Grass and forest potential evapotranspiration comparison using five methods in the Atlantic Coastal Plain
Studies examining potential evapotranspiration (PET) for a mature forest reference compared with standard grass are limited in the current literature. Data from three long-term weather stations located within 10 km of each other in the USDA Forest Service Santee Experimental Forest (SEF) in coastal South Carolina were used to (1) evaluate monthly and annual PET estimates from five different methods with varying complexities [Penman-Monteith (P-M), Turc, Thornthwaite (Thorn), Priestley-Taylor (P-T), and Hargreaves-Samani (H-S)] at two grass reference sites; and (2) compare results for the grass sites with PET estimated using the P-M method for a forest reference site using measured daily climatic data for the 2011–2014 period. The grass reference sites are located at the SEF headquarters (SHQ) and in the Turkey Creek watershed (TC). The forest reference station is on a 27-m-tall tower above the canopy of a pine/mixed hardwood forest in watershed WS80 in the SEF. At the WS80 forest site, the highest annual PET (1,351 mm) was observed in 2011 with the lowest rainfall (934 mm), and the lowest PET (1,017 mm) was observed in 2013 with the highest rainfall (1,433 mm), which is consistent with the two grass sites. The temperature-based H-S method yielded estimated monthly and annual PETs that were in better agreement than those of another temperature-based Thorn method at both grass sites when compared against the P-M PET for the forest site. The P-M–based PET values estimated for the SHQ grass site were significantly lower ( α=0.05) than those obtained at the TC grass site and the P-M PET values for the WS80 forest site. The solar radiation-based Turc and temperature-based Thorn PET estimates at both grass sites were significantly different ( α=0.05) from the P-M PET estimates for the forest. These results for the grass sites demonstrate that PET estimates are sensitive to the method used, resulting in significantly different estimates using a single method even for nearby sites because of differences in the complexity of describing the PET process, climatic factors, and interaction with site vegetation types. When compared with the P-M PET for the forest site, the P-T method was in the closest agreement, with the highest R2 of 0.96 and the least bias of 9.7% in mean monthly estimates, followed by the temperature-based H-S with an R2 of 0.95 and a bias of 12.6% at the SHQ grass site. It is concluded that the simpler P-T and H-S methods appear to be adequate to estimate forest P-M PET and that their estimates are within the error bounds of the data-intensive P-M PET method for coastal forests.