Estimating reference evapotranspiration using remote sensing and empirical models in a region with limited ground data availability in Kenya

Evapotranspiration is an important component of the hydrological cycle and its accurate quantification is crucial for the design, operation and management of irrigation systems. However, the lack of meteorological data from ground stations is a clear barrier to the proper management of water resources in poor countries, increasing the risks of water scarcity and water conflicts. In the presented study, three temperature based ET models are evaluated in the Taita Hills, Kenya, which is a particularly important region from the environmental conservation point of view. The Hargreaves, the Thornthwaite and the Blaney–Criddle are the three tested methods, given that these are the most recommended approaches when only air temperature data are available. Land surface temperature data, retrieved from the MODIS/Terra sensor are evaluated as an alternative input for the models. One weather station with complete climate datasets is used to calibrate the selected model using the FAO-56 Penman–Monteith method as a reference. The results indicate that the Hargreaves model is the most appropriate for this particular study area, with an average RMSE of 0.47 mm d−1, and a correlation coefficient of 0.67. The MODIS LST product was satisfactorily incorporated into the Hargreaves model achieving results that are consistent with studies reported in the literature using air temperature data collected in ground stations.