Debris flows and debris floods occurrence in the Ribnishka River watershed (southern slopes of Ograzhden Mountain)

The Ribnishka River watershed, located on the southern slopes of Ograzhden Mountain is known for the repeated torrential events in the last few decades. In this paper, we represent a preliminary assessment of the debris floods and debris flows hazard in the Ribnishka River watershed. For this purpose, the topographic conditions in the watershed are considered, the source, transport, and deposition zones are characterized, as well as the observed sediment deposits in the river valley. The obtained results could be used in the development of risk management plans, but also provide new information on the development of debris floods and debris flows in this part of the country.

Riverbed Erosion Analysis of Winongo River Using HEC-RAS 5.0.7

Winongo River originates from small rivers on the slopes of Mount Merapi. This creates potential debris floods that will carry material such as sand and gravel, which can cause erosion and sedimentation in rivers. Riverbed erosion is the process of transporting materials on the riverbed that causing the elevation on the riverbed to fall. If the riverbed elevation decreases, it will cause the retaining wall building to become unstable and collaps. If this happens, it will have a negative impact on the people who live along the riverbanks. The impact of erosion and erosion analysis at the bottom of Winongo River is carried out using HEC-RAS 5.0.7. There are 200 cross-sections that had been analyzed. The analysis reveals that the locations have the potential of erosion on the riverbed and the damage that can occur in the riverbank. From the results of the analysis that have been carried out using the 2-year return period (Q2), there are erosion in 9 cross-sections on Winongo River which is located in Bambanglipuro District and Jl. Parangtritis. The depth of erosion that occurs reaches 0.96 m in the cross-section WN 173. The erosion causes damage to the retaining wall, such as cracks, flattening, and collaps.

Determining the Precipitation Intensity Threshold of Debris Flood Occurrence

In this chapter, the precipitation threshold at which debris floods occur was evaluated experimentally, and the factors that influence debris flood occurrence, including the bed slope, sediment layer thickness, sediment grain size, length of alluvial flow direction, precipitation intensity, and time of debris flood occurrence, were examined. The impacts of these factors on debris flood initiation were investigated through dimensional analysis. Then, a method was developed to estimate the precipitation intensity threshold based on a set of laboratory tests. Furthermore, different methods for determining the precipitation intensity threshold at which debris floods are initiated were assessed and discussed. The results of the experiments showed that the effect of the sediment layer thickness on debris flood occurrence can be ignored. Moreover, by independently evaluating the effect of each factor on debris flood occurrence, it was found that the sediment length and average diameter of sediments are influential to debris flood initiation. The results of this research provide a better understanding of debris flood mechanisms and occurrence thresholds of debris floods and can be employed to prepare a forecasting model.

Sediment-water flows in mountain catchments: Variability in response to high-magnitude hydrological events

<p>Sediment transfer in mountain streams occurs by processes classified as debris flows, hyperconcentrated flows, debris floods, and water flows. One of the most important tasks in investigating floods in mountain catchments is to identify the transport mechanisms since different sediment-water flows induce peculiar geomorphological dynamics and hazards. This study aims at testing how the energy of water and the amount of sediment involved during a high-magnitude hydrological event can modify the mechanisms of sediment transfer with respect to those occurring during ordinary floods.</p><p>The selected case study is the Tegnas catchment (Dolomites, Italy), which, in October 2018, was affected by a severe hydrological event (Vaia Storm) with a recurrence interval of about 200 years. The studied catchment drains an area of 51 km<sup>2</sup>, with a range in elevation between 2872 and 620 m a.s.l.. The classification of flows that occurred during the Vaia storm was addressed at the sub-reach scale applying a field survey protocol developed to classify the flood deposits based on their sedimentological and morphological features. Following the same approach, we also determined the flow types typifying the stream network during ordinary floods. Additionally, we considered flows predicted by three morphometric approaches for high-magnitude events, and took into account the geomorphological dynamics (e.g., channel changes) and the hydraulic constraints (i.e., unit stream power) that occurred during the Vaia storm.</p><p>Water flow was the dominant process during Vaia storm in the Tegnas main steam (12 sub-reaches), although debris flow and debris flood deposits were documented at 3 and 7 sub-reaches, respectively. Water flow was observed in response to ordinary events along the entire Tegnas Torrent. Most of the steep tributaries were affected by debris flows (6 tributaries), but also debris floods were recognized at 3 steep channels. The morphometric approaches had a satisfactory performance in predicting the two end-member flows, but often failed in recognizing sub-reaches affected by debris floods.</p><p>The comparison between the occurred high-magnitude flows, and the ordinary flows allowed us to infer the existence of relationships between the transport mechanisms, the hydraulic forcing, and channel dynamics. The upheaval of the ordinary flow types did not occur along the entire stream network. The transition from water flows to debris floods occurred for unit stream powers exceeding the threshold of 5000-6000 Wm<sup>-2</sup> or downstream of a channel delivering a large amount of sediment mobilized by debris flow to the receiving stream. The occurrence of debris floods, causing higher channel widening than water flows, appears to be facilitated by the injection of fine material into the flow, which can occur as consequence of channel-bank erosion and overbank floodwater re-entering the channel. Finally, morphometric approaches turned out to be adequate to provide a first-order discrimination of expectable high-magnitude flow types. However, the complex relationships found between flow types and a range of hydraulic, morphological, and geological controlling factors, reveal that a more detailed characterization is necessary for understanding the transport mechanisms and predicting geomorphic hazard that can affect specific channel sites during high-magnitude to extreme hydrological events.</p>

