TY - GEN
T1 - GreenhousePeat
T2 - 10th International Symposium on Land Subsidence, TISOLS 2020
AU - Koster, Kay
AU - Frumau, Arnoud
AU - Stafleu, Jan
AU - Dijkstra, Joris
AU - Hensen, Arjan
AU - Velzeboer, Ilona
AU - Martins, Joana Esteves
AU - Zaadnoordijk, Willem Jan
PY - 2020/4/22
Y1 - 2020/4/22
N2 - Oxidation of organic matter in peat above the phreatic groundwater table causes subsidence and carbon dioxide (CO2) emissions. Because 25% of the Netherlands has shallow peat layers in its subsurface, it is essential for Dutch policy makers and stakeholders to have reliable information on present day and near future CO2 emissions under changes in groundwater levels. Furthermore, it is important to reduce greenhouse gas emissions in view of international agreements. We are developing GreenhousePeat: a nationwide model that synthesizes information on peat organic carbon content, land subsidence, and CO2 emission monitoring to model present-day and future CO2 emissions from subsiding peatlands. Here, we discuss the approach and input data of GreenhousePeat. GreenhousePeat is based on a UNFCCC approved model to predict CO2 emissions, albeit based on new input data: 3-D organic matter maps, nationwide subsidence rates, and ranges in oxidation fraction. We validate model outcomes with previously documented CO2 emissions measured at four different locations. We found that for one site the upper bound of the model reproduces the measured CO2 emissions. The modelled emissions at two sites have a relative deviation of approximately 73% to 29% from the measured emissions. Whereas one site is a net CO2 sink, although low emissions were modelled. Finally, we conclude on the suitability of the model for CO2 emission forecasting and suggest improvements by incorporating groundwater level information and land use type.
AB - Oxidation of organic matter in peat above the phreatic groundwater table causes subsidence and carbon dioxide (CO2) emissions. Because 25% of the Netherlands has shallow peat layers in its subsurface, it is essential for Dutch policy makers and stakeholders to have reliable information on present day and near future CO2 emissions under changes in groundwater levels. Furthermore, it is important to reduce greenhouse gas emissions in view of international agreements. We are developing GreenhousePeat: a nationwide model that synthesizes information on peat organic carbon content, land subsidence, and CO2 emission monitoring to model present-day and future CO2 emissions from subsiding peatlands. Here, we discuss the approach and input data of GreenhousePeat. GreenhousePeat is based on a UNFCCC approved model to predict CO2 emissions, albeit based on new input data: 3-D organic matter maps, nationwide subsidence rates, and ranges in oxidation fraction. We validate model outcomes with previously documented CO2 emissions measured at four different locations. We found that for one site the upper bound of the model reproduces the measured CO2 emissions. The modelled emissions at two sites have a relative deviation of approximately 73% to 29% from the measured emissions. Whereas one site is a net CO2 sink, although low emissions were modelled. Finally, we conclude on the suitability of the model for CO2 emission forecasting and suggest improvements by incorporating groundwater level information and land use type.
UR - https://www.scopus.com/pages/publications/85088232619
UR - https://www.scopus.com/inward/citedby.url?scp=85088232619&partnerID=8YFLogxK
U2 - 10.5194/piahs-382-609-2020
DO - 10.5194/piahs-382-609-2020
M3 - Conference contribution
VL - 382
T3 - Proceedings of the International Association of Hydrological Sciences
SP - 609
EP - 614
BT - 10th International Symposium on Land Subsidence, TISOLS 2020
PB - Copernicus GmbH
Y2 - 17 May 2021 through 21 May 2021
ER -