The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Evaporative Demand Drought Index. Part I: Linking Drought Evolution to Variations in Evaporative Demand
Open accessAbstract
Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E0—the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E0 to surface drying anomalies that result from two distinct land surface–atmosphere interactions: 1) a complementary relationship between E0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E0, as in sustained droughts, and 2) parallel ET and E0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E0, a long-term, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in Part II.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Little change in global drought over the past 60 years
Sheffield, J., Wood, E. F., & Roderick, M. L. (2012) · Nature · doi:10.1038/nature11575 · Cited by 1,978
Cited by
Otkin, J. A., Svoboda, M., Hunt, E. D., Ford, T. W., Anderson, M. C., Hain, C., & Basara, J. B. (2018) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-17-0149.1 · Cited by 689
Self-citationHuntington, J. L., Hegewisch, K. C., Daudert, B., Morton, C. G., Abatzoglou, J. T., McEvoy, D. J., & Erickson, T. (2017) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-15-00324.1 · Cited by 363
Self-citationDrought evolution, severity and trends in mainland China over 1961–2013
Yao, N., Li, Y., Lei, T., & Peng, L. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.327 · Cited by 341
Pan-European seasonal trends and recent changes of drought frequency and severity
Spinoni, J., Naumann, G., & Vogt, J. V. (2017) · Global and Planetary Change · doi:10.1016/j.gloplacha.2016.11.013 · Cited by 319
Vicente‐Serrano, S. M., McVicar, T. R., Miralles, D. G., Yang, Y., & Tomas‐Burguera, M. (2020) · WIREs Climate Change · doi:10.1002/wcc.632 · Cited by 299
Metadata
- Authors
- Hobbins, M. T., Wood, A., McEvoy, D. J., Huntington, J. L., Morton, C., Anderson, M., & Hain, C.
- Venue
- Journal of Hydrometeorology
- Publisher
- American Meteorological Society
- Published
- 2016-06-01
- Volume
- 17
- Issue
- 6
- Pages
- 1745-1761
- ISSN
- 1525-7541 (ISSN-L)
- 1525-755X
- OpenAlex
- W2338735373
- Cited by
- 366
- References
- 1
- FWCI
- 17.05
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Evaporative Demand Drought Index. Part I: Linking Drought Evolution to Variations in Evaporative Demand. https://app.cochat.ai/papers/10.1175/jhm-d-15-0121.1
- The paper
- Hobbins, M. T., Wood, A., McEvoy, D. J., Huntington, J. L., Morton, C., Anderson, M., & Hain, C. (2016). The Evaporative Demand Drought Index. Part I: Linking Drought Evolution to Variations in Evaporative Demand. Journal of Hydrometeorology. https://doi.org/10.1175/jhm-d-15-0121.1
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.