Watershed water quality impacts of cover crop adoption
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Watershed Scale Water Quality Impacts Of Cover Crop Adaptation In A Two-stage Ditch System - Dr. Brittany Hanrahan, from the 2018 Conservation Tillage and Technology Conference, March 6 - 7, Ada, OH, USA. More presentations at https://www.youtube.com/channel/UCZBwPfKdlk4SB63zZy16kyA
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Watershed water quality impacts of cover crop adoption
- 1. Watershed-scale water quality impacts of cover crop adoption in a two-stage ditch system Dr. Brittany Hanrahan Research Biologist, USDA-ARS
- 2. Agricultural land use and the export of excess nutrients results in algal blooms followed by hypoxia Excess Nutrients Algal Blooms Algal Death & Decomposition Water Column Hypoxia Lake Erie (SRP) Gulf of Mexico (NO3 -) Peak run-off often occurs during spring snowmelt and storms.Boat wake, Maumee Bay, August 2015 Western Lake Erie algal bloom July 2015 (NASA) NOAA
- 3. Streams draining row crop agriculture export excess nutrients and sediments • For example, in Indiana, >90% of the ~50,000 km of stream/ditches are located within 500m of a row-crop field; land cover >80% row-crop. • Channelization, tile drainage, and fertilizer addition improve crop yields, but these practices also reduce nutrient retention and channel stability. Net Result: increased export of excess nutrients and sediments to downstream water bodies.
- 4. Watershed Boundary Shatto Ditch Stream Sampling Site Tile Drain Location NH4 + = 143 ug N/L SRP = 106 ug P/L NO3 - = 5.4 mg N/L • Agricultural watershed located in Kosciusko County, IN • Tributary of the Tippecanoe R. • Watershed characteristics: • Total area: 1333 ha • Agricultural area: ~80% dominated by corn & soy • Stream Characteristics: • High nutrient concentrations year-round • Presentation Outline: • In-stream: two-stage ditch • Watershed: cover crops Shatto Ditch Watershed Project Context: Study Site Average flow = ~116 L/s; Range = <10 – 2000 L/s
- 5. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Two-Stage Ditch Implementation ↑ bank stability ↑ denitrification ↑ water quality Only decreased total NO3 --N export by ~10% Landscape Context How does the two-stage function ~10 years later? Project Context: Timeline
- 6. In-stream restoration: Two-stage ditch • Engineered for channel stability • Increased sedimentation → particles settle out on floodplains • Increased nutrient retention→ more time/space for removal Channelized During late-fall construction After one growing season Floodplains each 3-4 m wide Stream width triples during storms
- 7. Does the two stage improve water quality? • Two-stage reduced water column turbidity, even as practice “aged”. • Mechanism: two-stage slows water velocities during storms, promotes sediment and P retention on floodplains. • During floodplain inundation, two-stage increased denitrification N-removal (3- 24x higher); also increased as two-stage “matures” over time. • Mechanism: two-stage ditch enhances nutrient retention on floodplains by tripling bioreactive surface area. Turbidity during floodplain inundation (1 yr) (2 yr) (3 yr) (5 yr) (7 yr) (Nat.) Increasing two-stage age (years) CRE SHA KLA CRO BUL CEAP Turbidity(NTU) 0 100 200 300 400 500 * * * * * Channelized Two-stage N-removal during inundation (1 yr) (2 yr) (3 yr) (5 yr) (7 yr) (Nat.) CRE SHA KLA CRO BUL CEP Reach-scaleN-removal (kgN/km/d) 0 4 8 12 16 23x 3x 4x 24x 4x 7x Stream channel Floodplain Davis et al. 2015, Mahl et al. 2015, JAWRA.
- 8. The two-stage is a viable tool in the “nutrient management toolbox” and can be implemented to improve water quality while maintaining productive agriculture. Best practices to maximize improvements with two- stage occur when floodplain benches: • inundate regularly (i.e., >12 events/yr). • retain tile outflows for as long as possible. • are vegetated and allowed to “age” over time.
