A Nonparametric Multivariate Multi-Index Drought Monitoring Framework
نویسندگان
چکیده
Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, droughtmonitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDMand provides additional information and insights into drought monitoring.
منابع مشابه
A comparison of parametric and non-parametric methods of standardized precipitation index (SPI) in drought monitoring (Case study: Gorganroud basin)
The Standardized Precipitation Index (SPI) is the most common index for drought monitoring. Although the calculation of this index is usually done by using the gamma distribution fitting of precipitation data, studies have shown that for accurate monitoring of drought, the optimal distribution of precipitation in each month should be determined. On the other hand, in non-stationary time series,...
متن کاملComparing Univariate and Multivariate Indices in Drought Monitoring
In this study, drought characteristics of Arak, Bandar Anzali, Tabriz, Tehran, Rasht, Zahedan, Shiraz and Kerman stations during the statistical period of 1956 to 2015 were studied by Reconnaissance Drought Index (RDI) and Standardized Precipitation Index. Precipitation and temperature data were needed to calculate RDI. Precipitation data was also required to estimate SPI. In this study, Drinc ...
متن کاملAssessment of Multivariate Standardized Drought Index (MSDI) and Meteoro-Agricultural Drought Monitoring in Chaharmahal and Bakhtiari Porvince
Drought, as one of the most complicated natural events, causes many direct and indirect damages each year. Hence, single variable identification and monitoring of drought may not be appropriate enough for decision-making and management. In this study, in order to monitor the meteorological-agricultural drought in Chaharmahal and Bakhtiari province, Multivariate Standardized Drought Index (MSDI)...
متن کاملA generalized framework for deriving nonparametric standardized drought indicators
This paper introduces the Standardized Drought Analysis Toolbox (SDAT) that offers a generalized framework for deriving nonparametric univariate and multivariate standardized indices. Current indicators suffer from deficiencies including temporal inconsistency, and statistical incomparability. Different indicators have varying scales and ranges and their values cannot be compared with each othe...
متن کاملA multivariate approach for persistence-based drought prediction: Application to the 2010–2011 East Africa drought
The 2011 East Africa drought caused dire situations across several countries and led to a widespread and costly famine in the region. Numerous dynamic and statistical drought prediction models have been used for providing drought information and/or early warning. The concept of Ensemble Streamflow Prediction (ESP) has been successfully applied to univariate drought indicators (e.g., the Standar...
متن کامل