The Huaibei Plain is one of the most severe water scarcity areas in China. Understanding of hydroclimatic variation in this area at different timescales and its relationship with global teleconnection patterns are important for assessment of water resources utilization. In this study, spatiotemporal changes of seasonal and annual precipitation and temperature, including trend, abrupt change, variability, and periodicity were examined to recognize the potential remarkable changes during the last 41 years. The relationship between precipitation in the Huaibei Plain and teleconnection patterns using climate indexes was revealed by applying singular value decomposition. Results showed a nonsignificant annual precipitation increase about 2.4 mm/year. The annual average temperature increased about 1.2°C during 1970–2010. The abrupt change of annual precipitation mainly occurred during the 1970s and 1980s, while the primary mutation points for temperature were detected in 1990s, especially in 1997. The mean areal precipitation is characterized by a statistically significant 2- to 4-year periodicity at different phases, and the 2- to 5-year band is the major cycle for annual average temperature in this region. A statistically strong 5- to 8-year periodicity for precipitation could be detected from the middle of the 1980s to the end of the 1990s. Precipitation has positive correlation with the West Pacific Pattern and El Nino Southern Oscillation. The investigated results might have considerable implications for managing water resources in the Huaibei Plain.
This study explored the effects of interactions between waves and current on storm surge in the Pearl River Estuary (PRE) using a fully coupled wave–current model. The model was validated based on in situ observations during the traverse of super typhoon Mangkhut. The results indicated that the model could reproduce the storm surge and wave setup processes. Numerical experiments showed that simulations of storm surge are minimally affected by wave setup. The wave setup during super typhoon Mangkhut reached up to 0.23 m and contributed to the total near shore storm surge by up to 8%. The simulations of the coupled model showed a better correlation with observations compared to those of an uncoupled model. The storm surge increased with transport upstream in a tidal-dominated outlet, whereas it decreased in a river-dominated outlet. The storm surge and wave setup increased and decreased, respectively, during spring tide as compared to that during a neap tide. The storm surge increased with increasing runoff in the upper river reaches, whereas there was little change in the tidal-dominated lower river reaches. This research emphasizes the importance of integrating the effects of multiple dynamic factors in the forecasting of storm surge and provides a reference for similar studies in other estuaries with multiple outlets and a complex river network.
The development of high-precision, long-term, hourly-scale precipitation data is essential for understanding extreme precipitation events. Reanalysis systems are particularly promising for this type of research due to their long-term observations and wide spatial coverage. This study aims to construct a more robust precipitation dataset by integrating three widely-used reanalysis precipitation estimates: Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA2), Climate Forecast System Reanalysis (CFSR), and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5). A novel integration method based on the generalized three-cornered hat (TCH) approach is employed to quantify uncertainties in these products. To enhance accuracy, the high-density daily precipitation data from the Asian Precipitation-Highly-Resolved Observation Data Integration Towards Evaluation (APHRODITE) dataset is used for correction. Results show that the TCH method effectively identifies seasonal and spatial uncertainties across the products. The TCH-weighted product (TW), calculated using signal-to-noise ratio weighting, outperforms the original reanalysis datasets across various watersheds and seasons. After correction with APHRODITE data, the enhanced integrated product (ATW) significantly improves accuracy, making it more suitable for extreme precipitation event analysis. Quantile mapping was applied to assess the ability of TW and ATW to represent extreme precipitation. Both products showed improved accuracy in regional average precipitation, with ATW demonstrating superior improvement. This integration method provides a robust approach for refining reanalysis precipitation datasets, contributing to more reliable hydrological and climate studies.
This paper presents an experimental research method for sediment transportation around intake and outfall of power plants in tidal areas and then provides a reference for sand-protecting design of power plants.Based on crucial conditions of similarity theory for tide sediment movable bed physical model,program controlled tide generating system is used,the sediment movable bed model is established.Under typical tide and flood operating models,a test on intake and outfall of a plant in tidal area is carried out,and the sediment influent to intake and outfall are analyzed.Based on the above works,optimal structure of intake and outfall is obtained.The test could provide a reference for sediment transportation in intake and outfall of power plants in tide areas.
