Characterization Of Drought Events Research Articles

Spatiotemporal Variation of Drought Characteristics Based on Standardized Precipitation Index in Central Java over 1990-2010

Drought is a natural hazard that results from a deficiency of precipitation, leading to low soil moisture and river flows, reduced storage in reservoirs, and less groundwater recharge. This study investigates the spatial variations of drought characteristics (drought event frequency, duration, severity, and intensity). This study using the Standardized Precipitation Index (SPI) to analyse the drought characteristics in Central Java during 1990-2010. The rain gauge station data and CHIRPS rainfall data over Central Java is used to calculate the SPI index. The SPI was calculated at multiple timescales (1-, 3-, 6-, 12-, 24- and 48-month), the run theory was used for identification and characterization of drought events. Analysis of drought characteristics by SPI from 1990 to 2010 shows the longest drought event is four months, the maximum drought severity is 6.06, and the maximum drought intensity is 2.02. El Nino year probability drought occurrence reached 100% in August for moderate drought, severe drought, and extreme drought category, whereas the probability drought occurrences in the Normal and La Nina year range 0-70% for moderate drought, 0-50% for severe drought category and 0-40% for extreme drought category. The results of this study may help inform researchers and local policymakers to develop strategies for managing drought.

Characterization of Bias during Meteorological Drought Calculation in Time Series Out-of-Sample Validation

The standardized precipitation index (SPI) is used for characterizing and predicting meteorological droughts on a range of time scales. However, in forecasting applications, when SPI is computed on the entire available dataset, prior to model-validation, significant biases are introduced, especially under changing climatic conditions. In this paper, we investigate the theoretical and numerical implications that arise when SPI is computed under stationary and non-stationary probability distributions. We demonstrate that both the stationary SPI and non-stationary SPI (NSPI) lead to increased information leakage to the training set with increased scales, which significantly affects the characterization of drought severity. The analysis is performed across about 36,500 basins in Sweden, and indicates that the stationary SPI is unable to capture the increased rainfall trend during the last decades and leads to systematic underestimation of wet events in the training set, affecting up to 22% of the drought events. NSPI captures the non-stationary characteristics of accumulated rainfall; however, it introduces biases to the training data affecting 19% of the drought events. The variability of NSPI bias has also been observed along the country’s climatic gradient with regions in snow climates strongly being affected. The findings propose that drought assessments under changing climatic conditions can be significantly influenced by the potential misuse of both SPI and NSPI, inducing bias in the characterization of drought events in the training data.

Spatial comparability of drought characteristics and related return periods in mainland China over 1961–2013

The proper understanding of the spatiotemporal characteristics of multi-year droughts and return periods is important for drought risk assessment. This study evaluated and compared the spatiotemporal variations of drought characteristics and return periods within mainland China between 1961 and 2013. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Composite Index (CI) were calculated at multiple timescales, the run theory was used for objective identification and characterization of drought events while Kendall’s τ method was used to analyze their dependencies. Within the univariate framework, marginal distributions of duration, severity, and peak were derived by fitting Exponential, Weibull and GDP distributions respectively and the drought return periods was investigated and mapped. Comparison of drought indices showed that SPEI and CI performed better than SPI in delineating spatial patterns of drought characteristics. This might be attributed to the temperature effect on evapotranspiration and therefore on drought index. Considering the increasing trend in reference evapotranspiration in the 21st century, the importance of utilizing temperature-based drought index is imperative. Severe and extreme droughts occurred in the late 1990s in many places in China while persistent multi-year severe droughts occurred more frequently over North China, Northeast China, Northwest China and Southwest China. The spatial patterns showed that regions characterized by higher drought severity were associated with higher drought duration. The North China, Northwest China, and Southwest China had much longer drought durations during the 1990s and 2000s. As droughts normally cover large areas, regional drought return periods has been showed to be more effective in providing support for drought management than station based drought return periods. Studies on the spatial comparability of drought return periods across mainland China have therefore been undertaken for drought mitigation and effective utilization of water resources.

An analytical formulation of return period of drought severity

Planning and management of water resources systems under drought conditions often require the estimation of return periods of drought events characterized by high severities. Among the several methods proposed for describing droughts, the run method is the most suitable to provide an objective identification and characterization of drought events. According to such a method, droughts are identified as consecutive intervals where the investigated hydrological variable is continuously below a fixed threshold, and may be described by means of two characteristics, namely, drought duration and drought severity. Since both characteristics are necessary to estimate water deficit risks, frequency analysis of drought events cannot be based on the same approach generally used for flood analysis, such as maximum annual series or partial duration series of a single characteristic. In particular, the evaluation of return period for drought events needs to consider both duration and severity in order to take into account the pluriannual duration of several droughts. Very often a reliable analysis of the probabilistic structure of droughts based on the observed samples, using an inferential approach, cannot be properly carried out due to the limited number of drought events which can be identified even on quite long historical series. This problem has been faced by Shiau and Shen (2001), who have determined the conditional distribution of drought severity given a drought duration on the basis of generated hydrological series. In this paper their approach is extended by deriving analytically the parameters of the probability distribution of drought severity based on the stochastic process describing the underlying hydrological variable. More specifically, a gamma distribution is adopted to model drought severity and its parameter are theoretically determined as a function of the threshold level and the coefficient of variation of annual precipitation series assumed independent and lognormal distributed. Then, the return period of drought events with severity greater than or equal to a fixed value is computed as the mean interarrival time of drought events with a certain severity or greater. Such procedure has been applied on 88 annual series of data recorded in Sicilian rainfall stations, by computing for each series the return period corresponding to drought of fixed severity and by plotting the spatial distribution in order to provide a description of drought spatial variability at a regional level.

Spatial characterization of drought events using synthetic hydrology

This paper describes an approach to spatial drought analysis based on multi-site streamflow synthesis. The approach developed can be used to assist with the quantification of the return period for the drought of record and can also be used to facilitate the identification of daesign drought events of a specified return period. The approach was applied to the Nelson–Churchill River basin in Manitoba, Canada. For this system, the impacts of droughts on power generation were investigated in addition to a determination of the return period for the drought of record. Key words: droughts, streamflow generation, frequency analysis, hydroelectric power.