Posters

HS5.5.1

Global and regional water management is facing major challenges to reach targeted water quality goals. Globally major socio-economic developments are triggering a new water quality challenge, particularly in developing and transition countries. Increasing population and expanding public water supplies that fail to adequately address the treatment of wastewater flows, lead to significant water quality deterioration. Regionally the diffuse transfer of pollutants from land to water presents a major challenge, being co-dependent on changing weather patterns such as the frequency and magnitude of storms, the periodicity of droughts, land modifications and response time lags; leading to water quality degradation, risk to human and ecosystem health, food security, and the economy.

The United Nations Sustainable Development Goal 6 requires countries to monitor progress towards ‘ensuring sustainable management of water and sanitation for all' and set-up appropriate monitoring systems and indicators. SDG6 requires defining base lines, trends and targets to review the effectiveness of pollution mitigation measures. While high frequency monitoring and/or long time series have improved our process-based understanding of pollutant losses to water at catchment level, the patterns in water quality due to source management could be confounded by the effect of larger climate and weather cycles. Moreover, in many data poor locations, policy and management can only be informed by the interpretation of lower resolution data.

To this end, Bayesian approaches have become increasingly popular in water quality modelling, thanks to their ability to handle uncertainty comprehensively (data, model structure and parameter uncertainty) and as flexible statistical and data mining tools. Furthermore, graphical Bayesian Belief Networks can be powerful decision support tools that make it relatively easy for stakeholders to engage in the model building process and draw on all available information from expert knowledge to high resolution data sets.

This session focuses on global and regional water quality research and assessments concerning methods and data sets required to evaluate sustainable development measures. We invite submissions on: (i) methods to assess signals and trends in water quality, (ii) assessment of hydrological and biogeochemical processes on pollutant transfer and their relationship to climate effects, time lags and/or adaptive management changes, (iii) development of new modelling and data-driven frameworks identifying hotspots of water quality degradation posing a risk to human and ecosystem health, water and food security, and (iv) model and data based evaluations of strategies to improve water quality.

Keynote speaker:
Prof Peter Reichert: “The need for Bayesian approaches in water research and management.”
Eawag, Swiss Federal Institute of Aquatic Science and Technology; Department of Systems Analysis, Integrated Assessment and Modelling

Share:
Convener: Martina Flörke | Co-conveners: Ilona Bärlund, Rémi Dupas, Per-Erik Mellander, M. T. H. van Vliet
Orals
| Fri, 12 Apr, 08:30–10:15
 
Room 2.95
Posters
| Attendance Fri, 12 Apr, 14:00–15:45
 
Hall A

Attendance time: Friday, 12 April 2019, 14:00–15:45 | Hall A

Chairperson: Ilona Bärlund, Rémi Dupas
A.72 |
EGU2019-140<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Ana Carolina Russo, Marcio Antonio da Silva Pimentel, Paulo Scarano Hemsi, and Edison Russo
A.73 |
EGU2019-7116<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Chung-Yen Huang
A.74 |
EGU2019-8403<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Elefteria Psillakis, Niki Koutela, Maria-Liliana Saru, and Elena Fernández
A.75 |
EGU2019-15154<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
DongHyun Kim, Seokil Jung, Sukjun Chae, and Seung Oh Lee
A.76 |
EGU2019-6947<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Cheng-Yun Hsieh
A.77 |
EGU2019-4785<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Study on the Effect of copper, zinc toxicity according to changing Hardness concentration using D.magna
(withdrawn)
chun sang Hong and sung jong Lee
A.78 |
EGU2019-4382<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Rodrigo Quintela and Fernando Fan
A.79 |
EGU2019-1764<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Xizhi Nong, Dongguo Shao, Yi Xiao, Hua Zhong, and Yanqing Zhang
A.80 |
EGU2019-2142<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Ping Wang
A.81 |
EGU2019-4587<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Kyung-Seok Ko, Dong-Chan Koh, Jong-Sik Ryu, Yong Hwa Oh, Youn-Young Jung, and Ho Jeong Jo
A.82 |
EGU2019-4600<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Ching-Ping Liang, Chia-Hui Wang, and Jui-Sheng Chen
A.83 |
EGU2019-5466<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Lukas Knoll, Lutz Breuer, and Martin Bach
A.84 |
EGU2019-6409<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Chan-Hyeok Jeon, Chang-Seong Kim, and Jin-Yong Lee
A.85 |
EGU2019-6494<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Chang-Seong Kim and Jin-Yong Lee
A.86 |
EGU2019-6147<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Elisa Coraggio, Dawei Han, Theo Tryfonas, and Weiru Liu
A.87 |
EGU2019-6492<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
navid yaraghi, anna-kaisa ronkanen, ali torabihaghighi, and bjorn klove
A.88 |
EGU2019-6507<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Maimoona Raza and Jin-Yong Lee
A.89 |
EGU2019-17852<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Joelle Reine Youego Sihon, Jean-Jacques Braun, Stephane Audry, Jerome Viers, Yves Auda, Jules Remy Ndam Ngoupayou, Dieudonne Bisso, Derviche Nguemou Tchado, and Roland Apouamoun Yiagnigni
A.90 |
EGU2019-7443<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Stefano Ghergo, Daniele Parrone, Eleonora Frollini, and Elisabetta Preziosi
A.91 |
EGU2019-8694<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"><span title="Early career scientist: an ECS is an undergraduate or postgraduate (Masters/PhD) student or a scientist who has received his or her highest degree (BSc, MSc, or PhD) within the past seven years. Provided parental leave fell into that period, up to one year of parental leave time may be added per child, where appropriate.">ECS</span></span>
Wenxun Dong and Yanjun Zhang
A.92 |
EGU2019-10367<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Eleonora Frollini, Stefano Ghergo, Elisabetta Preziosi, Emanuele Romano, and Marco Marcaccio
A.93 |
EGU2019-17862<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Volodimir Osadchyi, Nataliia Osadcha, Juriy Nabyvanets, Nina Mostova, Olga Ukhan, Yulia Luzovitska, and Denis Klebanov
A.94 |
EGU2019-7009<span style="font-size: .8em!important; font-weight: bold; vertical-align: super; color: green!important;"></span>
Ting-Syuan Yu and Loung-Yie Tsai