Comparison of the Damaged Area Caused by an Agricultural Dam-Break Flood Wave Using HEC-RAS and UAV Surveying

This study examines the usability of unmanned aerial vehicle (UAV) data surveyed just after an agricultural reservoir collapse by comparing the survey results with the simulation results of the HEC-RAS (Hydrologic Engineering Centers River Analysis System) flood wave propagation to the downstream areas. A 61,400 m3 storage dam broken by 89.0 mm (over 30.0 mm/hr rainfall intensity) of rainfall on August 21st, 2014 was considered. The reservoir water capacity curve and downstream damaged areas were estimated by drone surveying 3 days after the dam break. The flood wave by the overtopped dam break was propagated using the HEC-HMS (Hydrologic Engineering Centers Hydrological Modeling System) reservoir inflow from the watershed. The model results showed flood inundation depths of 0.1 to 2.2 m, mainly in rice paddy areas along the stream, and the overtopped dam-break scenario exhibited 59% correspondence with the drone-surveyed areas.

section_content: Dam break is a serious devastating disaster that occurs around the world and causes large amounts of damage to people worldwide [1]. In South Korea, there are 17,531 agricultural reservoirs, with 88. 4%, 9. 1%, and 2. 5% having storage capacities of less than 0. 1 million m 3, between 0. 1 and 1. 0 million m 3, and over 1. 0 million m 3, respectively. These reservoirs now hold 55% of the irrigation water among the total supply to 447,000 ha, with a total capacity of 2. 78 billion m 3. damaged areas estimated using many approaches. Carling et al. [2] conducted dam-breach modeling with 1-and 2-dimensional hydraulic models that were specially developed for ice dam failures via piping and overtopping. Sarhadi et al. [3] presented a methodology to assess floodplain mapping at ungauged rivers via 1-dimensional hydraulic inundation modeling. They used high-resolution digital terrain models (DTMs), land use characteristics, and channel properties to identify the critical and vulnerable areas affected by floods in different return periods. You et al. [1] reviewed earth-rock dam safety using high-resolution digital surface model (DSM) data. Evangelista et al. [4] presented the application of a multi-stage first-order centered scheme GMUSTA (Generalized MUlti STAge) to solve a two-phase flow model with four equations. Prakash et al. [5] attempted to simulate the impact of dam-wall failure scenarios using the Smoothed Particle Hydrodynamics (SPH) method on flood inundation, including modeling of dam-wall fragments. 

The prediction of flood magnitude at ungauged reaches is an important task in designing river engineering and hydraulic structures and remains a fundamental challenge for hydrologists [6]. Although considerable research has been conducted based on available information for dam-break problems, the lack of data from ungauged regions still remains an issue in providing accurate predictions of flood magnitude, which is a key factor for reliable flood inundation mapping [3]. The most important data required to perform hydrologic and hydraulic dam-break simulations relate to the topographic relationship between the reservoir water level and storage and the cross sections of the stream, including protected lowlands. 

A high-resolution DTM or DSM is critical to extract the details of the channel topography, obtain the water surface elevations at the cross sections, and simulate flood inundation and depth [3] [7]. Many studies have considered the HEC-RAS (Hydrologic Engineering Centers River Analysis System) performance by high-resolution DSM extracted from new data sources, such as Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) data [8] - [13]. In addition to these various studies, the unmanned aerial vehicle (UAV) remote sensing is an easy and increasingly popular approach to obtain high-quality terrain data. The UAV, also known as a drone, is an aircraft combined with a ground control station and communication support equipment that is flown without a pilot on board and can be remote controlled automatically or semi-automatically by using preprocessed programs or artificial intelligence. 

Recently, many studies on dam break have been performed, with the resulting damaged areas estimated using many approaches.
section_name: Introduction

section_name: Materials and Methods

section_content: The broken dam is located in the southeastern part of South Korea, with a latitude and longitude of 35. 895˚N and 128. 96˚E, respectively. The Goeyeon reservoir dam was built in 1945 for rice paddy irrigation water supply to the downstream area. The dam was broken by the 92. 6 mm rainfall event with over 30 mm/hr rainfall intensity in August 21 st, 2014 after reaching the maximum water level to the bank top. The cause of reservoir collapse was predicted as overtopping by the rain storm, but was not certain with piping possibility. Figure 1 shows the location of the reservoir, the part of the broken dam, and the cut section of the bank. Figure 2 shows the GIS input data of the upper watershed of the reservoir for the HEC-HMS modeling.
section_name: Study Area and Input Data

section_content: A rotary-wing drone of 3. 5 kg weight carried with the Sony NEX-5T sensors was used to acquire the image data (Figure 3 ). It has 4 cm by 4 cm spatial resolution with JPEG image format. Table 1 shows the specification of the drone. The autopilot flight was applied by the inertial measurement unit (IMU) and onboard GPS. The integration of sensors with IMU and GPS enabled to obtain the geo-referenced images. For post-processing, the DSM was produced by the terra In order to orient and relate the drone images to the ground, twenty GCPs (Ground Control Points) were investigated and four checking points were arranged for uniform horizontal and vertical accuracy. With 60% end laps as well as 60% side laps, the drone routed two times for 0. 43 km 2 areas with total 338 images of first 153 images and second 185 images respectively. In this study, calibrated and validated UVA geospatial data obtained from the Korea Rural Development Administration (KRDA). Details regarding the estimation process of the UVA geospatial data can be found in Park and Park [18].
section_name: UAV Specification and Imaging Process

section_content: HEC-HMS and HEC-RAS were used to develop the dam break and inundation modeling. Numerous previous studies have shown these models to provide accurate and useful results in flood-related studies [19] [20]. 

