Presentation by Guus Kruitwagen (Witteveen+Bos) at the Seminar Models and decision-making in the wake of climate uncertainties, during the Deltares Software Days South-East Asia 2023. Wednesday, 22 February 2023, Singapore.

1. BlueCAN: GHG-emissions
from surface waters
Guus Kruitwagen, Witteveen + Bos

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3. Background
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˗ Global urgency to reduce greenhouse gas (GHG) emissions
˗ IPCC obliges nations to report all GHG emissions
˗ Relevance of marsh wetlands for regulation of carbon emissions is well known
˗ Restoration of marshes important mechanism to enhance carbon sequestration -> NBS
˗ No data on contribution of freshwater systems available in IPCC database
˗ Knowledge on GHG emissions from freshwater needed to be able to identify effective GHG
control measures

4. BlueCAN - Hypothesis
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1. Surface waters are a significant source of GHG-emissions
2. Magnitude of emissions is influenced by water quality
3. Water quality management can contribute to GHG sequestration

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Saunois et al. 2016 Global methane
emissions by source type (TgCH4 yr−1)
in review paper: Saunois et al. 2020
The Global Methane Budget 2000-2017

7. Water quality and GHG-emissions
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8. Research questions
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1. What is the magnitude of GHG emissions from
Dutch surface waters?
2. Which processes contribute to GHG-emissions from
surface waters?
3. How can GHG-emissions from the Dutch surface
waters be reduced?

9. Research approach
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- Development of predictive model
- Catchment area approach
- Life cycle analysis
- Different types of waterbodies
- Supporting measurements in field and lab

10. Closer look into the modelling
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- Why a GHG-model?
· Quantitive estimation of GHG emissions from waterbodies
· Insight in dominant processes
· Insight in causal relations
· Imply case-specific parameters

11. BlueCAN-model
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Integration of elements from 2 ecological models:
PCLake/PCDitch: Foodweb processes (algae and plants)
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Delft3D-ECO: Carbon balance from water and sediment
Integrated model to combine processes and make reliable GHG flux estimates

12. Delft3D-Delwaq (Delft3D-ECO) PCLake/PCDitch
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BlueCAN-model

13. BlueCAN-model
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- (meta) Model in webapplication
- Input parameters based on system characteristics:
· Water depth
· Sediment type
· Fetch, flow rate, and surface area
· Nutrient loading
- Input from water and nutrient balances
- Calibration with field measurements

14. Calibration
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- Field measurements from
a eutrophic pond in
temperate climate
- Year round data
- Patterns comparable
Field measurements
Model results
(van Bergen et al., 2019)

15. Calibration
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- The GHG emissions show a seasonal dynamic
- CO2 emissions occur year round
- Diffusion and ebullition of CH4 to the air occur primarily in summer
- Half of CH4 is oxidized to CO2 before it reaches the surface

16. Prediction of emissions in relation to P loading
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- Use of BlueCAN model for wide variety of representative characteristics
of Dutch waterbodies
- Range of eutrophication (P-load)
- Thousands of runs with different settings and varying P-loads

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Emissions year round
CO2 diffusion CH4 diffusion CH4 ebullition

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Oligotrophic Mesotrophic Eutrophic Hypertrophic

19. BlueCAN output to date
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- BlueCAN model enables prediction of GHG emissions from temperate surface waters
- Indication of the GHG fluxes from surface waters based on few input parameters
- Positive correlation between GHG emissions and eutrophication
- Important building blocks for IPCC database
- Perspective to control emissions through water quality management
- Support for application of NBS measures in wetlands

20. Outlook
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- Ambition for further research to understand driving processes
- Validation with more case studies
- Extension of BlueCAN to other climate zones, including tropical waters
- Relevancy to water, river and reservoir managers

21. Questions?
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For futher information:
Witteveen+Bos - guus.kruitwagen@witteveenbos.com
Deltares - martine.kox@deltares.nl