Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site). 相似文献
Plenty of geomechanics tests and theories have confirmed the existence of non-coaxiality while soil is subjected to principal stress rotation. This paper investigated the influence of one particular principal stress path, which is a ‘heart-shape’ stress path that is normally induced by high-speed train loading, on the non-coaxiality of reconstituted soft clay. Hollow cylinder apparatus was employed to carry out series of undrained dynamic tests. The goals of this study were to (1) reveal the essential factors of complex cyclic loading paths that influence non-coaxiality in clayey soil and (2) quantify the influence of the factors on variation in non-coaxiality under the high-speed training loading. To analyze the non-coaxiality under high-speed train loading, (a) the pure rotation stress path was utilized as comparison for underling the different influence that ‘heart-shape’ stress path has from other conventional cyclic stress paths. (b) Two variables, dynamic stress ratio and tension–compression amplitude ratio, were introduced in analyzing the evolution of the non-coaxial angle. (c) Based on the test results, equations for describing the revolution of non-coaxiality were proposed which can help to describe the variation in non-coaxial angle under complex loadings quantitatively and understand the influence of the major factors of the stress path intensively.
