Research ArticleResearch Section

Comparing the short- and long-term impacts of subsurface drainage installation on soil physical and biological properties

A.L. Frankl, K.T. Sherbine, J.S. Strock, F.G. Fernández, A.M. Cates and L.A. Pease
Journal of Soil and Water Conservation November 2023, 78 (6) 457-465; DOI: https://doi.org/10.2489/jswc.2023.00147

Abstract

Subsurface drainage is a common practice used to support agricultural production and increase yields in poorly drained soils. Following decades of subsurface drainage installation, agricultural fields often have increased water discharge and nutrient losses. However, few studies have evaluated the changes in soil properties or soil health metrics at different ages of subsurface drainage. In this study, we attempt to quantify changes to soil properties over time. To achieve this, we sampled six fields in northwest Minnesota representing two timescales: three fields were drained more than 15 years prior to sampling (i.e., subsurface drainage installed prior to 2006), and three fields were drained within 5 years of sampling (i.e., subsurface drainage installed after 2016). We evaluated three soil physical properties: saturated hydraulic conductivity (Kfs), bulk density, and aggregate stability, as well as three soil health metrics at 0 to 15 and 15 to 30 cm: water-extractable organic carbon (WEOC) and nitrogen (WEON), and potentially mineralizable carbon (PMC). The fields with older drainage systems had greater Kfs, WEON (all depths), WEOC (15 to 30 cm), and PMC (15 to 30 cm). There were no differences in bulk density, aggregate stability, WEOC (0 to 15 cm), and PMC (0 to 15 cm). We suspect that the increased Kfs is likely the result of further development of preferential flow pathways in fields with older drainage systems. These preferential flow paths could also be areas with increased microbial diversity and activity, indicated by the higher biological indicators in the fields with older drainage systems. Our findings suggest that nutrient losses, soil physical properties, and soil health metrics evolve over time. These metrics should be tracked as a standard practice in drainage research to improve our understanding of how subsurface drainage installation changes long-term soil properties. This knowledge will improve the information provided to growers and help them more effectively manage their soil’s health and reduce nutrient losses into waterways.

Key words:

Introduction

Subsurface drainage is a common practice used to support agricultural production in poorly drained soils. Drainage removes excess water from the soil profile, lowering water tables and increasing field trafficability. This allows for timely field operations, prevents water logging, and increases yields (Abid and Lal 2009; Evans and Fausey 2015). As of 2017, 22.5 million ha of agricultural land were reported to have artificial subsurface drainage, a 12.7% increase from 2012 (USDA 2017). In Minnesota alone, 3.3 million ha (approximately 32% of statewide agricultural land) utilized subsurface drainage in 2017, a 20.0% increase from 2012 (USDA 2012, 2017). Drainage systems in the United States are also aging. In 1985, the USDA estimated that 15.1 million ha in the United States had been artificially drained, suggesting that a substantial percentage of subsurface drainage systems may be over 40 years old (Pavelis 1987). There is a need to understand to what extent long-term drainage impacts soil properties and the transport of nutrients through the soil.

Previous studies have tracked long-term nutrient losses from subsurface drainage (Kladivko et al. 2004; Kladivko and Bowling 2021), while others have utilized models to simulate changes in hydrology or nutrient losses due to subsurface drainage over time (Ahmed et al. 2007; Negm et al. 2016; Singh et al. 2020). However, relatively few studies have evaluated changes in soil properties and soil health metrics associated with long-term subsurface drainage, particularly in Midwest cropping systems (Talukolaee et al. 2018; Welage 2020). In their 31-year long-term drainage study, Kladivko and Bowling (2021) noted increasing trends in both volume and peak flow rates over time. They hypothesize that these changes may be due to changes in soil properties from drainage. In our study, we explore the potential mechanisms for observed changes in drainage discharge by evaluating soil physical and biological properties in fields with different drainage ages.

