Nonstationarity in the occurrence rate of floods in the Tarim River basin, China, and related impacts of climate indices Academic Article uri icon

abstract

  • © 2016 Elsevier B.V. Amplification of floods in the Xinjiang, China, has been observed, but reports on their changing properties and underlying mechanisms are not available. In this study, occurrence rates of floods in the Tarim River basin, the largest inland arid river basin in China, were analyzed using the Kernel density estimation technique and bootstrap resampling method. Also analyzed were the occurrence rates of precipitation extremes using the POT (Peak over Threshold)-based sampling method. Both stationary and non-stationary models were developed using GAMLSS (Generalized Additive Models for Location, Scale and Shape) to model flood frequency with time, climate index, precipitation and temperature as major predictors. Results indicated: (1) two periods with increasing occurrence of floods, i.e., the late 1960s and the late 1990s with considerable fluctuations around 2-3 flood events during time intervals between the late 1960s and the late 1990s; (2) changes in the occurrence rates of floods were subject to nonstationarity. A persistent increase of flood frequency and magnitude was observed during the 1990s and reached a peak value; (3) AMO (Atlantic Multidecadal Oscillation) and AO (Atlantic Oscillation) in winter were the key influencing climate indices impacting the occurrence rates of floods. However, NAO (North Atlantic Oscillation) and SOI (South Oscillation Index) are two principle factors that influence the occurrence rates of regional floods. The AIC (Akaike Information Criterion) values indicated that compared to the influence of climate indices, occurrence rates of floods seemed to be more sensitive to temperature and precipitation changes. Results of this study are important for flood management and development of mitigation measures.

author list (cited authors)

  • Gu, X., Zhang, Q., Singh, V. P., Chen, X. i., & Liu, L.

citation count

  • 22

publication date

  • July 2016