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Accurate estimates of annual nutrient loads are required to evaluate trends in water quality following changes in land use or management and to calibrate and validate water quality models. While much emphasis has been placed on understanding the uncertainty of watershed-scale nutrient load estimates in naturally drained systems, few studies have focused on artificially drained landscapes in the Midwestern US and Canada. The objective of this study was to quantify uncertainty in annual dissolved reactive phosphorus (DRP) and nitrate-nitrogen (NO3-N) load estimates from four tile drain outlets and two tile drained headwater watersheds in Ohio, USA and Ontario, Canada. High temporal resolution datasets of discharge (10 to 30 min) and nutrient concentration (2 hr to daily) were collected over a 1 to 2 year period at each site and used to calculate a ‘true’ nutrient load. Monte Carlo simulations were used to subsample the measured data to assess the effects of sample frequency, calculation algorithm, and compositing strategies on the uncertainty of load estimates. Results showed that uncertainty in annual DRP and NO3-N load estimates was influenced by both the sampling interval and the load estimation algorithm. Uncertainty in annual nutrient load estimates increased with increasing sampling interval for all of the load estimation algorithms tested. Continuous discharge measurements and linear interpolation of nutrient concentrations yielded the least amount of uncertainty, but still tended to underestimate ‘true’ load. Compositing strategies generally improved the precision of load estimates compared to discrete grab samples; however, they often reduced the accuracy. Based on the results of this study, we recommended that nutrient concentration be measured at least daily for DRP and every 3 to 7 days for NO3-N in tile drains and tile drained headwater watersheds to accurately (±10%) estimate annual loads.
