JDI-Precipitation-Viewer

By Rao S Govindaraju1, Shivam Tripathi1

1. Purdue University

Helps visualize the Joint Deficit Index (JDI) of Precipitation

Launch Tool

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Archive Version 1.4z
Published on 13 Jan 2014, unpublished on 13 Jan 2014 All versions

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Abstract

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.

Credits

Shih-Chieh Kao

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

Researchers should cite this work as follows:

  • Rao S Govindaraju; Shivam Tripathi (2009), "JDI-Precipitation-Viewer," https://mygeohub.org/resources/firsttesttool.

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