SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales 
Authors:Abiodun, O.O., H. Guan, V.E.A. Post and O. Batelaan 
Journal:Hydrology and Earth System Sciences 
Volume (Issue):22(5) 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:evapotranspiration assessment 
Secondary Application Category:hydrologic assessment 
Watershed Description:44 km^2 Sixth Creek located in the western part of the Mountain Lofty ranges in the state of South Australia, Australia. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000– 2005) and 7-year validation period (2007–2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9% were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.