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Predicting Playa Inundation Using a Long Short‐Term Memory Neural Network
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2021
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Source: Water Resources Research, 57(12)
[PDF-4.19 MB]
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Journal Title:Water Resources Research
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Description: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 the probability of playa inundation for 71,842 playas in the Great Plains from 1984 to 2018. At the level of individual playas, the model achieved an F1-score of 0.522 on a withheld test set, displaying the ability to predict complex inundation patterns. When simulating playa inundation
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Source:Water Resources Research, 57(12)
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DOI:
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ISSN:0043-1397;1944-7973;
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Rights Information:Other
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Compliance:Library
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