HS2.3.2 | Water quality and availability modeling, risk analysis and decision support under current conditions and future scenarios
EDI
Water quality and availability modeling, risk analysis and decision support under current conditions and future scenarios
Convener: Albert NkwasaECSECS | Co-conveners: Miriam Glendell, Danlu GuoECSECS, Rohini Kumar, Matthew Miller, Olivia MillerECSECS, Michelle van Vliet
Orals
| Wed, 17 Apr, 14:00–18:00 (CEST)
 
Room 2.31
Posters on site
| Attendance Thu, 18 Apr, 16:15–18:00 (CEST) | Display Thu, 18 Apr, 14:00–18:00
 
Hall A
Posters virtual
| Attendance Thu, 18 Apr, 14:00–15:45 (CEST) | Display Thu, 18 Apr, 08:30–18:00
 
vHall A
Orals |
Wed, 14:00
Thu, 16:15
Thu, 14:00
Quantifying and understanding the impacts of environmental change on water quality and availability across space and time is critically important for ensuring that there is enough water of suitable quality to meet human and ecosystem needs now and in the future. Consequently, there is an urgent need for tools such as models, remote sensing, machine-learning and artificial intelligence algorithms that can anticipate these impacts and address the resulting environmental changes. These assessments in turn facilitate more effective water management that safeguards the critical ecosystem goods and services provided by freshwater resources. In addition, some of these tools, within both Bayesian and frequentist paradigms, enable consideration of prediction reliability, relating uncertainties to a decision makers’ attitudes and preferences towards risks, all while accounting for the uncertainty related to our system understanding, data and random processes. We seek contributions that apply modeling and other approaches to:
• investigate climate change impacts on water quality and quantity from local to global scales, including climate impact attribution studies
• quantify and couple supply and demand in support of water management including vulnerability assessment, scenario analysis, indicators, and the water footprint
• project future water supply and demand in the context of a changing climate, land use, population growth, and other potential drivers of change
• quantify the uncertainty of model predictions (due to data, model structure and parameter uncertainty)
• interpret and characterize uncertainties in machine-learning and data mining approaches that learn from large, possibly high-resolution data sets
• address the problem of scaling (e.g. disparity of scales between processes, observations, model resolution and predictions)
• test transferability and generalizability of findings
• assess water quality and quantity in either data-rich or data-sparse environments
• involve stakeholders in model development and maximise the use of expert knowledge to inform risk analysis and decision support, incl. monitoring, reporting and catchment management
• assess robustness in water quality and quantity hotspots

Orals: Wed, 17 Apr | Room 2.31

Chairpersons: Albert Nkwasa, Miriam Glendell, Rohini Kumar
EGU24-18007
|
solicited
|
Highlight
|
On-site presentation
Joseph Alcamo
EGU24-14412
|
On-site presentation
Bruna Grizzetti et al.
EGU24-3427
|
ECS
|
Highlight
|
On-site presentation
Edward R. Jones et al.
15:00–15:10
EGU24-2180
|
Highlight
|
On-site presentation
Maryna Strokal et al.
EGU24-2349
|
ECS
|
On-site presentation
Ilaria Micella et al.
EGU24-3370
|
ECS
|
On-site presentation
Shuman Liu et al.
15:40–15:45
Coffee break
Chairpersons: Matthew Miller, Michelle van Vliet, Olivia Miller
EGU24-7691
|
ECS
|
On-site presentation
Amber van Hamel and Manuela Brunner
EGU24-19357
|
On-site presentation
Fatemeh Karandish and Markus Berger
17:55–18:00

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

Display time: Thu, 18 Apr 14:00–Thu, 18 Apr 18:00
Chairperson: Albert Nkwasa
EGU24-10198
|
ECS
|
On-site presentation
Carolin Winter et al.
EGU24-22136
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On-site presentation
Edward R. Jones et al.
EGU24-9619
|
ECS
|
On-site presentation
Olinda Jack Mariano Rufo et al.

Posters virtual: Thu, 18 Apr, 14:00–15:45 | vHall A

Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 18:00
Chairpersons: Danlu Guo, Michelle van Vliet
EGU24-13703
|
Virtual presentation
Danlu Guo et al.