OxTalks is Changing
Oxford Events, the new replacement for OxTalks, will launch on 16th March. From now until the launch of Oxford Events, new events cannot be published or edited on OxTalks while all existing records are migrated to the new platform. The existing OxTalks site will remain available to view during this period.
From 16th, Oxford Events will launch on a new website: events.ox.ac.uk, and event submissions will resume. You will need a Halo login to submit events. Full details are available on the Staff Gateway.
Harnessing spatial patterns of satellite data for multivariate hydrological model calibration
Conventionally, hydrological models are calibrated with streamflow data. However, streamflow-only calibration does not guarantee a reliable spatial representation of other hydrological fluxes and states with a distributed hydrological model. The increasing availability of satellite remote sensing (SRS) data has promoted the development of spatial hydrology and large-scale hydrological modelling. Multivariate calibration based on the simultaneous use of multiple SRS products can improve model performances.
This talk will present various multivariate calibration approaches based on the simultaneous incorporation of streamflow data and spatial patterns of multiple SRS products using the Mesoscale Hydrologic Model (mHM), implemented over the Volta River Basin (West Africa). The SRS products describe different hydrological processes (i.e. evaporation, soil moisture and terrestrial water storage change). A new bias insensitive spatial pattern metric is proposed as objective function. The impact of the choice of the SRS products, the calibration strategies and the meteorological forcing are investigated through various scenarios.
Results show an improvement in the prediction of spatial patterns of evaporation and soil moisture, while a deterioration is observed in the temporal dynamics of streamflow and terrestrial water storage change. Overall, it is found that spatial patterns of SRS products are their key feature, which can be used without absolute values to improve the predictive skill of hydrological models, thereby advancing the spatiotemporal prediction of floods and droughts.
Date:
29 November 2022, 15:30
Venue:
Dyson Perrins Building, off South Parks Road OX1 3QY
Venue Details:
Desert Room (first floor)
Speaker:
Dr Moctar Dembélé (University of Oxford / International Water Management Institute)
Organising department:
School of Geography and the Environment
Organiser:
Dr Anya Leenman (University of Oxford)
Organiser contact email address:
anya.leenman@chch.ox.ac.uk
Host:
Prof Simon Dadson (University of Oxford)
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Anya Leenman