Bauer-Gottwein, Peter

Jiang, Liguang

Madsen, Henrik

Online Research Database In Technology

                       General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal   If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.     Downloaded from orbit.dtu.dk on: May 16, 2018Satellite altimetry-derived water level for calibration of river morphological parametersin hydrodynamic modelsJiang, Liguang; Madsen, Henrik; Bauer-Gottwein, PeterPublished in:Geophysical Research AbstractsPublication date:2018Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Jiang, L., Madsen, H., & Bauer-Gottwein, P. (2018). Satellite altimetry-derived water level for calibration of rivermorphological parameters in hydrodynamic models. Geophysical Research Abstracts, 20, [EGU2018-12562-1].Geophysical Research AbstractsVol. 20, EGU2018-12562-1, 2018EGU General Assembly 2018© Author(s) 2018. CC Attribution 4.0 license.Satellite altimetry-derived water level for calibration of rivermorphological parameters in hydrodynamic modelsLiguang Jiang (1), Henrik Madsen (2), and Peter Bauer-Gottwein (1)(1) Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark(ljia@env.dtu.dk; pbau@env.dtu.dk), (2) DHI, Agern Allé 5, 2970 Hørsholm, Denmark (hem@dhigroup.com)Hydrodynamic (HD) modeling has become an essential tool for understanding and predicting hydrologic pro-cesses and has been an important research topic in hydrological science. HD models can simulate details of riverflow that rainfall-runoff models alone cannot elucidate, such as the water depth, inundation extent, distributedwater-surface elevation (WSE), and timing of peak flows. Therefore, HD modeling is of paramount importance inflood forecasting and management systems.One of the key steps in HD modeling is calibration where model parameters are adjusted to minimize thedifference between modeled and measured quantities. Model calibration has conventionally relied on surveyedbathymetric data. However, river bathymetry data is not available in most parts of the world. This impedes rivermodeling and operational flood forecasting for poorly monitored basins.Advances in remote sensing observations have played an increasingly prominent role in hydrologic and hy-draulic fields, and have promoted the estimates of key hydrologic and hydraulic variables (e.g., snow depth, WSE,river geometry, discharge, and storage, etc.). WSE derived from satellite altimetry is complementary to gaugedata, especially in data-sparse and ungauged regions. Moreover, satellite altimetry provides spatially-distributedWSE, which is valuable for calibration of models with distributed, non-uniform parameters.This work investigates the added value of a constellation of altimetry missions for calibrating a 1D HDmodel (MIKE Hydro River) and explores parameter sensitivity of altimetry-derived SWE. To this end, aseries of calibration experiments are carried out using synthetic and real-world data from multiple missions(Envisat/SARAL, Jason-1/2, CryoSat-2) over the Songhua River basin. In this wide-channel river model, spatiallyvariable Manning’s roughness coefficient (n) and river bed elevation (Z0) are considered for 23 cross sections.The synthetic experiments show that the spatial variability of n and Z0 can be well constrained by CryoSat-2,and to a lesser extent by Envisat and SARAL with regularized inversion method. However, Jason-1/2 alonecannot constrain these parameters due to the coarse spatial sampling pattern. We find that higher accuracy ofaltimetry-derived WSE does not proportionally decrease parameter uncertainty for all cross sections. Instead,increased spatial sampling density helps to capture the spatial variability of morphological parameters. Weconclude that increased spatial sampling density is more important than temporal sampling density and dataaccuracy for calibrating morphological parameters of large-scale river models.

Satellite altimetry-derived water level for calibration of river morphological parameters in hydrodynamic models

http://orbit.dtu.dk/ws/files/146794782/EGU2018_12562_1.pdf

Satellite altimetry-derived water level for calibration of river morphological parameters in hydrodynamic models

Abstract

Similar works

Full text

Available Versions

Online Research Database In Technology