracking which resulted in a slower movement of water from the soil surface to the subsurface drains before exiting the field. This form of flow is commonly referred to as matrix flow.
Phosphorus losses in surface and subsurface drainage Similar to hydrology, P losses from Gagnon and Marchand were measured during the 2005-06 hydrologic year. Despite a lower P concentration and P-Saturation than Marchand and the absence of a manure application in 2006 at Gagnon, it produced 4.0 kg ha-1 of total phosphorus (TP) while Marchand only produced 1.2 kg ha-1. The reason for such a substantial difference in annual TP loading is because TP loss from the subsurface drainage at Gagnon was much greater than Marchand, while surface runoff loads were comparable. Gagnon’s elevated TP loss in the subsurface drainage system is a result of particulate phosphorus. PP contributed 1.8 kg ha-1 of TP through the subsurface drainage system and subsurface PP loss from Marchand was negligible. Because subsurface PP loss was substantial at Gagnon and not at Marchand it is assumed that the form of flow (preferential vs. matrix) influences the TP loading. The results from the data gathered during the 2005-06 year led the researchers of this study to investigate a method to estimate the extent of preferential flow on an event basis at the field-scale in order to estimate the risk of subsurface P loss from a particular field.
Estimating preferential Flow Table 3 illustrates the relationships between EC and concentration of cation tracers in tile drain. For both sites, a strong positive correlation was found between EC and Ca2+, Mg2+with a R2 value ranging from 0.98 and 0.99 for Gagnon site. Given these results, the Ca2+ and Mg2+ were chosen as tracer. Table 3. Relationships between electric conductivity (µS/cm) and concentration of cation tracers (mg/l) Gagnon
Marchand
2+
0.99**
0.96**
+
0.98**
0.65*
2+
0.99**
0.98**
+
0.98**
0.61*
Ca K
Mg
Na
7
** and * significant at α=0.05 and 0.01 respectively.
Figure 2 shows the rainfall and tile drain flow from 20 October for Gagnon site. Figure 3 presents the result of the hydrograph separation. Figure 4 and 5 show the result from 14 March for Marchand site. These events vary greatly in rainfall intensity. We noted also that hydrographs vary. Graphical comparison shows that preferential flow was the dominant (70%) form of water transport through the clay loam soil profile (Gagnon), while matrix flow was the dominant (80%) form of transport through the sandy soil loam soil (Marchand). Also, the peak of preferential flow coincided with the peak of the tile drain for both sites. Moreover, hydrograph separation from Gagnon site indicates that the contribution of preferential flow was relatively higher with Mg2+cation compared to Ca2+ tracer. It’s likely due to the fact that Ca2+ was more correlated to EC than Mg2+. Gagnon- Oct 20, 2006 Hydrograph 0
30
Precipitation 25
Subsurface Drianage Surface Runoff
20
2
Precip. (mm)
Flow (l/s)
4 15 6 10 8
5
10
0 Da t e
Figure 2. Rainfall and tile drain flow from Gagnon site Gagnon oct 2006 (Mg)
Gagnon - Oct. 20, 2006 (Ca) 30
30
Preferential flow
Preferential flow
Preferential flow Matrix flow
25
25
Matrix flow
Tile drain flow (l/s)
20 15 10
20 15 10
5 5
0 20-Oct
21-Oct
21-Oct
21-Oct
22-Oct
22-Oct
22-Oct
0 1930
300
1030
Date
1800
130
900
1630
Date
Figure 3. Separated tile drain flow hydrograph from Gagnon site Marchand- March 14, 2007 Hydrograph 12
0 Precipitation Subsurface Drianage
10
Surface Runoff
3
6
6
4
Precip. (mm)
8 Flow (l/s)
Tile drain flow (l/s)
Matrix flow
9 2
12
0 Date
Figure 4. Rainfall and tile drain flow from Marchand site
8
Marchand March 14, 2007 (Ca)
Marchand March 14, 2007 (Mg)
12
10 9 Preferential flow
Preferential flow
8
Matrix flow
6
3
Matrix flow
7
Tile drain flow (l/s)
Tile drain flow (l/s)
9
6 5 4 3 2 1
0 13-Mar
14-Mar
15-Mar
16-Mar
17-Mar
18-Mar
18-Mar
0
19-Mar
945
815
645
515
345
Date
215
45
2315
2145
Date
Figure 5. Separated tile drain flow hydrograph from Marchand site
Figure 6 shows the relationship between the percentage of PP loads in tile drain and the percentage of contribution preferential flow to tile drain. The correlation was more interesting from Gagnon site with Ca2+ cation (R2 = 0.79) compared to Mg 2+ tracer (R2 = 0.66). Thus, Ca2+ cation might separate satisfactorily the contribution of preferential and matrix flows to tile drain. Moreover, figure 6 illustrates how preferential flow might affect PP transport mechanism. Conversely, increasing contribution of preferential flow increases the ratio of PP losses in tile drain. In addition, the non-relationship observed herein is consistent with the initiation of turbulent flow through macropores according to Germann and Beven (1981).