- 9. SDW: 10 years later Roley et al. Eco Apps 2012 Two-Stage DitchChannelized Two-stage: After 10 yearsChannelized: After 10 years • In 2007, a two-stage ditch was constructed in 600 m of Shatto Ditch Watershed • Established treatment and control reaches for comparison No maintenance or dredging has occurred since 2007
- 10. Reference Two-Stage DN(ugN[gDM]-1hr-1) 0.0 0.1 0.2 0.3 0.4 Reference Two-Stage ER(ugO2[gDM]-1hr-1) 0.0 0.5 1.0 1.5 2.0 How does the two-stage in the Shatto Ditch function after 10-years? * • DN was >30% higher in the restored, two-stage than in the naturalizing reference 2-way ANOVA Reach: p<0.05 Floodplain Soil Organic Matter (%) 0 5 10 15 20 DN(ugN[gDM] -1 hr-1) 0.00 0.25 0.50 0.75 Naturalized Restored OrganicMatter(%) 0 2 4 6 8 10 12 Res . %OM * • DN ↑ with %OM in floodplain soils; driven by higher OM in restored (+22%) SLR; r2=0.56, p<0.001 Nat. Hanrahan et al. Biogeochemistry 2018 Immediately after construction After 1 growing season Vegetation re-established rapidly ↑ OM via growth/decomp Channelized
- 11. Two-stage jump starts ecosystem function • Area of two-stage floodplain = 6x higher than “naturalizing” channelized • >30 years until equal area of the two-stage • No loss of drainage capacity in the two-stage system Both systems effectively remove N, but two-stage implementation restores DN rapidly and requires little to no maintenance.
- 12. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Two-Stage Ditch Implementation ↑ bank stability ↑ denitrification ↑ water quality Only decreased total NO3 --N export by ~10% Watershed-scale planting of winter cover crops Landscape Context Project Context: Timeline
- 13. Harvest Begins and Cover Crops Planted Cover Crops Overwinters Cover Crops grow during critical times of N and P export • Crops that are planted after cash-crop harvest and grow when fields are normally fallow or bare • Field-scale studies: cover crops ↓N export via tile drains by 13-94% • However, the goal of our study examine the influence of planting cover crops at the watershed-scale on nutrient loss from “working lands” May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr Cover crops have the potential to address nutrient loss from agricultural watersheds
- 14. SHATTO DITCH WATERSHED USDA-CIG (2012-2015) • Oct 2012-13: pre-treatment, 320 acres (12% of croppable acres) in cover crops • Oct 2013-14: cover crops↑ to 1,610 (67%); note: Indiana avg = 5% • Oct 2014-15: cover crops on 1,561 acres; projected ↑ to 1,660 in 2015-16 • Planted mostly annual ryegrass (“farmer choice”), no other stipulations GOAL: “saturate” watershed with cover crops, isolate effect of watershed-scale cover crops, measure dissolved N and P loss. 3,300 acres, 85% row crop
- 15. Cover crops in SDW
- 16. • Sampling Sites: • Identified tile drain outlets along 8 km of stream from “headwaters” to outlet at the Tippecanoe River • Sampling Frequency: • Collect water samples every 14 days: • 23 tile drain outlets (~2 per field) • Watershed oultlet • Samples analyzed for NO3 --N and SRP on Lachat Flow Injection Auto Analyzer • Tile load calculations: • Measure instantaneous Q (L s-1) at each tile drain Watershed outlet Tile drain outlet Flow to Tippecanoe River Methods: Field and Lab
