SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land use catchment in New Zealand 
Authors:Me, W., J.M. Abell and D.P. Hamilton 
Year:2015 
Journal:Hydrology and Earth System Sciences 
Volume:19 
Pages:4127-4147 
Article ID: 
DOI:10.5194/hess-19-4127-2015 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Secondary Application Category:pollutant cycling/loss and transport 
Watershed Description:77 km^2 Puarenga River, located in the central part of the North Island, New Zealand. 
Calibration Summary: 
Validation Summary: 
General Comments: 
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. 
Language:English 
Keywords: