Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling

Abstract

Rainfall intensity is one of the most crucial meteorological parameters which is extensively used by water resource planners, hydrologists, irrigation experts, flood and draught regulatory authorities. Particularly, sub-daily temporal rainfall time series is quite essential for detailed planning of urban drainage design, storm water management. However, due to non-availability of reliable fine resolution rainfall data, under current scenario temporal disaggregation of existing rainfall record using various stochastic techniques is emerging as one of the most sought after option. In the present study, the Microcanonical Multiplicative Random Cascade (MMRC) model has been adopted for disaggregation of daily rainfall values to 1 h scale. Though MMRC is capable of generating statistically reliable rainfall time series, it is not competent enough to preserve the extreme rainfall characteristics.

In this paper, a new model has been presented where copula theory has been integrated with MMRC model to capture the dependence structure between coarse time step rainfall and its corresponding finer time steps. The procedure of disaggregation of coarse resolution rainfall series has been accomplished by this new Integrated MMRC-copula model with higher accuracy as it accounts for the random splitting procedure of cascade generator more precisely compared to MMRC model which generally leads to overestimation of extreme rainfall. An overall improved performance of the Integrated MMRC-Copula model in contrast to MMRC supports the model’s pertinence in the field of temporal disaggregation of rainfall.