Combining TRIGRS and Massflow Models for the Assessment of Flash Flood Disasters Related to Sediment Supply in Mountainous Watersheds

2021 ◽  
Author(s):  
Tong Sun ◽  
Xiekang Wang ◽  
Xufeng Yan
Keyword(s):  
Flash Flood ◽  
Coupling Effect ◽  
Flash Floods ◽  
Sediment Supply ◽  
Landslide Stability ◽  
Sediment Loads ◽  
Flood Disasters ◽  
Mountainous Watersheds ◽  
Mountainous Basin ◽  
Landslide Distribution

<p>Abstract: Evaluation of a large number of rainstorm disasters shows that the coupling effect of sediment supply and floodwaters is one predominant cause for the occurrence of flash flood disasters. Rainfall-induced shallow landslides often provide an adequate source of solid materials to recharge moving sediment during flash floods. In this study, we used the TRIGRS model to analyze the rainfall-related landslide stability in a mountainous basin and gain potential landslide volumes as potential sources for sediment loads. Then, with the calculated results of landslides as input, the Massflow model was used to evaluate how the landslides as sediment loads evolved with flows. The results showed that there was a large amount of sediment deposited in the channel, which can be initiated and transported by heavy rainfalls, leading to the destruction of villages at the mouth of gullies. In general, this study offers a strategy of evaluating sediment-coupled flash flood disasters that the TRIGRS can provides the estimate of landslide distribution and volume first and the Massflow provides the estimate of subsequent movement of the solids caused by flash floods.</p>

scholarly journals Spatiotemporal clustering of flash floods in a changing climate (China, 1950–2015)

2020 ◽  
Author(s):  
Nan Wang ◽  
Luigi Lombardo ◽  
Marj Tonini ◽  
Weiming Cheng ◽  
Liang Guo ◽  
...  
Keyword(s):  
Flash Flood ◽  
Extreme Rainfall ◽  
Flash Floods ◽  
Scan Statistics ◽  
Spatiotemporal Pattern ◽  
Precipitation Trend ◽  
Wet Season ◽  
Extreme Rainfall Events ◽  
Space And Time ◽  
Flood Disasters

Abstract. The persistence over space and time of flash flood disasters – flash floods that have caused either economical or life losses, or both – is a diagnostic measure of areas subjected to hydrological risk. The concept of persistence can be assessed via clustering analyses, performed here to analyse the national inventory of flash flood disasters in China occurred in the period 1950–2015. Specifically, we investigated the spatiotemporal pattern distribution of the flash flood disasters and their clustering behavior by using both global and local methods: the first, based on the Ripley's K-function, and the second on Scan Statistics. As a result, we could visualize patterns of aggregated events, estimate the cluster duration and make assumptions about their evolution over time, also with respect precipitation trend. Due to the large spatial (the whole Chinese territory) and temporal (66 years) scale of the dataset, we were able to capture whether certain clusters gather in specific locations and times, but also whether their magnitude tends to increase or decrease. Overall, the eastern regions in China are much more subjected to flash flood disasters compared to the rest of the country. Detected clusters revealed that these phenomena predominantly occur between July and October, a period coinciding with the wet season in China. The number of detected clusters increases with time, but the associated duration drastically decreases in the recent period. This may indicate a change towards triggering mechanisms which are typical of short-duration extreme rainfall events. Finally, being flash flood disasters directly linked to precipitation and their extreme realization, we indirectly assessed whether the magnitude of the trigger itself has also varied through space and time, enabling considerations in the context of climatic changes.

scholarly journals Spatiotemporal clustering of flash floods in a changing climate (China, 1950–2015)

2021 ◽  
Vol 21 (7) ◽  
pp. 2109-2124
Author(s):  
Nan Wang ◽  
Luigi Lombardo ◽  
Marj Tonini ◽  
Weiming Cheng ◽  
Liang Guo ◽  
...  
Keyword(s):  
Flash Flood ◽  
Extreme Rainfall ◽  
Flash Floods ◽  
Scan Statistics ◽  
Spatiotemporal Pattern ◽  
Precipitation Trend ◽  
Wet Season ◽  
Extreme Rainfall Events ◽  
Space And Time ◽  
Flood Disasters

