Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Predicting Playa Inundation Using a Long Short-Term Memory Neural
  Network   In the Great Plains, playas are critical wetland habitats for migratory birds
and a source of recharge for the agriculturally-important High Plains aquifer.
The temporary wetlands exhibit complex hydrology, filling rapidly via local
rain storms and then drying through evaporation and groundwater infiltration.
Using a long short-term memory (LSTM) neural network to account for these
complex processes, we modeled playa inundation for 71,842 playas in the Great
Plains from 1984-2018. At the level of individual playas, the model achieved an
F1-score of 0.538 on a withheld test set, displaying the ability to predict
complex inundation patterns. When averaging over all the playas in the entire
region, the model is able to very closely track inundation trends, even during
periods of drought. Our results demonstrate potential for using LSTMs to model
complex hydrological dynamics. Our modeling approach could be used to model
playa inundation into the future under different climate scenarios to better
understand how wetland habitats and groundwater will be impacted by changing
climate.

19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
13
The categories of this paper are: quant-ph