Some properties, such as saturated hydraulic conductivity (Kfs) of soil, have been widely measured and modeled in past drainage research (Hundal et al. 1976; Bouma et al. 1979; Jia et al. 2008; Alakukku et al. 2010; Welage 2020). Understanding how Kfs changes over decades of subsurface drainage use can help growers better understand the evolution of water and nutrient dynamics in their fields. Additionally, preferential flow, or the rapid transmission of water and nutrients through the soil profile via macropores (Bouma 1981), often leads to increased volumes of water and nutrient losses through drainage systems (Stone and Wilson 2006). In systems with long-term drainage, preferential flow paths and cracks often develop in soil over time and increase drainage, infiltration, and Kfs (Kladivko and Bowling 2021).

Alongside assessing water flow through soil with Kfs, bulk density and aggregate stability are direct metrics of soil structure aeration and porosity (Hundal et al. 1976). Bulk density has been shown to decrease with the installation of subsurface drainage systems (Chow et al. 1993; Baker et al. 2004), although the effects are of varying magnitudes, with some effects not statistically significant (Hundal et al. 1976; Lal and Fausey 1993; Wells and Williams 1996; Jia et al. 2008). The impact of subsurface drainage on wet aggregate stability remains unclear, with some studies noting an increase in aggregate stability (Hundal et al. 1976; Baker et al. 2004; Abid and Lal 2009), and others finding negligible or decreasing aggregation properties (Lal and Fausey 1993; Kumar et al. 2014).

As drainage alters the soil physical environment, it can also alter soil biological processes in the soil ecosystem and microorganism activity, specifically by altering pore size distribution (Görres et al. 1999; Kravchenko and Guber 2017). However, few studies have examined the impact of drainage on soil biological metrics. Some studies have noted the loss of carbon (C) in dissolved form following subsurface drainage and the concurrent depletion of soil organic C stock; however, overall C stocks may be balanced by increased crop productivity (Jacinthe et al. 2001; McTiernan et al. 2001; Ruark et al. 2009; Kumar et al. 2014). Several organic matter fractions have been proposed as commercially scalable indicators of soil microbial activity and biological health. For example, the Haney Soil Health Test, also known as the Soil Health Tool, commonly used by many laboratories and the USDA Natural Resources Conservation Service (NRCS) to evaluate soil health (Haney et al. 2012) includes potentially mineralizable C (PMC), water-extractable organic C (WEOC), and water-extractable organic nitrogen (WEON) as metrics of microbially available substrate. Assessing baseline expectations for drained and undrained conditions is critical for interpreting results. The PMC, WEOC, and WEON have frequently illustrated changes in soil with cropping system (Grebliunas et al. 2016; Diederich et al. 2019), but they have also been seen to vary seasonally (Martin and Sprunger 2022; Zhelezova et al. 2022). Recent work in northwestern Minnesota found that PMC, WEOC, and WEON did not shift in the first two years of subsurface drainage (Sherbine et al. 2023), but no study has evaluated these pools over longer periods of changed hydrology. Recent work has shown that WEOC is very sensitive to soil moisture, with higher levels released after dry conditions (Homyak et al. 2018; Patel et al. 2021b). Examining differences in PMC, WEOC, and WEON at two drainage ages may provide valuable information on how microbially available C/N pools evolve with changing hydrology. Providing more baselines and interpretations to the established Haney Soil Health Test will help further the applicability of these indicators, generating a common framework for soil health practices (Stewart et al. 2018).

In this study, we attempt to quantify differences between fields with different drainage ages and use these measurements to better understand the impact of drainage age on soil physical properties and biological indicators. We then propose mechanistic explanations for these differences. At sites with long-term drainage, we expect to see increases in Kfs and aggregate stability, as well as decreases in bulk density, all trends seen in other locations in the Midwest. We also expect to see decreases in biological indicators due to C depletion in the soil profile; however, increased crop productivity from subsurface drainage installation may mitigate this effect. Focusing on the relationship between drainage age and soil properties is a novel approach to understanding the effects and dynamics of long-term drainage on the soil ecosystem.

