What is it about?
This research is related to the accumulation of multiple time series variables. An example is taken from the field of hydrology.
Featured Image
Photo by Stephen Dawson on Unsplash
Why is it important?
Continuous and accurate drought monitoring is useful for making drought mitigation policies. From an operational point of view, drought characterization allows early warning drought risk analysis. The primary issue in making advance drought management and mitigation policies is the selection of appropriate drought index for accurate and precise drought monitoring and forecasting. However, the uncertainty in the estimation of drought classes always exists in probabilistic models of SPI, SPEI and SPTI. n this paper, we aimed to develop a new criterion – the PWJADI to overcome the uncertainty in the accurate determination of drought classes. The PWJADI has capability to give joint decision on the classification of the region under study based on various drought indices. The developed model is on the drought classification of SPI, SPEI and SPTI at one month time scale.
Perspectives
In this study, we introduced a new joint aggregative criterion for assessing accurate drought classes by using SPI, SPEI and SPTI drought indices. We found that aggregate decisions based on three drought indices (SPI, SPEI and SPTI) can be useful for accurate and precise drought monitoring. We concluded from the analysis of three meteorological stations as follows: 1- The choice of appropriate probability distribution for each drought indicator increase its efficiency for exact drought category. 2- There are positive correlations among each quantitative value of SPI, SPEI and SPTI, but it does not guarantee that in a particular month each drought indicator produces same drought class. 3- The transient memories as a weight help to reduce the error rate of inaccurate drought class. 4- Utilization of more than one drought index for drought monitoring, the proposed model can be considered for making reliable drought mitigation policies. Further, the inferences and numerical computations can be generalized for other time scales and other drought indices such as RDI.
Zulfiqar Ali
Quaid-i-Azam University
Read the Original
This page is a summary of: A Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for drought monitoring systems, Tellus A Dynamic Meteorology and Oceanography, March 2019, Taylor & Francis,
DOI: 10.1080/16000870.2019.1588584.
You can read the full text:
Contributors
The following have contributed to this page
