A Parsimonious Hydrological Model for a Data Scarce Dryland Region

Inapplicability of state of the art hydrological models due to scarce data motivates the need for a modeling approach that can be well constrained to available data and still model the dominant processes. Such an approach requires embedded model relationships to be simple and parsimonious in parameters for robust model selection. Simplicity in functional relationship is also important from water management point of view if these models are to be coupled with economic system models for meaningful policy assessment. We propose a similar approach, but rather than selecting (through calibration) processes from a set of processes predefined in terms of functionalities or modules, we model already known dominant processes in dryland areas (evaporation, Hortonian overland flows, transmission loses and subsurface flows) in a simple manner by explicitly programming them as constraints and obtain parameters by minimizing a performance based objective function. Such use of mathematical programming allows flexible model calibration and simulation in terms of available data and constraints. The model results of the approach are however not perfect given its infancy. Nonetheless its imperfections can guide us to further improvements, in particular with regards to model structure improvement.