Encounter Probability and Risk of Flood and Drought under Future Climate Change in the Two Tributaries of the Rao River Basin, China

Abstract

Extreme hydrometeorological events have far-reaching impacts on our daily life and may occur more frequently with rising global temperatures. The probability of the concurrence of these extreme events in the upper reaches of the river network is of particular importance for the lower reaches, which is referred to as the encounter probability of extreme events, and may have even stronger socio-economic impacts. In this study, the Rao River basin in China is selected as an example to explore the encounter probability and risk of future flood and drought based on the encounter probability model. The reference period was 1971–2000, and the future prediction periods were 2020–2049 and 2070–2099. The calibrated and validated statistical downscaling model (SDSM) was used to generate future daily precipitation and daily mean temperature. The calibrated and validated Xin’anjiang model was used to predict future daily mean streamflow in the basin. In addition, the encounter probability model was established using the joint distribution of occurrence dates and magnitudes of daily mean streamflow to investigate the encounter probabilities of flood and drought under future climate change. Results show that, for flood occurrence dates, the encounter probability during the flood season would decrease in the two future periods while the dates would generally be earlier. For flood magnitudes, the encounter probability of the two tributaries’ floods and the probability of flood at each tributary would decrease (e.g., the encounter probability with the same-frequency of 100-years would reduce by 53% to 95%), which indicates reduced risk of future major floods in the study area. For drought occurrence dates, the encounter probability during the non-flood season would decrease. For drought magnitudes, the encounter probability would decrease (e.g., the encounter probability with the same-frequency of 100-years would reduce by 18% to 33%), even though the probability of future drought at each tributary would increase. Such analyses provide important probabilistic information to help us prepare for the upcoming extreme events.

Climatological Study of SPEI Drought Index Using Observed and CRU Gridded Dataset over Ethiopia

“…Drought is a complex phenomenon (Van Loon, 2015) and as a result of water shortage has more direct and significant impacts on environmental, social, and economic aspects than any other major natural disasters (Dai, 2013;Erian et al, 2010Erian et al, , 2021Liu et al, 2020a;Vogt et al, 2018;Zabihi et al, 2017). Droughts can arise either from climate extremes (e.g., advection of hot and dry air masses or prevailing anticyclonic conditions) or from the complex interaction of natural processes and high levels of human activity that affect the water balance (Erian et al, 2021;Van Loon et al, 2016).…”