Climate and land use changes have substantially affected hydrologic cycles and increased the risk of drought. Reservoirs are one of the important means to provide resilience against hydrologic variability and achieve sustainable water management. Therefore, adaptive reservoir operating rules are needed to mitigate their adverse effects. In this study, the Hanjiang River Basin in southeast China was selected as the study area. Future climate and land use projections were produced by the Delta method and CA-Markov model, respectively. Future climate forcings and land use patterns were then incorporated into a distributed hydrologic model to evaluate river flow regime shifts. Results revealed that climate and land use changes may lead to severe drought conditions in the future. Lower flows are shown to be more sensitive to environmental changes and a decline of monthly flows could reach up to nearly 30% in the dry season. To address the threat of increasing drought uncertainties in the water supply system, the aggregation-decomposition method incorporated with hedging rules was applied to guide the multi-reservoir operation. Parameters of optimal hedging rules were obtained by a multi-objective optimization algorithm. The performance of hedging rules was evaluated by comparison to standard operating policies and conventional operating rules with respect to reliability, resiliency, vulnerability, and sustainability indices. Results showed that the multi-reservoir system guided by hedging rules can be more adaptive to the environmental changes.
Coastal vegetation is effective in dissipating incident wave energy during storm conditions, which offers valuable protection to coastal communities. Determining vegetation drag coefficient (CD) is of great importance to the quantification of vegetation-induced wave dissipation. Recently, a direct measuring approach has been developed to derive vegetation drag coefficient more accurately compared to the conventional calibration approach. However, as this approach requires perfectly in-phase force and velocity signals, there are two difficulties associated with it. The first difficulty is the availability of a suitable force sensor to compose synchronized force–velocity measuring systems. The second difficulty is related to realigning the obtained timeseries of force and velocity data. This technical note develops a new synchronized force–velocity measuring system by using standard force sensors and an acoustic doppler velocimeter (ADV). This system is applied together with an automatic realignment algorithm to ensure in-phase data for CD deviation. The algorithm reduces the phase shift between force–velocity signals from ca. 0.26 s to 0.003 s. Both time-varying and period-averaged CD can be obtained using this method. The derived CD can be used to accurately reproduce the measured maximum total acting force on vegetation (R2 = 0.759), which shows the reliability of the automatic alignment algorithm. The newly-developed synchronized force–velocity measuring system and alignment algorithm are expected to be useful in future experiments on vegetation–wave interactions with various hydrodynamic and vegetation settings.
Satellite-based precipitation estimates with high quality and spatial-temporal resolutions play a vital role in forcing global or regional meteorological, hydrological, and agricultural models, which are especially useful over large poorly gauged regions. In this study, we apply various statistical indicators to comprehensively analyze the quality and compare the performance of five newly released satellite and reanalysis precipitation products against China Merged Precipitation Analysis (CMPA) rain gauge data, respectively, with 0.1° × 0.1° spatial resolution and two temporal scales (daily and hourly) over southern China from June to August in 2019. These include Precipitation Estimates from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5-Land), Fengyun-4 (FY-4A), Global Satellite Mapping of Precipitation (GSMaP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). Results indicate that: (1) all five products overestimate the accumulated rainfall in the summer, with FY-4A being the most severe; additionally, FY-4A cannot capture the spatial and temporal distribution characteristics of precipitation over southern China. (2) IMERG and GSMaP perform better than the other three datasets at both daily and hourly scales; IMERG correlates slightly better than GSMaP against CMPA data, while it performs worse than GSMaP in terms of probability of detection (POD). (3) ERA5-Land performs better than PERSIANN-CCS and FY-4A at daily scale but shows the worst correlation coefficient (CC), false alarm ratio (FAR), and equitable threat score (ETS) of all precipitation products at hourly scale. (4) The rankings of overall performance on precipitation estimations for this region are IMERG, GSMaP, ERA5-Land, PERSIANN-CCS, and FY-4A at daily scale; and IMERG, GSMaP, PERSIANN-CCS, FY-4A, and ERA5-Land at hourly scale. These findings will provide valuable feedback for improving the current satellite-based precipitation retrieval algorithms and also provide preliminary references for flood forecasting and natural disaster early warning.
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