The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
A Nonparametric Multivariate Multi-Index Drought Monitoring Framework
Open accessAbstract
Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, drought monitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDM and provides additional information and insights into drought monitoring.
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
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
Nelsen, R. B. (1999) · Lecture Notes in Statistics · doi:10.1007/978-1-4757-3076-0 · Cited by 7,744
Statistical Methods in the Atmospheric Sciences
Ramsey, P. H. (1996) · Technometrics · doi:10.1080/00401706.1996.10484553 · Cited by 7,601
MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G.-K., et al. (2011) · Journal of Climate · doi:10.1175/jcli-d-11-00015.1 · Cited by 4,852
Dai, A., Trenberth, K. E., & Qian, T. (2004) · Journal of Hydrometeorology · doi:10.1175/jhm-386.1 · Cited by 2,041
A Review of Twentieth-Century Drought Indices Used in the United States
Heim, R. R. (2002) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477-83.8.1149 · Cited by 2,021
Use of a standardized runoff index for characterizing hydrologic drought
Shukla, S., & Wood, A. W. (2008) · Geophysical Research Letters · doi:10.1029/2007gl032487 · Cited by 1,400
Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., et al. (2002) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477-83.8.1181 · Cited by 1,256
Characteristics and trends in various forms of the Palmer Drought Severity Index during 1900–2008
Dai, A. (2011) · Journal of Geophysical Research · doi:10.1029/2010jd015541 · Cited by 1,066
Ebert, E. E., Janowiak, J. E., & Kidd, C. (2007) · Bulletin of the American Meteorological Society · doi:10.1175/bams-88-1-47 · Cited by 1,029
Cited by
Remote sensing of drought: Progress, challenges and opportunities
AghaKouchak, A., Farahmand, A., Melton, F. S., Teixeira, J., Anderson, M. C., Wardlow, B. D., & Hain, C. R. (2015) · Reviews of Geophysics · doi:10.1002/2014rg000456 · Cited by 989
Self-citationA generalized framework for deriving nonparametric standardized drought indicators
Farahmand, A., & AghaKouchak, A. (2015) · Advances in Water Resources · doi:10.1016/j.advwatres.2014.11.012 · Cited by 512
Self-citationIran’s Socio-economic Drought: Challenges of a Water-Bankrupt Nation
Madani, K., AghaKouchak, A., & Mirchi, A. (2016) · Iranian Studies · doi:10.1080/00210862.2016.1259286 · Cited by 396
Self-citationGRACE Groundwater Drought Index: Evaluation of California Central Valley groundwater drought
Thomas, B. F., Famiglietti, J. S., Landerer, F. W., Wiese, D. N., Molotch, N. P., & Argus, D. F. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.06.026 · Cited by 346
Drought indicators revisited: the need for a wider consideration of environment and society
Bachmair, S., Stahl, K., Collins, K., Hannaford, J., Acreman, M., Svoboda, M., Knutson, C., Smith, K. H., Wall, N., Fuchs, B., et al. (2016) · WIREs Water · doi:10.1002/wat2.1154 · Cited by 316
Metadata
- Authors
- Hao, Z., & AghaKouchak, A.
- Venue
- Journal of Hydrometeorology
- Publisher
- American Meteorological Society
- Published
- 2014-02-01
- Volume
- 15
- Issue
- 1
- Pages
- 89-101
- ISSN
- 1525-7541 (ISSN-L)
- 1525-755X
- OpenAlex
- W1975693754
- Cited by
- 440
- References
- 25
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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: A Nonparametric Multivariate Multi-Index Drought Monitoring Framework. https://app.cochat.ai/papers/10.1175/jhm-d-12-0160.1
- The paper
- Hao, Z., & AghaKouchak, A. (2014). A Nonparametric Multivariate Multi-Index Drought Monitoring Framework. Journal of Hydrometeorology. https://doi.org/10.1175/jhm-d-12-0160.1
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.