To demonstrate the rainfall error propagation through a hydrological model, we
employed a parsimonious conceptual hydrological model (HyMOD) as described by
Boyle et al. (2001) (Figure 13.7) in the model simulation.
HyMOD stream flow simulation proceeded under two scenarios: (1) the error as a
variable ratio of rain rates based on Equation (13.1) and (2) the error as a fixed ratio of
rain rates. In each error scenario, 100 ensemble members of the HyMOD simulation
were used to derive the confidence interval of stream flow prediction by using the
Monte Carol method. The simulated runoff output and its 95% uncertainty bound
FIGURE 13.3 Error distribution as a function of spatial and temporal scales (left) at
increasing rain rates (right) Percentage of error to rain rate.
258
SPATIOTEMPORAL SCALES OF REMOTE SENSING PRECIPITATION
employed a parsimonious conceptual hydrological model (HyMOD) as described by
Boyle et al. (2001) (Figure 13.7) in the model simulation.
HyMOD stream flow simulation proceeded under two scenarios: (1) the error as a
variable ratio of rain rates based on Equation (13.1) and (2) the error as a fixed ratio of
rain rates. In each error scenario, 100 ensemble members of the HyMOD simulation
were used to derive the confidence interval of stream flow prediction by using the
Monte Carol method. The simulated runoff output and its 95% uncertainty bound
FIGURE 13.3 Error distribution as a function of spatial and temporal scales (left) at
increasing rain rates (right) Percentage of error to rain rate.
258
SPATIOTEMPORAL SCALES OF REMOTE SENSING PRECIPITATION