Abstract. The persistence over space and time of flash flood disasters – flash floods that have caused either economical losses or loss of life or both – is a diagnostic measure of areas subjected to hydrological risk. The concept of persistence can be assessed via clustering analyses, performed here to analyze the national inventory of flash flood disasters in China that occurred in the period 1950–2015. Specifically, we investigated the spatiotemporal pattern distribution of the flash flood disasters and their clustering behavior by using both global and local methods: the first based on Ripley's K function, and the second on scan statistics. As a result, we could visualize patterns of aggregated events, estimate the cluster duration and make assumptions about their evolution over time, also with respect to the precipitation trend. Due to the large spatial (the whole Chinese territory) and temporal (66 years) scale of the dataset, we were able to capture whether certain clusters gather in specific locations and times but also whether their magnitude tends to increase or decrease. Overall, the eastern regions in China are much more subjected to flash flood disasters compared to the rest of the country. Detected clusters revealed that these phenomena predominantly occur between July and October, a period coinciding with the wet season in China. The number of detected clusters increases with time, but the associated duration drastically decreases in the recent period. This may indicate a change towards triggering mechanisms which are typical of short-duration extreme rainfall events. Finally, being flash flood disasters directly linked to precipitation and their extreme realization, we indirectly assessed whether the magnitude of the trigger itself has also varied through space and time, enabling considerations in the context of climatic change.

scholarly journals A Survey of Remote Sensing and Geographic Information System Applications for Flash Floods

2021 ◽  
Vol 13 (9) ◽  
pp. 1818
Author(s):  
Lisha Ding ◽  
Lei Ma ◽  
Longguo Li ◽  
Chao Liu ◽  
Naiwen Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Flash Flood ◽  
Flash Floods ◽  
Geographic Information ◽  
Flood Disaster ◽  
Future Research ◽  
Time Zone ◽  
Gis Technologies

Flash floods are among the most dangerous natural disasters. As climate change and urbanization advance, an increasing number of people are at risk of flash floods. The application of remote sensing and geographic information system (GIS) technologies in the study of flash floods has increased significantly over the last 20 years. In this paper, more than 200 articles published in the last 20 years are summarized and analyzed. First, a visualization analysis of the literature is performed, including a keyword co-occurrence analysis, time zone chart analysis, keyword burst analysis, and literature co-citation analysis. Then, the application of remote sensing and GIS technologies to flash flood disasters is analyzed in terms of aspects such as flash flood forecasting, flash flood disaster impact assessments, flash flood susceptibility analyses, flash flood risk assessments, and the identification of flash flood disaster risk areas. Finally, the current research status is summarized, and the orientation of future research is also discussed.

Using convection-permitting climate models and a high-resolution distributed hydrological model to assess future changes in Alpine flash floods.

2021 ◽  
Author(s):  
Marjanne Zander ◽  
Pety Viguurs ◽  
Frederiek Sperna Weiland ◽  
Albrecht Weerts
Keyword(s):  
High Resolution ◽  
Natural Hazards ◽  
Climate Models ◽  
Flash Flood ◽  
Regional Climate ◽  
Flash Floods ◽  
Flood Frequency ◽  
Climate Dynamics ◽  
Future Climate ◽  
European Climate

