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,
The 11th International Drainage Symposium
Des Moines, Iowa, August 31, 2022
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
Excessive nutrients in surface water
cause major water quality
degradation and fish kills.
Several best management practices (BMPs) have been proposed
to reduce nutrients and sediment losses from drained cropland to
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;
Improve water quality.
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.
Drainage water recycling (DWR)
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.
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
Soil: AltaVista fine
Corn (2019, 2021),
(1) Inflow from forested land (2) Outflow (3) Subsurface drainage, DWR
(4) Subirrigation (5) Surface runoff , CT (6) Surface runoff, DWR
Flow and water quality data were collected at the reservoir inlets and
outlet for two years (May 2019 – April 2021).
Water quality samples
Nitrogen: NO3-N, NH4-N, TKN, TN
Phosphorous: Ortho-P, TP
Flow and water quality measurements
at reservoir outlet
Flow and water quality measurements
of runoff from DWR field
Precipitation and air temperature
Reservoir water level and water temperature
Topographical survey of the storage reservoir
Bathymetric survey using
Reservoir water level
Automated and manual
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.
Reservoir Water Balance
Water balance was conducted for the reservoir for two years
(May 2019-Apr. 2021).
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.
Reservoir Nutrient and Sediment
Nutrient and sediment balances were conducted for the reservoir for
two years (May 2019-Apr. 2021).
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
𝐿𝐼𝑅𝑅 and 𝐿𝑜𝑢𝑡 are nutrient/sediment mass load leaving reservoir via
irrigation and outflow, respectively.
Reservoir Hydraulic Retention Time
The average time that inflow water remains in the
reservoir before it is released.
𝑉𝑚𝑎𝑥 is reservoir storage capacity
𝑷 + 𝑸𝒊𝒏 + 𝑸𝑹𝑶_𝑫𝑾𝑹 + 𝑸𝑹𝑶_𝑪𝑻 + 𝑸𝑫𝑹𝑵
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.
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
Surface runoff was the main source of water for the reservoir (82%)
Sediment Concentration and Loads
TSS concentration was significantly reduced by 86%.
Cin Cout CR
(mg L-1) (mg L-1) (mg L-1) (%)
2019 391 50 341* 87*
2020 300 45 255* 85*
Total 319 46 273* 86*
TSS Load was significantly reduced by 87%.
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
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
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.
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