Tributary bays of the Three Gorges Reservoir (TGR) are suffering from environmental problems, e.g., eutrophication and algae bloom, which could be related to the limited water exchange capacity of the tributary bays. To understand and quantify the water exchange capacity of a tributary bay, this study investigated the water residence time (RT) in a typical tributary bay of TGR, i.e., the Zhuyi Bay (ZB), using numerical simulation and the adjoint method to obtain the RT. The results show that RT of ZB with an annual mean of 16.7 days increases from the bay mouth to the bay top where the maximum can reach 50 days. There is a significant seasonal variation in RT, with higher RT (average 20 days) in spring and autumn and lower RT (average < 5 days) in the summer. The sensitivity experiments show that the TGR water level regulation has a strong influence on RT. The increase in the water level could increase RT of ZB to some extent. Density currents induced by the temperature difference between the mainstream and tributaries play an important role in the water exchange of ZB, while the impacts of the river discharges and winds on RT are insignificant.

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The composition and change of runoff are closely related to climate change and human activities. To design effective watershed water resources management measures, there is a need for a clear understanding of the impact of climate change and human activities on baseflow and surface runoff. The purpose of this essay is to quantify their impact on the annual total stream flow, surface runoff, and base flow in the Weihe River Basin (WRB) using a two-stage annual precipitation partitioning method, wherein the surface runoff and base flow are separated from the measured total flow by using a one-parameter digital filter method for which the common filter parameter value is 0.925. The stream flow records were split into two periods: 1960–1970 (pre-change period) and 1971–2005 (post-change period) based on the hydrological breakpoints detected. We found that climate change and human activities have different impacts on base flow and surface runoff. We attributed the decrease in surface runoff due to climate change accounting for 76–78%, while we determined that human activities were responsible to the decrease in base flow accounting for 59–73% of the total observed change. We concluded that both climate change and human beings contributed to the hydrologic change through different hydrological processes: climate change dominated the surface runoff change, while human influences controlled the base flow change. To achieve the expected goals of ecological restoration, appropriate measures must be taken by watershed management in the WRB to mitigate the likely impacts of climate change on water hydrology.

As a major threat to ecosystem functions and national food security, soil erosion also exerts an influence on the water quality in basins and the operation and maintenance of hydropower plants. Existing discussions about trends of soil erosion focus mainly on its variation and mutation over time. Few studies have addressed the spatial mutation of soil erosion and its influence mechanism. In this research, Sen’s slope estimation was coupled with a Mann–Kendall model to explore the spatiotemporal distribution, spatial mutation characteristics and influence mechanisms of soil erosion, and conduct a case study on the Middle and Lower reaches of the Lancang River Basin (ML-LRB) in China. There are three main conclusions from this study: (1) During 2000–2019, the annual soil erosion in the ML-LRB variation ranged from 0 to 7.00 × 103 t/(km2·a) with a multi-year mean of 1.53 × 103 t/(km2·a), decreasing year by year from north to south, while an increasing trend began to appear in the central above region after 2015. (2) The areas with decreased soil erosion were much larger than those with increased soil erosion during 2000–2019, and there was a concentrated increase in soil erosion in Dali and in Xishuangbanna. (3) The mutation of the soil erosion intensity was spatially consistent with that of the Normalized Difference Vegetation Index (NDVI). Overall, this paper provides a new perspective for the study of factors affecting the trends and spatial mutation of soil erosion.