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Satellite-based precipitation products (SPPs) have greatly improved their applicability and are expected to offer an alternative to ground-based precipitation estimates in the present and the foreseeable future. There is a strong need for a quantitative evaluation of the usefulness and limitations of SPPs in operational meteorology and hydrology. This study compared two widely used high-resolution SPPs, the Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) in Poyang Lake basin which is located in the middle reach of the Yangtze River in China. The bias of rainfall amount and occurrence frequency under different rainfall intensities and the dependence of SPPs performance on elevation and slope were investigated using different statistical indices. The results revealed that (1) TRMM 3B42 usually underestimates the rainy days and overestimates the average rainfall as well as annual rainfall, while the PERSIANN data were markedly lower than rain gauge data; (2) the rainfall contribution rates were underestimated by TRMM 3B42 in the middle rainfall class but overestimated in the heavy rainfall class, while the opposite trend was observed for PERSIANN; (3) although the temporal distribution characteristics of monthly rainfall were correctly described by both SPPs, PERSIANN tended to suffer a systematic underestimation of rainfall in every month; and (4) the performances of both SPPs had clear dependence on elevation and slope, and their relationships can be fitted using quadratic equations. [ABSTRACT FROM AUTHOR]

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h(q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h(q). However, the relationship between the width of the singularity spectrum (Δα) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations. [ABSTRACT FROM AUTHOR]

Water resources in the Yangtze River, the longest river in China, are of great importance for the water security of China. In this study, 146 years (1865-2010) of streamflow data were used to investigate the changes in streamflow of the Yangtze River. The Mann-Kendall test and wavelet coherence analysis were used to test the change points in annual streamflow. The streamflow data, combined with the meteorological dataset of the Climatic Research Unit (CRU) from 1901 to 2010, showed that the Yangtze River streamflow changes occurred in four major periods over the past century: 1901-1930, 1931-1960, 1961-1990, and 1991-2010. The average annual streamflow for the four periods was 497.26, 499.11, 476.25, and 471.93 mm, respectively. The period from 1901 to 1930 was considered the baseline period for estimating the streamflow changes during the other three periods. We found that the streamflow increase during 1931-1960 was mainly influenced by climatic variation, while the streamflow decrease during 1961-1990 was mainly attributed to human activities because of tremendous population growth and rapid economic development. During the period 1991-2010, both climatic variation and human activities led to a decrease in streamflow, and human activities were still the main driving factor for the streamflow decrease. However, the contribution proportion of human activities to the streamflow decrease during 1991-2010 was much smaller than that during 1961-1990. The estimation results indicated that human activities have become the dominant driving factors of the streamflow changes in the Yangtze River Basin since 1961. Human activities, such as booming socio-economic development and fast population growth, have brought new challenges for water resources management in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]