author = "Hartanto, I. M. and Kwast, J. van der and Alexandrilis, T. K. and 
                         Almeida, Waldenio Gambi de and Song, Y. and Andel, S. J. van and 
                         Solomatine, D. P.",
          affiliation = "{UNESCO-IHE Institute for Water Education} and {UNESCO-IHE 
                         Institute for Water Education} and {Aristotle University of 
                         Thessaloniki} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {UNESCO-IHE Institute for Water Education} and 
                         {UNESCO-IHE Institute for Water Education} and {UNESCO-IHE 
                         Institute for Water Education}",
                title = "Data assimilation of satellite-based actual evapotranspiration in 
                         a distributed hydrological model of a controlled water system",
              journal = "International Journal of Applied Earth Observation and 
                 year = "2017",
               volume = "57",
                pages = "123--135",
                month = "May",
             keywords = "Hydrology Data assimilation, Particle filter, Evapotranspiration 
                         Controlled water system, Earth observation.",
             abstract = "Advances in earth observation (EC) and spatially distributed 
                         hydrological modelling provide an opportunity to improve modelling 
                         of controlled water systems. In a controlled water system human 
                         interference is high, which may lead to incorrect parameterisation 
                         in the model calibration phase. This paper analyses whether 
                         assimilation of EO actual evapotranspiration (ETa) data can 
                         improve discharge simulation with a spatially distributed 
                         hydrological model of a controlled water system. The EO ETa 
                         estimates are in the form of eight-day ETa composite maps derived 
                         from Terra/MODIS images using the ITA-MyWater algorithm. This 
                         algorithm is based on the surface energy balance method and is 
                         calibrated for this research for a low-lying reclamation area with 
                         a heavily controlled water system: the Rijnland area in the 
                         Netherlands. Data assimilation (DA) with the particle filter 
                         method is applied to assimilate the ETa maps into a spatially 
                         distributed hydrological model. The hydrological model and DA 
                         framework are applied using the open source software SIMGRO and 
                         PCRaster-Python respectively. The analysis is done for a period 
                         between July and October 2013 in which a high discharge peak 
                         followed a long dry-spell. The assimilation of EC ETa resulted in 
                         local differences in modelled ETa compared to simulation without 
                         data assimilation, while the area average ETa remained almost the 
                         same. The modelled cumulative discharge graphs, with and without 
                         DA, showed distinctive differences with the simulation, with DA 
                         better matching the measured cumulative discharge. The bias of 
                         simulated cumulative discharge to the observed data reduced from 
                         14% to 4% when using DA of EO ETa. These results showed that 
                         assimilating EO ETa may not only be effective in the more common 
                         applications of soil moisture and crop-growth modelling, but also 
                         for improving discharge modelling of controlled water systems.",
                  doi = "10.1016/jjag.2016.12.015",
                  url = "http://dx.doi.org/10.1016/jjag.2016.12.015",
                 issn = "0303-2434",
             language = "en",
           targetfile = "hartanto_data.pdf",
        urlaccessdate = "14 abr. 2021"