Challenges in modelling benthic nutrient fluxes- the importance of observations

Elin Almroth Rosell, SMHIHELCOM-EUSBSR workshop, 28-29 November 2017

RCO-SCOBIRossby Centre Ocean modelSwedish Coastal and Ocean BIogeochemical model

3D- model

model domain: the Baltic Sea

High horizontal resolution (2 nm)and 83 vertical levels

Model setup

Sweden

Norway Finland

A new approach to model oxygen dependent benthic phosphate fluxes in the Baltic SeaElin Almroth-Rosell, Kari Eilola, Ivan Kuznetsov, Per O.J. Hall and H.E. Markus Meier. Journal of marine systems 144 (2015) 127-141

Phosphate and oxygen in bottom water

Central Baltic Sea: SHARK data. Observations (150-190 m)

PO4 µmol/L

Oxygen and H2S as ”negative oxygen” (ml/L)

The data are collected from; 1) Viktorsson et al., 2012 .; 2) Laima et al., 2001; 3) Koop et al., 1990; 4) Conley et al., 1997; 5) Pitkänen et al., 2001; 6) Hille et al., 2005; 7) Graca et al., 2006 ; 8) Lehtoranta and Heiskanen, 2003. The different study sites are: 1, 4, 5, 8: Gulf of Finland 2: North east Germany 3: Northern Baltic Proper 6: Baltic Proper 7: The Gulf of Gdansk

K. Eilola et al. / Journal of Marine Systems 75 (2009) 163–184

Background

Adsorption mechanism:

Phosphateadsorb on Fe(III)oxides.

PBT BIP

WIP OrgP water PO4 water

SIN

KIO

P

PBTOUTBIP

BURIALPBT BURIALBIP

SED

PLO

SS

SED

IPLO

SS

Mineralization

PBTO

UT P

O4

SCAV

PO4

LIBP

PO4

SIN

KIIP

SCOBI news - Phosphorus dynamics

Cai and Sayles, 1996

[O2]BW OPD

Oxygen penetration depth

Model results: Oxygen penetration depth (validation?)

Validation of Benthic Phosphorus and Nitrogen in the Swedish Coastal zone

Model (SCM) and a Model Implementation of

MicrophytobenthosIvo Hoefsloot

MSc guided research Utrecht University – SMHISupervisors: Elin Almroth-Rosell1, Moa Edman1, Caroline Slomp2

1 Swedish Meteorological and Hydrological Institute, Göteborg, Sweden

2 Utrecht University, Utrecht, The Netherlands

Swedish Coastal zoneModel (SCM)

9

99

Collected dataSource Type Area P samples N samples Period Comments(Malmaeus and Karlsson, 2012)

Publication Stockholm Archipelago

26 0 2008-2010

(Rydin et al., 2011)

Publication Stockholm Archipelago

4 0 2008

(Puttonen et al., 2014)

Publication Stockholm Archipelago

253 0 2008-2012

(Ekeroth et al., 2016)

Publication Stockholm Archipelago

4 4 2010-2013

Caroline Slomp

Personal comm.

Stockholm Archipelago

3 3 2015

Magnus Karlsson

Personal comm.

Stockholm Archipelago

65 0 2008-2009

SGU Database Stockholm Archipelago

71 0 1996-2010

Unknown water depth in all samples

Stockholm Vatten

Report Stockholm Archipelago

25 24 2007

SMHI-Sharkweb

Database Sundsvall Bay/ Ångermans-älven

296 296 2003-2011

Unknown water depth in 104 samples

Data collection from literature, databases (SGU, SHARKWEB)

Criteria: water content, coordinates, depth in sediment

Low amount of available data

Not enough N data in the Stockholm area

10

1010

N- validation Stockholm Archipelago

11

1111

P - validation Stockholm Archipelago P (mmol m-2)

Wat

erde

pth

(m)

Time-series of modelled phosphorus and observational data

P (mmol m-2)

Wat

erde

pth

(m)

13

1313

Nitrogen validation Sundsvall N (mmol m-2)

Wat

erde

pth

(m)

Conclusion Validation data for modelling and model developement are of

great importance, both in time and space

Don’t compare apples and pears! To be able to compare observations and model data the data need to have the same unit, which might only be possible if alsoother parameters are measured such as water content or porosity.

How to know what to measure? Communication

Thank you for your attention!

Mineral-bound phosphorus dynamics

Central Baltic Sea: SHARK data. Observations (150-190 m)

PO4 µmol/L

Oxygen and H2S as ”negative oxygen” (ml/L)

Forward

Jilbert et al. (2011), Fig. 4b

Arkona Basin station BY2. Solid line: September 2009Dashed line: June 2007

Seasonal variability Oxygen

Porewater profiles: Fe2+ and HPO42- Solid phase profiles: Fe-P.

Faeces Excretion

NH4

PO4

NBT

ND

PD

A1 A2 A3

O2

H2S

N2

Ni

Nitrogen fixation

Assimilation

Phytoplankton sinking Detritus sinking

Grazing Grazing

Mortality

Decomp

Decomp

Predation

Sedimentation

Resuspension

To lower layer To lower layer

Burial

Decomp

Decomp

Nitrification

Denitri- fication

ZOO

Inorganic P Resuspension

BIP

PBT IPW

Nitrification NO3

Denitrification

SCOBI news – Swedish Coastal and BIogeochemical model

RCO-SCOBIRossby Centre Ocean modelSwedish Coastal and Ocean BIogeochemical model The model domain covers the

Baltic Sea

• horizontal resolution of 3.7 km (2 nautical miles)

• 83 vertical levels • layer thicknesses of 3 m• maximum depth amounts to 249

m.

Model setup

Sweden

Norway Finland

In this study the main focus has been on the Baltic proper, during the period 1980 to 2008.

A new approach to model oxygen dependent benthic phosphate fluxes in the Baltic SeaElin Almroth-Rosell, Kari Eilola, Ivan Kuznetsov, Per O.J. Halland H.E. Markus Meier. Journal of marine systems 144 (2015) 127-141

Model system and study site

Evaluation, model results

Basin nameNoSocc

NoSYears

A Sandöfjärden 209 23B Kanholmsfjärden 206 23C Solöfjärden 213 23D Trälhavet 215 23E S. Vaxholmsfjärden 131 23F Stora Värtan 141 23G Strömmen 249 23H Baggensfjärden 173 20

Model results, validation

Biogeochemical reactor

1. External nutrient input.

2. Internal nutrient cycling and biogeochemical processing.

3. Internal nutrient removal.

4. Nutrient export.

Energy

Nutrient exportNutrient and oxygen supply

Life in the sea

Modeling theBiogeochemical reactor

1. Assume: e.g. initial conditions.

• Assume there is potential for life (live organic matter)

2. Idealize: e.g. model the most important known processes.

• How do we decide which processes we should include?

Energy

Nutrient exportNutrient and oxygen supply

Life in the sea

Resuspension

Ice

1

2

3

4

5

Redrawn from original figure produced 2012by K. Eilola for BACC II book

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