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This study investigated uncertainties in the modeling of hydrological impacts of climate change on projected flood frequencies of the Zhujiang River, South China. The hydrological model HBV-D was applied to simulate and project future stream flow based on a multi-model ensemble. As this implies high uncertainties, the magnitude of three uncertainty sources, i.e. emission scenarios, GCM structure, and downscaling techniques, were determined in relation to the observed and projected natural variability. The relative change in each uncertainty source and the overall dominance among the three sources were further analyzed. The changes in flood frequency are projected for five return periods (2, 5, 10, 20, and 50 years) and three future time periods (2020s, 2050s, and 2080s). The results suggest that in comparison to the natural variability of the multi-model ensemble, the uncertainty sources show much stronger variations. The range of their relative change and their dominance vary with the lead-time and return period. In most of the return periods, the dominant uncertainty can primarily be attributed to downscaling techniques and emission scenarios, while GCMs structure is minor in the 2020s. However, downscaling technique is the second dominant source behind GCM structure, while emission scenarios represent the lowest uncertainty ranges of the three sources for the projected flood frequency in the 2050s and 2080s. The uncertainty and projected impact of climate change differs also between the four applied GCMs, as compared to the natural variability MK3_5 shows higher ranges than CCSM3, MK3_5 and ECHAM5. The upper bounds (95% percentile) in uncertainty mostly show an increasing tendency with increasing return period, and partially with increasing lead-time. Hence, the more extreme the return period (higher flood frequency) the higher is the uncertainty of the model projections. It is therefore essential that climate change impact assessments consider a wide range of climate scenarios derived from different GCMs under multiple emission scenarios and including several downscaling techniques. The uncertainty due to natural variability should also be considered more intensely. The projection of flood frequency and the identification and quantification of the uncertainties in the modeling is important for the implementation of adaptation policies into water resource planning in the Zhujiang River basin, South China. This study will enrich the scientific research on the uncertainty from different sources of modeling results in river basin parameters, and help to obtain conclusive results on the importance of different sources of uncertainty.

This study investigated future changes of dryness/wetness in ten large river basins: the Songhuajiang River basin, the Liaohe River basin, the Haihe River basin, the Yellow River basin, the Huaihe River basin, the Yangtze River basin, the Pearl River basin, the Southeast River basins, the Southwest River basins and the Northwest Inland River basins across China during the first 50 years of the 21st century. The study was carried out according to the Standardized Precipitation Index (SPI), which is calculated by monthly precipitation data of ECHAM5/MPI-OM. Three anthropogenic greenhouse gas emission scenarios, SRES-A2, SRES-A1B and SRES-B1 have been considered. The frequency of dry/wet periods in these river basins was calculated and the trend detected by the Mann–Kendall non-parametric test. The results reveal that there is a trend towards drier conditions from northeast to southwest China in scenario A2 and a similar spatial distribution pattern in scenario A1B and B1. Areas with a high frequency of drought are detected under all three scenarios. In the next half century, the Haihe River basin, northeast China, is expected to show a significant trend towards drier conditions, which pass the 95% confidence level in scenario A2. In the Yellow River basin, the Huaihe River basin, the Yangtze River basin and the Pearl River basin, an obvious trend towards wetter conditions has been detected in scenario A1B. The Songhuajiang River basin, the Haihe River basin, the Yellow River basin and the Huaihe River basin show a trend towards wetter conditions, which passed the 90% confidence level in scenario B1. The future dryness/wetness frequency situation is complex in the ten large river basins.

Gridded climate data sets are widely used in the analysis, modeling and forecasting of the consequences of climate change. The objective of this study is to compare the impact of different climate datasets (station vs. gridded) on the parameterization of a hydrological model (developed using SWAT2005) of the River Xiangxi, the largest tributary of Yangtze River in the Hubei part of the Three Gorges Reservoir. Climate data used in this study derive from two sources: point daily observations from the Xingshan meteorological station (STN) and gridded (0.5° × 0.5°) monthly observations of the CRU TS3.0 global dataset (CRU) downscaled to daily data using a weather generator. Data from 1970 to 1974 were applied for sensitivity analyses and autocalibration and subsequently validate hindcasts over the period 1976-1986. Despite there being only slight differences in mean annual precipitation (1003 mm vs. 1052 mm) between STN and CRU, the data differ more in their estimates of the number of rain days (136 vs. 112) and wet days standard deviation (11.75 mm vs. 18.49 mm). The mean, maximum and minimum temperatures from CRU are all lower than those from STN. SWAT parameter sensitivity analysis results show slight differences in the relative rank of the most sensitive parameters, with the differences mainly caused by the lower temperature and more intensive rainfall in CRU relative to STN. Autocalibrated parameters showed very similar values, except for the surface runoff lag coefficient which is higher for the CRU dataset compared to that derived from the STN dataset. Statistic results for discharge simulated based on CRU compared rather well with that based on STN CRU as evaluated using the standard statistics of the Nash?Sutcliffe efficiency, coefficient of determination, and percent error. The sensitivity analysis and autocalibration tool embedded in SWAT2005 is a powerful utility in hydrological modeling of the River Xiangxi, and the CRU dataset appears to be appropriate for application to hydrological modeling in this case, thus providing a good basis for climate change studies.

