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August 31 - 1116 - Hassam Moursi

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August 31 - 1116 - Hassam Moursi

  1. 1. The Impact of Drainage Water Recycling on Reduction of Nutrients and Sediment Losses from a Drained Field in Eastern North Carolina Hossam Moursi, Mohamed Youssef, Chad Poole, Celso Castro-Bolinaga, George Chescheir, Robert Richardson The 11th International Drainage Symposium Des Moines, Iowa, August 31, 2022 1
  2. 2.  Drainage is essential for crop production on naturally poorly drained soils with shallow water table.  Drainage water carries nutrients and, sediment from drained fields to surface water.  Excessive nutrients in surface water cause major water quality degradation and fish kills. https://oceanservice.noaa.gov 2  Several best management practices (BMPs) have been proposed to reduce nutrients and sediment losses from drained cropland to surface water. Introduction
  3. 3. Irrigated Field Pump On-farm reservoir Drainage Water Recycling (DWR)  Stores surface and subsurface drainage water in reservoirs during wet periods to use for supplemental irrigation during dry periods of the growing season.  DWR could potentially:  Increase crop yield;  Conserve water;  Improve water quality. 3 Introduction
  4. 4.  Limited studies investigated the performance of DWR.  Performance of DWR systems varies depending on field conditions, thus evaluating DWR across a wide range of conditions is necessary.  Concentration reduction caused by natural removal processes, which occur in the reservoir of the DWR systems has not been adequately investigated.  DWR has never been investigated in the U.S. Southeast. 4 Drainage water recycling (DWR) Introduction
  5. 5. Research Objectives Experimentally quantify the effect of DWR on reducing losses of nutrients and sediment from agricultural fields to surface water bodies; and investigate the factors affecting removal efficiency of the reservoir. 5
  6. 6. Methods 6
  7. 7. Experimental Site  Located in Beaufort county, in eastern North Carolina.
  8. 8. Experimental Site  Two treatments: Subirrigated from on-farm reservoir (DWR) vs. non-irrigated (control treatment; CT)  Area: DWR=11.48 ha, CT=11.23 ha, and reservoir =0.38 ha 8  Soil: AltaVista fine sandy loam.  Crops: Corn (2019, 2021), Soybeans (2020).
  9. 9. (1) Inflow from forested land (2) Outflow (3) Subsurface drainage, DWR (4) Subirrigation (5) Surface runoff , CT (6) Surface runoff, DWR 9  Flow and water quality data were collected at the reservoir inlets and outlet for two years (May 2019 – April 2021). Field Measurements
  10. 10.  Flow measurements  Water quality samples  Nitrogen: NO3-N, NH4-N, TKN, TN  Phosphorous: Ortho-P, TP  Sediment: TSS 10 Field Measurements Flow and water quality measurements at reservoir outlet Flow and water quality measurements of runoff from DWR field
  11. 11. Field Measurements  Precipitation and air temperature  Reservoir water level and water temperature  Topographical survey of the storage reservoir 11 Bathymetric survey using ADCP Reservoir water level Automated and manual rain gauges
  12. 12. 12  Reservoir area-volume-depth relationship Field Measurements Reservoir elevation map
  13. 13. Water Management at DWR Treatment A water level control structure (left) installed at the outlet of the main drain of DWR treatment. A smart drainage system (right) is connected to the control structure to automatically manage drainage and sub-irrigation. 13
  14. 14. Reservoir Water Balance  Water balance was conducted for the reservoir for two years (May 2019-Apr. 2021). 14 𝚫𝑽 = 𝑷 + 𝑸𝒊𝒏 + 𝑸𝑹𝑶_𝑫𝑾𝑹 + 𝑸𝑹𝑶_𝑪𝑻 + 𝑸𝑫𝑹𝑵 − 𝑸𝑰𝑹𝑹 − 𝑸𝒐𝒖𝒕 − 𝑺 − 𝑬 Δ𝑉 is change in reservoir water volume; 𝑃 is precipitation; 𝑄𝑖𝑛 is inflow water from upstream forested land; 𝑄𝑅𝑂_𝐷𝑊𝑅 and 𝑄𝑅𝑂_𝐶𝑇 are surface runoff from DWR and CT treatments; 𝑄𝐷𝑅𝑁 is subsurface drainage flow from DWR treatment; 𝑄𝐼𝑅𝑅 is irrigation water; 𝑄𝑜𝑢𝑡 is outflow released from the reservoir; S is seepage losses from the reservoir; E is evaporation.
  15. 15. Reservoir Nutrient and Sediment Balances  Nutrient and sediment balances were conducted for the reservoir for two years (May 2019-Apr. 2021). 15 𝜟𝑳 = 𝑳𝑸_𝒊𝒏 + 𝑳𝑹𝑶_𝑫𝑾𝑹 + 𝑳𝑹𝑶_𝑪𝑻 + 𝑳𝑫𝑹𝑵 − 𝑳𝑰𝑹𝑹 − 𝑳𝒐𝒖𝒕 Δ𝐿 is change in nutrients/sediment mass load in reservoir; 𝐿𝑄_𝑖𝑛 is nutrient/sediment mass load from upstream forested land; 𝐿𝑅𝑂_𝐷𝑊𝑅 and 𝐿𝑅𝑂_𝐶𝑇 are nutrient/sediment mass loads in surface runoff from DWR and CT treatments, respectively; 𝐿𝐷𝑅𝑁 is nutrient/sediment mass load in the subsurface drainage flow from DWR treatment; 𝐿𝐼𝑅𝑅 and 𝐿𝑜𝑢𝑡 are nutrient/sediment mass load leaving reservoir via irrigation and outflow, respectively.
