Uncertainty assessment in historical precipitation time series
(EN)
Τσανης Γιαννης
(EL)
Δαλιακοπουλος Ιωαννης
(EL)
Κουτρουλης Αριστειδης
(EL)
Tsanis Giannis
(EN)
Daliakopoulos Ioannis
(EN)
Koutroulis Aristeidis
(EN)
Πολυτεχνείο Κρήτης
(EL)
Technical University of Crete
(EN)
Precipitation is the most important and well studied hydro-meteorological variable and
its characteristics and variability have challenged various scientific fields like water resources
management and climate change. As a hydrological model input, precipitation
is a space and time dependent variable with an uncertainty introduced due to instrument
or measurement errors. This paper presents an uncertainty assessment of precipitation
time series using the Data Uncertainty Engine (DUE), a tool developed within
the framework of the EC-funded project HarmoniRiB (Harmonised Techniques and
Representative River Basin Data for Assessment and Use of Uncertainty Information
in Integrated Water Management). The precipitation series are from the Geropotamou
Watershed, Crete, Greece. The results of this study will help identify the uncertainty in
the precipitation measurements and will provide decision makers with more reliable
information from both raw data and models.
(EN)
