Remote sensing in water balance modelling for evapotranspiration at a rural watershed in Central Greece. (16th April 2019)

• Record Type: Journal Article
• Authors: Dalezios, Nicolas R.; Dercas, Nicholas; Blanta, Anna; Faraslis, Ioannis N.
• Is Part Of: International journal of sustainable agricultural management and informatics. Volume 4:Number 3/4(2018)
• Page Start: 306
• Page End: 337
• Publication Date: 2019-04-16
• Subjects: remote sensing -- rural watershed -- evapotranspiration -- ET -- satellites -- water balance models -- water resources management; Sustainable agriculture -- Management -- Periodicals; Sustainable agriculture -- Data processing -- Periodicals; Agricultural productivity -- Management -- Periodicals; Agricultural productivity -- Data processing -- Periodicals; Agricultural resources -- Data processing -- Periodicals; Agricultural systems -- Management -- Periodicals; Agricultural systems -- Data processing -- Periodicals; 338.1
• Languages: English
• ISSNs: 2054-5819

Abstract

There is an increasing trend in water balance modelling for remote sensing tools, which provide distributed information of watershed features. The paper's objective consists of exploring the remote sensing potential for evapotranspiration estimation in water balance modelling of a small rural watershed with limited data, namely Portaikos rural mountainous watershed of 132 km 2 in Central Greece. Three water balance models with small number of parameters are used, namely Abulohom's, GR2M and Xiong-Guo model, respectively. Two approaches are considered. At first, monthly potential evapotranspiration derived from conventional meteorological data is used as input to the models. Second, air temperature is derived from land surface temperature (LST) of NOAA/AVHRR satellite images for monthly evapotranspiration estimation. Time series of the above parameters for 13 years (1981-1993) are used. The remote sensing potential for evapotranspiration estimation is assessed by comparing the observed and simulated monthly runoff at the output of Portaikos watershed. Four error statistics are used for validation. The results are considered quite satisfactory for the four error statistics. The GR2M shows relatively better performance than the other models for all the error statistics, as well as for the satellite-based approach, which shows slightly better performance than the conventional approach.