- 17. Sampling Date Oct-12 Apr-13 Oct-13 Apr-14 Oct-14 Apr-15 Oct-15 Apr-16 Oct-16 Average[NO3 - -N](mgL -1 ) 0 5 10 15 20 25 Stream Bare Soil - No Cover Crops Cover Crops TEMPORAL PATTERNS OF STREAM AND TILE DRAIN [NITRATE] • 2013: tile drain NO3 - without cover crops higher than with cover crops, especially during Winter/Spring. • 2014 - 2016: tile NO3 - in Year 1-3 of cover crop planting is lower; similar or even lower than tiles with cover crops for >2 years. • Approach: stream and tile drain samples every 14d to quantify the impact of cover crops on water quality. Hanrahan and Tank, unpublished data. Pre-Treatment 2012-2013 Year 1 2013-2014 Year 2 2014-2015 Stream Bare Soil - No Cover Crops Cover Crops Year 3 2015-2016
- 18. Sampling Date Oct-12 Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14 Jan-15 Apr-15 Jul-15 Oct-15 Jan-16 Apr-16 Jul-16 Oct-16 Average[SRP](ug/L) 100 200 300 400 500 TEMPORAL PATTERNS OF STREAM AND TILE DRAIN [SRP] • 2013: w/o cover crops, tile [SRP] variable but generally lower than stream [SRP] • 2014-2016: “saturate” CC, tile [SRP] is lower than the stream, less variable. Hanrahan and Tank, unpublished data. Pre-Treatment 2012-2013 Year 1 2013-2014 Year 2 2014-2015 Stream Bare Soil - No Cover Crops Cover Crops Year 3 2015-2016
- 19. ESTIMATE NUTRIENT MASS LOSS VIA TILE DRAINS NUTRIENT CONCENTRATION (MG/L) * FLOW (L/S) = FLUX (KG/DAY)
- 20. Data with outliers removed Spring 2013Summer 2013 1 2 3 4 5 6 7 8 9 10 11 12 Average[NO3 -]Flux(kgN/day) 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Tile Tile Tile COVER CROPS REDUCE NITRATE EXPORT FROM FIELDS ESPECIALLY DURING SPRING TILE DRAIN NITRATE FLUX Hanrahan and Tank, unpublished data. Spr Sum Fall Win Pre-Treatment 2012-2013 Year 1 2013-2014 Year 2 2014-2015 ↓ 55% in Spring 2014 ↓ 47% in Spring 2015 Year 3 2015-2016 Spr Sum Fall Win Spr Sum Fall Win Spr Sum ↓ 83% in Spring 2016 Tile Drain No Cover Crops 2013 Tile Drain Cover Crops 2013 Tile Drain Cover Crops 2014-2016
- 21. Spring 2013Summer 2013 1 2 3 4 5 6 7 8 9 10 11 12 AverageSRPFlux(g/day) 0 2 4 6 8 10 12 14 Tile D Tile D Tile D COVER CROPS REDUCE SRP EXPORT FROM FIELDS, BOTH DURING SPRING & SUMMER Hanrahan and Tank, unpublished data. Pre-Treatment 2012-2013 Year 1 2013-2014 Year 2 2014-2015 TILE DRAIN SRP FLUX ↓ 50% in Spring 2014 ↓ 78% in Spring 2015 Spr Sum Fall Win Spr Sum Fall Win Spr Sum Fall Win Spr Sum Year 3 2015-2016 Tile Drain No Cover Crops 2013 Tile Drain Cover Crops 2013 Tile Drain Cover Crops 2014-2016 ↓ 82% in Spring 2016
- 22. ESTIMATING WATERSHED-SCALE NUTRIENT EXPORT • Use stage-discharge relationship to estimate daily Q. • Apply C-Q relationship to estimate daily [NO3] or [SRP] • Daily Q * [N or P] = N or P per day exported from SDW annual. 67-70% cover crops12% cover crops
- 23. Results Slide 1 Oct-07 Apr-08 Oct-08 Apr-09 Oct-09 Apr-10 Oct-10 Apr-11 Oct-11 Apr-12 Oct-12 Apr-13 Oct-13 Apr-14 Oct-14 Apr-15 Oct-15 Apr-16 Oct-16 Discharge(Ls-1) 0 500 1000 1500 2000 2500 3000 StreamNO3 - (mgL -1 ) 0 2 4 6 8 10 12 14 StreamSRP(mgL -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 Discharge NO3 - (mg L-1 ) SRP (mg L-1 ) Pre-Cover Crops (2008-2013) Post Cover Crops (2014-2016) Chapters 5 & 6 Does cover crop planting reduce N and P export from the watershed outlet? • 9-year record of stream discharge, NO3 --N and SRP at the watershed outlet • 6-years PRE cover crop = 2008-2013; 3-years POST cover crop 2014-2016 Hanrahan and Tank, unpublished data.
