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Summary: In this paper, the trends of the annual streamflow and precipitation and cross correlations between them were analyzed in nine large river basins of China during 1956–2005. The results indicate that: (1) the annual mean streamflow decreases in arid and semi-arid regions of north China; however, increasing trends occur in south and Southwest China; (2) the annual streamflow and precipitation exhibit reasonable correlation in nine large river basins except those located in inland areas. The annual streamflow over most areas of China is fed by precipitation; however, the decline in streamflow is faster than the decreases of precipitation since 1970s in the arid and semi-arid regions of north China. The relationship between the annual precipitation and streamflow presents a non-stationary state in north China. This non-stationary relationship is strongly influenced by both human activities and precipitation changes; (3) a significant increase of water use might be the major factor responsible for the steeper decline in streamflow than in precipitation in Haihe River, Yellow River and Songliao River basins in north China. In inland river areas, increase of water use and actual evapotranspiration might result in decline in streamflow although precipitation has an increase tendency. This paper sheds light on the non-stationary relationship between annual precipitation and streamflow and possible underlying causes, which will be helpful for a better understanding of the changes of precipitation and streamflow in China at large scale and in other regions of the world. [Copyright &y& Elsevier]

Summary The climate elasticity of runoff is an important indicator that is used to quantify the relationship between changes in runoff and changes in climate variables. It is a function of both climate and catchment characteristics. Recently, Yang and Yang (2011) proposed an analytical derivation of climate elasticity (YY2011), in which a parameter n was used to represent the impact of the catchment characteristics. In China, both climate and catchment characteristics have large spatial variations. To understand the spatial variation of hydrologic response to climate change, this paper divided China into 210 catchments, further calculated the parameter n , and then estimated the climate elasticity and evaluated the contribution of climate change to runoff for each catchment. The results show that n ranges from 0.4 to 3.8 (with a mean of 1.3 and a standard deviation of 0.6), which has a logarithmic relationship with catchment slope; the precipitation elasticity ranges from 1.1 to 4.8 (with a mean of 1.9 and a standard deviation of 0.6), which shows a large regional variation, smaller values (1.1–2.0) mainly appearing in Southern China, the Songhua River basin and the Northwest, and larger values (2.1–4.8) mainly appearing in the Hai River basin, the Liao River basin and the Yellow River basin. In addition, climate contribution to runoff exhibits a large regional variation, the largest positive values (1.1–3.1%/a) occurring in the Northwest, the largest negative values (−1.0 to −0.5%/a) occurring in the Hai River basin and the middle reach of the Yellow River basin. In theory, the YY2011 method is a first-order approximation. The approximation underestimates the precipitation ( P ) contribution to runoff when P increases and overestimates that when P decreases, and the relative error has a median of ∼3% and a maximum of ∼20% when 10% precipitations change in those catchments of China. [ABSTRACT FROM AUTHOR]

Summary: Oxygen and hydrogen stable isotopes (δ 18O and δD) in precipitation collected in every event from 2007 to 2009 in Guangzhou, South China, are presented in this paper. The total correlation between δ 18O and δD is obtained as δD =(8.46±0.13) δ 18O+(15.0±0.9). More negative δ 18O and δD generally occur during summer and autumn, while less negative or even positive δ 18O and δD occur during winter and spring. Significant negative correlations between precipitation δ 18O and temperature, and between precipitation δ 18O and precipitation amount are observed. Regression line changes from year to year are likely due to changes in moisture sources for the precipitation. The moisture contributed by adjacent seas or local evaporation account for the main precipitation during winter and early spring, while summer monsoon brings huge amounts of moisture from remote seas associated with higher temperature and larger precipitation amounts. Seasonal variations of the precipitation D-excess provide more details for changes in moisture sources. Higher D-excess values during winter and early spring are estimated to correspond to a lesser proportion of remote moisture, while lower D-excess values during summer and autumn correspond to larger remote moisture transported by summer monsoons. This generally agrees with the results of model analysis on single isobaric backward trajectories for air parcels during specific time periods. Results of this study imply that precipitation δ 18O and δD, as well as some related paleoclimate proxies such as δ 18O in speleothem and tree ring, and δD in plant-derived organic compounds and tree ring, currently cannot indicate changes in temperature or precipitation amount separately, but should be comprehensive proxies for monsoon climate. [ABSTRACT FROM AUTHOR]