Actual evapotranspiration is an important compound of water and energy balance systems. Two models were used, the Surface Energy Balance System (SEBS) combines remote sensing data and meteorological in-situ data to solve the energy balance equation and assess AET. A hydrological balance model, the Backet Botton Hole (BBH) uses Hydrological and rainfall in-situ data. Results indicate an overestimation of AET-SEBS compared to AET-BBH which are consistent with results found by other researchers.

The current study proposed random block based nonparametric disaggregation model so that the weakness point of the existing nonparametric disaggregation models can be resolved with preserving the long-term persistence. The proposed model illustrates superior performance for disaggregating the net basin supply of the LCRR basin in the Great Lakes, which experienced the worst flood in 2011.

Previous evaluation of rainfall estimation by satellite algorithms showed an insufficient over Northern Tunisia. That was why we tried the WRF. We selected four heavy rainy days. For each day, 99 combinations of Cu and PBL are simulated. The sensitivity study highlighted the large difference in the estimation by the different schemes. The use of several verification techniques was extremely helpful to choose the best combinations for each event. The ensemble method gave very satisfying results.