Stream power

About: Stream power is a research topic. Over the lifetime, 1135 publications have been published within this topic receiving 51324 citations.

Assessment of Spatial Patterns of Sediment Transport and Delivery for Soil and Water Conservation Programs

Abstract: Soil erosion has tremendous impacts on most river systems throughout the United States. Such non-point pollution results from land-use and agricultural practices and leads to sedimentation downstream, a decrease in the transport capacity of streams, an increase in the risk of flooding, filling of reservoirs, and eutrophication. This paper uses a spatially-explicit model to identify the sediment sources and delivery paths to channels and link these sediment supply processes to in-channel sediment transport and storage. The paper analyzes hillslope erosion and deposition rates using the Unit Stream Power Erosion and Deposition model in a GIS to estimate patterns of sediment supply to rivers in order to predict which portions of the channel network are more likely to store large amounts of fine sediments and thus are most sensitive to the effects of on and off-site soil erosion. This study focuses on the Pitman Creek Basin, a predominantly agricultural sub-basin in the Upper Green River in Kentucky. Results indicate that while much of the eroded sediments are redistributed within the hillslope system, a large proportion is also delivered to the channel. Sediment delivery to the stream is estimated using buffers defined in accordance with currently implemented conservation practices. These predictions have been tested by sampling the fine sediment content of the streambed at key locations along the channel network and comparing the observed patterns to those predicted by the soil erosion model. Overall, high intensity erosion tends to occur at contact between different vegetation covers, on barren lands and croplands, and 15-25% slopes poorly protected by vegetation, thus highlighting several erosion hot spots.

Channel erosion in steep gradient, gravel-paved streams

Abstract: Discharges were measured in steep gradient (> 5 percent) gravel-paved streams from 1988 to 1991 in order to empirically determine erosional thresholds based on sediment size, related to critical velocity, tractive force, and unit stream power. Results suggest that the empirical relationship between sediment size and unit stream power provides an accurate and simple methodology for determining the minimum erosion threshold discharge for steep gradient streams common in western Washington and other similar mountain terrains.

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Abstract: Gully erosion is a serious threat to the state of ecosystems all around the world. As a result, safeguarding the soil for our own benefit and from our own actions is a must for guaranteeing the long-term viability of a variety of ecosystem services. As a result, developing gully erosion susceptibility maps (GESM) is both suggested and necessary. In this study, we compared the effectiveness of three hybrid machine learning (ML) algorithms with the bivariate statistical index frequency ratio (FR), named random forest-frequency ratio (RF-FR), support vector machine-frequency ratio (SVM-FR), and naïve Bayes-frequency ratio (NB-FR), in mapping gully erosion in the GHISS watershed in the northern part of Morocco. The models were implemented based on the inventory mapping of a total number of 178 gully erosion points randomly divided into 2 groups (70% of points were used for training the models and 30% of points were used for the validation process), and 12 conditioning variables (i.e., elevation, slope, aspect, plane curvature, topographic moisture index (TWI), stream power index (SPI), precipitation, distance to road, distance to stream, drainage density, land use, and lithology). Using the equal interval reclassification method, the spatial distribution of gully erosion was categorized into five different classes, including very high, high, moderate, low, and very low. Our results showed that the very high susceptibility classes derived using RF-FR, SVM-FR, and NB-FR models covered 25.98%, 22.62%, and 27.10% of the total area, respectively. The area under the receiver (AUC) operating characteristic curve, precision, and accuracy were employed to evaluate the performance of these models. Based on the receiver operating characteristic (ROC), the results showed that the RF-FR achieved the best performance (AUC = 0.91), followed by SVM-FR (AUC = 0.87), and then NB-FR (AUC = 0.82), respectively. Our contribution, in line with the Sustainable Development Goals (SDGs), plays a crucial role for understanding and identifying the issue of “where and why” gully erosion occurs, and hence it can serve as a first pathway to reducing gully erosion in this particular area.

Dynamic characteristics of sandbar evolution in the lower Lancang-Mekong River between 1993 and 2012 in the context of hydropower development

Abstract: Hydropower development activities in the Lancang-Mekong River basin have become increasingly intense in recent decades, with potential impacts on river landforms and even the evolution of the estuarine delta. River sandbars are very sensitive to changes in runoff and sediment concentration; therefore, to analyze the dynamic characteristics of sandbar evolution in the lower Lancang-Mekong River (i.e., Mekong River), this study compared the dynamic parameters of the river before and after dam construction, using multiple regression equations based on data from historical remote sensing imagery, runoff, channel width, and gross domestic product (GDP) per capita. The results show that the sandbars have shrunk significantly since 2005, being consistent with the shrinkage of the Mekong delta, which suggests that the shrinkage of the two landforms may be dominated by the same factors. The direct factors causing this shrinkage phenomenon are a relative increase in erosive forces and a decrease in sediment sources simultaneously, which is specifically due to the slight increases of stream power and runoff shear stress, damming, sand mining activities downstream, urbanization and others. However, compared to climate changes, GDP-related human activities that manipulate these direct factors are likely a more significant driving force behind the changes in sandbar size. When the GDP per capita of the downstream basin was less than 1,614 USD/yr, the increase in the intensity of human activities led to an increase in sandbars. Conversely, when the GDP per capita exceeded 1,657 USD/yr beginning in 2005–2006, the sandbars shrank. This study reminds us that the impact of human activities on the evolution of downstream fluvial landforms is increasing in the lower Mekong River.