- 24. Results Slide 1 Does cover crop planting reduce N and P export from the watershed outlet? Annual NO3 - Yield(kgha -1 ) 0 5 10 15 20 25 30 Water Year 2008 2009 2010 2011 2012 2013 2014 2015 2016 Annual SRPYield(kgha -1 ) 0.0 0.1 0.2 0.3 0.4 0.5 Discharge(Ls-1) 0 1000 2000 3000 Discharge Mean = 19 kg NO3 - ha-1 17 kg NO3 - ha-1 Mean = 0.24 kg SRP ha-1 0.17 kg SRP ha-1 • Average of total annual NO3 - export in post cover crop period = ↓11% • Average of total annual SRP export in post cover crop period = ↓30% • Monthly and seasonal totals = also ↓ export in post cover crop period • Need to account for variability in flow Pre-Cover Crops (2008-2013) Post Cover Crops (2014-2016)
- 25. Results Slide 1 Cover crops reduced N and P loss from the Shatto Ditch Watershed • ↓ [NO3 --N] and [SRP] from tiles with cover crops • ↓ NO3 --N and SRP flux or mass loss from tiles with cover crops • ↓ average watershed NO3 --N and SRP export during post- cover crop years • Challenging to detect statistically • Cover crops may help address N and P loss from agricultural watersheds
- 26. Acknowledgements Advisor Dr. Jennifer L. Tank Tank Labbers Dr. Sheila Christopher, Arial Shogren, Martha Dee, Matt Trentman, Shannon Speir, Ursula Mahl, Eric Pitts, Rob Davis, Sarah Winikoff; Drs. Sarah Roley, AJ Reisinger, Peter Levi, Laura Johnson, Natalie Griffiths, Tim Hoellein, Denise Bruesewitz Undergraduates Elizabeth Berg, Anna Kottkamp, Karen Huang, Mary Mecca, Kyle White; Nicole Gorman, Eddie Lopez, Matt Kirian, Erik Maag, Audrey Thellman IWI/ECI Lizzie Willows, Kara Prior, Lienne Sethna, Brett Peters, Milan Budhathoki, Kemal Gokkaya, Peter Annin, Alex Gumm, Joanna McNulty, CEST Suzyanne Guzicki, Jon Loftus Collaborators Dr. Antoine Aubeneau, Dr. Diogo Bolster, Dr. Emma Rosi, Dr. Jen Drummond, Dr. Sara McMillan, Dr. Robert Hall; Dr. Kevin King, Dr. Mark Williams, Dr. Chi-hua Huang, Stan Livingston; Kent Wamsley; Andrea Baker, Chad Schotter, Darci Zolman, SWCD Board Landowners Robert Foltz, Michael Long, The Romine Family, The Severns Family, Steven Miler and Creighton Brothers LLC; Jaimie Scott
- 27. QUESTIONS?
Editor's Notes
- Agriculture is the dominant land use across much of the Mississippi River Basin; particularly in the Midwestern Corn Belt This figure show agricultural land use in light green But excess nutrients that leave or runoff agricultural fields into adjacent streams can have negative consequences on downstream water bodies Excess nitrogen and phosphorus are transported to downstream systems where they fuel, or fertilize algal blooms When those algal blooms die and decompose, oxygen is stripped from the water column causing areas of little to no oxygen often leading to hypoxia (no oxygen) where aquatic organisms can no longer survive In the Gulf of Mexico, excess NO3 creates a “dead zone” every year that ranges in size from Connecticut to New Jersey (nearly XXXX square miles) Closer to home, algal blooms in Lake Erie are fueled by soluble or dissolved reactive phosphorus Additonally, peak runoff often occurs during spring storm and snowmelt events so these algal blooms generally occur from the spring to summer (when people want to be out enjoying these water bodies!)
