Estimation of Suspended Sediment Concentration in Downstream of the Ba River Basin using Remote Sensing Images

Assessing the tendency of suspended sediment concentration (SSC) in the river watershedsenables a better understanding of the hydromorphological properties of its basins and the associatedprocesses. In addition, analyzing this trend is essential to address several important issues such as erosion,water pollution, human health risks, etc. Therefore, it is critical to determine a proper method to quantifyspatio-temporal variability in SSC. In recent years, remote sensing and GIS technologies are being widelyapplied to support scientists, researchers, and environmental resource investigators to quickly andsynchronously capture information on a large scale. The combination of remote sensing and GIS data willbecome the reliable and timely updated data source for the managers, researchers on many fields. Thereare several tools, software, algorithms being used in extracting information from satellites and support forthe analysis, image interpretation, data collection. The information from satellite images related to waterresources includes vegetational cover, flooding events on a large scale, rain forecast, populationdistribution, forest fire, landslide movements, sedimentation, etc., and especially information on waterquality, sediment concentration. This paper presents the initial result from LANDSAT satellite imageinterpretation to investigate the amount of sediment carried downstream of the Ba river basin.

Suspended sediment in lowland rivers – towards identifying the ratios of mineral and organic components and their variation during the year

Concentrations of suspended sediment transported by rivers are influenced by interactions between multiple drivers that act on a range of spatial and temporal scales. Such levels vary over the year, as well as across multi-year periods. Most conventional approaches to determining suspended load are based upon analyses of total suspended sediment concentration (SSC), i.e., the sum of mineral and organic matter. This approach makes it difficult, if not impossible, to determine the impact of multiple environmental factors on changes in suspension concentration precisely. The present paper focuses on the mineral and organic components of suspended sediment with the aim of determining how our knowledge of the share of each individual component can improve interpretations of SSC fluctuations during a hydro-logical year. The analysis conducted (personal and other researchers’ results) has shown that mineral and organic suspensions demonstrate mutually incompatible opposite trends under influence of environmental factors. This analysis of organic components identifies clear seasonal trends, which indicates that organic suspensions of autogenous origin have a strong influence on the dynamics of changes in suspension concentration; such analyses are rarely included in assessments of SSC dynamics.

Prediction and classification of suspended sediment and zooplankton signals from acoustic Doppler current profiler backscatter data using artificial neural networks

Characterization of each underwater object has its challenges, especially for small objects. The process of quantifying acoustic signals for these small objects can be done using high-frequency hydroacoustic instruments such as an acoustic Doppler current profiler (ADCP) combined with the artificial intelligence (AI) technique. This paper presents an artificial neural network (ANN) methodology for classifying an object from acoustic and environmental data in the water column. In particular, the methodology was tuned for the recognition of suspended sediments and zooplankton. Suspended sediment concentration and zooplankton abundance, which extracted from ADCP acoustic data, were used as input in the backpropagation method along with other environmental data such as effects of tides, currents, and vertical velocity. The classifier used an optimal number of neurons in the hidden layer and a feature selection based on a genetic algorithm. The ANN method was also used to estimate the suspended sediment concentration in the future. This study provided new implications for predicting and classifying suspended sediment and zooplankton using the ADCP instrument. The proposed methodology allowed us to identify the objects with an accuracy of more than 95%.

Surf Zone Turbulence and Suspended Sediment Dynamics—A Review

The existence of sandy beaches relies on the onshore transport of sand by waves during post-storm conditions. Most operational sediment transport models employ wave-averaged terms, and/or the instantaneous cross-shore velocity signal, but the models often fail in predictions of the onshore-directed transport rates. An important reason is that they rarely consider the phase relationships between wave orbital velocity and the suspended sediment concentration. This relationship depends on the intra-wave structure of the bed shear stress and hence on the timing and magnitude of turbulence production in the water column. This paper provides an up-to-date review of recent experimental advances on intra-wave turbulence characteristics, sediment mobilization, and suspended sediment transport in laboratory and natural surf zones. Experimental results generally show that peaks in the suspended sediment concentration are shifted forward on the wave phase with increasing turbulence levels and instantaneous near-bed sediment concentration scales with instantaneous turbulent kinetic energy. The magnitude and intra-wave phase of turbulence production and sediment concentration are shown to depend on wave (breaker) type, seabed configuration, and relative wave height, which opens up the possibility of more robust predictions of transport rates for different wave and beach conditions.