Articles | Volume 22, issue 5
Research article
08 May 2018
Research article |  | 08 May 2018

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

Olanrewaju O. Abiodun, Huade Guan, Vincent E. A. Post, and Okke Batelaan

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.

Short summary
In recent decades, evapotranspiration estimation has been improved by remote sensing methods as well as by hydrological models. However, comparing these methods shows differences of up to 31 % at a spatial resolution of 1 km2. Land cover differences and catchment averaged climate data in the hydrological model were identified as the principal causes of the differences in results. The implication is that water management will have to deal with large uncertainty in estimated water balances.