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In this paper, we revisit the classical energy transport equation for pure tidal flows in estuaries by including the effects of residual water level and freshwater discharge. Starting from the one-dimensional mass and momentum conservations, we derive analytical expressions for energy flux and its dissipation, which can be used to explore the interaction between tide and river from an energy perspective. It has been shown that the potential energy flux is dominant over the kinetic energy flux, and the energy contribution made by tide-river interaction is negligible compared with that due to tidal flow and freshwater discharge. A critical position corresponding with zero energy flux can be identified, reflecting a balance between along-channel tidal amplitude and residual water level. Assuming the variation of system energy tends to zero, we derive the long-term equilibrium bed profile with a convex-up shape, where we identify the location of a second estuarine turbidity maximum (ETM) at a position determined by the balance between river- and tide-induced energy flux. The dynamic response of tidal propagation extent and critical position with zero energy flux are shown to adjust to reflect seasonal changes towards the formation of a bed profile that is in dynamic equilibrium. Key policy insights: A new analytical method is derived to calculate energy transport and energy dissipation in river-tide estuaries. Equilibrium bed profile determined by minimum entropy production has a convex-up shape where the minimum depth coincides with the location of zero along-channel energy flux. The location of a second estuarine turbidity maximum is consistent with the location where there is a balance between river- and tide-induced energy flux. [ABSTRACT FROM AUTHOR]

Extreme integrated vapor transport (IVT) is a crucial driving factor of extreme precipitation events (EPEs). This paper presents a complex network‐based characterization of propagations from extreme IVT to EPEs. Specifically, the propagations are tracked from extreme IVT to EPEs by event synchronization; and then the source zones of extreme IVT contributing to EPEs are identified by two‐layer complex network. A case study is devised for North America based on the daily NCEP/NCAR Reanalysis 1 from 1948 to 2021. Overall, eight communities of EPEs are identified: the west coast of United States (US) tend to receive substantial EPEs from the Pacific Ocean; the Gulf of Alaska tends to receive oceanic EPEs propagating inland; western Canada typically experiences large amount of out tendencies and the EPEs tend to accumulate in the Baffin Island and Labrador Peninsula; the southeastern US and the northern Great Plains tend to experience northward propagations from Mexico. Along the west coast of North America, the propagations from extreme IVT to EPEs typically originate from the eastern North Pacific between 160°W and 110°W, and make landfalls in 4 days. These propagations are influenced by anomalous cyclonic circulations developing over the Gulf of Alaska forced by eastward Rossby waves. The coincidence rate of these propagations with atmospheric rivers is, respectively, 85.31% in autumn, 91.35% in winter, 73.94% in spring, and 64.52% in summer. Overall, the observed propagations from extreme IVT to EPEs yield insights into the mechanism of atmospheric moisture transport and the predictability of precipitation. Plain Language Summary: Owing to different synoptic systems such as atmospheric rivers, low‐level jets, and tropical cyclones, there exist profound propagations from extreme integrated vapor transport to extreme precipitation. Focusing on North America, this paper is concentrated on the complex network underlying extreme integrated vapor transport and extreme precipitation events. It is found that the Rocky Mountains play an important part in shaping the propagations from extreme integrated vapor transport to extreme precipitation events. In particular, along the west coast of North America, extreme integrated vapor transport originating from the eastern North Pacific tends to be blocked by the Rocky Mountains, causing rising/cooling and leading to extreme precipitation. Overall, along the Rocky Mountains, there exist eight communities of extreme precipitation. Key Points: There exists a complex network on propagations from extreme integrated vapor transport to extreme precipitation events in North AmericaIn the west coast of North America, the propagations typically originate from eastern North Pacific and make landfalls in 4 daysThe coincidence rate of propagations with atmospheric rivers is, respectively, above 90% and 60% in boreal winter and summer [ABSTRACT FROM AUTHOR]

