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\begin{document}

\title{A probabilistic approach to characterizing drought using satellite
gravimetry}



\author[1]{Peyman Saemian}%
\author[1]{Mohammad Javad Tourian}%
\author[1]{Omid Elmi}%
\author[1]{Nico Sneeuw}%
\author[2]{Amir AghaKouchak}%
\affil[1]{University of Stuttgart}%
\affil[2]{University of California, Irvine}%


\vspace{-1em}



  
  \date{May 24, 2024}


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\begin{abstract}
In the recent past, the Gravity Recovery and Climate Experiment (GRACE)
satellite mission and its successor GRACE Follow-On (GRACE-FO), have
become invaluable tools for characterizing drought through measurements
of Total Water Storage Anomaly (TWSA). However, the existing approaches
have often overlooked the uncertainties in TWSA that stem from GRACE
orbit configuration, background models, and intrinsic data errors. Here
we introduce a fresh view on this problem which incorporates the
uncertainties in the data: the Probabilistic Storage-based Drought Index
(PSDI). Our method leverages Monte Carlo simulations to yield realistic
realizations for the stochastic process of the TWSA time series. These
realizations depict a range of plausible drought scenarios that later on
are used to characterize drought. This approach provides probability for
each drought category instead of selecting a single final category at
each epoch. We have compared PSDI with the deterministic approach (SDI)
over major global basins. Our results show that the deterministic
approach often leans towards an overestimation of storage-based drought
severity. Furthermore, we scrutinize the performance of PSDI across
diverse hydrologic events, spanning continents from the United States to
Europe, the Middle East, Southern Africa, South America, and Australia.
In each case, PSDI emerges as a reliable indicator for characterizing
drought conditions, providing a more comprehensive perspective than
traditional deterministic indices. In contrast to the common
deterministic view, our probabilistic approach provides a more realistic
characterization of the TWS drought, making it more suited for adaptive
strategies and realistic risk management.%
\end{abstract}%



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