Materials and Methods

Seven agricultural fields were sampled (table 1): three were drained before 2005 (referred to as “>15”), three after 2016 (referred to as “<5”), and one was never drained (“undrained”; used as benchmark). All fields were located within the Red River of the North Basin (RRB), and within Polk, Marshall, and Traverse counties (figure 1). To minimize variability, we targeted silty clay loam soils as defined by NRCS’ SSURGO, but found some sites were classified as clay (table 1). Crops were either corn (Zea mays L.) or wheat (Triticum spp. L) and are typically rotated in this region with soybean (Glycine max L.) and sugar beet (Beta vulgaris L.). While Farm 2 was strip-tilled, the other fields were conventionally tilled during the year of sampling. All sampling occurred during July of 2021, with similar soil conditions due to drought.

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Table 1

Site descriptions for sampling locations. All sampling locations used conventional tillage (generally intensive, high disturbance) and management practices unless noted. Particle percentages are from Laser Particle Size Analysis (PSA) and are an average of 16 samples at each field, including 8 samples from 0 to 15 cm and 8 from 15 to 30 cm.

Figure 1
Figure 1

Approximate site locations in the Red River of the North Basin (RRB). Extent of the RRB in Minnesota, North Dakota, and South Dakota is highlighted. NWROC is “Northwest Research and Outreach Center.”

Soil Sampling. At each field, eight sampling locations were identified for analysis. At each sampling location, 7 cm diameter cores were sampled from 0 to 15 cm and 15 to 30 cm using an AMS Soil Core Sampler between rows (AMS, American Falls, Idaho). These cores were used for bulk density, texture, PMC, WEOC, and WEON.

Hydrology is known to vary spatially based on subsurface drainage line locations, but we were not able to fully account for this in our sampling design. At Northwest Research and Outreach Center (NWROC) sites, four sampling locations were located within 2 m of a subsurface drainage line, and four were located equidistant between drain lines. However, at on-farm sites, the exact locations of subsurface drains were unknown, and samples were distributed approximately one and a half drain spacings apart (i.e., 27 m for fields with 18 m spacing) to capture variation.

Hydraulic Conductivity. At each sampling location, a SATURO Infiltrometer (METER Group, Inc., Pullman, Washington) was used to calculate field Kfs. The SATURO dual head infiltrometer is a single-ring infiltrometer. To measure Kfs, the SATURO ponded water onto the soil surface inside an insertion ring pounded 10 cm deep in the soil. The SATURO then automatically pumped air and water to achieve specific pressures on the soil surface. During each 95-minute run, two cycles were deployed at two heads (0 cm for low pressure and 10 cm for high pressure). At each pressure, once steady-state conditions were achieved, the infiltration rates were measured for 10 minutes and Kfs was calculated by the SATURO infiltrometer software that uses a simplified equation derived from Reynolds and Elrick (1990) (equation 1):

Embedded Image 1

where D1 is the high-pressure head, D2 is the lower pressure head, Δ = 0.993 × insertion depth of the infiltrometer + 0.578 × radius of the infiltrometer, i1 is the infiltration rate at the high-pressure head, and i2 is the infiltration rate at the lower pressure head. Machine error (if the machine was not able to reach constant pressure due to soil terrain or large roots) occurred during field analysis, and runs that demonstrated inadequate equilibration were discarded or re-run.

We hypothesized that we would observe differences in Kfs between measurements taken nearby subsurface drainage lines and those equidistant between lines; however, the connection between drain spacing and Kfs (or infiltration) are not clear (Jia et al. 2008; Welage 2020). Additionally, we expected hydraulic conductivity rates to be potentially impacted by historic crop (or standing crop) due to decomposed root material (Mitchell et al. 1995; Govaerts et al. 2007).

Aggregate Stability. Soil samples for aggregate stability analysis were collected at 0 to 15 cm within a 15 × 15 cm area using a shovel (eight samples per site). Soil was gently broken along natural structural planes and lightly mixed in the field (Norris et al. 2020). Samples were then air-dried, lightly mixed, and a subsample of aggregated soil was selected for analysis, avoiding loose, unaggregated soil.

