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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Data and code for "Terrestrial water cycle acceleration-deceleration: Non-binary and space-time divergent"

Authors: Daniel Althoff; Georgia Destouni;

Data and code for "Terrestrial water cycle acceleration-deceleration: Non-binary and space-time divergent"

Abstract

This dataset provides all data compiled and generated for the manuscript entitled "Terrestrial water cycle acceleration-deceleration: Non-binary and space-time divergent" (manuscript under consideration). This includes the boundaries for 3614 hydrological catchments, the curated data used for analysis and modelling, the developed machine learning model, shapley values and area of applicability results, and data for global extrapolation It also contains the code in a Quarto file ('Code.qmd') and a markdown file ('Code.html') which shows how to access and use the data, and generic sample codes used to generate these results. Code - R session info: R version 4.2.1 (2022-06-23 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 22621) Matrix products: default locale: [1] LC_COLLATE=Portuguese_Brazil.utf8 LC_CTYPE=Portuguese_Brazil.utf8 [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C [5] LC_TIME=Portuguese_Brazil.utf8 attached base packages: [1] stats [2] graphics [3] grDevices [4] utils [5] datasets [6] methods [7] base other attached packages: [1] bundle_0.0.0.9200 [2] stacks_1.0.0 [3] bonsai_0.1.0 [4] rules_1.0.0 [5] finetune_0.2.0 [6] yardstick_1.0.0 [7] workflowsets_1.0.0 [8] workflows_1.0.0 [9] tune_1.0.0 [10] tibble_3.1.7 [11] rsample_1.0.0 [12] recipes_1.0.1 [13] purrr_0.3.4 [14] parsnip_1.0.0 [15] modeldata_1.0.0 [16] infer_1.0.2 [17] dials_1.0.0 [18] scales_1.2.0 [19] broom_1.0.0 [20] tidymodels_1.0.0 [21] ggplot2_3.3.6 [22] rnaturalearth_0.1.0 [23] sf_1.0-8 [24] terra_1.6-3 [25] lubridate_1.8.0 [26] stringr_1.4.0 [27] tidyr_1.2.0 [28] dplyr_1.0.9 [29] pacman_0.5.1

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Keywords

machine learning, evapotranspiration, runoff, precipitation, shapley values, area of applicability, global water flux partitioning, dissimilarity index

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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