2021
DOI: 10.1007/s10661-021-08875-9
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An investigation into the impact of nine catchment characteristics on the accuracy of two phosphorus load apportionment models

Abstract: Funding No funding was provided for this study aside from supervisory support through Harper Adams University. Conflicts of interest/Competing interests NAAvailability of data and material Data were sourced from the National River Flow Archive and the EA historical river water quality. These were obtained under licence and are unavailable for distribution without the express permission of NRFA or the EA.

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(1 citation statement)
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“…The efficiency metrics for the LAM (R 2 = 0.73-0.98, NSE = 0.54-0.83) were satisfactory and comparable with other monthly model simulation results using SWAT, AGNPS and HSPF (R 2 > 0.50 and NSE > 0.50, Moriasi et al 2007). Notably, these results were comparable or superior to nutrient simulations for other watersheds using the LAM (R 2 =0.26-0.98, NSE=0.70-0.98; Chen et al 2013;Greene et al 2011;Mockler et al 2017;Stevenson et al 2021). Collectively, these assessments validate the feasibility of using the LAM for apportioning PS, surface runoff and groundwater contributions of P to the Shuanggang River.…”
Section: Riverine P Sources Apportionmentsupporting
confidence: 58%
“…The efficiency metrics for the LAM (R 2 = 0.73-0.98, NSE = 0.54-0.83) were satisfactory and comparable with other monthly model simulation results using SWAT, AGNPS and HSPF (R 2 > 0.50 and NSE > 0.50, Moriasi et al 2007). Notably, these results were comparable or superior to nutrient simulations for other watersheds using the LAM (R 2 =0.26-0.98, NSE=0.70-0.98; Chen et al 2013;Greene et al 2011;Mockler et al 2017;Stevenson et al 2021). Collectively, these assessments validate the feasibility of using the LAM for apportioning PS, surface runoff and groundwater contributions of P to the Shuanggang River.…”
Section: Riverine P Sources Apportionmentsupporting
confidence: 58%