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\begin{document}

\title{Modelling large-scale seasonal variations in water table depth over
tropical peatlands in Riau, Sumatra}



\author[1]{Symon Mezbahuddin}%
\author[2]{Tadas Nikonovas}%
\author[3]{Allan Spessa}%
\author[1]{Robert Grant}%
\author[3]{Muhammad Imron}%
\affil[1]{University of Alberta}%
\affil[2]{Project Officer, Towards a Fire Early Warning System for Indonesia (ToFEWSI) project}%
\affil[3]{Principal Investigator, ToFEWSI project}%


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  \date{June 17, 2024}


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\begin{abstract}
Water table depth (WTD) is the predominant biophysical control over the
occurrence of peat and forest fires in tropical peatlands. In Indonesia,
prolonged droughts caused by El-Ni\selectlanguage{ngerman}ño and/or positive Indian Ocean Dipole
(IOD), exacerbated by extensive peat drainage for agriculture and
plantation establishment, can promote severe peatland fires by lowering
WTD and hence desiccating surface and sub-surface peats. The severe
drought episode of late 2015 across Indonesia, caused by a strong El
Nino and a positive IOD, led to a major and damaging increase in
peatland fires, highlighting an urgent need to develop operational
systems to forecast potentially severe fire events to mitigate the
impacts of fire and haze. The 2002 ASEAN Agreement on Transboundary Haze
Pollution, signed and ratified by a total of 10 ASEAN states, including
Indonesia, identifies a critical need for such systems based on
near-time climate projections. However, such systems have not yet been
developed. While an operational early warning system for forecasting
dangerous burning conditions in Indonesia is currently within reach
using state-of-the-art modelling tools, such as the ECMWF's System 5
seasonal forecast model (SEAS5), development is still hampered by
insufficient knowledge about the influence of fluctuations in peat
moisture on fire, particularly during periods of extreme drought. The
main objectives of this study were: i) to deploy a process-based
ecosystem model ``ecosys'' to study how WTD and peat moisture profiles
change in tropical peatlands across Riau province, Sumatra, in response
to drought and land cover change, focusing on the 2015 drought; and ii)
to examine whether those changes could have been predicted using SEAS5.
Model spin-up from 2008-2014 was driven by inputs from ECMWF's climate
reanalysis data (ERA5), followed by 3 parallel simulations for 2015,
driven by ERA5, ERA5 climatology, and SEAS5 hindcasts. Model outputs of
peat moisture profiles and WTD showed how peat moisture and WTD were
significantly affected by weather and land uses during the dry season of
2015 which were corroborated well against data from Soil Moisture Active
Passive satellite and site-level monitoring networks. Our work is a
pioneering attempt to perform large-scale process-based modelling to
predict seasonal variations in tropical peatland WTD.%
\end{abstract}\selectlanguage{ngerman}%



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