SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Impact of precipitation pre-processing methods on hydrological model performance using high-resolution gridded dataset 
Authors:Abbas, S.A. and Y. Xuan 
Volume (Issue):12(3) 
Article ID:840 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:hydrologic assessment 
Watershed Description:2,215 km^2 Dee River, which flows to the Irish Sea and is located in northern Wales in the eastern part of the United Kingdom. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:: Effective representation of precipitation inputs is one of the essential components in hydrological model structures, especially when gauge measurements for the modelled catchment are sparse. Assessment of the impact of precipitation pre-processing is often nontrivial as precipitation data are very limited in the first place. In this paper, we demonstrate a study using a semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT) to examine the impact of different precipitation pre-processing methods on model calibration and the overall model performance with regards to the operational use. A river catchment in the UK is modelled to test against the three pre-processing methods: the Centroid Point Estimation Method (CPEM), the Grid Area Method (GAM) and the Grid Point Method (GPM). Cross-calibration and validation are then carried out by using the high-resolution Centre for Ecology & Hydrology–Gridded Estimate Areal Rainfall (CEH-GEAR) dataset. The results show that the proposed methods GAM and GPM can improve the model calibration significantly against the one calibrated with the existing CPEM method used by the model; the performance differences in the validation among the calibrated models, however, remain small and become irrelevant. The findings indicate that it is preferable to always make use of high-quality rainfall data, when available, with a better pre-processing method, even with models that are previously calibrated with low-quality rainfall inputs. It is also shown that such improvements are affected by the size of catchment and become less significant for smaller catchments. 
Keywords:Hydrological modelling; Precipitation pre-processing; Calibration; Cross-validation; SWAT; Gridded Rainfall Dataset