Comparison of Riverbed Changes between Sediment Budget Analysis with Measured Data and River Survey: Case Application to Part of Geumgang

Sediment measurement data are utilized as basic data for various river plans and research. The aim of this study is to compare between sediment budget analysis and riverbed monitoring results. The spatial range was from the Gongju-si (Gemganggyo) station to the Buyeo-gun (Baekjegyo) station in Geumgang, and the temporal range in this study was from 2011 to 2016. The estimated change in riverbed amount using the sediment budget analysis was 2,430,243 tons for sediments loaded over six years in the section. The analyzed riverbed changes sedimentation using the riverbed monitoring method were 2,165,146 tons based on the low level and 3,055,489 tons based on the flood level. Based on the riverbed monitoring performance, the relative errors in the sediment budget analysis results through sediment measurements were 10.9% and -25.7% for the low water and flood levels, respectively.

Analyzing the Application of X-Band Radar for Improving Rainfall Observation and Flood Forecasting in Yeongdong, South Korea

The mountainous Yeongdong region of South Korea contains mountains over 1 km. Owing to this topographic blockage, the region has a low-density rain-gauge network, and there is a low-altitude (~1.5 km) observation gap with the nearest large S-band radar. The Korean government installed an X-band dual-polarization radar in 2019 to improve rainfall observations and to prevent hydrological disasters in the Yeongdong region. The present study analyzed rainfall estimates using the newly installed X-band radar to evaluate its hydrological applicability. The rainfall was estimated using a distributed specific differential phase-based technique for a high-resolution 75 m grid. Comparison of the rainfall estimates of the X-band radar and the existing rainfall information showed that the X-band radar was less likely to underestimate rainfall compared to the S-band radar. The accuracy was particularly high within a 10 km observation radius. To evaluate the hydrological applicability of X-band radar rainfall estimates, this study developed a rain-based flood forecasting method—the flow nomograph—for the Samcheok-osib stream, which is vulnerable to heavy rain and resultant floods. This graph represents the flood risk level determined by hydrological–hydraulic modeling with various rainfall scenarios. Rainfall information (X-band radar, S-band radar, ground rain gauge) was applied as input to the flow nomograph to predict the flood level of the stream. Only the X-band radar could accurately predict the actual high-risk increase in the water level for all studied rainfall events.

The Evaluation of Failure Structure Condition with Plaxis Program on the Poso I Hydropower Barrage

The Poso I Hydropower Station is located on the Poso River, at the downstream section of the Poso Lake in Central Sulawesi Province. At the weir site, the catchment area is 1906.30 km2, and the structures are designed for a 50 year return period. Flood discharge is 1456.50 m3/s, with the mean annual release being 127.85 m3/s. The total supply water level is 510.50m, and the minimum operating level is 506.00 m. The model uses an undistorted model with a scale of 1 to 60. The barrage needs to be reviewed for failure factors that are likely to occur similar to those used in potential failures in the construction of dams in general. The study was considered in three conditions: empty barrage condition, average level, and flood level. With the piping calculation method, the barrage used Lane and Bligh method. While the calculation of barrage sliding stability used Finite Element Method with Plaxis 2D program simulation got the safety factor at the empty condition and flood level. It is caused by water pressure at flood level conditions that influence barrage stability. Safety factor value exceeded permits made. The Poso I Hydropower Station was safe.

Dependence of floodplain birds’ dynamics on the spring flood height and duration in the middle Ob River

Inter-annual variations in the total number of birds in floodplains of rivers are mainly associated with their flooding. The minimum population density during the nesting period was in a year with high and prolonged spring floods. The restoration and maximum development of shrubs took place with a significant simultaneous increase in the abundance of birds in subsequent years. Drying and simplification of vegetation cover were noted in all floodplain bird habitats during low-water periods. This process was accompanied by a decline in the number of birds. We identified four groups of bird species according to the criterion of the relationship “abundance – level and duration of the flood”. In the first group of bird species, abundance increased during high floods (3 species). In the second group, the abundance decreased sharply during high and prolonged floods (7 species). In the third group, the level and duration of the spring flood did not affect the abundance (9 species). In the fourth group, a very weak tendency of the negative flood level impact on the abundance of birds was noted (6 species).

