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Predicting the transport of bedload tracer particles is a problem of significant theoretical and practical interest. Yet, little understanding exists for transport in rivers in the presence of bedforms, which may trap grains and thereby influence travel distance. In a series of flume experiments with a sandy gravel bed in a large experimental flume, bed elevation and tracer travel distances were measured at high resolution for a range of discharges. As discharge increased, bedform height increased and bedform length decreased, increasing bedform steepness. For all tracer sizes and flow conditions, bedforms act as primary controls on the tracer travel distances. Bedform trapping increases linearly with the ratio of bedform height to tracer grain size, with 50% trapping efficiency for a ratio of two and 90% trapping efficiency for a ratio of four. A theoretical model based on the extended active layer formulation for sediment transport is able to capture much of the distribution of measured travel distances for all tracer sizes and discharges, providing a first connection between tracer transport theory and bedform trapping and indicating normal diffusion of tracers at relatively small timescales. Variable bedform geometry can influence trap efficiency for individual bedforms and the theoretical model can help identify “preferential trapping” conditions. The distribution of tracer travel distances for a mixture of grain sizes and variable discharge, as expected in natural rivers, displays heavy tail characteristics.

 

Bedload particle hops are defined as successive motions of a particle from start to stop, characterizing one of the most fundamental processes of bedload sediment transport in rivers. Although two transport regimes have been recently identified for short and long hops, respectively, there is still the lack of a theory explaining the mean hop distance–travel time scaling for particles performing short hops, which dominate the transport and may cover over 80 % of the total hop events. In this paper, we propose a velocity-variation-based formulation, the governing equation of which is intrinsically identical to that of Taylor dispersion for solute transport within shear flows. The key parameter, namely the diffusion coefficient, can be determined by hop distances and travel times, which are easier to measure and more accurate than particle accelerations. For the first time, we obtain an analytical solution for the mean hop distance–travel time relation valid for the entire range of travel times, which agrees well with the measured data. Regarding travel times, we identify three distinct regimes in terms of different scaling exponents: respectively, $\sim$ 1.5 for the initial regime and $\sim$ 5/3 for the transition regime, which define the short hops, and 1 for the Taylor dispersion regime defining long hops. The corresponding distribution of the hop distance is analytically obtained and experimentally verified. We also show that the conventionally used exponential distribution, as proposed by Einstein, is solely for long hops. Further validation of the present formulation is provided by comparing the simulated accelerations with measurements. 

Understanding channel migration is essential in interpreting long‐term evolution of fluvial systems and their deposits. Using data from an experimental delta, we analyzed the kinematics of the upstream channel and assessed the relative dominance of continuous lateral channel migration versus abrupt changes (i.e., avulsions). Detailed investigation of channel centerline location at minute intervals reveals a short‐term correlation between the magnitude of migration rates measured at the same location and a spatial correlation that diminishes with distance between points. The main finding is that the channel migrates across the entire deltaic domain without large and abrupt lateral shifts but through continuous lateral migration at variable rates. Long periods of back and forth small moves are separated by short bursts of rapid lateral migration. This finding contradicts the default expectation that that aggrading systems are characterized by avulsions and suggests that highly mobile rivers tend to avulse less. We contrast this with another experiment conducted under similar conditions but with finer sediment supplied at a lower rate which shows drastically less lateral migration; the kinematics is instead dominated by periodic flow reconfiguration episodes akin to avulsions, an indication that channel migration‐style depends on the sediment load. The characteristics of these two experiments parallel two regions of the Mississippi River, the meandering and highly mobile alluvial plain and the less dynamic deltaic region, suggesting that bedload sediment deposition at the transition into backwater zone plays an important role in re‐shaping the river planform and migration style.

 

The knowledge of structural controls of river networks (RNs) on transport dynamics is important for modeling and predicting environmental fluxes. To investigate impacts of RN’s topology on transport processes, we introduce a systematic framework based on the concept of dynamic clusters, where the connectivity of subcatchments is assessed according to two complementary criteria: minimum‐ and maximum‐flow connectivity. Our analysis from simple synthetic RNs and several natural river basins across the United States reveals the key topological features underlying the efficiency of flux transport and aggregation. Namely, the timing of basin‐scale connectivity at low‐flow conditions is controlled by the abundance of topologically asymmetric junctions (side‐branching), which at the same time, result in a slow‐down of the flux convergence at the outlet (maximum‐flow). Our results, when compared with observed topological trends in RNs as a function of climate, indicate that humid basins exhibit topologies which are “naturally engineered” to slow‐down fluxes.