- These issues are compounded by conventional management practices of agricultural systems like surface and subsurface drainage systems that are prevalent throughout the Midwest For example, in Indiana where I conducted my dissertation research, >90% of the >48,000km of streams (~30,000 miles) are within 500 m (~1600 ft) of a row-crop field Additionally, drainage systems (channelized streams) are designed to move water quickly and efficiently away from fields – making them effective transporters of nutrients that enter from adjacent fields While these practices – channelization, tile drainage, and fertilizer addition – improve crop yields, they also reduce nutrient retention and channel stability in agricultural streams With the net result being increased export of excess nutrients and sediments to downstream water bodies
- The work I’m going to talk about today all took place in the Shatto Ditch Watershed Which is a small, agricultural watershed located in Kosciusko County, IN The ditch itself is a tributary of the Tippecanoe River, which is important because the Tippe has “high” freshwater mussel diversity and is listed as one of the Nature Conservancy’s “last great places” The watersheds is a little over 1300 ha and nearly 80% of the land use is for row-crop agriculture in corn or soybeans The stream itself is a relatively small, first-order stream with average flow of ~120L/s; but flow can range anywhere from <10L/s in the late summer/early fall to >2000L/s during spring storms And nutrient concentrations are very high consistent with streams across much of the Midwest So I’m going to split this talk into two parts today by first talking about the two-stage ditch and then talking about watershed-scale implementation of cover crops
- First, I want to provide some context because this hasn’t always been a watershed-scale project. I’m going to use this timeline as a way to organize the “phases” of this project because it sort of grew organically Work in the Shatto Ditch Watershed (located in Kosciusko County, IN) began as a demonstration project for the two-stage ditch In 2007, 600 m of two-stage ditch was constructed at the bottom of the watershed. The effects of the two-stage were then measured/quantified extensively from ~2007-2012 and I’ll summarize some of these findings in the next few slides. We then “returned” to the two-stage in 2016 to examine/measure it’s function 10 years after construction
- I’ve already mentioned the channelized ditch typical of Midwestern agricultural systems and how these ditches are designed to move (or remove) water as quickly and efficiently as possible. As such, these systems have extremely “flashy” hydrographs (respond rapidly to precipitation with large increases in flow (depth), and return to baseflow quickly) and also unstable – the speed with which this water moves creates incredible stress on the stream banks that causes bank erosion/slumping. This is BAD for farmers because it slowly encroaches on their land, resulting in a LOST of acreage. Originally, the two-stage ditch was designed to increase bank stability --- essentially, you go into a stream and create these mini-floodplains that allow water to “spill out” of the main channel during high flows and onto these benches (or 2nd stage), slowing water velocity. These benches also provide some ADDED benefits --- they are vegetated, slowing the velocity even more and allowing sediments in the water to settle out onto these floodplains. The benches ALSO increase the bioreactive surface area of these streams (the goal is to triple the area); so the benches increase retention time (contact time) AND surface area for biology to work on removing nutrients from the water column, ultimately REDUCING the amount that is exported downstream.
- A lot of work had proven that the two-stage increases channel stability, but the next question was: Does the two-stage improve water quality? We first measured changes in turbidity (or water cloudiness) This figure shows average turbidity (so higher = cloudier or less clear) in channelized (gray bars) compared to two-stage (red bars) systems What we see is that turbidity is lower in the two-stage demonstrating an increase in water clarity The mechanism behind this is that the two-stage slows water velocities allowing sediment (and associated phosphorus) settle out onto the floodplains We also measured changes in N removal (via denitrification or the microbial process that converts NO3 to N2 gas, permanently removing N from the system) This figure shows total N removal in the two-stage floodplains (in green) and we found that N removal was 3-24x higher in the two-stage floodplains compared to the stream The mechanism here is that the floodplains are increasing the AREA for biological activity, including denitrification
- These early studies really demonstrated that the two-stage is a viable tool in the nutrient management toolbox But these studies also revealed some “best practices” that can maximize two-stage efficacy, including regular inundation, tile flow retention, and vegetation
- Earlier, I mentioned that we eventually “returned” to the two-stage to examine its function 10 years later So as a reminder, the two-stage was constructed in the Fall of 2007 At the time, the upstream channelized ditch was established as the experimental “control” for comparison with the newly-constructed two-stage So this is what the newly-constructed two-stage and upstream channelized ditch looked like in 2007Importantly, no maintenance or dredging has occurred in the upstream reach since 2007 And this is what the restored two-stage looks like after 10 years, while this is what the upstream naturalized reach looks like after 10 years As you can see, the stream has started to form its own natural floodplains (via hydrologic processes/variability) And what we really wanted to know was, after 10 years of natural floodplain formation, how does the two-stage compare to the upstream system?? Is the two-stage still “better” at N removal than a “naturalizing channelized ditch”??
