Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Regional Ombrian Curves: Design Rainfall Estimation for a Spatially Diverse Rainfall Regime

Version 1 : Received: 28 March 2022 / Approved: 29 March 2022 / Online: 29 March 2022 (13:39:12 CEST)

A peer-reviewed article of this Preprint also exists.

Iliopoulou, T.; Malamos, N.; Koutsoyiannis, D. Regional Ombrian Curves: Design Rainfall Estimation for a Spatially Diverse Rainfall Regime. Hydrology 2022, 9, 67. Iliopoulou, T.; Malamos, N.; Koutsoyiannis, D. Regional Ombrian Curves: Design Rainfall Estimation for a Spatially Diverse Rainfall Regime. Hydrology 2022, 9, 67.

Journal reference: Hydrology 2022, 9, 67
DOI: 10.3390/hydrology9050067

Abstract

Ombrian curves, i.e. curves linking rainfall intensity to return period and time-scale, are well-established engineering tools, crucial to the design against storm waters and floods. Whereas at-site construction of such curves is considered a standard hydrological task, it is a rather challenging one when large regions are of interest. Regional modelling of ombrian curves is particularly complex due to the need to account for spatial dependence together with the increased variability of rainfall extremes in space. We develop a framework for the parsimonious modelling of the extreme rainfall properties at any point in a given area. This is achieved by assuming a common ombrian model structure except for a spatially varying scale parameter which is itself modelled by a spatial smoothing model for the 24 h average rainfall maxima that employs elevation as an additional explanatory variable. The fitting is performed on the pooled all-stations data using an advanced estimation procedure (K-moments) that allows both for reliable high-order moment estimation and simultaneous handling of space-dependence bias. The methodology is applied in the Thessaly region, a 13 700 km2 water district of Greece characterized by varying topography and hydrometeorological properties.

Keywords

ombrian curves; intensity-duration-frequency curves; rainfall extremes; regionalization; regional frequency analysis; spatial rainfall; design rainfall

Subject

EARTH SCIENCES, Environmental Sciences

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