River network rearrangements promote speciation in lowland Amazonian birds

Large Amazonian rivers impede dispersal for many species, but lowland river networks frequently rearrange, thereby altering the location and effectiveness of river-barriers through time. These rearrangements may promote biotic diversification by facilitating episodic allopatry and secondary contact among populations. We sequenced genome-wide markers to evaluate histories of divergence and introgression in six Amazonian avian species-complexes. We first tested the assumption that rivers are barriers for these taxa and found that even relatively small rivers facilitate divergence. We then tested whether species diverged with gene flow and recovered reticulate histories for all species, including one potential case of hybrid speciation. Our results support the hypothesis that river dynamics promote speciation and reveal that many rainforest taxa are micro-endemic, unrecognized and thus threatened with imminent extinction. We propose that Amazonian hyper-diversity originates in part from fine-scale barrier displacement processes, including river dynamics, which allow small populations to differentiate and disperse into secondary contact.

A Numerical Study of the Critical Threshold for Landslide Dam Formation Considering Landslide and River Dynamics

Landslide dam formation can be influenced by the erosive capacity of river flow and the dynamic characteristics of the landslide. When the deposition rate of a landslide that reaches a river is higher than the erosion rate of river flow, the landslide can form a dam by blocking the channel. Hence, in this paper, a dimensionless discharge threshold for landslide dam formation considering landslide and river dynamics is established and studied numerically. A two-layer depth-averaged model coupled with an erosion term is presented to simulate river and landslide movements and their interactions. Several numerical cases are simulated to study the influence of landslide and river dynamics on the critical threshold for dam formation by considering some key factors, such as landslide velocity and the angle between the river and landslide transport directions. Through the simulations, three types of landslide intrusion into river can be reflected: a dam forms quickly, a dam forms or does not form close to a critical state, and no dam forms. The results show that these factors together affect the process of dam formation if the difference between the landslide and river discharges is relatively small. All results are helpful to further clarify the formation of such dams for natural hazard prevention under future climate change conditions.

Towards a better understanding of river dynamics in semi-urbanised areas: a machine learning analysis on time-series satellite images

<p>River channels and floodplains have been highly modified over the last 70 years to mitigate flood risk and to gain lands for agricultural activities, settlements and soft infrastructures (e.g., cycle paths). River engineering measures simplified the geomorphologic complexity of river system, usually from braided or wandering channels to highly-confined single-thread channel. Meanwhile, rivers naturally adjust and self-organise the geomorphologic function as response of all the disturbances (e.g., flood events, river-bed degradation, narrowing, control works) altering sediment and water transfer, exacerbating bank erosion processes and streambank failures, and exposing bare sediment that can be subsequently colonized by pioneer species. In this context, river management has to address river dynamics planning sustainable practices with the aim to combine hydraulic safety, river functionality, and ecological/environmental quality. These actions require the detection of river processes by monitoring the geomorphological changes over time, both over the active riverbank and the close floodplains. Thus, remote sensing technology combined with machine learning algorithms offers a viable decision-making instrument (Piégay et al., 2020).</p><p>This study proposes a procedure that consists in applying image segmentation and classification algorithms (i.e., Random Forest and dendrogram-based method) over time-series high resolution RGB-NIR satellite-images, to identify the fluvial forms (bars and islands), the vegetation patches and the active riverbed. The study focuses on three different reaches of Oglio River (Valcamonica, North Italy), representative of the most common geomorphic changes in Alpine rivers.</p><p>The results clearly show the temporal evolution/dynamics of vegetated and non-vegetated bars and islands, as consequence of human and natural disturbances (flood events, riparian vegetation clear-cutting, and bank-protection works). Moreover, the procedure allows to distinguish two stages of riparian vegetation (i.e., pioneer and mature vegetated areas) and to quantify the timing of colonization and growth. Finally, the study proposes a practical application of the described methodology for river managers indicating which river management activity (including timing, intensity and economic costs) is more appropriate and sustainable for each studied reach.</p><p> </p><p>References: Piégay, H., Arnaud, F., Belletti, B., Bertrand, M., Bizzi, S., Carbonneau, P., Dufour, S., Liébault, F., Ruiz‐Villanueva, V. and Slater, L.: Remotely sensed rivers in the Anthropocene: state of the art and prospects, Earth Surf. Process. Landf., 45(1), 157–188, https://doi.org/10.1002/esp.4787, 2020.</p>

