Effect of water sampling strategies on the uncertainty of phosphorus load estimation in subsurface drainage discharge.

Accurate phosphorus (P) load estimation in subsurface drainage water is critical to assess the field-scale efficacy of conservation practices. The HydroCycle-PO4 instrument measures real-time total reactive P (TRP) concentration without the need for sample filtration, thereby enabling comparative evaluation of different sampling strategies. The main objective of this study was to evaluate the effects of water sampling strategies on the uncertainty of P load estimation. Hourly TRP concentration and hourly drainage discharge measurements formed the reference P load dataset. Four hypothetical water sampling strategies were evaluated: (a) time-proportional discrete sampling, (b) time-proportional composite sampling, (c) flow-proportional discrete sampling, and (d) flow-proportional composite sampling. All sampling strategies underestimated TRP load compared with the reference dataset. Total reactive P load underestimation changed from 0.2 to 51% as time-proportional discrete sampling intervals increased from 3 h to 14 d. Total reactive P load underestimation changed from 12 to 43% as the time-proportional compositing scenario increased from 1 to 7 d, each with one aliquot per day. In the case of flow-proportional discrete sampling scenario, the lowest (0.6%) and the highest (-5.1%) uncertainties were observed when 1- and 5-mm flow intervals were used. The relative error based on the results provided by the flow-proportional composite sampling ranged from 0.2% when using 1-mm flow interval to -6.7% when using 5-mm flow interval. In conclusion, the flow-proportional sampling strategies provided a more accurate estimate of cumulative P load with fewer number of samples because a greater portion of samples were taken at higher flow rates compared with time-proportional sampling strategies.

Mapping of Agricultural Subsurface Drainage Systems Using Unmanned Aerial Vehicle Imagery and Ground Penetrating Radar.

Agricultural subsurface drainage systems are commonly installed on farmland to remove the excess water from poorly drained soils. Conventional methods for drainage mapping such as tile probes and trenching equipment are laborious, cause pipe damage, and are often inefficient to apply at large spatial scales. Knowledge of locations of an existing drainage network is crucial to understand the increased leaching and offsite release of drainage discharge and to retrofit the new drain lines within the existing drainage system. Recent technological developments in non-destructive techniques might provide a potential alternative solution. The objective of this study was to determine the suitability of unmanned aerial vehicle (UAV) imagery collected using three different cameras (visible-color, multispectral, and thermal infrared) and ground penetrating radar (GPR) for subsurface drainage mapping. Both the techniques are complementary in terms of their usage, applicability, and the properties they measure and were applied at four different sites in the Midwest USA. At Site-1, both the UAV imagery and GPR were equally successful across the entire field, while at Site-2, the UAV imagery was successful in one section of the field, and GPR proved to be useful in the other section where the UAV imagery failed to capture the drainage pipes' location. At Site-3, less to no success was observed in finding the drain lines using UAV imagery captured on bare ground conditions, whereas good success was achieved using GPR. Conversely, at Site-4, the UAV imagery was successful and GPR failed to capture the drainage pipes' location. Although UAV imagery seems to be an attractive solution for mapping agricultural subsurface drainage systems as it is cost-effective and can cover large field areas, the results suggest the usefulness of GPR to complement the former as both a mapping and validation technique. Hence, this case study compares and contrasts the suitability of both the methods, provides guidance on the optimal survey timing, and recommends their combined usage given both the technologies are available to deploy for drainage mapping purposes.

Adsorption Media for the Removal of Soluble Phosphorus from Subsurface Drainage Water.

Phosphorus (P) is a valuable, nonrenewable resource in agriculture promoting crop growth. P losses through surface runoff and subsurface drainage discharge beneath the root zone is a loss of investment. P entering surface water contributes to eutrophication of freshwater environments, impacting tourism, human health, environmental safety, and property values. Soluble P (SP) from subsurface drainage is nearly all bioavailable and is a significant contributor to freshwater eutrophication. The research objective was to select phosphorus sorbing media (PSM) best suited for removing SP from subsurface drainage discharge. From the preliminary research and literature, PSM with this potential were steel furnace slag (SFS) and a nano-engineered media (NEM). The PSM were evaluated using typical subsurface drainage P concentrations in column experiments, then with an economic analysis for a study site in Michigan. Both the SFS and generalized NEM (GNEM) removed soluble reactive phosphorus from 0.50 to below 0.05 mg/L in laboratory column experiments. The most cost-effective option from the study site was the use of the SFS, then disposing it each year, costing $906/hectare/year for the case study. GNEM that was regenerated onsite had a very similar cost. The most expensive option was the use of GNEM to remove P, including regeneration at the manufacturer, costing $1641/hectare/year. This study suggests that both SFS and NEM are both suited for treating drainage discharge. The use of SFS was more economical for the study site, but each site needs to be individually considered.

