Seasonal and event‐based drivers of runoff and phosphorus export through agricultural tile drains under sandy loam soil in a cool temperate region

Abstract

Frequent algal blooms in surface water bodies caused by nutrient loading from agricultural lands are an ongoing problem in many regions globally. Tile drains beneath poorly and imperfectly drained agricultural soils have been identified as key pathways for phosphorus (P) transport. Two tile drains in an agricultural field with sandy loam soil in southern Ontario, Canada were monitored over a 28-month period to quantify discharge and the concentrations and loads of dissolved reactive P (DRP) and total P (TP) in their effluent. This paper characterizes seasonal differences in runoff generation and P export in tile drain effluent and relates hydrologic and biogeochemical responses to precipitation inputs and antecedent soil moisture conditions. The generation of runoff in tile drains was only observed above a clear threshold soil moisture content (~0.49 m 3 ·m À3 in the top 10 cm of the soil; above field capacity and close to saturation), indicating that tile discharge responses to precipitation inputs were governed by the available soil-water storage capacity of the soil. Soil moisture content approached this threshold throughout the nongrowing season (October -April), leading to runoff responses to most events. Concentrations of P in effluent were variable throughout the study but were not correlated with discharge (p > 0.05). However, there were significant relationships between discharge volume (mm) and DRP and TP loads (kg ha À1 ) for events occurring over the study period (R 2 ≥ 0.49, p ≤ 0.001). This research has shown that the hydrologic and biogeochemical responses of tile drains in a sandy loam soil can be predicted to within an order of magnitude from simple hydrometric data such as precipitation and soil moisture once baseline conditions at a site have been determined.

Incorporating Rainfall-Runoff Events into Nitrate-Nitrogen and Phosphorus Load Assessments for Small Tile-Drained Catchments

“…M5, however, for both P compounds, gave unsatisfactory estimates of the monthly loads since the temporal changes of P concentrations were not covered by the regular sampling, as discovered in other studies when a weekly time step of sampling was employed [18,33,34].…”

“…For both P forms, higher proportions of REs for P loads were found. The higher share of RE on P loads compared to N loads was caused by the well documented different patterns of N and P leaching from soil into drainage waters [10,34], when P concentrations substantially rose with the elevated discharge across all the sites. This manifested the most at the sites with a substantial share of REs in the runoff (P53 site).…”

“…M2 appeared to be quite a reasonable algorithm for the assessment of N-NO 3 loads, when only grab sampling (without continuous monitoring of discharge) was employed. However, it still gave large underestimations, especially for both phosphorus compounds, as the grab sampling rarely captured different REs with different P concentration values, as documented by [31][32][33][34].…”

“…The within-site differences between the number and magnitudes of REs and their share of total runoff and between the N-NO 3 , P-PO 4 , and P tot loads were brought about most probably by the distinct hydrological connectivity and runoff formation pattern in particular drainage-catchment systems [7,21,34,46]. This connectivity is affected by the position of a drainage system in a particular part of a slope (higher, lower) and by local soil variability [42,43,[47][48][49].…”

“…These studies often conclude that the most dominant factors influencing nutrient fluxes are precipitation characteristics and catchment hydrological connectivity. This pertains, compared to nitrogen, to a greater extent to phosphorus, as high P concentrations in water from land drainage are associated predominantly with elevated flows, both from ploughland and grassland [4,5,[32][33][34]. Load assessment approaches without continuous discharge measurements and event sampling tend to underestimate P loads especially [33,35].…”