To assess wet aggregate stability in lab, a 50 g subsample was placed on a stack of four sieves (2 mm, 1 mm, 250 μm, and 53 μm), and soaked by capillary for 10 minutes (Kemper and Rosenau 1986). Samples were then shaken using a mechanical sieving machine through a stroke length of 4 cm, 30 times per minute for 10 minutes. All sample materials were collected from each sieve and oven-dried at 105°C until a constant weight was achieved. Each fraction was then weighed and corrected for moisture and coarse fragments (Aksakal et al. 2020).

Bulk Density. Field-moist soil cores were weighed, dried at 110°C for at least 24 hours, and weighed again. Using these measurements, soil water gravimetric water content (GWC) was calculated (equation 2):

Embedded Image 2

Bulk density (g cm−3) was also calculated for each sample (equation 3):

Embedded Image 3

The volume of sample was calculated from the volume of the soil core.

Textural Analysis. To determine soil texture, Laser Particle Size Analysis (PSA) was conducted on a subset of samples (four sampling locations at each site, at both depths) (table 1). Particle size analysis was chosen as the preferred method due to its relative accuracy with smaller particle sizes (Miller and Schaetzl 2012). Approximately 0.5 g of soil (dried, ground, and passed through a <2 mm sieve) was placed in a 30 mL bottle. Then, 5 mL of 5% sodium hexametaphosphate (Na6[(PO3)6]; dispersing agent) and 5 mL of bleach (to remove organic matter) were added to the sample. Samples were then brought to a volume of 25 mL with deionized water and shaken for 24 hours at 30 rpm. Shaken samples were then analyzed using a Malvern Mastersizer 3000 (Malvern Panalytical, Malvern, United Kingdom), determining fractions of particle size and soil texture.

Potentially Mineralizable Carbon. PMC measures part of the microbially available soil C. This assay indicates both the activity of the microbial community and the amount and quality of substrate available (Franzluebbers et al. 2000; Cates et al. 2019). The PMC assay measures carbon dioxide (CO2) flush under optimal conditions. Ground soil samples (3.0 g) in triplicates were rewetted to 50% water-filled pore space, sealed in a 1 L canning jar to incubate for 24 hours at 25°C, and the concentration of CO2 in each jar was measured using a LiCor LI-830 and corrected using blanks (1 L canning jar without soil or water, incubated under the same conditions).

Water-Extractable Organic Carbon/Nitrogen. WEOC and WEON, measures of microbially available substrate, were estimated on 16 subsamples (method adapted from Haney et al. [2012]). Ground and dried soil samples (4.0 g) and 40 mL of deionized water were placed into centrifuge tubes, shaken for 10 minutes on a reciprocal shaker, and centrifuged for 5 minutes at 3,500 rpm. The supernatant filtered through Whatman 2V filter paper was placed into glass vials and diluted 1:4 with deionized water for analysis to create a 19.9 mL sample. To neutralize organic C, 0.1 mL of 2 M hydrochloric acid was added to each sample. Extracts were then mixed and measured in a Shimadzu TOC-L Laboratory Total Organic Carbon Analyzer (Shimadzu, Kyoto, Japan) for organic C and total N (TN). Extracts were also evaluated at the University of Minnesota Research Analytical Laboratory for inorganic N (nitrates [NO3−], nitrites [NO2−], and ammonium [NH4+]). These values were then subtracted from TN to calculate WEON.

Statistical Analysis. All statistical analyses were completed using the R programming language (version 4.2.0; R Core Team 2022). Following checks for normality, mixed models were analyzed using analysis of variance (ANOVA). Terms of the model included: drainage age (fixed), depth (fixed), and crop (random; interaction term between drainage and crop also used). Crop was included to account for different water use between crops. If depth was statistically significant, separate models were constructed for each depth. Transformations were used as necessary (WEON and WEOC were log-transformed). The statistical threshold for significance was 10%. Although included in the visual analysis, the undrained field was not included in the statistical analysis due to lack of replication.