 

Abstract. The Indian Ocean presents two distinct climate regimes. The north Indian Ocean is dominated by the monsoons, whereas the seasonal reversal is less pronounced in the south. The prevailing wind pattern produces upwelling along different parts of the coast in both hemispheres during different times of the year. Additionally, dynamical processes and eddies either cause or enhance upwelling. This paper reviews the phenomena of upwelling along the coast of the Indian Ocean extending from the tip of South Africa to the southern tip of the west coast of Australia. Observed features, underlying mechanisms, and the impact of upwelling on the ecosystem are presented. In the Agulhas Current region, cyclonic eddies associated with Natal pulses drive slope upwelling and enhance chlorophyll concentrations along the continental margin. The Durban break-away eddy spun up by the Agulhas upwells cold nutrient-rich water. Additionally, topographically induced upwelling occurs along the inshore edges of the Agulhas Current. Wind-driven coastal upwelling occurs along the south coast of Africa and augments the dynamical upwelling in the Agulhas Current. Upwelling hotspots along the Mozambique coast are present in the northern and southern sectors of the channel and are ascribed to dynamical effects of ocean circulation in addition to wind forcing. Interaction of mesoscale eddies with the western boundary, dipole eddy pair interactions, and passage of cyclonic eddies cause upwelling. Upwelling along the southern coast of Madagascar is caused by the Ekman wind-driven mechanism and by eddy generation and is inhibited by the Southwest Madagascar Coastal Current. Seasonal upwelling along the East African coast is primarily driven by the northeast monsoon winds and enhanced by topographically induced shelf breaking and shear instability between the East African Coastal Current and the island chains. The Somali coast presents a strong case for the classical Ekman type of upwelling; such upwelling can be inhibited by the arrival of deeper thermocline signals generated in the offshore region by wind stress curl. Upwelling is nearly uniform along the coast of Arabia, caused by the alongshore component of the summer monsoon winds and modulated by the arrival of Rossby waves generated in the offshore region by cyclonic wind stress curl. Along the west coast of India, upwelling is driven by coastally trapped waves together with the alongshore component of the monsoon winds. Along the southern tip of India and Sri Lanka, the strong Ekman transport drives upwelling. Upwelling along the east coast of India is weak and occurs during summer, caused by alongshore winds. In addition, mesoscale eddies lead to upwelling, but the arrival of river water plumes inhibits upwelling along this coast. Southeasterly winds drive upwelling along the coast of Sumatra and Java during summer, with Kelvin wave propagation originating from the equatorial Indian Ocean affecting the magnitude and extent of the upwelling. Both El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events cause large variability in upwelling here. Along the west coast of Australia, which is characterized by the anomalous Leeuwin Current, southerly winds can cause sporadic upwelling, which is prominent along the southwest, central, and Gascoyne coasts during summer. Open-ocean upwelling in the southern tropical Indian Ocean and within the Sri Lanka Dome is driven primarily by the wind stress curl but is also impacted by Rossby wave propagations. Upwelling is a key driver enhancing biological productivity in all sectors of the coast, as indicated by enhanced sea surface chlorophyll concentrations. Additional knowledge at varying levels has been gained through in situ observations and model simulations. In the Mozambique Channel, upwelling simulates new production and circulation redistributes the production generated by upwelling and mesoscale eddies, leading to observations of higher ecosystem impacts along the edges of eddies. Similarly, along the southern Madagascar coast, biological connectivity is influenced by the transport of phytoplankton from upwelling zones. Along the coast of Kenya, both productivity rates and zooplankton biomass are higher during the upwelling season. Along the Somali coast, accumulation of upwelled nutrients in the northern part of the coast leads to spatial heterogeneity in productivity. In contrast, productivity is more uniform along the coasts of Yemen and Oman. Upwelling along the west coast of India has several biogeochemical implications, including oxygen depletion, denitrification, and high production of CH4 and dimethyl sulfide. Although weak, wind-driven upwelling leads to significant enhancement of phytoplankton in the northwest Bay of Bengal during the summer monsoon. Along the Sumatra and Java coasts, upwelling affects the phytoplankton composition and assemblages. Dissimilarities in copepod assemblages occur during the upwelling periods along the west coast of Australia. Phytoplankton abundance characterizes inshore edges of the slope during upwelling season, and upwelling eddies are associated with krill abundance. The review identifies the northern coast of the Arabian Sea and eastern coasts of the Bay of Bengal as the least observed sectors. Additionally, sustained long-term observations with high temporal and spatial resolutions along with high-resolution modelling efforts are recommended for a deeper understanding of upwelling, its variability, and its impact on the ecosystem. 

River beds evolve as a result of a complex interaction between strongly nonlinear processes such as near‐bed turbulence, particle‐particle interaction, and particle‐bed interaction. This interaction contributes to the initiation and evolution of extremely variable river bed elevation patterns, commonly known as bedforms that span across a range of spatiotemporal scales. In this paper, we employ a refined definition of entropy, that is, the multiscale entropy (MSE), to characterize the observed variability in the fluctuations of bed elevation time series under variable discharges obtained from a field‐scale laboratory flume. The MSE accounts for the sequence of data points in a series and quantifies the complexity and lack of information in a system. We show that the MSE of bed elevation fluctuations is higher for higher discharges. When compared with surrogates, which are the linearized series of a signal, the MSE provides across‐scale information about the underlying nonlinearity and linear correlation in a signal. The MSE difference between the original and surrogate series is due to the inherent nonlinearity that is higher for higher discharge at the smaller scales and peaks at intermediate scales. These results indicate the presence of a heterogeneous arrangement of extreme fluctuations that enhances the underlying complexity in bed elevation, rendering them less predictable at higher discharges. We further investigate the role of asymmetry of the bed elevation increments in observed complexity. Our results of asymmetry together with entropy suggest that characteristics of both small‐ and large‐scale features should be included for the accurate predictive modeling of sediment transport.

