Spatial-Temporal Change Analysis for Multivariate Drought Risk Based on Bayesian Copula: Application to the Balkhash Lake Basin

Abstract

In this study, a spatial-temporal Bayesian copula (SBC) method is developed through integrating spatial-temporal analysis and Bayesian copula into a general framework. SBC method can help model dependence structures of variable pairs and handle the uncertainty caused by parameter in copulas, and SBC can reveal the spatial and temporal changes of drought events. SBC is applied to the Balkhash Lake Basin (in Central Asia) to analyze spatial-temporal characteristic and drought risk in 1901-2020. Several findings can be summarized: (1) Balkhash Lake Basin suffered 53 drought events in 1901-2020, and five typical severe drought events occurred in 1916-1920, 1943-1945, 1973-1977, 1995-1998 and 2007-2009; (2) the most severe drought event lasted for 40 months (1973.10-1977.1), affecting 335,800 km2 of the study basin; (3) drought usually develops from east to west, and Ili River delta and alluvial plain has the highest frequency of drought (47.2%), following by plateau desert (28.3%) and arid grassland in north Balkhash Lake (24.5%); (4) drought shows significant seasonality in the study basin, which usually begins in spring and summer (64.2%) and ends in summer and autumn (66.0%); and drought risk of middle and lower reaches of Ili River is highest in spring and summer; (5) in Balkhash Lake Basin, multivariate characteristics (duration, severity and affected area) significantly affect drought risk; (6) the range of drought risk is [1.9%, 18.1%], [3.7%, 33.1%], [8.7%, 46.0%], [16.0%, 55.1%] and [27.6%, 59.8%] when guarantee rate is 0.99, 0.98, 0.95, 0.90 and 0.80, respectively.