This paper describes the development and validation of grid-based regional prediction equations of a conceptual monthly water balance model parameters. The purpose of the research is generally to provide gridded values of the model parameters using catchment characteristics for simulating monthly runoff at ungauged rivers, which at most suffer from lack of hydrological information. The catchment indices (characteristics) that are used in developing the prediction equations of the model

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... s are mean annual rainfall, average slope, NDVI, TWI, aspect, flow length, flow direction, maximum soil moisture, elevation, etc. The monthly water balance model has three parameters; C, k and SC. Not all catchment characteristics are correlated to all parameters, but parameter C was better correlated with mean annual rainfall and NDVI; and parameter SC with mean annual rainfall, NDVI and average slope. Parameter k was not significantly correlated to any of the indices, and hence taken as the average of optimized values. The monthly water balance model was calibrated for a group of selected 28 gauged catchments using FORTRAN program that uses Shuffled Complex Evolution algorithm optimization technique. The model inputs used in optimizing the parameters in the calibration are areal precipitation, calculated using Thiessen polygon method, and monthly potential evapotranspiration calculated using Penman-Montieth and Thornthwait. The monthly potential evapotanspiration obtained using Thorthwait methed is underestimated and it was adjusted by multiplying each monthly value by mean monthly ratio of Penman to Thornthwaite. The R2, IVF and MSE were the criteria used to evaluate the optimization technique. The optimized parameter values were related to physical catchment indices using regression [...]