Root-zone soil moisture in the regional scale has always been a missing element of the hydrological cycle. Knowing its value could be a great help for estimating evapotranspiration, erosion, runoff, permeability, Irrigation need etc. The recently developed Soil Moisture Analytical Relationship (SMAR) can relate the surface soil moisture to the moisture of deeper layer using a physical balance equation. In recent years, development of satellite technologies has provided the opportunity to have an estimation of parameters with temporal and spatial variability. A number of satellites (SSM/I, AMSR-E, TRMM/TMI and SMMR) succeeded in retrieving surface soil moisture using passive microwave remote sensing. Thus, assimilating surface soil moisture satellite data into SMAR seems very promising in estimation of root-zone moisture in the regional or watershed scales. SMAR proved to effectively estimate the root zone soil moisture in the previous studies, yet there is still room for some modifications regarding this topic. For example, the soil water loss function (i.e. deep percolation and evapotranspiration) assumed to be linear in SMAR model. In this regard, the soil moisture profile data from two research sites (AMMA and SCAN) were investigated. The results showed that after a rainfall, soil water losses decrease exponentially until they reach a minimum steady state and knowing this will help to modify SMAR equation.

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