While global streamflow reanalysis has been evaluated at different spatial scales to facilitate practical applications, its local performance in the time–frequency domain is yet to be investigated. This paper presents a novel decomposition approach to evaluating streamflow reanalysis by combining wavelet transform with machine learning. Specifically, the time series of streamflow reanalysis and observation are respectively decomposed and then the approximation components of reanalysis are evaluated against those of observed streamflow. Furthermore, the accumulated local effects are derived to showcase the influences of catchment attributes on the performance of streamflow reanalysis at different scales. For streamflow reanalysis generated by the Global Flood Awareness System, a case study is devised based on streamflow observations from the Catchment Attributes and Meteorology for Large-sample Studies. The results highlight that the reanalysis tends to be more effective in characterizing seasonal, annual and multi-annual features than daily, weekly and monthly features. The Kling–Gupta efficiency (KGE) values of original time series and approximation components are primarily influenced by precipitation seasonality. High values of KGE tend to be observed in catchments where there is more precipitation in winter, which can be due to low evaporation that results in reasonable simulations of soil moisture and baseflow processes. The longitude, mean precipitation and mean slope also influence the local performance of approximation components. On the other hand, attributes on geology, soils and vegetation appear to play a relatively small part in the performance of approximation components. Overall, this paper provides useful information for practical applications of global streamflow reanalysis. [ABSTRACT FROM AUTHOR]

Predicting flood event classes aids in the comprehensive investigation of flood behavior dynamics and supports flood early warning and emergency plan development. Existing studies have mainly focused on historical flood event classification and the prediction of flood hydrographs or certain metrics (e.g., magnitude and timing) but have not focused on predicting flood event classes. Our study proposes a new approach for predicting flood event classes based on the class membership functions of flood regime metrics and hydrological modeling. The approach is validated using 1446 unimpacted flood events in 68 headstream catchments widely distributed across China. The new approach performs well, with class hit rates of 68.3% ± 0.4% for all events; 65.8% ± 0.6%, 56.8% ± 0.9%, and 69.5% ± 0.9% for the small, moderate and high spike flood event classes, respectively; and 82.5% ± 1.2% and 75.4% ± 1.1% for the moderate and high dumpy flood event classes, respectively. Furthermore, it performs better in the basins of northern China than in those of southern China, particularly for the small spike flood event class in the Songliao and Yellow River Basins, with hit rates of 80.0% ± 3.2% and 78.8% ± 3.2%, respectively. Our results indicate that the new approach will help improve the prediction performance of flood events and their corresponding classes, and provide deep insights into the comprehensive dynamic patterns of flood events for early warning and control management. Plain Language Summary: The prediction of flood event classes is more effective and informative than that of individual events for obtaining comprehensive dynamic characteristics of flood events for early warning and development of emergency plans. However, this is challenging owing to massive flood events with remarkable spatiotemporal heterogeneity and unclear class membership functions. We propose a class prediction approach for flood events using the class membership functions of flood behavior metrics based on frequency analysis and catchment hydrological modeling. This approach deeply mines the behavior characteristics of historical flood events with a strong mathematical basis and cooperates with hydrological models to predict flood classes. Over thousand unimpacted flood events in 68 headstream catchments across China were selected to validate the robustness of the prediction scheme. Our results show that the proposed approach well predicts the flood class with class hit rates of 68.3% ± 0.4% for all events; 65.8% ± 0.6%, 56.8% ± 0.9%, and 69.5% ± 0.9% for the small, moderate and high spike flood event classes, respectively; and 82.5% ± 1.2% and 75.4% ± 1.1% for the moderate and high dumpy flood event classes, respectively. Our study has strong implications for scientific flood warning research and flood mitigation management. Key Points: A prediction approach for flood event classes is developed using class membership functions of flood regime metrics with hydrological modelClass membership degree is estimated using the frequency distribution function, which fits well with statistical significanceAverage class hit rates are 68.3% ± 0.4% for all the events and predictions of dumpy flood class are better than those of spike flood classes [ABSTRACT FROM AUTHOR]

Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]