Although past work has noted that contrasts in turbidity often are detectable on remotely sensed images of rivers downstream from confluences, no systematic methodology has been developed for assessing mixing over distance of confluent flows with differing suspended sediment concentrations. In contrast to field measurements of mixing below confluences, remote-sensing data can provide detailed information on spatial patterns of surficial mixing over long distances along river systems, which can be utilized for mixing studies downstream of large river confluences.This dissertation consists of three main themes. The first study presents a methodology that uses remote sensing and USGS gaging station data to estimate spatial patterns of surficial suspended sediment concentrations (SSC) downstream of confluences along large rivers and to determine changes in the amount of mixing over distance from confluences. The method develops a calibrated Random Forest (RF) model by relating SSC data from river gaging stations to individual bands and derived spectral indices for the pixels corresponding to the locations of USGS gaging stations. The calibrated model is then used to predict SSC values for every river pixel in remotely sensed images, which provides basis for mapping of spatial variability in SSCs along the river. A new methodology is introduced to average surficial SSC data at cross sections spaced uniformly along the river. The method works as proxy to existing time averaging techniques in the fields. Mixing value at each cross-section is computed using the spatially averaged cross-section data and a new mixing metric that can work with low initial concentrations differences between tributaries and takes into account upstream SSC variance. The section provides three examples of model application where spatial pattern of changes in this metric over distance is used to define rates and length scales of surficial mixing of suspended sediment downstream of a confluence.The second study comprised of investigation of influence of different potential controlling factors on mixing downstream of confluences. Based on dimensional analysis and extant literature, the factors that could be calculated with remote sensing and available gaging station data were identified and regressed against observed mixing lengths to determine influence of each one of them on lateral mixing. Longitudinal variations in mixing with changes in channel geometry was also determined. Contrary to the current understanding, none of the factors identified in the literature showed any relation with the mixing lengths. The lack on observed relation between all of the factors indicates that mixing processes at large rivers are more complex then at small confluences. The study ascertains the need for additional applications of the methodology on other large rivers to identify uniqueness or commonalities between this confluence and other large confluences around the world. Furthermore, the methodology can also be used to evaluate how variations in mixing over time and space influence water quality and ecological conditions along the river.The third part presents a methodology to implement streamtube method to compute lateral mixing lengths downstream of the confluence. The method uses planform data from satellite imageries, hydrologic data from USGS, and bathymetric data from USACE to compute streamtube parameters. Mixing lengths determined by streamtube method are compared with the mixing lengths observed in the second study. Streamtube method relies heavily on flow discharges and mixing lengths decrease linearly with increasing discharge. However, the second study did not find any such relation between the discharge and mixing lengths. It is therefore concluded that the simple theoretical assumptions embodied in the streamtube model do not hold well for the mixing downstream of the confluence.
【 预 览 】
附件列表
Files
Size
Format
View
Satellite remote sensing of mixing dynamics at a large river confluence
PDF
download
878987797
028-85220240