<p>Flash Floods are damaging natural hazards which often occur in the European Alps. Precipitation patterns and intensity may change in a future climate affecting their occurrence and magnitude. For impact studies, flash floods can be difficult to simulate due the complex orography and limited extent & duration of the heavy rainfall events which trigger them. The new generation convection-permitting regional climate models improve the intensity and frequency of heavy precipitation (Ban et al., 2021).</p><p>Therefore, this study combines such simulations with high-resolution distributed hydrological modelling to assess changes in flash flood frequency and occurrence over the Alpine terrain. We use the state-of-the-art Unified Model (Berthou et al., 2018) to drive a high-resolution distributed hydrological wflow_sbm model (e.g. Imhoff et al., 2020) covering most of the Alpine mountain range on an hourly resolution. Simulations of the future climate RCP 8.5 for the end-of-century (2096-2105) and current climate (1998-2007) are compared.</p><p>First, the wflow_sbm model was validated by comparing ERA5 driven simulation with streamflow observations (across Rhone, Rhine, Po, Adige and Danube). Second, the wflow_sbm simulation driven by UM simulation of the current climate was compared to a dataset of historical flood occurrences (Paprotny et al., 2018, Earth Syst. Sci. Data) to validate if the model can accurately simulate the location of the flash floods and to determine a suitable threshold for flash flooding. Finally, the future run was used to asses changes in flash flood frequency and occurrence. Results show an increase in flash flood frequency for the Upper Rhine and Adige catchments. For the Rhone the increase was less pronounced. The locations where the flash floods occur did not change much.</p><p>This research is embedded in the EU H2020 project EUCP (EUropean Climate Prediction system) (https://www.eucp-project.eu/), which aims to support climate adaptation and mitigation decisions for the coming decades by developing a regional climate prediction and projection system based on high-resolution climate models for Europe.</p><p> </p><p>N. Ban, E. Brisson, C. Caillaud, E. Coppola, E. Pichelli, S. Sobolowski, …, M.J. Zander (2021): “The first multi-model ensemble of regional climate simulations at the kilometer-scale resolution, Part I: Evaluation of precipitation”, manuscript accepted for publication in Climate Dynamics.</p><p>S. Berthou, E.J. Kendon, S. C. Chan, N. Ban, D. Leutwyler, C. Schär, and G. Fosser, 2018, “Pan-european climate at convection-permitting scale: a model intercomparison study.” Climate Dynamics, pages 1–25, DOI: 10.1007/s00382-018-4114-6</p><p>Imhoff, R.O., W. van Verseveld, B. van Osnabrugge, A.H. Weerts, 2020. “Scaling point-scale pedotransfer functions parameter estimates for seamless large-domain high-resolution distributed hydrological modelling: An example for the Rhine river.” Water Resources Research, 56. Doi: 10.1029/2019WR026807</p><p>Paprotny, D., Morales Napoles, O., & Jonkman, S. N., 2018. "HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870". Earth System Science Data, 10, 565–581, https://doi.org/10.5194/essd-10-565-2018</p>

scholarly journals Assessment of flash floods taking into account climate change scenarios in the Llobregat River basin

2013 ◽  
Vol 13 (12) ◽  
pp. 3145-3156 ◽  
Author(s):  
M. Velasco ◽  
P. A. Versini ◽  
A. Cabello ◽  
A. Barrera-Escoda
Keyword(s):  
River Basin ◽  
Extreme Events ◽  
Hydrological Model ◽  
Flash Flood ◽  
Flash Floods ◽  
Climate Change Scenarios ◽  
Whole Process ◽  
The Future ◽  
Peak Over Threshold ◽  
Llobregat River

Abstract. Global change may imply important changes in the future occurrence and intensity of extreme events. Climate scenarios characterizing these plausible changes were previously obtained for the Llobregat River basin (NE Spain). This paper presents the implementation of these scenarios in the HBV (Hydrologiska Byråns Vattenbalansavdelning) hydrological model. Then, the expected changes in terms of flash flood occurrence and intensity are assessed for two different sub-basins: the Alt Llobregat and the Anoia (Llobregat River basin). The assessment of future flash floods has been done in terms of the intensity and occurrence of extreme events, using a peak over threshold (POT) analysis. For these two sub-basins, most of the simulated scenarios present an increase of the intensity of the peak discharge values. On the other hand, the future occurrence follows different trends in the two sub-basins: an increase is observed in Alt Llobregat but a decrease occurs in Anoia. Despite the uncertainties that appear in the whole process, the results obtained can shed some light on how future flash floods events may occur.

Spatiotemporal evolution and driving factors of China’s flash flood disasters since 1949

2018 ◽  
Vol 61 (12) ◽  
pp. 1804-1817 ◽  
Author(s):  
Yesen Liu ◽  
Zhenshan Yang ◽  
Yaohuan Huang ◽  
Changjun Liu
Keyword(s):  
Flash Flood ◽  
Driving Factors ◽  
Spatiotemporal Evolution ◽  
Flood Disasters

scholarly journals Geomatic-Based Flood Loss Assessment and Its Application in an Eastern City of China

Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 126
Author(s):  
Youjie Jin ◽  
Jianyun Zhang ◽  
Na Liu ◽  
Chenxi Li ◽  
Guoqing Wang
Keyword(s):  
Spatial Resolution ◽  
Loss Rate ◽  
Flash Flood ◽  
Economic Loss ◽  
Economic Losses ◽  
Risk Level ◽  
Loss Assessment ◽  
Flood Loss ◽  
Flood Disasters

Flash-flood disasters pose a serious threat to lives and property. To meet the increasing demand for refined and rapid assessment on flood loss, this study exploits geomatic technology to integrate multi-source heterogeneous data and put forward the comprehensive risk index (CRI) calculation with the fuzzy comprehensive evaluation (FCE). Based on mathematical correlations between CRIs and actual losses of flood disasters in Weifang City, the direct economic loss rate (DELR) model and the agricultural economic loss rate (AELR) model were developed. The case study shows that the CRI system can accurately reflect the risk level of a flash-flood disaster. Both models are capable of simulating disaster impacts. The results are generally consistent with actual impacts. The quantified economic losses generated from simulation are close to actual losses. The spatial resolution is up to 100 × 100 m. This study provides a loss assessment method with high temporal and spatial resolution, which can quickly assess the loss of rainstorm and flood disasters. The method proposed in this paper, coupled with a case study, provides a reliable reference to loss assessment on flash floods caused disasters and will be helpful to the existing literature.

scholarly journals Designating Appropriate Areas for Determining Potential Rainwater Harvesting in Arid Region Using a GIS-based Multi-criteria Decision Analysis ‏

2021 ◽  
Author(s):  
Mohamed Abd-el-Kader ◽  
Ahmed Elfeky ◽  
Mohamed Saber ◽  
Maged AlHarbi ◽  
abed Alataway
Keyword(s):  
Water Management ◽  
Saudi Arabia ◽  
Decision Analysis ◽  
Rainwater Harvesting ◽  
Flash Flood ◽  
Flood Hazard ◽  
Flash Floods ◽  
Flood Mitigation ◽  
Water Harvesting ◽  
Multi Criteria Decision Analysis

Abstract Flash floods are highly devastating, however there is no effective management for their water in Saudi Arabia, therefore, it is crucial to adopt Rainfall Water Harvesting (RWH) techniques to mitigate the flash floods and manage the available water resources from the infrequent and rare rainfall storms. The goal of this study is to create a potential flood hazard map and a map of suitable locations for RWH in Wadi Nisah, Saudi Arabia for future water management and flood prevention plans and to identify potential areas for rainwater harvesting and dam construction for both a flood mitigation and water harvesting. This research was carried out using a spatiotemporal distributed model based on multi-criteria decision analysis by combining Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision-Making tools (MCDM). The flood hazard mapping criteria were elevation, drainage density, slope, direct runoff depth at 50 years return period, Topographic witness index, and Curve Number, according to the Multi-criteria decision analysis, while the criteria for RWH were Slope, Land cover, Stream order, Lineaments density, and Average of annual max-24hr Rainfall. The weight of each criteria was estimated based on Analytical Hierarchy Process (AHP). In multi-criteria decision analysis, 21.55 % of the total area for Wadi Nisah was classified as extremely dangerous and dangerous; 65.29 % of the total area was classified as moderate; and 13.15 % of the total area was classified as safe and very safe in flash flood hazard classes. Only 15% of Wadi Nisah has a very high potentiality for RWH and 27.7%, 57.31% of the basin has a moderate and a low or extremely low potentiality of RWH, respectively. According to the developed RWH potentiality map, two possible dam sites were proposed. The maximum height of the proposed dams, which corresponded to the cross section of dam locations, ranged from 6.2 to 9 meters; the maximum width of dams ranged from 573.48 to 725 meters; the maximum storage capacity of reservoirs, which corresponded to the distribution of topographic conditions in the surrounding area, ranged from 3976104.499 m3 to 4328509.123 m3; and the maximum surface area of reservoirs ranged from 1268372.625 m2 to 1505825.676.14 m2. These results are highly important for the decision makers for not only flash flood mitigation but also water management in the study area.

scholarly journals Flash Flood Susceptibility Assessment Based on Geodetector, Certainty Factor, and Logistic Regression Analyses in Fujian Province, China

