Integrated assessment for hydrometeorological drought based on Markov chain model

Abstract

Drought assessment based on a single index cannot comprehensively reflect the characteristics of a drought affected by multiple factors. Therefore, the main purpose of this study is to accurately assess the drought by constructing an integrated drought assessment method (PDSI-SDI) that can combine the meteorological drought and hydrological drought at the same time. To better evaluate and forecast the drought, the Markov chain model is employed in this study to calculate the expected residence time, return period and transition probabilities of the drought. Furthermore, the Mann–Kendall method is adopted to predict the trend of the drought. The Weihe River Basin is selected as the study area, and according to the distribution characteristics of the water system, it is divided into five districts in order to better assess the drought. Results indicate that: (1) spatially, drought probabilities increase from south to north and west to east. (2) Temporally, probabilities of spring droughts are the highest, followed by summer droughts and autumn droughts, winter droughts have the lowest probabilities, extreme droughts are more likely to occur in autumn. (3) Drought preferentially transfers within the same scenario, except scenario 4 (meteorological drought with no hydrological drought) in autumn is prone to shift to scenario 1 (no meteorological drought with no hydrological drought). (4) There is a significant drying trend of the drought in the Weihe River Basin at the significance level of 95 %. The integrated drought assessment method and other methods adopted in this study can be applied in other regions as well.