This paper deals with development of parsimonious models for dryland areas. The modelling approach is to capture the dominant processes of dryland areas in a data-limited environment. Two processes, evaporation and subsurface flows, are identified as dominant and are modelled at monthly time steps for a study area in western India. The area is represented by interconnected linear (in storage-discharge relationship) reservoirs, and each reservoir is parameterized to represent the two fluxes. The parameters are estimated based on GRACE (terrestrial storage change) and MERRA2D (evaporation flux) data simultaneously. Finally, parsimony in parameters of the overall model (of interconnected linear reservoirs) is achieved by regionalizing recession parameters in terms of soil characteristics. This study elicits an approach that is urgently needed in data and water scarce regions.