Abstract
It is important in water resource planning to accurately estimate the spatial distribution of evapotranspiration (ET) as an input parameter for hydrological studies. Although, conventional pan evaporation, lysimetric and eddy covariance techniques have been used, they only estimate point values. Hence, this study aimed at estimating the spatial distribution of ET within the Pra River Basin (a forest ecological zone) of Ghana, using cloud-free Landsat 8 (OLI/TIRS) satellite images employing the SEBAL methodology. The study further estimates the spatial distribution ET in relation to major climatic variables, Land Use Land Cover (LULC) types and energy balance components. The overall spatial distribution of ET had a mean value of 5.63 mm/day. Spatial distribution of ET (mm/day) for water body (5.51–7.81) and uncultivated forest (5.10–7.71) were high, while moderately average values were observed for logged forest (4.80–7.51). Settlement and bare landscapes observed low rates ((2.05–5.10) mm/day). Spatially, ET was higher in the upper western, central and the eastern parts of the basin, but lower in the northern part and pockets of areas at the southern part of the basin where settlement/bare landscape and logged forest dominate. Areas with high temperature and high solar radiation experiences high ET, while low wind speed, low to average temperature and solar radiation areas experience low ET. Also, areas with both high net radiation and ground heat flux but low to average sensible heat flux experiences high ET and vice versa. Linear regression analysis showed good fit with slope of 0.76 and R2 of 0.93 indicating that 93 % of the variations in observed field measurement of ET fitted perfectly well with ET distributions generated by the SEBAL model.
Highlights
It is crucial and important in water resource planning to accurately estimate the spatial distribution of evapotranspiration (ET) as an input parameter to simulate and predict both present and future hydrological processes of major river basins (Kundu et al, 2017, 2018; Long and Singh, 2012; Oguntunde, 2004; Bastiaanssen et al, 2005)
The Kappa coefficient was 0.942 and the overall accuracy was 97% indicating that the classification process avoided about 97% of the errors generated from the completely random classification compared to the ground truth points
3 cloud-free Landsat 8 (OLI/thermal infra-red (TIR)) images from different path and rows were mosaicked and used to model the spatial distribution in ET patterns based on SEBAL model within the PRB
Summary
It is crucial and important in water resource planning to accurately estimate the spatial distribution of evapotranspiration (ET) as an input parameter to simulate and predict both present and future hydrological processes of major river basins (Kundu et al, 2017, 2018; Long and Singh, 2012; Oguntunde, 2004; Bastiaanssen et al, 2005). ET is the most complex hydrologic parameter to estimate (Bastiaanssen et al, 1998; Sett et al, 2018) as it depends on factors such land use land cover (LULC) and climate change (Li et al, 2017) whose dominance is influenced by anthropogenic activities (Awotwi et al, 2019).
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