POTENSI EROSI DAN SEDIMENTASI HULU DANAU LIMBOTO

Since 1932, Limboto Lake has been experiencing siltation, in 2006 it was measured that about 4.000 hectare of lake was covered. It was predicted by many that in 2031 Lake Limboto would disappear. The ‘Lake Limboto Revitalization’ has been conducted since 2017 by conducting many activities, including sabo plan implementation (also known as sabo technology). This study was originally conducted to review sabo plan in Limboto Lake, however this particular report was conducted to measure potential of erosion and sedimentation using WaTEM/SEDEM Model. Among 12 upstream rivers/Sub-DAS flowing into Limboto Lake, here were rivers with most potential to bring erosion and sedimentation into the lake to the least: Batulayar 193.662 m3, Biyonga Boluta 123.095 m3, Alo1 120.273m3, Alo 115.204 m3, Molamahu 73.058 m3, Marisa 57.075 m3, Pulubala 53.445 m3, Pone 40.254 m3, Molamahu1 39.585 m3, Pilolalenga 32.306 m3, Talumelito 32.247 m3, Pulubala2 31.267 m3, Tuladengi 28.908 m3, Pone1 27.306 m3, Payunga 26.746 m3, Biyonga Boluta1 25.895 m3, Pilolalenga1 21.841 m3, Tabongo 20.151 m3, Pulubala1 17.741 m3, and Tabongo1 11.031 m3. Considering the river dynamics as well as absence of secondary data about rivers, it was crucial to review sabo plan and to measure sedimentation potential per year.

GIS Application in Fluvial Geomorphology and Landscape Changes

The main purpose of this Special Issue of Water is to propose on overview of studies and researches, in which the use of GIS is functional to the representation of fluvial geomorphology and river dynamics, linear erosion processes, erosion rates, ancient landscapes reshaped by the fluvial action, flooding areas, and historical anthropic changes of the river landscape and land use [...]

HyLands 1.0: a hybrid landscape evolution model to simulate the impact of landslides and landslide-derived sediment on landscape evolution

Landslides are the main source of sediment in most mountain ranges. Rivers then act as conveyor belts, evacuating landslide-derived sediment. Sediment dynamics are known to influence landscape evolution through interactions among landslide sediment delivery, fluvial transport and river incision into bedrock. Sediment delivery and its interaction with river incision therefore control the pace of landscape evolution and mediate relationships among tectonics, climate and erosion. Numerical landscape evolution models (LEMs) are well suited to study the interactions among these surface processes. They enable evaluation of a range of hypotheses at varying temporal and spatial scales. While many models have been used to study the dynamic interplay between tectonics, erosion and climate, the role of interactions between landslide-derived sediment and river incision has received much less attention. Here, we present HyLands, a hybrid landscape evolution model integrated within the TopoToolbox Landscape Evolution Model (TTLEM) framework. The hybrid nature of the model lies in its capacity to simulate both erosion and deposition at any place in the landscape due to fluvial bedrock incision, sediment transport, and rapid, stochastic mass wasting through landsliding. Fluvial sediment transport and bedrock incision are calculated using the recently developed Stream Power with Alluvium Conservation and Entrainment (SPACE) model. Therefore, rivers can dynamically transition from detachment-limited to transport-limited and from bedrock to bedrock–alluvial to fully alluviated states. Erosion and sediment production by landsliding are calculated using a Mohr–Coulomb stability analysis, while landslide-derived sediment is routed and deposited using a multiple-flow-direction, nonlinear deposition method. We describe and evaluate the HyLands 1.0 model using analytical solutions and observations. We first illustrate the functionality of HyLands to capture river dynamics ranging from detachment-limited to transport-limited conditions. Second, we apply the model to a portion of the Namche Barwa massif in eastern Tibet and compare simulated and observed landslide magnitude–frequency and area–volume scaling relationships. Finally, we illustrate the relevance of explicitly simulating landsliding and sediment dynamics over longer timescales for landscape evolution in general and river dynamics in particular. With HyLands we provide a new tool to understand both the long- and short-term coupling between stochastic hillslope processes, river incision and source-to-sink sediment dynamics.

Fluvial piracies in the NE sector of the Sierra de Aconquija (Tafí Valley, NW Argentina)

The Sierra de Aconquija is a recently uplifted mountain chain in NW Argentina. The NE side of the sierra is drained by the Muñoz and Los Alisos rivers – whose base level is the Las Carreras Depression that is located to the SW of the Tafí valley. Two of the major headwaters of the Muñoz River suffered during its Holocene development from piracy by the Los Alisos River. These piracies had important consequences on the size of both basins and the functioning of their alluvial fans. The main causes of the captures were changes in river dynamics during Lateglacial and Holocene glacial events. Neotectonic activation does not seem to be the most determining factor, although there are active Holocene faults nearby (Las Carreras Fault 2). Geomorphological and human occupation data recovered from the alluvial fans enables us to estimate that the most recent capture was produced during the Late Holocene.