- So we measured N removal via denitrification again and found that denitrification was >30% higher in the two-stage floodplains compared to the naturalized/channelized ditch When we look at what was driving these differences, we can see that DN increased with increasing OM in floodplains soils and that the difference between restored and naturalized floodplains was likely because OM was 22% higher in the restored reach And this makes sense if we think about the process that establishes both of these floodplains: This is what the two-stage looked like immediately following construction But this is what the two-stage look like after just 1 growing seasons demonstrating that rapid establishment of vegetation on the benches promoted organic matter accumulation through growth/decomposition as well as slowing water velocity that promoted OM deposition from the aquatic environment
- I was then interested in determining if DN varied among lateral zones within the floodplains First, DN was higher in the restored reach in both active floodplain zones (NS, MD), again demonstrating enhanced function as a result of restoration I also found that DN varied among lateral zones in ONLY the restored reach, with DN higher in NS compared to MD compared to UP And this was largely driven by variation in floodplain soil QUALITY among the 3 lateral zones in the restored reach In particular, the C:N ratio decreased with increasing %organic matter in the NS floodplain soils, likely indicating the effect of frequent inundation events that deposited high quality OM (low C:N ratio) on the floodplain
- In summary, we found that two-stage construction essentially “jump-started” the natural floodplain formation process THUS jumpstarting function (in this case N removal) of the ecosystem Total floodplain area was nearly 6x higher in the two-stage compared to the “naturalizing” channelized ditch It would take >30 years for the channelized stream to accumulate equivalent floodplain area or essentially “catch up” to the two-stage Not to mention the loss of drainage (and/or land) in the meantime While both floodplains removed N, the two-stage restored function (or enhanced N removal) more rapidly So while it may be a big investment up-front, benefits are big and little to no maintenance is needed over the long term
- Now I’m briefly going to return to my project timeline: And recall that the two-stage benefits include: improving bank stability (decreasing bank erosion), enhancing denitrification (increasing permanent N removal), and improved water quality (decreasing N and P concentrations) However, this 600 m reach of two-stage at the base of SDW only reduced total N export by ~10% Essentially, the sheer amount of nutrients entering from row-crop agricultural fields throughout the watershed overwhelmed the two-stage (not a silver bullet) That’s when we started thinking about this as a “watershed-scale” problem and attempted to address the source or amount of nutrients entering from the landscape by planting cover crops
- The practice that we chose to implement and examine was winter cover crops because they have the potential to reduce N by addressing two main issues bare soil during times of high nutrient loss Cover crops are crops – like grasses – that literally cover the soil and have been historically used to reduce soil erosion, improve soil quality, control weeds, etc. and they represent this “hallmark” of sustainable agricultural systems Planted just before or after harvest, establishing roots and vegetative land cover in the fall Some cover crop species will then overwinter and grow back in the spring, providing vegetative land cover in the spring during those critical times of nutrient export Indeed, field-scale studies conducted on experimental farms have found that cover crops reduce N loss from tile drains by 13-94% (from Delaware to Iowa) However, the goal of our study was to plant cover crops at the watershed-scale (>50% of acres) and examine their influence on nutrient loss from tile drains and stream outlet of a watershed dominated by working lands or those used/operated by the producers themselves (NOT on controlled, experimental farms)
- The first year of the study was our “pre-treatment” year, or PRE watershed-scale planting of cover crops when only 2 fields or ~320 acres were planted in cover crops In the fall of 2013, cover crop acreage increased to a little over 1600 acres or 67% of croppable acres in the watershed Maintained >60% of croppable acres in cover crops for the next two years Our ultimate goal was to “saturate” the watershed with cover crops to isolate the effect of watershed-scale cover crops while measuring dissolved N land P loss
- Annual ryegrass --- great! If planted early… Need to plant in September or Early October to ensure root establishment before the first frost kill. Once it’s established, it has an extensive root system that uses A LOT of water and N (perfect combination) and removes these from deep soil profiles (up to 60 inches deep --- amazing)