Significant quasi-cycles in precipitation time series of 132 climate stations spread over China from 1951 to 2002 have been detected by applying Autocorrelation Spectral Analysis (ASA). By the same method, significant quasi-cycles have also been identified in time series of the potential influencing factors: Southern Oscillation Index (SOI), Sea Surface Temperature (SST) and Sea Level Pressure (SLP). Similarities between some precipitation time series spectra and the spectrum of a potential driving force have been detected; e.g. several series from the Yangtze River's middle reaches show 3–4-year cycles which are similar to the SOI and several SST signals. These time series have been further investigated by low-pass filtering with the Savitzky–Golay filter and by means of correlation analysis. It is proved that the SOI and the SSTs of the Bay of Bengal are in relatively stable anti-phase. However, no stable link between these signals and the precipitation series in the Yangtze River basin can be detected. Subsequent analyses of 850 hPa winds lead to the outcome that certain wind patterns could either suppress or force the SST and SOI teleconnection signals.

The present study examines the spatial and temporal variation of extreme precipitation over the Yangtze River Basin based on meteorological data for 1960–2004. From 147 stations, regional characteristics of extreme precipitation are analyzed using a rotated empirical orthogonal function (REOF). Non-parametric trend analysis and wavelet transformation analysis are applied to analyze the temporal variation of extreme precipitation. The results show that (1) 6 leading modes of extreme precipitation exist in the following area: east/north-eastern Yangtze, north/central Yangtze, south-eastern Yangtze, north-western Yangtze, western Yangtze and south/south-western Yangtze; (2) significant positive changes can be found for extreme precipitation averaged for the east/north-eastern Yangtze and the western Yangtze basin, and statistically significant abruption is detected in year 1986 for both regions; (3) significant negative trends can be detected over the north-western Yangtze basin with abruption in the years 1968 and 1990; and (4) long-term trends and inter-decadal oscillations of extreme precipitation can be found for 6 mode domains, but not constant periodicity. The increase in heavy precipitation in the middle-lower reaches can partly explain the frequent occurrence of floods in the 1990s. It is difficult to predict the trends of heavy precipitation for future years, but possible alternating of high-frequency extreme precipitation in the middle and lower reaches indicates flood disaster might be aggravated in the incoming decade of the 21st century in the Yangtze River Basin.

The present study examines the spatial and temporal trends of precipitation, flood/drought, runoff, high and low river flow during flood season (May–October) for the Yangtze River Basin. Analyses are based on daily meteorological data for 137 stations from 1960 to 2004, daily hydrological data for two discharge-measuring stations at the Yangtze River and monthly hydrological data for one station for the same reference period. Flood/drought examination was done for the western, middle, and lower Yangtze River Basin. Significant precipitation changes can be detected for June and July during 1960–2004. The strongest precipitation increase was detected in the lower Yangtze region. A statistically significant negative trend can be found in September over the Yangtze River Basin, especially at the middle region. Changes of the precipitation extremes from May to October are of direct importance to the occurrences of high and low river flow. The main increase of flooding events can be detected for July in the lower Yangtze region, together with significant upward trends both for the monthly runoff and for the high river water stage. Drought frequency increased in the middle Yangtze River Basin in May, September and October, where downward trends for the monthly runoff and low river flow especially in May. During these months, flood and drought hazards in the Yangtze River Basin have been aggravated.

A 5.67-m-thick section in loess-like sediments at Xiashu was exposed during archaeological excavation of the Fangniushan Paleolithic site. ESR dating and grain-size analysis suggested that the sediments are wind-blown in origin and were deposited within a period of about 400 kyr. Environmental proxy indicators, including magnetic susceptibility, frequency-dependent magnetism, Kd, median grain size and clay grade percentage show that five warm and humid climatic periods occurred in the study region in the mid-Pleistocene, namely at 130–90, 192, 195–198, 203–230 and 345–357 ka. These five periods roughly correspond to the S1, S2, S3, S4 and S5 paleosols in the Chinese Loess Plateau stratigraphy and also to the deep-sea oxygen isotope stages 5, 7, 9, 11, and 13–15. The upper four climatic periods are comparable to the four warm climatic periods recorded in the Laohushan Xiashu loess section. Discovery of stone implements from the sixth and the seventh layers during the archaeological excavation indicates human activities at that time, and the environmental proxies suggest that the environment was suitable for human activities.