Capturing temporal variability for estimates of annual hydrochemical export from a first‐order agricultural catchment in southern Ontario, Canada

Abstract

Abstract:This 2-year study (2000, 2001) reports annual nutrient (phosphorus, nitrate) export from a first-order agricultural watershed in southern Ontario based on an intensive monitoring programme. The importance of storm and melt events in annual export estimates is demonstrated and the temporal variability in nutrient loading during events is related to processes occurring within the catchment. The feasibility of predicting event-related nutrient export from hydrometric data is explored. The importance of sampling frequency throughout events is also shown. Export of total phosphorus (TP), soluble reactive phosphorus (SRP) and nitrate (NO 3 ) for 2000 and 2001 averaged 0Ð35 kg ha 1 year 1 , 0Ð09 kg ha 1 year 1 , and 35 kg ha 1 year 1 (as N) respectively. Approximately 75% of annual TP export, 80% of annual SRP export and 70% of annual NO 3 export occurred during 28 events per year. A small number of large-magnitude events (>34 mm) accounted for 18-42% of annual TP export, 0-61% of annual SRP export and 13-33% of annual NO 3 export. Our results show that temporal variability in nutrient export is largely governed by discharge in this basin, and NO 3 export can be predicted from discharge. SRP and TP export can also be predicted from discharge, but only for events that are not large in magnitude. The sampling interval throughout events is important in obtaining precise estimates of nutrient export, as infrequent sampling intervals may over-or under-estimate nutrient export by š45% per event for P. This study improves our understanding of NO 3 and P export patterns and our ability to predict or model them by relating temporal variability in event nutrient export to discharge and processes occurring within the basin, and also by exploring the significance of sampling interval in the context of the importance of individual events, season and temporal variability during events.

Rainfall–runoff response and event-based runoff coefficients in a humid area (northwest Spain)

“…Martínez-Fernández et al 2005, Macrae et al 2007. However, in the Corbeira catchment, variations in the runoff coefficient have been limited, despite the notable differences in annual rainfall during the study period.…”

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

“…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].…”

“…Intensively managed tile-drained landscapes have been found to have a considerable potential for N and P losses, with regard to different soil conditions and cropping systems, especially during periods with elevated flows [3][4][5][6][7][8][9]. Nutrient concentrations in drainage waters may change rapidly within a rainfall-runoff event due to variable pre-event and event soil/catchment moisture conditions, related soil biogeochemical processes [10][11][12][13], precipitation characteristics, and water flow paths into drainage and with different origin and residence times [14][15][16][17].…”

Estimation of tributary total phosphorus loads to Hamilton Harbour, Ontario, Canada, using a series of regression equations

“…A major impediment to stronger regression relationships is hysteresis (Williams, 1989) because distinct TP concentration versus flow relationships have been found for the rising and falling limbs of a hydrograph over the course of an event Hooper, 2006a,2006b;Hirsch et al, 2010;Macrae et al, 2007;O'Connor et al, 2011). By addressing the issue of event-scale hysteresis, the performance of the regression approach can be further improved.…”

“…Accurate characterization of TP dynamics during high flow conditions was deemed critical to increasing the accuracy of TP loading estimates as the majority of annual TP loads occur during brief, high flow events such as storm events and the spring freshet (Booty et al, 2013;Duan et al, 2012;Horowitz, 2013;Macrae et al, 2007;Old et al, 2003;Richards and Holloway, 1987;Sharpley et al, 1993). Thus, not only was an updated event-based monitoring dataset needed, but also a simple TP loading estimation method with minimal data requirements will be essential to evaluate compliance with loading objectives and project the future state of the Harbour.…”