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The world’s largest hydropower dam, the Three Gorges Dam (TGD), spans the upper Yangtze River in China, creating a 660-km long and 1.1-km wide reservoir upstream. Several recent studies reported a considerable decline in sediment load of the Lowermost Yangtze River (LmYR) and a rapid erosion in the subaqueous delta of the river mouth after the closure of the TGD in 2003. However, it is unknown if the TGD construction has also affected river channel and bed formation of the LmYR. In this study, we compared bathymetric data of the last 565 kilometers of the Yangtze River’s channel between 1998 and 2013. We found severe channel erosion following the TGD closure, with local riverbed erosion up to 10 m deep. The total volume of net erosion from the 565-km channel amounted to 1.85 billion m3, an equivalent of 2.59 billion metric tons of sediment, assuming a bulk density of 1.4 t/m3 for the riverbed material. The largest erosion occurred in a 100-km reach close to the Yangtze River mouth, contributing up to 73% of the total net eroded channel volume.

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ABSTRACT

Sediment properties are known to influence acoustic backscatter intensity. This sediment-acoustic relationship has been investigated previously through using physical geoacoustic models and empirical methods and found to be complex and nonlinear. Here we employ a robust machine-learning statistical model (random forest decision tree) to investigate the most likely nonlinear sediment-backscatter relationships. The analysis uses colocated sediment and acoustic backscatter data (collected from a 300-kHz multibeam sonar system) for 564 locations in four different areas on the Australian margin. Seven sediment grain size properties (%gravel, %sand, %mud, mean grain size, sorting, skewness, and kurtosis) were used to predict the acoustic backscatter responses at individual incidence angles. The modeling results demonstrate the effectiveness of this multivariate predictive approach for the investigation of sediment-acoustic relationship. Thus, we find that for incidence angles between 1°and 41°, the sediment variables explain around 70% of variance in the backscatter intensity. Sediment mud content was found to be the most important sediment variable in the model and has a significant negative relationship with backscatter intensity. Mean grain size was the second ranked sediment variable and found to have a positive relationship with backscatter intensity. The results also show that sediment mud content plays a key role in sorting-backscatter and sand-backscatter relationships. Using only two sediment properties, mud content and mean grain size, together it was possible to largely explain the sediment-acoustic relationship. The strongest backscatter return occurred with medium sediment mud content and large mean grain sizes (or muddy coarse sand).

Evaluation of river basins requires land-use and land-cover (LULC) change detection to determine hydrological and ecological conditions for sustainable use of their resources. This study assessed LULC changes over 28 years (1990–2018) in the Wami–Ruvu Basin, located in Tanzania, Africa. Six pairs of images acquired using Landsat 5 TM and 8 OLI sensors in 1990 and 2018, respectively, were mosaicked into a single composite image of the basin. A supervised classification using the Neural Network classifier and training data was used to create LULC maps for 1990 and 2018, and targeted the following eight classes of agriculture, forest, grassland, bushland, built-up, bare soil, water, and wetland. The results show that over the past three decades, water and wetland areas have decreased by 0.3%, forest areas by 15.4%, and grassland by 6.7%, while agricultural, bushland, bare soil, and the built-up areas have increased by 11.6%, 8.2%, 1.6%, and 0.8%, respectively. LULC transformations were assessed with water discharge, precipitation, and temperature, and the population from 1990 to 2018. The results revealed decreases in precipitation, water discharge by 4130 m3, temperature rise by 1 °C, and an increase in population from 5.4 to 10 million. For proper management of water-resources, we propose three strategies for water-use efficiency-techniques, a review legal frameworks, and time-based LULC monitoring. This study provides a reference for water resources sustainability for other countries with basins threatened by LULC changes.

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