Measurement of soil water characteristic curve using HYPROP2.

Soil water characteristic curve (SWCC) has an important application in drainage, irrigation, soil physical behavior, and modeling hydrology and nutrient transport. However, measurement of the SWCC is often very time consuming, inaccurate and requires a lot of effort. In order to determine an accurate SWCC, we used HYPROP2. This method article extensively describes the topics which were not covered well by the instrument's manual such as collecting soil samples, use of the HYPROP refill unit, degassing water prior to degassing the tensio shafts and other procedures. Advice is provided in terms of better handling of the equipment to receive all four phases of an optimal measuring curve. Following the step-by-step procedure mentioned in this article would provide a high-quality SWCC. Our measurements were performed on both clay loam and sandy loam soils to show differences in the SWCC. We found that the upper tensio shaft took longer to cavitate for sandy loam soil compared to the clay loam soil.•This paper describes an efficient and accurate method to determine the SWCC using HYPROP2.•This method showed quick and reliable measurements of SWCC for a clay loam and sandy loam soil.•This method includes procedure for soil sample collection and laboratory analysis with HYPROP2.

Data of bromide sorption experiments with woodchips and tracer testing of denitrification beds.

Three different woodchip forms were tested for bromide sorption including ground woodchip, unwashed woodchips, and washed woodchips. We used six varying initial bromide concentrations to conduct the bromide sorption experiments with each woodchip form. Data on the initial and equilibrium bromide concentrations, wood mass, and initial and equilibrium solution pH from each of the six experiments are presented. Seven bromide tracer tests were conducted on field-scale denitrification beds. In this paper, data from each of the tracer tests including variation of bromide concentration over time and hydraulic indices of the tracer tests are presented. Interpretation of the data can be found in the research article entitled "Efficacy of bromide tracers for evaluating the hydraulic performance of denitrification beds treating agricultural drainage water" [1].

Comparison of Contaminant Transport in Agricultural Drainage Water and Urban Stormwater Runoff.

Transport of nitrogen and phosphorus from agricultural and urban landscapes to surface water bodies can cause adverse environmental impacts. The main objective of this long-term study was to quantify and compare contaminant transport in agricultural drainage water and urban stormwater runoff. We measured flow rate and contaminant concentration in stormwater runoff from Willmar, Minnesota, USA, and in drainage water from subsurface-drained fields with surface inlets, namely, Unfertilized and Fertilized Fields. Commercial fertilizer and turkey litter manure were applied to the Fertilized Field based on agronomic requirements. Results showed that the City Stormwater transported significantly higher loads per unit area of ammonium, total suspended solids (TSS), and total phosphorus (TP) than the Fertilized Field, but nitrate load was significantly lower. Nitrate load transport in drainage water from the Unfertilized Field was 58% of that from the Fertilized Field. Linear regression analysis indicated that a 1% increase in flow depth resulted in a 1.05% increase of TSS load from the City Stormwater, a 1.07% increase in nitrate load from the Fertilized Field, and a 1.11% increase in TP load from the Fertilized Field. This indicates an increase in concentration with a rise in flow depth, revealing that concentration variation was a significant factor influencing the dynamics of load transport. Further regression analysis showed the importance of targeting high flows to reduce contaminant transport. In conclusion, for watersheds similar to this one, management practices should be directed to load reduction of ammonium and TSS from urban areas, and nitrate from cropland while TP should be a target for both.

Modeling nitrate removal in a denitrification bed.

Denitrification beds are promoted to reduce nitrate load in agricultural subsurface drainage water to alleviate the adverse environmental effects associated with nitrate pollution of surface water. In this system, drainage water flows through a trench filled with a carbon media where nitrate is transformed into nitrogen gas under anaerobic conditions. The main objectives of this study were to model a denitrification bed treating drainage water and evaluate its adverse greenhouse gas emissions. Field experiments were conducted at an existing denitrification bed. Evaluations showed very low greenhouse gas emissions (mean N2O emission of 0.12 µg N m(-2) min(-1)) from the denitrification bed surface. Field experiments indicated that nitrate removal rate was described by Michaelis-Menten kinetics with the Michaelis-Menten constant of 7.2 mg N L(-1). We developed a novel denitrification bed model based on the governing equations for water flow and nitrate removal kinetics. The model evaluation statistics showed satisfactory prediction of bed outflow nitrate concentration during subsurface drainage flow. The model can be used to design denitrification beds with efficient nitrate removal which in turn leads to enhanced drainage water quality.