Source areas, connectivity, and delivery rate of sediments in mountainous-forested hillslopes: A probabilistic approach

Changes in hydrological behaviours triggered by earthquake disturbance in a mountainous watershed

Landslides induced by strong earthquakes often destroy large amounts of landscape vegetation which can trigger significant changes in runoff potential and flood flow. Little is known about hydrological behaviours imposed by co-seismic landslides and their post-earthquake evolution. Therefore, we collected time-series datasets (2007-2018) of underlying surface conditions (USC) changes including landslide expansion and recovery in a watershed affected by the Wenchuan earthquake to further quantify how the large physical disturbance affected the flood hydrological behaviours. The hydrological model HEC-HMS was calibrated and validated to predict the historical hydrological behaviours based on 5 min time-series data in rainfalls and streamflow (2018-2019), showing a good model performance with a mean Nash-Sutcliffe efficiency of 0.76. It was found that, shortly after the earthquake, the sharp expansion with 11% of landslide areas elevated the magnitudes of runoff potential, peak discharge, and runoff volume by >10%, and the peak to time for the high-magnitude flood was advanced by 25 min compared to the pre-earthquake levels. The tipping point along the hydrological disturbance-recovery trajectory was detected within 2011 with higher flood peaks and volumes, and the periods of 2011-2013 (i.e. 3-5 years post-earthquake) were deemed to be a rapid recovery period, revealing an unstable hydrological function. These findings are significant for clearly understanding the magnitude and timing, as well as greater risks of post-earthquake catastrophic flooding in earthquake-stricken regions. Additionally, the post-earthquake accompanied rainstorm-induced geohazards, which limited the recovery of landscape vegetation, triggering an undulant but clear recovery process (1-7 years post-earthquake) of hydrological behaviours. These findings promoted our understanding of the spatiotemporal evolution of hydrological behaviours triggered by the earthquake, and further contribute to the development of adaptation and mitigation strategies for the unpredictable flash floods triggered by future abrupt natural hazards in earthquake-affected regions.

Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran

This paper aims to apply and compare the performance of the three machine learning algorithms–support vector machine (SVM), bayesian logistic regression (BLR), and alternating decision tree (ADTree)–to map landslide susceptibility along the mountainous road of the Salavat Abad saddle, Kurdistan province, Iran. We identified 66 shallow landslide locations, based on field surveys, by recording the locations of the landslides by a global position System (GPS), Google Earth imagery and black-and-white aerial photographs (scale 1: 20,000) and 19 landslide conditioning factors, then tested these factors using the information gain ratio (IGR) technique. We checked the validity of the models using statistical metrics, including sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC). We found that, although all three machine learning algorithms yielded excellent performance, the SVM algorithm (AUC = 0.984) slightly outperformed the BLR (AUC = 0.980), and ADTree (AUC = 0.977) algorithms. We observed that not only all three algorithms are useful and effective tools for identifying shallow landslide-prone areas but also the BLR algorithm can be used such as the SVM algorithm as a soft computing benchmark algorithm to check the performance of the models in future.

Three topographical approaches to survey soil erosion on a mountain trail affected by a forest fire. Barranc de la Manesa, Llutxent, Eastern Iberian Peninsula

Soil erosion on mountain trails threaten the sustainability of soils and vegetation. There is a wide theoretical knowledge about the effects produced by mountain recreational activities, but particularly for soil erosion there is a shortage of field data. This is why it is necessary to properly survey the soil losses on mountain trails. The most widely applied method in scientific literature is the Cross-Section field survey as is easy-to-apply and low-cost. However, there is a doubt about its accuracy and the development of the new technologies may improve the quality and accuracy of the measurements. Aerial and terrestrial photogrammetric methods are difficult to apply when vegetation is present but, an opportunity arises to apply this method when fire takes place. This paper analyses the soil losses in a recently fire-affected land to check the accuracy of the three methodologies to assess soil loss on mountain trails. The results obtained show an average soil loss between 1287 and 1404 Mg ha^-1 of trail erosion for the three methodologies applied, which implies that the Cross-Sectional-Area method, aerial photography and terrestrial photography provide very similar values. Therefore, the conventional Cross-Section field surveys method is useful and adequate to evaluate the impacts generated on mountain trails as it provides accurate measurement and can be repeated any time and below different vegetation covers. The terrestrial photogrammetric methods are accurate too, but they can only be used when there is very little vegetation cover such as in semiarid and arid landscapes or after forest fires. Moreover, they are more expensive and time consuming.

2D Runout Modelling of Hillslope Debris Flows, Based on Well-Documented Events in Switzerland

In mountain areas, mass movements, such as hillslope debris flows, pose a serious threat to people and infrastructure, although size and runout distances are often smaller than those of debris avalanches or in-channel-based processes like debris floods or debris flows. Hillslope debris-flow events can be regarded as a unique process that generally can be observed at steep slopes. The delimitation of endangered areas and the implementation of protective measures are therefore an important instrument within the framework of a risk analysis, especially in the densely populated area of the alpine region. Here, two-dimensional runout prediction methods are helpful tools in estimating possible travel lengths and affected areas. However, not many studies focus on 2D runout estimations specifically for hillslope debris-flow processes. Based on data from 19 well-documented hillslope debris-flow events in Switzerland, we performed a systematic evaluation of runout simulations conducted with the software Rapid Mass Movement Simulation: Debris Flow (RAMMS DF)—a program originally developed for runout estimation of debris flows and snow avalanches. RAMMS offers the possibility to use a conventional Voellmy-type shear stress approach to describe the flow resistance as well as to consider cohesive interaction as it occurs in the core of dense flows with low shear rates, like we also expect for hillslope debris-flow processes. The results of our study show a correlation between the back-calculated dry Coulomb friction parameters and the percentage of clay content of the mobilised soils. Considering cohesive interaction, the performance of all simulations was improved in terms of reducing the overestimation of the observed deposition areas. However, the results also indicate that the parameter which accounts for cohesive interaction can neither be related to soil physical properties nor to different saturation conditions.

Mapping water and sediment connectivity

Connectivity has become a key issue in the study of processes acting in hydro-geomorphic systems and has strong implications on the understanding of their behaviour. Given the high complexity of hydro-geomorphic systems and the large variety of the processes controlling the efficiency of water and sediment transfer through a catchment, mapping hydrological and sediment connectivity is fundamental to understand the linkages between different parts of the system and the role played by system configuration, natural landforms and man-made structures in favouring or obstacolating the continuity of runoff and sediment pathways. Furthermore, the analysis of changes on connectivity through time can help to investigate the effect of both natural and anthropic disturbance on water and sediment fluxes and associated processes. This special issue aimed to shed light on the latest advances inmapping water and sediment connectivity by means of field measurements, modelling and geomorphometric approaches along with quantitative methods for the analysis of connectivity temporal evolution.The special issue is composed of twenty-one papers presenting a huge variety of topics dealing with hydrological and sediment connectivity and their changes through time in different geographical andclimatic regions of the world, at different spatial and temporal scales. This special issue highlights the importance of connectivity assessment to properly address sediment and water-related issues and to improve management strategies in hydro-geomorphic systems.