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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10501 - Hydrology

Projekt

<a href="/cs/project/GC20-14151J" target="_blank" >GC20-14151J: Plošné srážkové odhady kombinující pozorování z mikrovlnných spojů a statistickou asimilaci dat (SpraiLINK)</a><br>

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Journal of Hydrology

ISSN

0022-1694

e-ISSN

1879-2707

Svazek periodika

617

Číslo periodika v rámci svazku

C

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

13

Strana od-do

—

Kód UT WoS článku

000938685700001

EID výsledku v databázi Scopus

2-s2.0-85146679652