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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 19, issue 10
Hydrol. Earth Syst. Sci., 19, 4127–4147, 2015
https://doi.org/10.5194/hess-19-4127-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 19, 4127–4147, 2015
https://doi.org/10.5194/hess-19-4127-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 13 Oct 2015

Research article | 13 Oct 2015

Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land use catchment in New Zealand

W. Me1,2, J. M. Abell1,a, and D. P. Hamilton1 W. Me et al.
  • 1Environmental Research Institute, University of Waikato, Private Bag 3105, 3240 Hamilton, New Zealand
  • 2College of Hydrology and Water Resources, Hohai University, Nanjing, 210098, China
  • anow at: Ecofish Research Ltd., Suite 1220, 1175 Douglas Street, Victoria, British Columbia, Canada

Abstract. The Soil Water Assessment Tool (SWAT) was configured for the Puarenga Stream catchment (77 km2), Rotorua, New Zealand. The catchment land use is mostly plantation forest, some of which is spray-irrigated with treated wastewater. A Sequential Uncertainty Fitting (SUFI-2) procedure was used to auto-calibrate unknown parameter values in the SWAT model. Model validation was performed using two data sets: (1) monthly instantaneous measurements of suspended sediment (SS), total phosphorus (TP) and total nitrogen (TN) concentrations; and (2) high-frequency (1–2 h) data measured during rainfall events. Monthly instantaneous TP and TN concentrations were generally not reproduced well (24 % bias for TP, 27 % bias for TN, and R2 < 0.1, NSE < 0 for both TP and TN), in contrast to SS concentrations (< 1 % bias; R2 and NSE both > 0.75) during model validation. Comparison of simulated daily mean SS, TP and TN concentrations with daily mean discharge-weighted high-frequency measurements during storm events indicated that model predictions during the high rainfall period considerably underestimated concentrations of SS (44 % bias) and TP (70 % bias), while TN concentrations were comparable (< 1 % bias; R2 and NSE both ~ 0.5). This comparison highlighted the potential for model error associated with quick flow fluxes in flashy lower-order streams to be underestimated compared with low-frequency (e.g. monthly) measurements derived predominantly from base flow measurements. To address this, we recommend that high-frequency, event-based monitoring data are used to support calibration and validation. Simulated discharge, SS, TP and TN loads were partitioned into two components (base flow and quick flow) based on hydrograph separation. A manual procedure (one-at-a-time sensitivity analysis) was used to quantify parameter sensitivity for the two hydrologically separated regimes. Several SWAT parameters were found to have different sensitivities between base flow and quick flow. Parameters relating to main channel processes were more sensitive for the base flow estimates, while those relating to overland processes were more sensitive for the quick flow estimates. This study has important implications for identifying uncertainties in parameter sensitivity and performance of hydrological models applied to catchments with large fluctuations in stream flow and in cases where models are used to examine scenarios that involve substantial changes to the existing flow regime.

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This study examined the applicability of the SWAT model to a moderately steep, temperate, small–sized catchment in Rotorua, New Zealand. It highlighted the importance of using high–frequency, event–based monitoring data for model calibration to alleviate the potential of underestimation of storm–driven fluxes. Parameter sensitivity was quantified for discharge, sediment and nutrient fluxes dependent on the relative dominance of base flow and quick flow.
This study examined the applicability of the SWAT model to a moderately steep, temperate,...
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