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Water discharge and sediment load are often controlled by a combination of factors. However, the relationship between water and sediment load changes and meteorological oscillations has rarely been explored for different river sizes. Explanations for the various responses of water-sediment changes to meteorological factors in different rivers is important for understanding global hydrology. In this study, we analyzed data from 2002-2022 using cross-wavelet and wavelet coherence in an attempt to characterize the effects of large-scale climatic oscillations on 10 rivers in eastern China. Comparing the results shows that water releases lag three months or more behind SST variations. It also oscillates interannually (mostly every 8-16 months). Most rivers runoff lags changes in PDO by three months or more. The impact of ENSO (El Niño-Southern Oscillation) on each river basin gradually decreases from south to north. The impacts on northern rivers such as the Yellow River, Huai Riverand Liao River are weaker. At the same time, the water discharge changes in the Pearl River and Minjiang River basins in southeastern China are extremely rapid and sensitive to ENSO events. Meanwhile, the impacts of ENSO on large rivers lasted throughout the study period, while the impacts of ENSO on smaller rivers had intermittent periods, and the response rates of geographically similar mountain and stream-type rivers were not the same. The effect of the PDO (Pacific Decadal Oscillation) warm and cold phases was different for each region. Our research contributes to understanding the relationship between rivers and climate oscillations, advancing Water-Sediment Balance and Global Sustainability—key goals of the United Nations 2030 Agenda for Sustainable Development.

Estuaries serve as transitional zones between rivers and the ocean, and their mixed dynamic characteristics are crucial for the transport, transformation, and cycling of materials. This study investigates the mixing characteristics and their dominant factors in the Danshui Estuary and thermal discharge outlets through field measurements. Based on CTD (Conductance Temperature Depth) profiles and nutrient concentration measurements, the Danshui Estuary exhibited significant stratification during the October 2016 cruise, while vertical mixing was uniform during the March 2017 cruise. Vertical mixing was suppressed during stratification, but the nutrient concentration varied with salinity in a manner that was similar to non-stratified conditions, generally conforming to the theoretical dilution curve, which means physical mixing dominated here, indicating that horizontal mixing is predominant in the Danshui Estuary. The spatial scale calibrated horizontal dispersion coefficients were measured as 9.16 ± 1.57 m2 s−1 and 11.84 ± 1.71 m2 s−1 for stratified and non-stratified conditions, respectively, highlighting the Danshui Estuary’s strong horizontal mixing. Thermal discharge outlets are an important type of estuarine environment in non-natural estuaries. The 3D thermohaline structure measured by the underway CTD revealed an upwelling of cold and high-salinity water during the flood tide. The calculated Richardson number during the flood tide was approximately 0.7, indicating a very strong stratification effect. The horizontal dispersion coefficients calibrated by spatial scale showed no significant difference between different tides (flood tide: 0.53 ± 0.18 m2 s−1, ebb tide: 0.46 ± 0.17 m2 s−1). Therefore, the slower temperature decay during the flood tide, as reflected by the e-folding time (flood tide: 4.19 ± 2.33 min, ebb tide: 2.14 ± 0.40 min), is attributed to the strong stratification. Based on these findings, it is recommended that the power plant mitigates the impact of waste heat on the marine environment by increasing discharge during the ebb tide and reducing it during the flood tide.

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

Precipitation patterns are highly valued in the fields of weather forecasting, water resource management, and estuary environment research. In this study, daily and monthly precipitation TRMM data from 1998 to 2019 were selected, and EOF analysis was employed to analyze the precipitation patterns of the Taiwan Strait and its neighboring regions. We obtained the following results: (1) The rainy season (May–June) is the main contributor to precipitation in the study area. The EOF first mode reflected the overall consistency of the precipitation spatial distribution. However, within each river basin, the magnitude of precipitation variation is spatially different. The magnitude of precipitation variation is significant in the northwestern part of the Minjiang River basin, the southwestern part of the Jiulong River basin, and the southwestern corner of the Hanjiang River basin. These areas happen to correspond to the mountain areas, revealing that topographic precipitation plays a role in the spatial distribution of precipitation in the three river basins. (2) The spatial distributions of the EOF first mode and of precipitation during El Niño in the Minjiang River basin are consistent. This reveals that ENSO is probably the dominant factor in precipitation in the Minjiang River basin. The significant increase in precipitation during El Niño compared with a normal year in the Minjiang River basin confirms this point. (3) In all three strong El Niño years, 1998, 2010, and 2016, the Minjiang River basin experienced significant heavy precipitation in the fall and winter, whereas the Jiulong River and Hanjiang River basins did not (except in 2016). In other words, the Minjiang River basin is more affected by ENSO, while the Jiulong River and Hanjiang River basins are only limitedly impacted by ENSO.

FETSWCM-SWAN and DualSPHysics models are used to study the storm flooding process of Dazuo Seawall in Quanzhou city, Fujian province, China. Firstly, a storm over-topping assessment method is proposed. Secondly, the water level and storm wave at the foot of Dazuo Seawall calculated by FETSWCM-SWAN during the process of Typhoon Usagi in 2013 and Typhoon Dujuan in 2015. Finally, the typical wave and storm run-up processes at Dazuo Seawall are modeled by DualSPHysics. The results show that the typical wave run-up of Dazuo Seawall is less than 2 m, but the storm wave run-up can reach 6.85 m under Usagi. The risk is high when high tide is encountered. The risk of storm flooding is classified into three grades. This risk assessment could provide decision-making support to government departments in warning against storm flooding threats.

Band structure and wave localization are investigated for sea surface water waves over large-scale sand wave topography. Sand wave height, sand wave width, water depth, and water width between adjacent sand waves have significant impact on band gaps. Random fluctuations of sand wave height, sand wave width, and water depth induce water wave localization. However, random water width produces a perfect transmission tunnel of water waves at a certain frequency so that localization does not occur no matter how large a disorder level is applied. Together with theoretical results, the field experimental observations in the Taiwan Bank suggest band gap and wave localization as the physical mechanism of sea surface water wave propagating over natural large-scale sand waves. [ABSTRACT FROM AUTHOR]