- We first identified tile drain outlets along the entire 8 km of Shatto Ditch and began collecting water samples directly from the flow of water at 23 representative, tile drain outlets or about 2 per field Each tile drain was categorized as either WITH COVER or WITHOUT COVER CROPS by visually identifying cover crop growing in the field, and confirming with the local Soil and Water Conservation District or the government agency that was helping us with this project In the 2013 pre-treatment year (i.e., before watershed scale planting of cover crops), only 2 fields were planted in cover crops and therefore tile drains with cover crops <<< tile drains without cover crops; in 2014-2016, cover crop acreage was dramatically increased, leaving us with an unbalanced experimental design where now the number of tile drains with cover crops >>> tile drains without cover crops Nevertheless, we had a record of tile drains from fields with and without cover crops during each year of the four year study We then collected water samples every 14days from a representative subset of tile drains throughout the water (those that flowed regularly), as well as the watershed outlet Each water sample was analyzed for NO3 and SRP (or DRP) concentration, and we measured instantaneous flow at each tile drain outlet as well
- First, we examined the temporal patterns of NO3 concentration So just to quickly orient you to these graphs… Average NO3 is on the y-axis and time is on the x-axis so each dot represents average NO3 on each sampling date for samples collected from the stream (in blue), tiles draining fields without cover crops (in brown), and tiles draining fields with cover crops (in green) During the 2013 pre-treatment year, we found that NO3 concentration from tiles draining fields without cover crops was much higher than those with cover crops NO3 from tiles draining CC fields was variable but generally lower in the following three years of cover crop planting, especially during 2016
- Temporal patterns of SRP were slightly different than NO3 First, let’s note that the magnitude of SRP concentration is MUCH lower than NO3 A LOT less SRP is being transported compared to NO3 During the pre-treatment year, tile SRP was variable but generally lower than stream SRP With cover crop planting, tile SRP appears less variable and remains considerably lower than stream SRP
- Using the nutrient concentration at each tile drain and mulitplying by the discharge from each tile drain, I am able to calculate the nutrient loss from each drain.
- 1 TD removed that represents the “headwater” or top of the stream – drains ~300 acres Still included in total watershed export because that estimate is made with data from the two-stage section of stream
- So just to show you what that data looks like, this figure shows daily discharge in blue, stream NO3 concentration from grab samples in green, and stream SRP concentrations in orange from October 2007 to October 2012 The pre-treatment year of the study described here began in October 2012 and we continued collecting grab samples from the watershed outlet from October 2012-October 2013 when cover crop acreage in SDW was minimal (~12%) In the late summer/fall of 2013, cover crops were then planted on >60% of croppable acres in SDW, marking the beginning of the POST cover crop period All of this equals
- However, because our goal was to examine changes in watershed export (again, mass loss), we needed to use these biweekly grab samples to estimate DAILY N and P loss from the watershed In order to do this, we first estimated daily N and P concentration For NO3, we used the linear relationship between NO3 concentration and discharge to PREDICT daily NO3 concentration using the discharge value from that given day For SRP, we interpolated between grab samples And we note that choosing these methods was informed by both our data and previously published research We then multiplied daily concentration by daily discharge to estimate daily NO3 and SRP export from the watershed outlet over the entire period of record
- So once we’ve estimated daily NO3 and SRP loss from the watershed, we aggregated or summed daily values to compare ANNUAL NO3 or SRP export before and after cover crop planting These bars represent TOTAL annual NO3 loss during pre (in brown) and post (in green) cover crop years And we found that average total annual NO3 export during the post cover crop period was 11% lower than the pre-cover crop period Additionally, we found that total annual SRP export during the post cover crop period was 30% lower than the pre-cover crop period However, as you can see, there is A LOT of year-to-year variability in the total nutrient export, which is largely driven by variation in FLOW changes in the timing and amount of precipitation that feed flows Therefore, we felt that accounting for variability in flow was
