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The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970., (Copyright © 2015. Published by Elsevier Inc.)

On the basis of monthly runoff series obtained in 1950–2013 and annual sediment load measured in 1956–-2013 at five key hydrological stations in the middle and lower reaches of the Yangtze River basin, this study used the Mann-Kendall methods to identify trend and abrupt changes of runoff and sediment load in relation to human activities. The results were as follows: (1) The annual and flood season runoffs showed significant decreasing trends at Yichang station, and showed slight downward trends at Hankou and Datong stations, while the abrupt changes of dry season runoff at Yichang, Hankou and Datong stations occurred in about 2007 and the change points were followed by significant increasing trends. The construction of the Three Gorges Dam, which began to operate in 2003, influenced the variations of runoff in the mainstream of Yangtze River, but the effect weakened with the distance along the downstream direction from TGD. (2) Since the 1990s, annual sediment loads at Yichang, Hankou, and Datong stations have been decreasing significantly, and after 2002, the annual sediment load at Yichang dropped below that of Hankou and Datong. The dams and deforestation/forestation contributed to the significant decreasing trend of the sediment load. In addition, the Three Gorges Dam aggravated the downward trend and caused the erosion of the riverbed and riverbanks in the middle and lower reaches. (3) The runoff and sediment load flowing from Dongting Lake into the mainstream of the Yangtze River showed significant decreasing trends at Chenglingji station after 1970s, and in contrast, slight increase in the sediment flow from Poyang Lake to the mainstream of the Yangtze River at Hukou station were detected over the post-TGD period (2003–2013). The result of the study will be an important foundation for watershed sustainable development of the Yangtze River under the human activities. [ABSTRACT FROM AUTHOR]

Summary Entropy theory has been increasingly applied in hydrology in both descriptive and inferential ways. However, little attention has been given to the small-sample condition widespread in hydrological practice, where either hydrological measurements are limited or are even nonexistent. Accordingly, entropy estimated under this condition may incur considerable bias. In this study, small-sample condition is considered and two innovative entropy estimators, the Chao–Shen (CS) estimator and the James–Stein-type shrinkage (JSS) estimator, are introduced. Simulation tests are conducted with common distributions in hydrology, that lead to the best-performing JSS estimator. Then, multi-scale moving entropy-based hydrological analyses (MM-EHA) are applied to indicate the changing patterns of uncertainty of streamflow data collected from the Yangtze River and the Yellow River, China. For further investigation into the intrinsic property of entropy applied in hydrological uncertainty analyses, correlations of entropy and other statistics at different time-scales are also calculated, which show connections between the concept of uncertainty and variability. [ABSTRACT FROM AUTHOR]

The Loess Plateau in China is overlain by deep and loose soil. As in other semi-arid regions, convective precipitation produces storms, typically of short duration, relatively high intensity and limited areal extent. Infiltration excess (Hortonian mechanism) of precipitation is conventionally assumed to be more prominent than saturation excess (Dunne mechanism) for storm runoff generation. This assumption is true at a point during the storm. However, the runoff generation mechanism is altered when the runoff is conditioned by a lateral redistribution movement of water, i.e. run-on, as the spatial scale increases. In the Loess Plateau, the effects of run-on may be significant, because of the deep and loose surface soil layer. In this study, the role of run-on for overland flow in the Upper Wei River basin, located in the Loess Plateau, is evaluated by means of a simple numerical model at the hillslope scale. The results show that almost all the Hortonian overland flow infiltrates into the soil along the flat hillslope and dry gully before it reaches the river channel. Most of the runoff is generated from the saturated soil near the river channel and from the subsurface. The run-on process takes much longer than the infiltration, facilitating rainfall–runoff modelling at a daily time step. A hydrological model is employed to investigate the characteristics of runoff generation in the Upper Wei River basin. The analysis shows that the subsurface flow contribution to total streamflow is more than 53% from October to March, while the overland flow contribution exceeds 72% from April to September. Editor D. Koutsoyiannis; Associate editor Dawen Yang Citation Liu, D.F., Tian, F.Q., Hu, H.C., and Hu, H.P., 2012. The role of run-on for overland flow and the characteristics of runoff generation in the Loess Plateau, China. Hydrological Sciences Journal, 57 (6), 1107–1117. [ABSTRACT FROM AUTHOR]

The evolution of the ecohydrological system driven by external climatic forcing and internal feedbacks between vegetation and hydrology, which is more remarkable in arid and semiarid regions, has attracted substantial research attention in recent years. To examine critically the state-of-the-art assumptions and dynamic equations used in the evolution study of an ecohydrological system, the rule of proceeding from simplicity to complexity should be followed. The riparian vegetation ecohydrological system in hyperarid regions (e.g. the lower Tarim River) can serve as a starting point given its simplicity, which has been seldom examined before in terms of system evolution. Further, the water transfer practice from 2000 to 2006 in the lower Tarim River serves as a valuable prototype experiment for model validation. This is because the remarkable changes in groundwater and vegetation in the area have taken place within a shorter period and thus can be easily observed. In the present study, the ecohydrological evolution model on riparian vegetation (ERV model) in hyperarid regions was proposed by coupling groundwater movement and vegetation dynamics. In the ERV model, the groundwater table serves as a critical feedback variable that determines the vegetation dynamics (colonization and mortality) and is determined by vegetation transpiration other than groundwater movement. The monitored groundwater table by wells and satellite-observed vegetation coverage from the Moderate Resolution Imaging Spectroradiometer are used for model validation. The simulation results show the good performance of the ERV model with uncalibrated parameters. It was also calibrated manually using a multiobjective method, and the fine-tuned parameters are close to the uncalibrated ones, indicating the robustness of the model. The analysis shows further that the increased evapotranspiration is substantially due to the water transfer and thus the vegetation growth, which implies the importance of ecohydrological coupling for long-term hydrological modelling. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from −0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle. [ABSTRACT FROM AUTHOR]