Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F23%3A00365912" target="_blank" >RIV/68407700:21110/23:00365912 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.jhydrol.2022.129051" target="_blank" >https://doi.org/10.1016/j.jhydrol.2022.129051</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jhydrol.2022.129051" target="_blank" >10.1016/j.jhydrol.2022.129051</a>

Result language

angličtina

Original language name

Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment

Original language description

A wide range of applications in the field of urban hydrology requires rainfall data with high spatio-temporal resolutions. Commercial microwave links (CMLs) densely cover urban areas and can provide high-resolution path-averaged quantitative precipitation estimates (QPEs). This study aims to reduce systematic errors in CML QPEs using rainfall and discharge observations commonly available in urban areas and to assess the potential of such precipitation estimates for discharge predictions in small urban catchments. CML QPEs are optimized using flow data observed at the catchment outlet and using hourly rain rates from rain gauges located at different distances from the catchment. Both optimized CML QPEs and traditional rain gauge data are propagated through a rainfall-runoff model and evaluated against observed discharges. To quantify uncertainties of runoff predictions, the deterministic hydrodynamic model is extended by a stochastic error model explicitly accounting for model bias. Resulting runoff prediction intervals, namely their width and reliability, show that optimized CML QPEs predict discharges only slightly worse than those based on benchmark rain gauge data (1 gauge / 0.5–1 km2), especially for rainfall events with high spatial variability. Unbiased CML QPEs obtained in this study represent high-quality rainfall data suitable for many urban hydrology tasks, including assessment and real-time control of urban stormwater systems.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10501 - Hydrology

Project

<a href="/en/project/GC20-14151J" target="_blank" >GC20-14151J: Spatial rainfall estimates using improved observations from commercial microwave links and statistical data fusion (SpraiLINK)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Hydrology

ISSN

0022-1694

e-ISSN

1879-2707

Volume of the periodical

617

Issue of the periodical within the volume

C

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

13

Pages from-to

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UT code for WoS article

000938685700001

EID of the result in the Scopus database

2-s2.0-85146679652