Development and Application of a Rainfall Temporal Disaggregation Method to Project Design Rainfalls

Abstract

A climate model is essential for hydrological designs considering climate change, but there are still limitations in employing raw temporal and spatial resolutions for small urban areas. To solve the temporal scale gap, a temporal disaggregation method of rainfall data was developed based on the Neyman–Scott Rectangular Pulse Model, a stochastic rainfall model, and future design rainfall was projected. The developed method showed better performance than the benchmark models. It produced promising results in estimating the rainfall quantiles for recurrence intervals of less than 20 years. Overall, the analysis results imply that extreme rainfall events may increase. Structural/nonstructural measures are urgently needed for irrigation and the embankment of new water resources.

Generating Continuous Rainfall Time Series with High Temporal Resolution by Using a Stochastic Rainfall Generator with a Copula and Modified Huff Rainfall Curves

“…The pulse-based model considers a rainfall event to consist of a cluster of rain cells whose occurrences follow a Poisson distribution. Rodriguez-Iturbe et al [18,19] examined two popular pulse-based models in detail: the Neyman-Scott cluster model [20][21][22][23][24][25] and Bartlett-Lewis cluster model [26][27][28][29][30][31].…”