Synthetic rainfall scenarios at high temporal resolutions are pivotal in numerous environmental applications. Despite the abundance of available simulation methods, their practical utilization among practitioners remains limited, often due to challenges in model calibration stemming from sample size constraints. We introduce a novel parsimonious approach for estimating parameters of multifractal disaggregation models, based solely on available Intensity-Duration-Frequency curves, which are widely and readily accessible within the practitioner community. The performance of the proposed approach is assessed using three case studies, wherein detailed statistical properties of the simulated time series are compared against observed benchmarks. Our results indicate the potential of our approach to facilitate the straightforward application of complex models.
Sub-daily rainfall simulation using multifractal canonical disaggregation: a parsimonious calibration strategy based on intensity-duration-frequency curves
Pierluigi Furcolo;
2024
Abstract
Synthetic rainfall scenarios at high temporal resolutions are pivotal in numerous environmental applications. Despite the abundance of available simulation methods, their practical utilization among practitioners remains limited, often due to challenges in model calibration stemming from sample size constraints. We introduce a novel parsimonious approach for estimating parameters of multifractal disaggregation models, based solely on available Intensity-Duration-Frequency curves, which are widely and readily accessible within the practitioner community. The performance of the proposed approach is assessed using three case studies, wherein detailed statistical properties of the simulated time series are compared against observed benchmarks. Our results indicate the potential of our approach to facilitate the straightforward application of complex models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
