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JDI-Precipitation-Viewer
Posted 14 May, 2009 in Tools
Available Versions
- 1.4 (Published)
- 1.3 (Unpublished)
- 1.2 (Unpublished)
- 1.1 (Unpublished)
- 1.0 (Unpublished)
- More...
Supporting Documents
- EWRI-Kansas_conference_paper.pdf (PDF, 237.19 Kb)
- kao-gov-hydrol.pdf (PDF, 1.62 Mb)
This tool is closed source.
| Version | 1.4 - published on 01 Jul. 2009 |
|---|---|
| Contributor(s) | Tanzima Zerin Islam, Rao S Govindaraju, Shivam Tripathi Purdue University |
| At a glance | Helps visualize the Joint Deficit Index (JDI) of Precipitation |
| Screenshots | |
| Description | Droughts are prolonged abnormalities of moisture deficits that vary widely across temporal and spatial scales. Many hydrometeorologic variables are used to monitor the status of a drought. However, because of the dependence structure between all affecting variables under various temporal windows, an integrated spatio-temporal analysis of droughts cannot be easily achieved. A copula-based drought analysis was performed by Kao et al. using long-term monthly precipitation dataset for the upper Midwest United States. The spatio-temporal dependence relationships between various drought variables were investigated, and their joint probability distribution was constructed by combining drought marginals and the dependence structure. A copula-based joint deficit index (JDI) was adopted for an objective (probability-based) description of the overall drought status and compared to the Palmer drought severity index results. Results from the copula-based JDI provide information for drought identification, and further allow a month-by-month assessment for future drought recovery. |
| references | Kao, S.-C., R.S. Govindaraju, and D. Niyogi (2009). "A spatio-temporal drought analysis for the Midwestern US." In World Environmental and Water Resources Congress 2009: Great Rivers, Kansas, May 17-21, pg. 4654-4663. |
| Cite this work | If you reference this work in a publication, please cite as follows: |
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