The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Multivariate Standardized Drought Index: A parametric multi-index model
Open accessAbstract
Defining droughts based on a single variable/index (e.g., precipitation, soil moisture, or runoff) may not be sufficient for reliable risk assessment and decision-making. In this paper, a multivariate, multi-index drought-modeling approach is proposed using the concept of copulas. The proposed model, named Multivariate Standardized Drought Index (MSDI), probabilistically combines the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI) for drought characterization. In other words, MSDI incorporates the meteorological and agricultural drought conditions for overall characterization of drought. In this study, the proposed MSDI is utilized to characterize the drought conditions over several Climate Divisions in California and North Carolina. The MSDI-based drought analyses are then compared with SPI and SSI. The results reveal that MSDI indicates the drought onset and termination based on the combination of SPI and SSI, with onset being dominated by SPI and drought persistence being more similar to SSI behavior. Overall, the proposed MSDI is shown to be a reasonable model for combining multiple indices probabilistically.
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
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) · Journal of Climate · doi:10.1175/2009jcli2909.1 · Cited by 9,493
Nelsen, R. B. (1999) · Lecture Notes in Statistics · doi:10.1007/978-1-4757-3076-0 · Cited by 7,744
(1993) · Cited by 7,699
Mishra, A. K., & Singh, V. P. (2010) · Journal of Hydrology · doi:10.1016/j.jhydrol.2010.07.012 · Cited by 5,436
Fonctions de répartition à N dimensions et leurs marges
Sklar, M. (1959) · HAL · Cited by 4,671
Multivariate Models and Dependence Concepts.
Ringrose, T., & Joe, H. (1998) · Biometrics · doi:10.2307/2533875 · Cited by 3,403
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
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 1×
“For example, the Palmer drought severity index (PDSI, [29]), derived from precipitation and temperature, has been widely used for drought characterization [8,7,35].”
MethodEverything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask
Genest, C., & Favre, A.-C. (2007) · Journal of Hydrologic Engineering · doi:10.1061/(asce)1084-0699(2007)12:4(347 · Cited by 1,618
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-citationSubstantial increase in concurrent droughts and heatwaves in the United States
Mazdiyasni, O., & AghaKouchak, A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422945112 · Cited by 720
Self-citationSpatio-temporal variation of drought in China during 1961–2012: A climatic perspective
Xu, K., Yang, D., Yang, H., Li, Z., Qin, Y., & Shen, Y. (2015) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.09.047 · Cited by 599
A 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-citationZhang, X., Hao, Z., Singh, V. P., Zhang, Y., Feng, S., Xu, Y., & Hao, F. (2022) · Science of The Total Environment · doi:10.1016/j.scitotenv.2022.156021 · Cited by 429
Self-citation
Metadata
- Authors
- Hao, Z., & AghaKouchak, A.
- Venue
- Advances in Water Resources
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 57
- Pages
- 12-18
- ISSN
- 0309-1708 (ISSN-L)
- OpenAlex
- W2115521437
- Cited by
- 960
- References
- 35
- FWCI
- 25.69
- 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: Multivariate Standardized Drought Index: A parametric multi-index model. https://app.cochat.ai/papers/10.1016/j.advwatres.2013.03.009
- The paper
- Hao, Z., & AghaKouchak, A. (2013). Multivariate Standardized Drought Index: A parametric multi-index model. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2013.03.009
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.