Results and Discussion

Climate and Sampling Conditions. The summer of 2021 was particularly dry and hot in northwestern Minnesota (table 2). The mean annual precipitation for Crookston is 565.9 mm (1991 to 2020, Midwest Regional Climate Center). In 2021, Crookston (all sampling sites located within approximately 150 km of Crookston) received 434.0 mm of rain, with only 209.3 mm between April and September. During the sampling period in July, Crookston (and nearby counties, including all sites from this study) received less than 2.5 mm of precipitation. Dry climatic conditions resulted in extremely dry soil conditions, and it was not possible to collect soil cores from 15 to 30 cm at Farm 2 (where GWC content ranged between 2.4% and 7.5%).

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Table 2

Mean annual precipitation (MAP) and mean annual temperature (MAT) for the past 30 years and in 2021 at each sampling location.

The unusual drought conditions during this study resulted in no drainage and homogeneous moisture conditions at all sites. The data in this study therefore represent the long-term effects of subsurface drainage (i.e., changes to soil properties), not the immediate effect of drainage on soil water status. In addition, the results from this study should be viewed with understanding of these exceptional climatic patterns and unique soil conditions during the period of study.

Soil Physical Properties. In the >15 fields, Kfs rates were 7.58 cm h−1 faster than <5 fields (p < 0.05) (figure 2, table 3). There was no significant difference between bulk density or aggregate stability of the two treatments (figures 3 and 4). There was no difference in soil physical properties between fields with standing wheat and those with standing corn.

Figure 2
Figure 2

Box and whisker plots of saturated hydraulic conductivity (Kfs) values for fields at >15 years (blue), <5 years (green), and undrained (pink). The whiskers demonstrate the minimum and maximum values, while the box outlines the lower quartile, median value, and upper quartile.

View this table:
Table 3

Summaries of soil physical properties and soil biological indicators.

Figure 3
Figure 3

Percentage water-stable aggregated by five size classes for the three treatments: fields drained for >15 years (left), <5 years (center), and an undrained (right) control.

Figure 4
Figure 4

Bulk density of soils at 0 to 15 cm (upper) and 15 to 30 cm (lower) from fields drained for >15 years (blue), <5 years (green), and an undrained (pink) control.

The faster Kfs rates observed on the >15 fields compared to the <5 fields may point to the development of macropores and subsequent prominent preferential flow paths to subsurface drains that occur over many years (decades) of subsurface drainage (Stamm et al. 1998; Stone and Wilson 2006). Although preferential flow pathways exist in soil profiles with or without subsurface drainage, the installation of drainage can increase the connectivity of macropores that enable preferential flow and have a significant effect on the rate of water movement through soils (King et al. 2015; Pluer et al. 2020).

While all fields were sampled at similar GWC levels (5% to 10%), it is likely that the smectite clay mineralogy seen in most of the clay-rich soils sampled in this study led to shrink-swell conditions and increased preferential flow paths (Beauchemin et al. 1998; Kladivko et al. 2001). Hydraulic conductivity rates have been demonstrated to vary with soil water content, with its highest values occurring when the soil has low antecedent water content (Messing and Jarvis 1990; Jabro 1996). It is possible that the Kfs values in this study are greater across all sites due to the drought conditions, but these conditions were likely not the source of variation between treatments, as soil GWC was similar across most fields (the undrained field was the highest at 11% GWC, which is below the wilting point for these soils). Therefore, the differences in Kfs can more likely be attributed to long-term changes in soil properties, and not drought conditions.

