Areal reduction factors from high-resolution rain gauges in Austria

Abstract. Areal Reduction Factors (ARFs) are widely used to convert point design precipitation derived from intensity–duration–frequency (IDF) curves into areal precipitation values for hydrological design. Despite their importance, ARFs remain highly uncertain, particularly for short durations and small areas, due to insufficient representation of precipitation spatial variability. In this study, ARFs are empirically derived using a fixed-area approach for the Feldbach region in southeastern Austria using the WegenerNet, a dense rain gauge network with high temporal resolution (5 minutes) for the period 2007–2022. The results confirm that ARFs generally increase with duration and decrease with area, while pronounced dependencies on season and return period are observed, particularly for sub-hourly durations. Contrary to common assumptions, an application of ARF is required even for areas as small as 1 km2, indicating that point measurements and pixel-based precipitation estimates cannot be considered equivalent. For sub-hourly durations, ARFs increase partially with the return period. Seasonal analysis reveals smaller ARFs during spring and summer, associated with convective precipitation, and higher values during winter. The relationship between ARFs and topography is found to be weak, with only negligible correlations between ARFs and station elevation.

Authors

Institutions

Publication Details

Journal
Natural hazards and earth system sciences
Published
2026-10-15
DOI
https://doi.org/10.5194/nhess-26-5057-2026
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Areal reduction factors from high-resolution rain gauges in Austria

Jannick Alpers, Hannes Müller‐Thomy, Golbarg Goshtasbpour, Kai Schröter
Natural hazards and earth system sciences
Precipitation Measurement and Analysis
article

Areal reduction factors from high-resolution rain gauges in Austria

Jannick Alpers, Hannes Müller‐Thomy, Golbarg Goshtasbpour, Kai Schröter
article en

Abstract

Abstract. Areal Reduction Factors (ARFs) are widely used to convert point design precipitation derived from intensity–duration–frequency (IDF) curves into areal precipitation values for hydrological design. Despite their importance, ARFs remain highly uncertain, particularly for short durations and small areas, due to insufficient representation of precipitation spatial variability. In this study, ARFs are empirically derived using a fixed-area approach for the Feldbach region in southeastern Austria using the WegenerNet, a dense rain gauge network with high temporal resolution (5 minutes) for the period 2007–2022. The results confirm that ARFs generally increase with duration and decrease with area, while pronounced dependencies on season and return period are observed, particularly for sub-hourly durations. Contrary to common assumptions, an application of ARF is required even for areas as small as 1 km2, indicating that point measurements and pixel-based precipitation estimates cannot be considered equivalent. For sub-hourly durations, ARFs increase partially with the return period. Seasonal analysis reveals smaller ARFs during spring and summer, associated with convective precipitation, and higher values during winter. The relationship between ARFs and topography is found to be weak, with only negligible correlations between ARFs and station elevation.

Natural hazards and earth system sciencesVol. 26(10)
Technische Universität Braunschweig (DE)
Climate action
Openalex Percentile: Top 95%
Precipitation Measurement and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.