Total particulate phosphorus %
100 y = 89,36 Ln(x) - 270,96 R 2 = 0,79 75
y = 85,25 Ln(x) - 252,79 R 2 = 0,66
50
25
0 0
10
20
30
40
50
60
70
Contribution of preferential flow to tile drain %
Figure 6. Relationship between contribution of preferential flow and percentage of PP loads in tile drain
Conclusions The clay loam site (site A) was more hydrologically responsive in terms of surface runoff and subsurface drainage than the sandy loam site. Subsurface drainage contributed 737 and 528 mm to surface waters at Gagnon and Marchand, respectively. PP was the dominant (78%) form of P loss from the subsurface drainage system at the clay loam site. It’s likely explained by the type of flows and soil profile. The preferential flow through a fine soil was dominant (70%), while matrix flow through a coarse soil is dominant (80%). Other factors increased the ratio of PP into tile drain. High intensity storms contribute larger proportions of preferential flow to tile drains than lower intensity storms. The peak of preferential flow coincided with the peak of tile drain. The strong positive relationship between PP rate and contribution of preferential to tile drain confirm that preferential flow is an important transport mechanism for PP.
9
Preliminary results indicate that the elements (Ca2+, Mg2+) predict satisfactorily the extent of preferential flow. The performance of tile drain separation is difficult to asses and requires further research.
References Beauchemin, S., R.R. Simard, M.A. Bolinder, M.C. Nolin, and D. Cluis. 2003. Prediction of phosphorus concentration in tile-drainage water from the Montreal lowlands soils. Canadian Journal of Soil Science. 83: 73–87. Buczko, U. and Kuchenbuch, R. O. 2007. Phosphorus indices as risk-assessment tools in the U.S.A. and Europe—a review. J. Plant Nutr. Soil Sci. 170: 445–460. Cann, D.B., P. Lajoie and P.C. Stobbe. 1947. Soil Survey of Shefford, Brome and Missisquoi Counties in the Province of Québec. Experimental Farm Service, Dominion Department of Agriculture in Co-operation with the Québec Department of Agriculture and Macdonald College, McGill University. Ottawa, QC: Edmond CloutierGardner, C.M.K., K.M. Cooper, and S. Hughes. 2002. Phosphorus in soil and field drainage water in the Thames catchment, UK. Science of the Total Environment. 282: 253–262. Chikhaoui, M., C.A. Madramootoo, and N. Stämpfli. 2006. Effect of tile drain spacing on phosphorus losses from agricultural fields. In. 22rd Eastern Canadian Symposium of the Canadian Association on Water Quality, Concordia University, Montréal. Enright, P. and C.A. Madramootoo. 2004. Phosphorus losses in surface runoff and subsurface drainage waters on two agricultural fields in Quebec. In Proceedings of the Eighth International Drainage Symposium, Sacramento, California, March 21, 2004. St. Joseph, MI: American Society of Agricultural Engineers. Germann, P. and Beven, K. 1981. Water flow in soil macropores. I. An experimental approach. J. Soil Sci. 32: 1-13. Heckrath, G., P.C. Brookes, P.R. Poulton and K.W.T. Goulding. 1995. Phosphorus leaching from soils containing different phosphorus concentrations in the Broadbalk experiment. Journal of Environmental Quality. 24: 904-910. Lake Champlain Basin Program (LCBP). 2007. The Lake Champlain Basin Atlas: Mississquoi/Pike Basin. Available online at [http://www.lcbp.org/Atlas/PDFmaps/nat_miss.pdf]. Migliaccio, K.W., I. Chaubey and B.E. Haggard. 2007. Evaluation of landscape and instream modeling to predict watershed nutrient yields. Environmental Modelling and Software. 22: 987-999 Michaud, A. R. and M. R. Laverdière. 2004. Effects of cropping, soil type and manure application on phosphorus export and bioavaibility. Can. J. Soil Sci. 84(3):295-305. Murphy, J. and J.R. Riley. 1962. A modified single solution method for the determination of phosphates in surface waters. Analytica.Chimica Acta. 27: 31-36. Sharpley, A.N., T.C. Daniel, and D.R. Edwards. 1993. Phosphorus movement in the landscape. Journal of Production Agriculture. 6: 492-500. Steenhuis, T.S., J. Boll, G. Shalit, J.S. Selker and I.A. Merwin. 1994. A simple equation for predicting preferential flow solute concentrations. J. Environ. Qual. 23:1058-1064. Stone, W.W. and J.T., Wilson. 2006. Preferential flow estimates to an agricultural tile drain with implication for Glyphosate transport. J. Environ. Qual. 35:1825-1835. Uusitalo, R., E. Turtola, T. Kauppila and T. Lilja. 2001. Particulate phosphorus and sediment in surface runoff and drainflow from clayey soils. Journal of Environmental Quality. 30: 589595.
10
Tran, T.S. and R.R. Simard. 1993. Mehlich III - Extractable elements. In Soil Sampling and Methods of Analysis, ed. M.R. Carter, 43-49. Lewis Publishers.
11