Because higher moisture regimes generally have less stable macroaggregates than lower moisture regimes, as well as microaggregates to a lesser extent (Lehrsch and Jolley 1992; Cates et al. 2019), we expected a relationship between drainage treatment and macroaggregate stability. Instead, it is likely that tillage was a confounding factor impacting aggregate distribution in this study (as discussed in Tisdall and Oades [1982], Hajabbasi and Hemmat [2000], and Kasper et al. [2009]). At Farm 2 (<5 drained), the only field with reduced tillage, 87% of all aggregates were >2 mm, compared to the study average of 60% (figure 3). The impact of reduced tillage on preserving macroaggregates is well known (Six et al. 2000; Mikha and Rice 2004; Kasper et al. 2009). For microaggregates, these results appear to be similar: Farm 2 has a much smaller percentage of microaggregates than the study average (7% compared to 12%). The differences are perhaps less extreme for microaggregates because they are more persistent through disturbance from tillage (Six et al. 2000; Kasper et al. 2009; Du et al. 2013). Controlling for tillage in future studies would allow for more exploration of the effect of the persistent hydraulic regime on aggregate size distribution.

Due to the number of studies citing decreased bulk density with subsurface drainage installation (Baker et al. 2004; Jia et al. 2008), we expected bulk density to decrease in fields with longer-term subsurface drainage, as longer-term drainage would have a stronger effect (or perhaps a relationship with another factor, such as tillage). Additionally, bulk density is often a predictor of Kfs and is used to approximate Kfs in models (Jabro 1992; Rawls et al. 1997). Our study found trends (also seen in Chow et al. [1993] and Baker et al. [2004]) of lower bulk density (but not statistically significant) with increased drainage age, particularly at the 15 to 30 cm depth increment (table 3, figure 4). Hundal et al. (1976) found similar results when comparing drained and undrained soils, with greater Kfs in drained soils, and smaller (but not statistically significant) bulk density in drained soils. It is possible that the reduction in bulk density caused by drainage becomes more apparent over time or that this effect is confounded by varying tillage practices.

The results from this study indicate that while Kfs (a function) related to soil physical properties changed due to drainage age, soil properties changed to a lesser extent (bulk density) or are more heavily controlled by other factors such as tillage (aggregate stability). While we expected to see these two properties change in greater magnitude, it is possible that these metrics’ sensitivity to drainage is lesser and therefore more difficult to identify.

Soil Biological Indicators. The >15 treatment had generally higher biological indicators (table 3). WEON was greater in the >15 treatment than in the <5 treatment at 0 to 15 cm (p < 0.01) (figure 5c). At the 15 to 30 cm depth increment, the >15 treatment had greater PMC and WEOC (p < 0.1), as well as greater WEON (p < 0.01) than the <5 treatment (figures 5a, 5b, 5c, and table 3). The random effect of crop was not significant at the 0 to 15 cm increment PMC, WEOC, and WEON (figures 5d, 5e, and 5f), but at the 15 to 30 cm increment, all three were greater in standing corn versus wheat (figures 5d, 5e, and 5f).

Figure 5
Figure 5

(a) Potentially mineralizable carbon (PMC), (b) water-extractable organic carbon (WEOC), and (c) water-extractable organic nitrogen (WEON) from fields drained >15 years (blue), <5 years (green), and undrained (pink) control at 0 to 15 cm and 15 to 30 cm. (d) PMC, (e) WEOC, and (f) WEON from standing corn (yellow) or wheat (red) including all drained fields. Note: Asterisk indicates difference between treatments (either drainage treatment in [a], [b], and [c] or crop in [d], [e], and [f]; p < 0.1).

For these biological indicators, it appears that there were two factors influencing biological activity on different timescales. On the seasonal scale, standing crop influenced the biological communities, as seen by the higher PMC, WEOC, and WEON values in standing corn versus standing wheat, particularly at the lower depth. Over a longer scale, we observed greater labile organic matter pools as drainage systems age (figure 5b).

At the time of sampling in late July, the standing wheat was nearing physiological maturity, and therefore its photosynthetic rate was in decline (Del Blanco et al. 2000; Shah and Paulsen 2003). In comparison, standing corn was at approximately the V10 to V12 growth stages at sampling, when photosynthesis, root exudate production, and microbial activity were likely significantly higher (Rochette and Flanagan 1997), boosting levels of higher biological indicators (Martin and Sprunger 2022).

