Forecasting annual maximum water level for the Negro River at Manaus
2021
More frequent and stronger flood hazards in the last two decades
have caused considerable environmental and socio-economic losses
in many regions of the Amazon basin. It is therefore critical to
advance predictions for flood levels, with adequate lead times, to
provide more effective and earlier warnings to safeguard lives and
livelihoods. Water-level variations in large, low-lying, free-flowing
river systems in the Amazon basin, like the Negro River, follow
large-scale precipitation anomalies. This offers an opportunity to
predict maximum water levels using observed antecedent rainfall.
This study aims to investigate possible improvements in the performance and extension of the lead time of existing operational statistical forecasts for annual maximum water level of the Negro River at
Manaus, occurring between May–July. We develop forecast models
using multiple linear regression methods, to produce forecasts that
can be issued in March, February and January. Potential predictors
include antecedent catchment rainfall and water levels, large-scale
modes of climate variability and the long-term linear trend in water
levels. Our statistical models gain one month of lead time against existing models for same skill level, but are only moderately better than
existing models at similar lead times. All models lose performance
at longer lead times, as expected. However, our forecast models can
issue skilful operational forecasts in March or earlier. We show the
forecasts for the Negro River maximum water level at Manaus for
2020 and 2021.
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