Positive Changes in Flood Mitigation Through Sand Dredging Works at Padas River and Tributary Based on HEC-RAS Hydrological Modelling

In the recent years, the impacts of floods have gained importance because of the increasing number of people who are affected by its adverse effects, especially in Beaufort area, Sabah, Malaysia. Flood destroyed critical infrastructures that are needed as shelter and also emergency relief for victim. This paper presents the findings of flood modelling undertaken to establish baseline and post mining flooding conditions during upstream storm and combination of upstream and downstream storm, respectively. A hydrologic model was established and calibrated based on 2014 flood. A structural approach by changing the physical dimension through dredging or sand mining between 2m to 3m is used for hydrology modelling is added into the existing floodgates and bunds. The outcome from sustainable sand is prevailing when it is able to reduce flood level for normal flow, upstream case, and both upstream and downstream case. Other findings are changes in velocity, shear and the significantly reduced power generated by the river during flooding.

Early Flood and Victim Detection

Thousands of people die because of earthquake and sometimes because of Tsunamis. The resulting damage can be minimized and lives can be saved if people living in the earthquake- tsunami prone area are already prepared to survive the strike. The warning systems can reduce the losses, by alerting people and monitors rising water in residential areas and fastest method to monitor flood that will help motorists or road user to avoid problem when flood occurred. Flood is an unavoidable natural disaster across the world, causing heavy flow of traffic and can also cause severe damage to properties and lives. For this reason, we created a flood detection system to monitor rising water level, flow rate and the rainfall density in residential areas. Using ultrasonic sensor, we created flood level sensing device which is attached to Node MCU controller to process the sensor’s analog signal into a usable digital value of distance. Each node will update its information in regular intervals and data stored in the Blynk application. Flood height is determined by subtracting the sensor’s height with respect to the floor minus the sensed distance between the sensor and the flood water. Natural disasters can cause losses, both assets and objects can even take lives. Convolutional Neural Network is one of the developments of Artificial Neural Networks for image classification, image segmentation, and object recognition with high accuracy and high performance. Convolutional Neural Network can learn to detect various images according to images from the dataset studied. The user can get real-time information on monitoring floods and victim detection over SMS based service. So to reduce the number of losses, the System is designed for detecting victims of natural disasters using the CNN method.

Quantifying Sediment Deposition Volume in Vegetated Areas with UAV Data

Floods are frequent hydro-meteorological hazards which cause losses in many parts of the world. In hilly and mountainous environments, floods often contain sediments which are derived from mass movements and soil erosion. The deposited sediments cause significant direct damage, and indirect costs of clean-up and sediment removal. The quantification of these sediment-related costs is still a major challenge and few multi-hazard risk studies take this into account. This research is an attempt to quantify sediment deposition caused by extreme weather events in tropical regions. The research was carried out on the heavily forested volcanic island of Dominica, which was impacted by Hurricane Maria in September 2017. The intense rainfall caused soil erosion, landslides, debris flows, and flash floods resulting in a massive amount of sediments being deposited in the river channels and alluvial fan, where most settlements are located. The overall damages and losses were approximately USD 1.3 billion, USD 92 million of which relates to the cost for removing sediments. The deposition height and extent were determined by calculating the difference in elevation using pre- and post-event Unmanned Aerial Vehicle (UAV) data and additional Light Detection and Raging (LiDAR) data. This provided deposition volumes of approximately 41 and 21 (103 m3) for the two study sites. For verification, the maximum flood level was simulated using trend interpolation of the flood margins and the Digital Terrain Model (DTM) was subtracted from it to obtain flooding depth, which indicates the maximum deposition height. The sediment deposition height was also measured in the field for a number of points for verification. The methods were applied in two sites and the results were compared. We investigated the strengths and weaknesses of direct sediment observations, and analyzed the uncertainty of sediment volume estimates by DTM/DSM differencing. The study concludes that the use of pre- and post-event UAV data in heavily vegetated tropical areas leads to a high level of uncertainty in the estimated volume of sediments.

