Despite its local and regional importance, hydro-meteorological data on the Sudd (one of Africa's largest wetlands) is very scanty. This is due to the physical and political situation of this area of Sudan. The areal size of the wetland, the evaporation rate, and the influence on the micro and meso climate are still unresolved questions of the Sudd hydrology. The evaporation flux from the Sudd wetland has been estimated using thermal infrared remote sensing data and a parameterization of the surface energy balance (SEBAL model). It is concluded that the actual spatially averaged evaporation from the Sudd wetland over 3 years of different hydrometeorological characteristics varies between 1460 and 1935 mm/yr. This is substantially less than open water evaporation. The wetland area appears to be 70% larger than previously assumed when the Sudd was considered as an open water body. The temporal analysis of the Sudd evaporation demonstrated that the variation of the atmospheric demand in combination with the inter-annual fluctuation of the groundwater table results into a quasi-constant evaporation rate in the Sudd, while open water evaporation depicts a clear seasonal variability. The groundwater table characterizes a distinct seasonality, confirming that substantial parts of the Sudd are seasonal swamps. The new set of spatially distributed evaporation parameters from remote sensing form an important dataset for calibrating a regional climate model enclosing the Nile Basin. The Regional Atmospheric Climate Model (RACMO) provides an insight not only into the temporal evolution of the hydro-climatological parameters, but also into the land surface climate interactions and embedded feedbacks. The impact of the flooding of the Sudd on the Nile hydroclimatology has been analysed by simulating two land surface scenarios (with and without the Sudd wetland). The paper presents some of the model results addressing the Sudd's influence on rainfall, evaporation and runoff of the river Nile, as well as the influence on the microclimate. The paper presents a case study that confirms the feasibility of using remote sensing data (with good spatial and poor temporal coverage) in conjunction with a regional climate model. The combined model provides good temporal and spatial representation in a region characterized by extremely scarce ground data.