- So once we’ve estimated daily NO3 and SRP loss from the watershed, we aggregated or summed daily values to compare ANNUAL NO3 or SRP export before and after cover crop planting These bars represent TOTAL annual NO3 loss during pre (in brown) and post (in green) cover crop years And we found that average total annual NO3 export during the post cover crop period was 11% lower than the pre-cover crop period Additionally, we found that total annual SRP export during the post cover crop period was 30% lower than the pre-cover crop period However, as you can see, there is A LOT of year-to-year variability in the total nutrient export, which is largely driven by variation in FLOW changes in the timing and amount of precipitation that feed flows Therefore, we felt that accounting for variability in flow was
- Thus, we used flow duration curve analysis to account for variability in flow A flow duration curve relates flow values to the percent of time those values have been met or exceeded; so the x-axis represents the duration amount, or “percent of time”, as in cumulative frequency distribution and the y-axis represents the flow value associated WITH that percent of time. So when we plotted the flow duration curves for pre-CC years (2008-2013) and post-CC years (2014-2016) and found that the curves looked very similar. We then used these flow duration curves to categorize NO3 export according to standard flow intervals When we examined WHEN NO3 export was occurring, we found that >70% of export occurred during high flows and moist conditions
- So our first question, was how does cover crop planting influence N and P loss from tile drains? And we answered this by comparing median instantaneous nutrient load between tiles without cover crops (in the grayish brown) to tiles with cover crops (in the colored boxes) during each year of the study (2013, 2014, 2015, and 2016) And from these direct comparisons, we found that NO3 load from tile drains with cover crops was 69-90% lower than tile drains without cover crops during spring Similarly we found that SRP loads were 20-78% lower in tile drains from fields with cover crops in spring While I am simply highlighting the results from spring – that really critical time of nutrient export from April to June – here, it is important to note that we COLLECTED water samples year-round and that these trends are generally consistent in fall, winter, and summer Therefore, I concluded that N and P loss from fields with cover crops was lower than fields without cover crops, likely demonstrating the role that increasing vegetative land cover had in increasing nutrient retention in agricultural fields
- We then wanted to determine which of the proximal drivers (concentration or discharge) were controlling nutrient loss from tile drains Thus, we regressed instantaneous load with both concentration and discharge, determining that both N and P loss were controlled by discharge Here again I am focusing specifically on data collected during the spring across all 4 years of the study and I found that tile drain NO3 loss increased with increasing discharge in tile drains regardless of cover crop planting However! Found that cover crops altered the relationship between tile flow and NO3- loss [in spring; LOWER intercept] such that NO3 loss from tiles with cover crops was 30% lower at similar flows This finding indicated that cover crops were reducing the pool of leachable NO3 in the soil profiles during spring In contrast, there was no difference in the regression relationship between tile flow and SRP load for tiles with and without cover crops Indicates that differences shown in the previous slide are largely driven by flow These results emphasize that cover crops have the potentially to effectively manage nutrient loss, but managing flow may be a better way to reduce loss from fields (using drainage management)
- Tile drain results reflected changes from individual fields, but we also wanted to know how watershed export, or the mass of N and P being transported by the stream itself differed between years with and without cover crops In order to do this, we also collected and filtered triplicate, grab samples from the stream outlet on each sampling date (every 14 days), measuring both NO3 and SRP on the lachat flow injection auto-analyzer Additionally, stream stage was measured continuously, which we related to hand measurements of in-stream discharge in order to estimate daily discharge from the SDW outlet Importantly, because this work builds on previously published research from our lab, both water chemistry grab samples and stream discharge have been measured at the stream outlet (using similar methods) since 2007
- Thus, we used flow duration curve analysis to account for variability in flow A flow duration curve relates flow values to the percent of time those values have been met or exceeded; so the x-axis represents the duration amount, or “percent of time”, as in cumulative frequency distribution and the y-axis represents the flow value associated WITH that percent of time. So when we plotted the flow duration curves for pre-CC years (2008-2013) and post-CC years (2014-2016) and found that the curves looked very similar. We then used these flow duration curves to categorize NO3 export according to standard flow intervals When we examined WHEN NO3 export was occurring, we found that >70% of export occurred during high flows and moist conditions