Multivariate Standardized Drought Index (MSDI)
Index name: Multivariate Standardized Drought Index (MSDI).
Ease of use: Green.
Origins: Developed by Hao and AghaKouchak at the University of California at Irvine, United States.
Characteristics: Uses information on both precipitation and soil moisture to identify and classify drought episodes by investigating precipitation and soil moisture deficits. It is helpful for identifying drought episodes where typical precipitation-based indicators or soil-moisture-based indicators may not indicate the presence of drought.
Input parameters: Monthly precipitation and soil moisture data are needed from the Modern Era Retrospective Analysis (MERRA)-Land systems. MERRA-Land data are generated by a 0.66° × 0.50° grid from 1980 onwards.
Applications: Useful for the identification and monitoring of drought in cases where precipitation and soil moisture are important contributors to impacts.
Strengths: The gridded and global data represent all areas well. With both a wet and a dry scale, it can be used to monitor more than just drought. It is excellent for areas lacking good surface observations with long periods of record. It is relatively easy to use in that it is computed without the need for input from users. Individual indices can be obtained from MSDI output.
Weaknesses: Grid size may not represent all areas and climate regimes equally. A period of record going back to 1980 is very short when considering climatic applications. To modify, the code and inputs would need to be obtained. Not all timescales are produced for SPI and Standardized Soil Moisture Index outputs.
Resources: The literature well explains the process and online resources and maps are readily available at the University of California – Irvine GIDMaPS webpage.
Hao, Z. and A. AghaKouchak, 2013: Multivariate Standardized Drought Index: a parametric multi-index model. Advances in Water Resources, 57: 12–18. DOI: 10.1016/j.advwatres.2013.03.009. (For more information on this paper, please contact the IDMP HelpDesk).
Hao, Z. and A. AghaKouchak, 2014: A Nonparametric Multivariate Multi-Index Drought Monitoring Framework. Journal of Hydrometerology, 15: 89-101. DOI: 10.1175/JHM-D-12-0160.1.