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\begin{document}

\title{An assessment of ensemble streamflowpredictions in the semi-arid Andes
Cordillera}



\author[1]{Eduardo Muñoz Castro}%
\author[1]{Maria Ignacia Orell}%
\author[1]{Tania Fernandez}%
\author[2]{Pablo A. Mendoza}%
\author[1]{Ximena Vargas}%
\affil[1]{Universidad de Chile}%
\affil[2]{Advanced Mining Technology Center, AMTC}%


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  \date{June 14, 2024}


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\begin{abstract}
In the semi-arid extratropical Andes Cordillera, the seasonal snowpack
acts as a natural water reservoir, releasing spring snowmelt runoff that
accounts for more than 60 \% of the total annual streamflow and sustains
multiple productive uses, population needs, and unique ecosystems.
Official seasonal streamflow forecasts (Sept-Mar runoff volumes) are
currently generated by the General Water Directorate of Chile (DGA),
based solely on regression-based methods that incorporate in-situ
meteorological variables observed during winter as predictors. This work
aims to assess the potential of the ensemble streamflow prediction (ESP)
methodology for improved seasonal forecasts in high mountain basins in
Central Chile, incorporating simple post-processing methods. To this
end, we apply the GR4J rainfall-runoff model, as implemented in the
airGR package, combined with the snow accumulation and ablation model
CemaNeige in a set of case study basins. Preliminary results show that
ESP forecast errors are smaller than those produced by the General Water
Directorate of Chile (DGA). Ongoing efforts are aimed to identify
potential differences and shortcomings in these techniques -- using
different verification measures -- in terms of their capability to
harness climatic and hydrologic sources of predictability.%
\end{abstract}%



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