10.5061/DRYAD.G4F4QRFQQ
Suarez Castro, Andrés F.
0000-0002-6621-3821
University of Queensland
Beyer, Hawthorne L.
University of Queensland
Kuempel, Caitlin D.
University of Queensland
Linke, Simon
Griffith University
Borrelli, Pasquale
University of Pavia
Hoegh-Guldberg, Ove
University of Queensland
Global sediment export based on InVEST Sediment Delivery Ratio model
Dryad
dataset
2021
FOS: Natural sciences
Australian Research Council
https://ror.org/05mmh0f86
CE140100020
Australian Research Council
https://ror.org/05mmh0f86
DP210102575
2021-07-31T00:00:00Z
2021-07-31T00:00:00Z
en
https://doi.org/10.1111/gcb.15811
13576911550 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Sediment runoff from disturbed coastal catchments is a major threat to
marine ecosystems. Understanding where sediments are produced and where
they are delivered enables managers to design more effective strategies
for improving water quality. In this context, targeted restoration of
degraded terrestrial areas provides opportunities to reduce land-based
runoff from coastal areas and consequently foster coral reef conservation.
To do this strategically, a systematic approach is needed to identify
watersheds where restoration actions will provide the highest conservation
benefits for coral reefs. This dataset is associated with the article
"Global forest restoration opportunities to foster coral reef
conservation", where we developed a systematic approach for
identifying global forest restoration opportunities that would also result
in large decreases in the flux of sediments to coral reefs. The dataset
presented here consists of a global sediment export layer produced using
the Sediment Delivery Ratio model of InVEST.
The sediment export per pixel is calculated using the soil erosion per
pixel, as well the amount of sediment eroded from each pixel that actually
reaches a stream or similar water course (Hamel et al. 2015). To model
soil erosion, we used a high-resolution global potential soil erosion
model developed by Borrelli et al. (2017) based on the revised universal
soil loss equation (RUSLE; Renard et al. 1997), estimating soil erosion in
each watershed. Sediment export was quantified using the InVEST sediment
delivery model (Hamel et al. 2015), which implements a soil loss algorithm
linked to the sediment connectivity algorithm proposed by Borselli et al.
(2008). More details about the methodological approach can be found in
Suárez-Castro et al. (2021). Following Borrelli et al, we have capped the
sediment export values to a maximum of 325 tonnes per hectare per year
for pixels classified as barren, 250 tonnes per hectare per year for
pixels classified as agricultural land and 50 tonnes per hectare per year
for pixels classified as forest.
Although substantial variations in model performance exist across regions,
there is a high correlation between observations and predictions for 58
out of 65 basins used for the model calibration (We only calibrated our
model for coastal basins having an effect on coral reefs). In addition,
our model showed good agreement with the spatial patterns of the soil
erosion model presented by Borrelli et al. (2017) (Spearman correlation
coefficient of 0.91, Suarez-Castro et al. 2021) for all the studied
regions. Even though the number of basins available for model validation
was low, the good fit with Borrelli’s erosion model provides confidence
that our model was able to correctly identify high and low sediment export
areas at global scales. Our aim was to generate estimates that allow us to
optimally capture relative differences and opportunities among watersheds,
rather than describing fine-scale within watersheds processes. This
modelling approach is thus suitable for our study as it allowed us
to capture major differences between sub-watersheds that can help to
identify hotspots of higher sediment export where priority actions should
focus. However, pixel level estimates should be taken with caution,
and calibration with localised data would be ideal if this dataset is used
in local scale studies.