The watershed runoff to reservoir was modeled using HEC-HMS. 

( )

where Q is the runoff, P is the rainfall, S is the maximum potential reten- The flood wave is calculated by the following kinematic wave equation and watershed parameters (K, T c ) are calculated by Kraven and Sabol equations. 

where Q is the flow discharge (m 3 /s), i V is the average velocity at cross-section i (m/s), i A is the area at cross-section i (m 2 ), R is the hydraulic radius (m), n is Manning's roughness coefficient, C is the conveyance (m 5/3 ), f S is the av- erage friction slope between adjacent cross-sections, A is the watershed area (km 2 ), L is the river length (km), S is the watershed slope, K is the storage constant (hr) from Kraven equation, and c T is the concentration time (hr) from Sabol equation.
section_name: HEC-HMS and HEC-RAS Model Theory

section_content: The dam break was established using HEC-HMS, developed by the US Army Corps of Engineers. HEC-HMS allows the modeler to choose two different methods for computing outflow through two dam-breach options: overtopping and piping. 

Two cases were applied in this study because the break cause was unknown. 

The 'overtopping dam break' is designed to represent failures caused by overtopping of the dam. This failure is most common in earthen dams but may also If a sufficient amount of material erodes, then a direct piping connection may be established from the reservoir water to the dam face. Once such a piping connection is formed, it is almost impossible to stop the dam from failing. The method begins the failure at a point in the dam face and expands it as a circular opening. When the opening reaches the top of the dam, it continues expanding as a trapezoidal shape. The flow through the circular opening is modeled as orifice flow, whereas it is modeled as weir flow in the second stage [22]. 

To apply dam break model, we need information on the collapse width, slope, and shape for collapse duration, cause of collapse, inflow hydrograph, and downstream cross section. The Goeyeon reservoir is a small reservoir and has no specifications related to the reservoir.
section_name: Dam-Break Simulation Using HEC-HMS

section_content: The one-dimensional hydraulic model of HEC-RAS is widely and commonly used to analyze the water surface profile, flow characteristics, and hydraulic structure. HEC-RAS computes the water surface elevation and velocity at successive cross-sections by solving continuity, energy, and flow resistance equations in a scheme called the standard step-backwater method [3] [23]. In this study, the excess water from the broken dam calculated by HEC-HMS was applied to HEC-RAS as a boundary condition, and the flood inundation map was visualized using the HEC-GeoRAS module, the extended module of ArcView and ArcMap and developed by Hydrologic Engineering Center of U. S. Army

Corps of Engineers and ESRI (Environmental Systems Research Institute). The basic structural dam information, watershed-and reservoir-related data, and downstream topographic data were collected from a national [24]. Figure 5 shows the flowchart of the study.
section_name: Dam-Break Simulation Using HEC-HMS

section_content: Using UAV images taken by Park and Park [18] to create accurate topographic and flood trace maps. In addition, we created a precise topographic map by using Google images before the collapse of the reservoir. These two topographical maps (Figure 6 (b)) were used to compare and analyze the situation before and after the collapse of the reservoir. In particular, the elevation-storage curve was calculated via the DSM using Equations (( 8 ) and ( 9 )) (Figure 7 and Figure 8 ). 

The UAV reservoir terrain detection was possible because the land surface was exposed by the dam break. In this study, the relationship between the reservoir surface area and the reservoir storage was derived by using the DSM from UAV image, Equation (10), and Equation ( 11 ) (Figure 8 ). 

( ) width × 1 m depth), the depth value of cell is equal to its volume. 

The reported irrigation area of the reservoir is 125 ha and the effective storage capacity is 61,000 m 3. Because of the lack of basic data such as dam minimum and maximum water levels in reservoir, we estimated water level in reservoir using accurate topographic map. The estimates of the topographic maps are overestimated. In order to calibrate this, we have derived the water level-water surface relation by setting the reported effective storage capacity of 61,000 m 3 to the maximum water level. As a result, the minimum water level is EL. 176. 77 m. 

