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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]

Recent events across many regions around the world have shown that short-term droughts (i.e., daily or weekly) with sudden occurrence can lead to huge losses to a wide array of environmental and societal sectors. However, the most commonly used drought indices can only identify drought at the monthly scale. Here, we introduced a daily scale drought index, that is, the standardized antecedent precipitation evapotranspiration index (SAPEI) that utilizes precipitation and potential evapotranspiration and also considers the effect of early water balance on dry/wet conditions on the current day. The robustness of SAPEI is first assessed through comparison with two typical monthly indices [Palmer drought severity index (PDSI) and standardized precipitation evapotranspiration index (SPEI)] and soil moisture, and then applied to tracking short-term droughts during 1961–2015 for the Pearl River basin in south China. It is demonstrated that SAPEI performs as well as SPEI/self-calibrating PDSI at the monthly scale but outperforms SPEI at the weekly scale. Moreover, SAPEI is capable of revealing daily drought conditions, fairly consistent with soil moisture changes. Results also show that many of the historical short-term droughts over the Pearl River basin have multiple peaks in terms of severity, affected area, and intensity. The daily scale SAPEI provides an effective way of exploring drought initiation, development, and decay, which could be conducive for decision-makers and stakeholders to make early and timely warnings. [ABSTRACT FROM AUTHOR]

Daily precipitation data from 590 stations in China covering a period of 1960-2005 are analysed using copulas, the modified Mann-Kendall (MK) trend test and linear regression. Changing characteristics of eight precipitation indices are investigated in both time and space. Results indicate that (1) the regions west of 100°E, particularly northwest China, exhibit a wetting tendency as reflected by increasing/decreasing number of consecutive rain/non-rain days; (2) the drying tendency is observed mainly in the regions covered by the Yellow River basin, the Huaihe River basin, and the Haihe River basin, and relatively moderate changes in precipitation indices are found in northeast China; (3) precipitation extremes are intensifying in the regions east of 100°E, particularly in case of south China, specifically the lower Yangtze River basin, the southeast rivers and the Pearl River basin. The intensification of precipitation extremes in south China is mirrored mainly by the decreasing number of rain days and increasing number of consecutive non-rain days. Besides an increasing percentage of P90 to the annual total precipitation, (4) the intensification of precipitation extremes has the potential to increase the probability of occurrence of natural hazards, particularly floods and droughts. The spatial distribution of flood- and drought-affected crop areas is in agreement with that of precipitation extremes, showing considerable impacts of precipitation extremes on meteor-hydrological hazards. An increasing number of consecutive non-rain days in south China will cause a higher risk of droughts. The regions east of 100°E are heavily populated and are economically developed. Food security, water security, and sustainable socioeconomy in China urgently call for effective water resource management policy. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

• A dynamic three-stage blending scheme is developed to simultaneously correct precipitation occurrence and intensity. • A new daily 0.25° precipitation dataset over mainland China is produced by merging four multi-satellite/reanalysis products. • Different data merging methods are systematically evaluated in 238 catchments over China. • Our developed approach can facilitate hydrological modelling by substantially improving the KGE of simulated streamflow. Satellite-retrieved and atmospheric reanalysis precipitation can bridge the spatiotemporal gaps of in-situ gauging networks, but estimation biases can limit their reliable applications in hydrological monitoring and modelling. To correct precipitation occurrence and intensity simultaneously, this study develops a three-stage blending approach to integrate three multi-satellite precipitation datasets (IMERG Final, TMPA 3B42V7 and PERSIANN-CDR), the ERA5 atmospheric reanalysis product and a gauge dataset within a dynamic framework. Firstly, the systematic biases of the four members were individually corrected by combining the local intensity scaling and ratio bias correction methods. Then, the "state weights" used for determining wet/dry events were optimized by evaluating a score function of the four bias-corrected members. Thirdly, the "intensity weights" were optimized using the cuckoo search (CS) algorithm and the Bayesian Model Averaging (BMA) method, respectively. The three-stage blending approach produced dynamic weights varying both spatially and temporally, and the performance was thoroughly evaluated over mainland China. Results show that the three-stage dynamic scheme performs better than individual datasets and two-stage blending methods in terms of all eight statistical metrics, and the CS algorithm outperforms the BMA method in the third stage. By randomly sampling validation sites using K-fold experiments, the developed algorithm also demonstrates a superior performance in ungauged regions. After interpolating and normalizing blending parameters of all gauges to entire domain using ordinary kriging, a new blended precipitation dataset with a daily 0.25° scale was produced. Four hydrological models are forced by blended and primary precipitations in 238 catchments over China, further confirming that the developed approach can facilitate hydrological modelling demonstrated by improving the Kling-Gupta efficiency of simulated streamflow by 12–35%. [ABSTRACT FROM AUTHOR]

• A framework is proposed to investigate the drought hazard propagation. • Drought hazards are quantified by the most-likely scenarios and uncertainty envelope. • Drought hazards tend to ascend from meteorological to hydrological droughts. As a major weather-driven disaster, drought can be assessed from meteorological to hydrological aspects. Although the propagation from meteorological to hydrological droughts has received lots of attention in recent years, the hazard transferability in such a propagation process has been less investigated. In this study, we propose a framework with the incorporation of copulas and a drought hazard propagation ratio (DHPR) to examine the drought propagation process, particularly to investigate the accompanying hazard transferability. Three catchments with few human activities located in two major river basins of China (i.e., the Yangtze River basin and the Yellow River basin) with different hydro-climatic conditions are selected as case studies. First, the standardized precipitation evapotranspiration index (SPEI) and the standardized runoff index (SRI) are calculated to measure meteorological and hydrological droughts for the 1961–2014 period. Subsequently, the drought duration and severity are identified using the theory of run, and then the most-likely scenarios and the corresponding uncertainty ellipse based on copulas are incorporated to appraise meteorological and hydrological drought hazards. Finally, a novel concept of DHPR is proposed to evaluate the hazard transferability from meteorological to hydrological drought. The results show that (1) the drought propagation generally shows lengthened duration, amplified severity, and the time-delay phenomenon among these catchments; (2) drought hazards represented by the most-likely scenarios of duration and severity and the uncertainty ellipse tend to ascend based on the bivariate frequency analysis; and (3) the hazard transferability is stable from meteorological to hydrological droughts, as indicated by the almost unchanged DHPR ranging between 1 and 2 for the most-likely scenarios and varying between 2 and 4 for the uncertainty ellipse under different return periods. The above results imply firm and robust correlations between meteorological and hydrological drought hazards, which can provide a supplement for revealing the drought propagation mechanism and would benefit drought risk assessment. [ABSTRACT FROM AUTHOR]