2020 ◽  
Vol 9 (12) ◽  
pp. 748
Author(s):  
Yifan Cao ◽  
Hongliang Jia ◽  
Junnan Xiong ◽  
Weiming Cheng ◽  
Kun Li ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Flash Flood ◽  
Pearson Correlation ◽  
Flash Floods ◽  
Ensemble Model ◽  
Susceptibility Assessment ◽  
Certainty Factor ◽  
Fujian Province ◽  
Flood Susceptibility ◽  
Susceptibility Maps

Flash floods are one of the most frequent natural disasters in Fujian Province, China, and they seriously threaten the safety of infrastructure, natural ecosystems, and human life. Thus, recognition of possible flash flood locations and exploitation of more precise flash flood susceptibility maps are crucial to appropriate flash flood management in Fujian. Based on this objective, in this study, we developed a new method of flash flood susceptibility assessment. First, we utilized double standards, including the Pearson correlation coefficient (PCC) and Geodetector to screen the assessment indicator. Second, in order to consider the weight of each classification of indicator and the weights of the indicators simultaneously, we used the ensemble model of the certainty factor (CF) and logistic regression (LR) to establish a frame for the flash flood susceptibility assessment. Ultimately, we used this ensemble model (CF-LR), the standalone CF model, and the standalone LR model to prepare flash flood susceptibility maps for Fujian Province and compared their prediction performance. The results revealed the following. (1) Land use, topographic relief, and 24 h precipitation (H24_100) within a 100-year return period were the three main factors causing flash floods in Fujian Province. (2) The area under the curve (AUC) results showed that the CF-LR model had the best precision in terms of both the success rate (0.860) and the prediction rate (0.882). (3) The assessment results of all three models showed that between 22.27% and 29.35% of the study area have high and very high susceptibility levels, and these areas are mainly located in the east, south, and southeast coastal areas, and the north and west low mountain areas. The results of this study provide a scientific basis and support for flash flood prevention in Fujian Province. The proposed susceptibility assessment framework may also be helpful for other natural disaster susceptibility analyses.

scholarly journals A GIS-Based Support Vector Machine Model for Flash Flood Vulnerability Assessment and Mapping in China

2019 ◽  
Vol 8 (7) ◽  
pp. 297 ◽  
Author(s):  
Junnan Xiong ◽  
Jin Li ◽  
Weiming Cheng ◽  
Nan Wang ◽  
Liang Guo
Keyword(s):  
Support Vector Machine ◽  
Vulnerability Assessment ◽  
Flash Flood ◽  
Flash Floods ◽  
Support Vector ◽  
Land Area ◽  
Analytic Hierarchy ◽  
Machine Model ◽  
Flood Vulnerability ◽  
Development Processes

Flash floods are one of the natural disasters that threaten the lives of many people all over the world every year. Flash floods are significantly affected by the intensification of extreme climate events and interactions with exposed and vulnerable socio-economic systems impede regional development processes. Hence, it is important to estimate the loss due to flash floods before the disaster occurs. However, there are no comprehensive vulnerability assessment results for flash floods in China. Fortunately, the National Mountain Flood Disaster Investigation Project provided a foundation to develop this proposed assessment. In this study, an index system was established from the exposure and disaster reduction capability categories, and is based on analytic hierarchy process (AHP) methods. We evaluated flash flood vulnerability by adopting the support vector machine (SVM) model. Our results showed 439 counties with high and extremely high vulnerability (accounting for 10.5% of the land area and corresponding to approximately 100 million hectares (ha)), 571 counties with moderate vulnerability (accounting for 19.18% of the land area and corresponding to approximately 180 million ha), and 1128 counties with low and extremely low vulnerability (accounting for 39.43% of the land area and corresponding to approximately 370 million ha). The highly-vulnerable counties were mainly concentrated in the south and southeast regions of China, moderately-vulnerable counties were primarily concentrated in the central, northern, and southwestern regions of China, and low-vulnerability counties chiefly occurred in the northwest regions of China. Additionally, the results of the spatial autocorrelation suggested that the “High-High” values of spatial agglomeration areas mainly occurred in the Zhejiang, Fujian, Jiangxi, Hunan, Guangxi, Chongqing, and Beijing areas. On the basis of these results, our study can be used as a proposal for population and building distribution readjustments, and the management of flash floods in China.

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