  16. 16. Reservoir Hydraulic Retention Time (HRT)  The average time that inflow water remains in the reservoir before it is released. 16 𝑉𝑚𝑎𝑥 is reservoir storage capacity 𝑯𝑹𝑻 = 𝑽𝒎𝒂𝒙 𝑷 + 𝑸𝒊𝒏 + 𝑸𝑹𝑶_𝑫𝑾𝑹 + 𝑸𝑹𝑶_𝑪𝑻 + 𝑸𝑫𝑹𝑵
  17. 17. Statistical Analysis  Non-parametric two-sample Wilcoxon-rank test was used to compare concentrations and loadings.  Multivariate linear correlation analysis was conducted to investigate the factors that could affect nutrients and sediment removal efficiency.  The factors included in this analysis were water temperature, hydraulic retention time (HRT), water volume, and reservoir inflow. 17
  18. 18. Results and Discussion 18
  19. 19. Reservoir Water Balance  Relatively dry (2019-2020), relatively wet (2020-2021). Year May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr Total 2019-2020 37 65 77 124 162 89 86 64 49 154 92 86 1086 2020-2021 166 112 126 150 105 55 208 162 129 175 76 24 1489 30-year normal 99 121 133 131 104 60 72 78 103 76 106 81 1163 19  Surface runoff was the main source of water for the reservoir (82%) Precipitation (mm)
  20. 20. Reservoir Water Balance  The reservoir remained nearly full most of the time except during the growing season. 20
  21. 21. Reservoir Water Balance (Last slide edited)  The reservoir received 2.5 times greater inflow in the wetter year. 21
  22. 22. Hydraulic Retention Time (HRT)  HRT for 2019-2020 (33.8 days) was almost three times longer than the HRT for 2020-2021 (12.4 days). 22
  23. 23. Nitrogen Concentration Reduction (CR)  Total nitrogen concentration in outflow (Cout) was significantly lower than that in inflow (Cin) by 40%. Year Cin Cout CR (mg L-1) (mg L-1) (mg L-1) (%) NO3-N 2019 5.05 2.04 3.01* 60* 2020 2.00 1.09 0.91* 45* Total 2.80 1.32 1.48* 53* NH4-N 2019 0.45 0.14 0.31* 70* 2020 0.09 0.08 0.01 14 Total 0.19 0.09 0.10* 51* ON 2019 0.66 0.82 -0.16 -25 2020 0.72 0.79 -0.08 -11 Total 0.69 0.80 -0.11 -16 TN 2019 6.16 3.00 3.16* 51* 2020 2.81 1.96 0.85* 30* Total 3.68 2.21 1.47* 40* 23
  24. 24. Nitrogen Loads  TN load was significantly reduced by 47%. 24
  25. 25. Phosphorous Concentration Reduction  Ortho-phosphate concentration in outflow was significantly lower than that in inflow.  Particulate P concentration in outflow was significantly higher than that in inflow. 25 Year Cin Cout CR (mg L-1) (mg L-1) (mg L-1) (%) Ortho-P 2019 0.28 0.13 0.16 56 2020 0.11 0.07 0.04* 35* Total 0.16 0.08 0.07* 46* PP 2019 0.07 0.11 -0.03* -42* 2020 0.08 0.10 -0.02 -21 Total 0.08 0.10 -0.02* -29* TP 2019 0.36 0.23 0.12 35 2020 0.19 0.17 0.02 11 Total 0.23 0.19 0.05 21
  26. 26. Phosphorous Loads  TP load was significantly reduced by 30%. 26
  27. 27. Sediment Concentration and Loads  TSS concentration was significantly reduced by 86%. Year Cin Cout CR (mg L-1) (mg L-1) (mg L-1) (%) TSS 2019 391 50 341* 87* 2020 300 45 255* 85* Total 319 46 273* 86* 27  TSS Load was significantly reduced by 87%.
  28. 28. Factors Affecting Nutrient and Sediment Dynamics in the Reservoir  Load reductions were positively correlated with HRT and water temperature, negatively correlated with reservoir inflow and water volume.  Water temperature was significantly correlated with the load reduction of NO3-N and NH4-N. Total inflow Water volume Water temperature HRT NO3-N -0.90* -0.74 0.85* 0.95* ON -0.25 -0.86* 0.70 0.63 NH4-N -0.70 -0.44 0.83* 0.80 TN -0.85* -0.72 0.76 0.99* OP -0.52 -0.49 0.56 0.46 PP -0.38 -0.89* 0.75 0.59 TP -0.59 -0.73 0.71 0.61 TSS -0.45 -0.33 0.50 0.58 28
  29. 29. Conclusions  The DWR reservoir retained 14% of total inflow.  The reservoir reduced TN, TP, and TSS concentrations by 40%, 21%, and 86%, respectively.  The reservoir reduced TN, TP, and TSS loadings by 47% 30%, and 87%, respectively.  The HRT was the major factor affecting the removal efficiency of N and sediment in the reservoir, while water volume was the most significant factor affecting the removal efficiency of organic N and P species.  The removal efficiency of the reservoir would be highest during the summer and early fall months.  The expected water quality benefits from the DWR systems would be highly correlated with the crop water requirements. 29
  30. 30. Thank you! 30

