HS6.8 | Applying Remotely Sensed Water Cycle Components in Hydrological Modelling, and Synthesizing them With In-Situ Data
EDI
Applying Remotely Sensed Water Cycle Components in Hydrological Modelling, and Synthesizing them With In-Situ Data
Convener: Zheng Duan | Co-conveners: Christina Anna OrieschnigECSECS, Jianzhi Dong, Hajar ChoukraniECSECS, Hongkai Gao, John W. Jones, Junzhi Liu
Orals
| Thu, 18 Apr, 08:30–10:15 (CEST)
 
Room 2.15
Posters on site
| Attendance Thu, 18 Apr, 16:15–18:00 (CEST) | Display Thu, 18 Apr, 14:00–18:00
 
Hall A
Orals |
Thu, 08:30
Posters on site
Thu, 16:15
The hydrological cycle involves the continuous movement of water on, above, and below the surface of the Earth. In general, hydrological cycle components (e.g., precipitation, evaporation, water storage, and runoff) are characterized by large temporal and spatial variability. Accurate monitoring of various hydrological cycle components and the development of hydrological models are important for improving our understanding of hydrological processes. Acquiring this understanding is a crucial prerequisite to ameliorate resource management, optimize the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts.

With significant development of sensor technology and sharply growing platforms in past decades, remote sensing offers an enhanced capability to monitor various hydrological cycle components at different temporal and spatial scales to complement, or even replace, in situ measurements. Considerable efforts have been made to explore the potential of remotely sensed data from a vast range of different platforms (e.g., satellite, airborne, drone, ground-based radar) and sensors (e.g., optical, infrared, microwave) in advancing hydrology research, particularly in poorly gauged and ungauged regions. The application of remote sensing in hydrology is expected to increase with enhanced recognition of its potentials and continuous development of advanced sensors (e.g., new satellite missions) and retrieval methods (e.g., innovative machine learning and data assimilation techniques).

This session aims to present and discuss recent advances in the remote sensing of hydrological cycle components, their application in hydrological modeling, and their synthesis with in-situ data. We particularly welcome contributions that explore:
- The performance of remotely sensed data in multi-variable calibration and spatial evaluation of hydrological models
- The added-value of spatially downscaling remotely sensed data in improving hydrological modeling
- The combination of in-situ and remotely sensed data to analyze water cycle components and hydrological extremes such as floods and droughts
- The development of novel methods to gather in-situ benchmark data to combine with remotely sensed approaches
- Synthesized advances of remote sensing applications in hydrology, in natural and anthropized ecosystems

Session assets

Session materials Session summary

Orals: Thu, 18 Apr | Room 2.15

Chairpersons: Zheng Duan, Christina Anna Orieschnig, John W. Jones
08:30–08:35
5-minute convener introduction
EGU24-16494
|
Highlight
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On-site presentation
CNES Earth Observation Programme and our vision for the monitoring of the water cycle
Sophie Le Gac et al.
EGU24-12835
|
ECS
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Virtual presentation
Improving Groundwater Recharge Estimation Using Remote Sensing Information in a Multiobjective Calibration.
Diego Cortes Ramos and Adriana Patricia Piña Fulano
EGU24-14248
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ECS
|
Highlight
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On-site presentation
Landscape and Burn Severity Controls on Post-fire Snowpack Response in Montane Forests 
David Rey and Graham Sexstone

Posters on site: Thu, 18 Apr, 16:15–18:00 | Hall A

Display time: Thu, 18 Apr 14:00–Thu, 18 Apr 18:00
Chairpersons: Hajar Choukrani, Jianzhi Dong, Hongkai Gao
EGU24-21704
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On-site presentation
An observational constraint of global soil moisture droughts 
Guoyong Leng et al.
EGU24-12415
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ECS
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On-site presentation
Applicability of cloud radar observations for an intra-event analysis of runoff on a steep vineyard
Tatiana Nomokonova et al.