The area and the storage capacity of each water level are shown in Table 3 and Figure 8. The estimated relationship between reservoir elevation-area-volume a graph using drone derived DSM.
section_name: Digital Surface Model and Elevation-Storage Curve: UAV Observations

section_name: Results and Discussion

section_content: Calibration of the model with appropriate data is a crucial step in the creation of a reliable basin representation. Watershed parameters such as infiltration coefficients, time of concentration, and baseflow may need modification to produce a best fit between model and observations. However, this study watershed as ungagged watershed has not directly measured runoff at reach or reservoir inflow. 

So, watershed parameters such as CN, K, TC were calculated from Equations ( were adjusted using actual flood map from UAV images. Table 4 shows the final watershed parameters and watershed characteristics.
section_name: Calibration of Watershed Parameters in Ungagged Watershed from HEC-HMS

section_content: Figure 9 shows the discharge of water with 2 dam-break scenarios; (a) overtopping and (b) piping. According to the national hazard investigation report [24],

the initial reservoir water level was set to 98% of full water level. The duration time of dam failure was set to 30 min. Under the condition of maximum 61,400 m 3 reservoir storage amount pouring to the downstream area, the peak discharge was up to 107. 9 m 3 /sec by overtopping and 140. 2 m 3 /sec by piping failure, respectively. To calculate the downstream inundation area and depth, HEC-RAS used the HEC-HMS flood wave discharges of Figure 8 as the boundary conditions, and the results were represented by HEC-GeoRAS. Figure 9 shows the estimated flood mapping results with two dam-break scenarios. To evaluate the performance of the model, the F statistic used Equation ( 12 ) to compare the drone and HEC-RAS inundation areas [3] [20] [25]. 

where o A is the UAV observed area of F statistic varies from "100" when observed and predicted areas coincide perfectly to "0" when there is no overlap between the predicted and observed areas. 

The inundation map indicated using UAV is the actual observation data, so it can be seen as flood trace. Two methods were used to evaluate flood inundation according to the collapse runoff of Goeyeon reservoir for the most suitable floodplain. The first is a simple comparison by area, and the second is the comparison of the flood trace using the Lee Sallee Shape Index (LSSI) method. The LSSI method is a method of measuring the degree of agreement between two data by overlapping the reference data with the measurement data [26]. In other words, the intersection area between the two data is divided by the union area, and the value is calculated as the generalized index. The index means indicator that measures the degree of spatial alignment between two data. The reference data in this study is flood trace from UAV and the measured data is each scenario result (Table 5 ). Figure 10 shows the UAV observed damaged areas with For overtopping dam break, the flood depth ranged from 0. 1 to 2. 2 m after the peak discharge of 15 -20 mins. As seen in Figure 10, the piping dam-break scenario simulated more inundation areas especially in the middle of the downstream area as the peak discharge was 32. 3 m 3 /sec higher than that in the overtopping scenario. Thus, we can infer that the dam would be broken by overtopping phenomenon. Looking at the areas between UAV and overtopping damaged areas, the difference increased at the end of downstream area. The errors may come from the road location crossing the stream at the end of downstream and the flood discharges along the roads. Otherwise, there is a possibility that the rice paddies at the downstream areas were inundated but they were not damaged by the flood wave attenuation.
section_name: HEC-HMS Dam Breach and HEC-RAS Inundation Modeling

section_content: In this study, the flood-damaged areas caused by a dam-break accident were investigated using a UAV, and the collected data were compared with the HEC-RAS simulation results. For a small agricultural reservoir of 61,400 m 3 water storage broken by 89. 0 mm rainfall event in August 21 st, 2014, the 2 dam-break scenarios of overtopping and piping were tested. To estimate the HEC-HMS parameters for the elevation-storage relationship of the reservoir, the high-resolution DSM was collected from drone surveying. The dam-break results by HEC-HMS were transferred to the HEC-RAS as the boundary conditions, and the flood areas and depth were expressed by using the HEC-GeoRAS module over the DSM map. 

The peak discharges for overtopping and piping failure were 107. 9 m 3 /sec and 140. 2 m 3 /sec, respectively, with flood inundation depths of 0. 1 -2. 2 m in the downstream area. From the distribution of the inundation areas from each dam-break scenario, we could infer that the dam was broken by the overtopping phenomenon. The discordance between the areas increased when it goes to the downstream area. The paddy rice near the dam was lodged by the fast velocity of the flood wave, but the far-downstream rice was less affected by the attenuated flood wave and recovered after drainage. In addition, the UAV surveying proved to be a valuable tool for the identification of flood-damaged areas and for economic loss evaluation. 

The result of the dam-break in this study showed that the reservoir collapsed by overtopping. Overall, we proposed the application method of UAV data in ungagged area such as small reservoir watershed. The result from this study can be used to predict the risk of collapse of old and small reservoirs. Therefore, small and old reservoirs must once again make a safety review in ungagged area where flooding has occurred in the past using UAV and modeling to prevent reservoir collapse. Then, action plan is provided for each reservoir level.
section_name: Summary and Conclusions

section_name: Acknowledgements

section_content: This research was supported by a grant ( 17AWMP-B079625-04 ) from the Water Management Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government.
section_name: Acknowledgements