Historical Landslide Fatalities in British Columbia, Canada: Trends and Implications for Risk Management

According to a Canadian government database, landslides are the most common type of disaster that occurs in the province of British Columbia. Recently there has been a trend in British Columbia toward using quantitative risk assessments to estimate life-loss risk at landslide hazard sites, and to compare these estimates with risk tolerance thresholds to determine the necessity for, and extent of, risk management measures. These risk estimates are most often calibrated by so-called ‘expert judgment’ because historical landslide fatality data are not readily available. This article addresses this gap by summarizing available historical data to better inform expert judgment. It shows that fatalities caused by landslides in British Columbia are rare (approximately one fatality per year in the last decade) and have decreased with time despite rapid population growth. Approximately half of these fatalities in the last decade are related to debris flows and debris floods that impact houses, whereas the other half are related to rockfalls, debris flows, and debris floods that impact highways. A comparison with other hazard types in the Canadian government’s disaster database suggests that, while not particularly deadly, landslides are still important because of the economic damage and service disruptions they cause. Although the data are specific to British Columbia, the methods for identifying and presenting landslide risk trends could be modified and adopted in other world regions where landslide fatality data are collected and quantitative risk management methods are utilized.

A Hybrid Intelligence Model for the Prediction of the Peak Flow of Debris Floods

Debris floods, as one of the most significant natural hazards, often threaten the lives and property of many people worldwide. Predicting models are essential for flood warning systems to minimize casualties of debris floods. Since HEC-HMS (Hydrologic Engineering Center’s Hydrological Modelling System) cannot simulate debris flow, this study proposes a new hybrid model that uses artificial intelligence models to overcome HEC-HMS’s insufficiency in reflecting the sediment concentration effect on the debris floods. A sediment concentration is an effective factor for evaluating debris flood peak flows. This led to the proposal of new hybrid models for predicting the debris flood peak flows on the basis of hybridization of the artificial intelligence models (Bayesian Network (BN) and Support Vector Regression–Particle Swarm Optimization (SVR-PSO)) and HEC-HMS. To estimate the sediment concentration of floods by using the proposed artificial intelligence models, we nominated an average basin elevation, an average basin slope, a basin area, the current day rainfall, the antecedent rainfall of the past 3 days, and the streamflow of the previous day the previous day as the effective variables. In the validation stage, the average of the Mean Absolute Relative Error (MARE) of the estimated values were 0.024, 0.038, and 0.024 for the typical floods that occurred in the Navrood, Kasilian, and the Amameh basins in the north of Iran, respectively. Similarly, we obtained values of 0.038, 0.073, and 0.040 for the debris flood events for the three respective locations. After predicting the debris flood peak flows by the proposed hybrid HMS-BN and HMS-SVR-PSO models, the average of the MAREs for all debris flood events was reduced to 0.013 and 0.014, respectively. The comparison of MAREs of the examined hybrid models shows that the HMS-BN model results in higher accuracy than the HMS-SVR-PSO model in the prediction of the debris flood peak flows. Generally, the absolute error of prediction by the proposed hybrid model is reduced to one-third of the HEC-HMS. The prediction of the debris flood peak flows using the proposed hybrid model can be examined in the debris flood warning systems to reduce the potential damages and casualties in similar basins.