Ecological and hydrological considerations for climber weed control in freshwater forested wetland restoration project on the Gulf of Mexico

Two herbaceous Ipomoea climbers grow over trees planted to restore a freshwater forested wetland in the Gulf of Mexico, causing high tree mortality and limiting restoration success. To better control these species, we evaluated their potential for biomass accumulation and regeneration following removal. We simulated the tree-climber relationship in a field experiment by varying light conditions and trellis availability, and by cutting aerial biomass. We also considered the spatial variability of the wetland’s flood level. Ipomoea tiliacea accumulated more biomass at low flood levels, while Ipomoea indica accumulated more biomass at higher flood levels. Despite this, I. tiliacea accumulated more biomass over the entire flood level gradient and the highest flood levels seem to prevent regeneration in both species. There was no vine seed germination, so for both species, regeneration relied on shoot production. I. tiliacea increased its growth more than I. indica when trellises were available, even under shade. It means that that restoration conditions favor I. tiliacea, which makes its management specially challenging. We recommend characterizing hydrology of the site under restoration to design more effective Ipomoea control strategies. Future efforts to restore this forested freshwater wetland should select areas with the highest flood levels, where I. tiliacea growth is limited, ensuring that the trees to be planted can withstand the flood levels. Removal should be avoided during the dry season, when low flood levels favor regeneration in both species.

A catastrophic multi-hazard event in 2020 in Kali Gandaki valley, Nepal Himalaya

<p>Multiple hazards (e.g. floods, landslides, earthquakes, glacial and landslide lake outburst floods) are threatening people, their goods and infrastructures in the high mountains of Nepal Himalaya. Floods and landslides are mainly driven by monsoonal precipitation. However, human impact often increases natural risks, like in the Kali Gandaki (KG) valley, the deepest valley (>5500 m) on earth, where the new two-lane road construction (since 2017) has caused many undercut and instable slopes.</p><p>In the light of previous events, we intend to assess the cascading multi-hazard events of 2020 in three tributary catchments of KG.</p><p>We adopted a pluri-disciplinary approach: interpretation of Sentinel-2 satellite images (March and November 2020), analysis of precipitation (stations of Lete and Tatopani, GPM satellite precipitation measurements), hydrologic and seismic data (Beni), geomorphological mapping, hydrological modelling in HEC-RAS, and field visits in July and November 2020, including interviews with locals.</p><p>On 20 July 2020 major hyper-concentrated flood events and landslides occurred in the Rupse, Thaplyang and Kahiku catchments (between Tatopani and Lete) destroying parts of the KG road, road bridges and a hotel (Rupse site). We focus on the Rupse River entering the KG valley at Rupse waterfall (height 108 m; kyanitic gneisses) then flowing down to the KG road and to KG River 200 m below. The major flood event lasted two hours and reached a max. flood level of 35 m at the edge of the waterfall. Upstream of the waterfall, four landslides (each about 250m wide, 200 m high) were triggered. Due to cloud coverage satellite scenes are missing to unravel whether the landslides caused the damming of the river and a landslide lake outburst flood or if the landslides were mainly triggered by the flood and increased sediment input to it.</p><p>Floods from these tributary catchments caused a major KG flood especially south of the Rupse catchment, which led to severe erosion and sedimentation in the channel; i.e. destruction of a pole of the national electricity grid, reactivation of the Kham Bhitta deep-seated landslide, destruction of the KG road (the construction of which probably contributed to this reactivation). <br>Seismic data from Beni, approximately 27 km downstream of the affected catchments, provide constraints on the timing and relative magnitude of the flood in the KG. The data show that a short duration high magnitude flood with a very rapid rise and recession passed through Beni on the afternoon of 20 July. In addition, station data of Lete and Tatopani shows that yearly rainfall totals of 1839.5 and 2140.2 mm, respectively, were the highest since 1970. March and April were already very wet, followed by extremely monthly rainfall totals of 499.7 mm and 551.5 mm at Lete and Tatopani, respectively.</p><p>Assessing the 2020 events demonstrates how important localized events in relatively small areas are to understand cascading multi-hazard processes in Himalayan mountain regions. In addition, such hydro-geomorphic functioning and related hazards should be carefully considered when planning road design and bridge sites together with landslide and water level monitoring, for a better traffic maintenance and safety.</p>