Abstract. From the Hindu Kush mountains to the Registan Desert, Afghanistan is a
diverse landscape where droughts, floods, conflict, and economic market
accessibility pose challenges for agricultural livelihoods and food
security. The ability to remotely monitor environmental conditions is
critical to support decision making for humanitarian assistance. The Famine
Early Warning Systems Network (FEWS NET) Land Data Assimilation System
(FLDAS) global and Central Asia data streams provide information on
hydrologic states for routine integrated food security analysis. While
developed for a specific project, these data are publicly available and
useful for other applications that require hydrologic estimates of the water
and energy balance. These two data streams are unique because of their
suitability for routine monitoring, as well as for being a historical record for
computing relative indicators of water availability. The global stream is
available at ∼ 1-month latency, and monthly average outputs are on a
10 km grid from 1982–present. The second data stream, Central Asia (21–56∘ N, 30–100∘ E), at ∼ 1 d latency,
provides daily average outputs on a 1 km grid from 2000–present. This paper
describes the configuration of the two FLDAS data streams, background on the
software modeling framework, selected meteorological inputs and parameters,
and results from previous evaluation studies. We also provide additional
analysis of precipitation and snow cover over Afghanistan. We conclude with
an example of how these data are used in integrated food security analysis.
For use in new and innovative studies that will improve understanding of
this region, these data are hosted by U.S. Geological Survey data portals
and the National Aeronautics and Space Administration (NASA). The Central
Asia data described in this paper can be accessed via the NASA
repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this
paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).