On a longer timescale, the older systems’ higher biological metrics may be the result of increased crop productivity due to drainage over time. While subsurface drainage may decrease C stocks over time in naturally poorly drained soil with high organic matter (Fernández et al. 2017), C flows into and from the system are likely greater, as demonstrated by increases in yield over time (Janzen 2006; Wood et al. 2016; Kladivko and Bowling 2021). Deeper sampling might provide more insight into this possibility, as C stocks could likely decrease deeper in the profile due to mineralization and aeration but remain elevated in the upper portion due to increased inputs (Mitchell 2020).

The increased hydraulic conductivity seen in >15 fields may have boosted soil organic matter metrics by increasing biological activity along preferential flow paths (Franklin et al. 2021). Preferential flow paths have been identified as areas of increased biological activity, with larger microbial biomass, although these pockets of increased biological activity have proved difficult to quantify (Bundt et al. 2001b; Baveye and Laba 2015). Preferential flow paths include reduced anoxic conditions (Anthony et al. 2020), wet-dry cycles, and superior nutrient and substrate supply that can facilitate pockets of high microbial activity compared to other parts of the soil profile (Bundt et al. 2001a; Chabbi et al. 2009; Fuhrmann et al. 2019; Franklin et al. 2021).

A secondary explanation for these increases in biological activity may be the antecedent moisture conditions. It was long believed that C-based biological indicators had a linear relationship with GWC and were dependent only on current moisture content (Patel et al. 2021b). However, recent studies have demonstrated that antecedent moisture can impact microbial communities and activity, and drought in particular can boost measurable labile C (Smith et al. 2017; Hawkes et al. 2020; Patel et al. 2021b, 2021a). Soil may experience variable distribution of water based on their antecedent moisture conditions; therefore, different sources of C may be activated based on antecedent moisture (Patel et al. 2021a). Soils with drier conditions had high levels of WEOC and C mineralization when re-wet, since they mobilize more C and provide greater access to substrates (Patel et al. 2021a, 2021b). In these high pH soils, where redox is not a main driver in microbial activity, it is possible that the longer-term wet-dry cycles, greater preferential flow after >15 years of drainage, and more rapid aeration of the soil profile generated drier antecedent moisture conditions in bulk soil not in contact with micropores, leading to greater active C pools measured in this study.

Summary and Conclusions

In summary, we found soil properties in fields with subsurface drainage likely evolved over time. As Kfs was elevated more significantly than other properties in longer drained fields, we suggest that preferential flow is a driver of this evolution. Interestingly, other soil physical properties changed with drainage age to a lesser extent, as tillage or other factors likely overshadowed the effect of changing hydrology. However, the changes in moisture and oxygen contents due to drainage had an apparent effect on microbial activity, increasing active N and C, especially below 15 cm.

While studies often compare drained and undrained plots, our study clarifies that drainage is not a static treatment, so drainage status could represent a spectrum of conditions rather than a static dichotomy. Subsurface drainage is an anthropogenic force that can dynamically change soil properties, particularly as those drainage systems age. At minimum, studies should contextualize their drainage systems by considering their age.

These results occurred under drought conditions and in specific soils. However, we anticipate that similar research on different soils under different crop management and climates will yield varying assessments of drainage effects on soil properties over time. While most long-term studies with subsurface drainage focus on water quality, more research should pair this idea with better understanding of changing physical and biological properties, as changes in water quality outcomes over time are a direct result of changing soil properties.

Acknowledgements

This work was supported by the Minnesota Corn Growers Association as well as the Minnesota Agricultural Fertilizer Research and Education Council. Thank you to the growers for allowing us to conduct research in their fields.

  • Received October 30, 2022.
  • Revision received June 11, 2023.
  • Accepted July 13, 2023.

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Comparing the short- and long-term impacts of subsurface drainage installation on soil physical and biological properties
A.L. Frankl, K.T. Sherbine, J.S. Strock, F.G. Fernández, A.M. Cates, L.A. Pease
Journal of Soil and Water Conservation Nov 2023, 78 (6) 457-465; DOI: 10.2489/jswc.2023.00147
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