Applicability of SPI and RDI for forthcoming drought events: a non-parametric trend and one way ANOVA approach
| Autor: | Mahendra Kumar Choudhary, Mrityunjay Singh Chauhan, Ankur Vishwakarma |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Atmospheric Science
Global and Planetary Change 010504 meteorology & atmospheric sciences 0208 environmental biotechnology Statistics Nonparametric statistics Environmental science 02 engineering and technology Management Monitoring Policy and Law 01 natural sciences 020801 environmental engineering 0105 earth and related environmental sciences Water Science and Technology |
| Zdroj: | Journal of Water and Climate Change. 11:18-28 |
| ISSN: | 2408-9354 2040-2244 |
| DOI: | 10.2166/wcc.2020.042 |
| Popis: | Monthly, seasonal and annual trends of rainfall and temperature (both minimum and maximum) have been analyzed using the Mann–Kendall trend test (a non-parametric test) and Sen's slope estimator for Sagar division, India from 1988 to 2018. Sagar division is a drought-prone zone of Madhya Pradesh, India. The same analysis has been performed for two drought indices, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Both indices were calculated to see the trend in the drought for 35 rain-gauge stations belonging to the study area. The study revealed that the minimum temperature had increased more than the maximum temperature in the last 31 years. The strong similarity in the results of Sen's slope of SPI and RDI were seen for both significant and non-significant trends. Analysis of variance (ANOVA) testing validates the substantial similarity between SPI and RDI based on Sen's slope. It also indicated the suitability of RDI for future projection of drought using the general circulation models (GCMs) or regional climate models (RCMs) in meteorological drought as well as the agricultural drought category. In contrast, the SPI indicated the meteorological drought only. The distribution of trends of temperature and drought indices were presented using the kriging interpolation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|