 

Abstract. Decreasing concentrations of dissolved oxygen in the ocean are considered one of the main threats to marine ecosystems as they jeopardize the growthof higher organisms. They also alter the marine nitrogen cycle, which isstrongly bound to the carbon cycle and climate. While higher organisms ingeneral start to suffer from oxygen concentrations < ∼ 63 µM (hypoxia), the marine nitrogen cycle responds to oxygenconcentration below a threshold of about 20 µM (microbial hypoxia),whereas anoxic processes dominate the nitrogen cycle at oxygenconcentrations of < ∼ 0.05 µM (functionalanoxia). The Arabian Sea and the Bay of Bengal are home to approximately21 % of the total volume of ocean waters revealing microbial hypoxia.While in the Arabian Sea this oxygen minimum zone (OMZ) is also functionallyanoxic, the Bay of Bengal OMZ seems to be on the verge of becoming so. Eventhough there are a few isolated reports on the occurrence of anoxia prior to1960, anoxic events have so far not been reported from the open northernIndian Ocean (i.e., other than on shelves) during the last 60 years.Maintenance of functional anoxia in the Arabian Sea OMZ with oxygenconcentrations ranging between > 0 and ∼ 0.05 µM is highly extraordinary considering that the monsoon reverses thesurface ocean circulation twice a year and turns vast areas of the ArabianSea from an oligotrophic oceanic desert into one of the most productiveregions of the oceans within a few weeks. Thus, the comparably lowvariability of oxygen concentration in the OMZ implies stable balancesbetween the physical oxygen supply and the biological oxygen consumption,which includes negative feedback mechanisms such as reducing oxygenconsumption at decreasing oxygen concentrations (e.g., reduced respiration).Lower biological oxygen consumption is also assumed to be responsible for aless intense OMZ in the Bay of Bengal. According to numerical model results,a decreasing physical oxygen supply via the inflow of water masses from thesouth intensified the Arabian Sea OMZ during the last 6000 years, whereas areduced oxygen supply via the inflow of Persian Gulf Water from the northintensifies the OMZ today in response to global warming. The first issupported by data derived from the sedimentary records, and the latterconcurs with observations of decreasing oxygen concentrations and aspreading of functional anoxia during the last decades in the Arabian Sea.In the Arabian Sea decreasing oxygen concentrations seem to have initiated aregime shift within the pelagic ecosystem structure, and this trend is alsoseen in benthic ecosystems. Consequences for biogeochemical cycles are asyet unknown, which, in addition to the poor representation of mesoscalefeatures in global Earth system models, reduces the reliability of estimatesof the future OMZ development in the northern Indian Ocean. 

Abstract. Over the past decade, our understanding of the IndianOcean has advanced through concerted efforts toward measuring the oceancirculation and air–sea exchanges, detecting changes in water masses, andlinking physical processes to ecologically important variables. Newcirculation pathways and mechanisms have been discovered that controlatmospheric and oceanic mean state and variability. This review bringstogether new understanding of the ocean–atmosphere system in the IndianOcean since the last comprehensive review, describing the Indian Oceancirculation patterns, air–sea interactions, and climate variability.Coordinated international focus on the Indian Ocean has motivated theapplication of new technologies to deliver higher-resolution observationsand models of Indian Ocean processes. As a result we are discovering theimportance of small-scale processes in setting the large-scale gradients andcirculation, interactions between physical and biogeochemical processes,interactions between boundary currents and the interior, and interactions between thesurface and the deep ocean. A newly discovered regional climate mode in thesoutheast Indian Ocean, the Ningaloo Niño, has instigated more regionalair–sea coupling and marine heatwave research in the global oceans. In thelast decade, we have seen rapid warming of the Indian Ocean overlaid withextremes in the form of marine heatwaves. These events have motivatedstudies that have delivered new insight into the variability in ocean heatcontent and exchanges in the Indian Ocean and have highlighted the criticalrole of the Indian Ocean as a clearing house for anthropogenic heat. Thissynthesis paper reviews the advances in these areas in the last decade. 

Catchments are complex systems containing channel networks and hillslopes. Channel networks interact with hillslopes and are pathways for transporting water, sediment, and nutrients. Understanding the branching and flux transport patterns of channel networks is critical for predicting the response of catchments to external forcing such as climate and tectonics. However, factors creating complexities in catchments are not fully understood. Here, we propose a new framework based on multiscale entropy approach to evaluate complexity of catchments using two different representations of channel networks. First, we investigate the structural complexity using the width‐function, which characterizes the spatial arrangement of channels. Second, we utilize the incremental area‐function along the main channel to study the functional complexity that captures the patterns of transport of fluxes. Our analysis reveals stronger controls of topological connectivity on the functional complexity than on structural complexity, indicating unchannelized surface (hillslope) contribution to the increase of heterogeneity in transport processes.