Editor's Notes

  • To alleviate wet stresses, drainage has been used on poorly drained soils with shallow water table to
  • Several management practices have been proposed to improve crop production and reduse nutrient losses from drained fields.
    DWR is an innovative practice stores…..
  • The field study was conducted on a privately owned from near….
  • Two treatment were implemented on the site as shown in this figure
  • We collected …
  • These are some examples of the typical Flow and water quality measurement stations installed at the study site. We used V notch weirs to measure flow, and automated water samplers to collect flow proportional samples. These were samples were analyzed for total nitrogen, ammonium, total kaledaal nitrogen, ….total suspended solids
  • We conducted several field measuremenst at the study site, we monitored ….
    We conducted a Topographical survey of the storage reservoir to estimate its storage capacity: Acoustic Doppler current profiler,
  • We used the data from the reservoir survey to draw and elevation map and generate the reservoir area depth volume relationship, This relationship was used to estimate the volume based on the measured WL
  • A water level control structure shown on the (left) side of this picture was installed at the outlet of the main drain of DWR treatment to control drainage from the field.
    A smart drainage system shown on the (right) was connected to the control structure to automatically manage drainage and sub-irrigation based on water table level
  • A daily water balance was conducted for the reservoir based on the daily measured discharge rates at the inflow points and the outflow point according to this equation, where
  • Similarly, Daily nutrient and sediment balances were conducted for each of the nitrogen and phosphorous species , and sediment by using this equation, where
  • The hydraulic retention time (HRT) whish is defined in this study as.. Was estimated using this equation by dividing the reservoir storage capacity by the summation of reservoir inflow sources
  • We conducted several sstatical analysis to compare
  • Now, I will move on to discuss the results from the WQ study
  • The first year of the study was relatively wet, especially during the first 3 months (may-july), where P was 50% less than the long term average, this P deficit was compensated by P in Sep and Feb that led to small deviation from the annual long term P.
    On the hand, the second year was relatively wet, with total P higher than long term by 28%. This years can be divided into two periods, the first period from May-Oct, which had comparable P to long term P, and the second period from Nov-feb whish was extremely wet with P greater than double the long-term normal .

    These two Pie charts summarize the water balance of the reservoir, the left chart shows the inflow budget.
  • And this graph shows the reservoir water level during the two years of the study, the reservoir stayed nearly full except for the growing season period when water was withdrawn for irrigation. It should be noted that at the beginning of the study the reservoir was partially drained to install the control structure at the reservoir outlet.
  • Due to the wet condition in the second year, the reservoir received 2.5 times ….
  • monthly HRT greatly varied depending on inflow volume and ranged from 3.5 days in Feb 2021 to 222.9 days in Oct 2020.
    This difference in HRT was caused by the relatively wet conditions frequently occurred during 2020-20221.
  • N conc reduction was mainly due to the reduction of NO3-N concentration. As a result of the extremely dry condition during the growing season of the first year, N losses from the field were much higher in first year compared to the second year. As shown in the table, N conc was more than two times Tn conc in the second year, and the reduction in first year also much higher, 51 vs 30%
    The ON concentration was not reduced in the reservoir since a portion of the inorganic species of nitrogen may have been assimilated by algae and eventually released from the reservoir outlet in the algae biomass as ON
  • Subsurface drainage exported the most of N to the reservoir with 53%, while frosted land exported the least amount. The reservoir reduced TN by 47%, 43% was assimilated, 4% was recycled back.
  • The reservoir significantly reduced Orth-P by 46%, however PP was significantly higher. Ortho-P can be easily consumed by aljee and aquatic plants, while PP settles to the bottom of the water column until it is released from the reservoir with sediment
  • Surface runoff exported the most of P to the reservoir, while drainage exported the least amount. The reservoir reduced TN by 30%, 21% was assimilated, 9% was recycled back.
  • The reservoir significantly reduced the concentration and loading of sediment by 86, and 87 respectively.
    Sediment in Runoff from DWR was highest with 64% of sediment. This can be attributed to two reasons: 1 the contributing area of DWR runoff was higher 2. the wetter soil profile of DWR due to higher water table level.
  • Factors affecting nutrient and sediment dynamics in the reservoir were investigated.
    In general, the results showed that nitrogen and phosphorous load reductions were positively correlated with the reservoir water temperature and HRT, and negatively correlated with total reservoir inflow and reservoir water volume
  • I’m happy to take any questions

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