scholarly journals Flood Hazard Modelling in Upper Mandakini Basin of Uttarakhand

2021 ◽  
Vol 16 (3) ◽  
pp. 880-889
Author(s):  
Gagandeep Singh ◽  
Vishwa Bandhu Singh Chandel ◽  
Simrit Kahlon
Keyword(s):  
Climate Changes ◽  
Flood Hazard ◽  
Anthropogenic Activities ◽  
Weather Extremes ◽  
Mountainous Regions ◽  
Flood Susceptibility ◽  
High Kinetic Energy ◽  
Glacial Melting ◽  
Natural Terrain ◽  
High Flood

Floods in Himalayan region raise serious concerns regarding ongoing path of development as recent manifestations of catastrophic events establish link between climate changes and risk to anthropogenic activities in mountainous regions. Scientists predict frequent occurrence of such disasters wherein rapid glacial melting; incidents of glacial lake outburst and weather extremes may trigger floods in the Himalayan mountains. This paper examined flood risk in Upper Mandakini basin through GIS based flood simulationto highlight flood potential and risk associated with such hazard in the study area.It is observed that floods in study area display hazardous interplay of natural terrain gradient, high kinetic energy of streams, and intense rainfall. The upper sections of basin that includes Kali Ganga, Mandani Ganga, Madhyamaheshwar and Mandakini rivers shows high flood susceptibility with greatest risk in the latter. Such hazardousness is likely to be intensified by ongoing anthropogenic activities in the basin.

scholarly journals Assessing the susceptibility of schools to flood events in Iran

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Saleh Yousefi ◽  
Hamid Reza Pourghasemi ◽  
Sayed Naeim Emami ◽  
Omid Rahmati ◽  
Shahla Tavangar ◽  
...  
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Rural Students ◽  
Flood Hazards ◽  
Analytic Hierarchy ◽  
Flood Susceptibility ◽  
Susceptibility Maps ◽  
High Flood ◽  
Analytic Hierarchy Process Method ◽  
Very High

Abstract Catastrophic floods cause deaths, injuries, and property damages in communities around the world. The losses can be worse among those who are more vulnerable to exposure and this can be enhanced by communities’ vulnerabilities. People in undeveloped and developing countries, like Iran, are more vulnerable and may be more exposed to flood hazards. In this study we investigate the vulnerabilities of 1622 schools to flood hazard in Chaharmahal and Bakhtiari Province, Iran. We used four machine learning models to produce flood susceptibility maps. The analytic hierarchy process method was enhanced with distance from schools to create a school-focused flood-risk map. The results indicate that 492 rural schools and 147 urban schools are in very high-risk locations. Furthermore, 54% of rural students and 8% of urban students study schools in locations of very high flood risk. The situation should be examined very closely and mitigating actions are urgently needed.

scholarly journals Analysis of Flood Vulnerability as a Support to Water Sensitive Urban Design Planning in Klaten Regency

2021 ◽  
Vol 26 (2) ◽  
pp. 183-193
Author(s):  
Desyta Ulfiana ◽  
Yudi Eko Windarto ◽  
Nurhadi Bashit ◽  
Novia Sari Ristianti
Keyword(s):  
Land Use ◽  
Urban Design ◽  
Flood Hazard ◽  
Flood Management ◽  
Flood Vulnerability ◽  
Geological Conditions ◽  
Order Preference ◽  
Water Sensitive Urban Design ◽  
High Flood ◽  
High Level

Klaten Regency is one of the regions that has a high level of flood vulnerability. The area of Klaten Regency which is huge and has diverse characteristics makes it difficult to determine an appropriate flood management model. Water Sensitive Urban Design (WSUD) is a model that focuses on handling water management problems with environmentally friendly infrastructure. Therefore, an analysis is carried out to determine the level of flood vulnerability and factors causing flooding to plan a WSUD design that is suitable for each sub-districts of Klaten Regency. The Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods are used to help the analysis. Aspects used as criteria are rainfall, slope, soil type, geological conditions, and land use. Based on the analysis, it could be concluded that Klaten Regency has two sub-districts with high flood hazard category, 21 sub-districts with medium category, and three sub-districts with low category. Bayat and Cawas are sub-districts that have a high level of flood vulnerability category. Meanwhile, Kemalang, Karangnongko and Polanharjo are districts with a low level of flood vulnerability category. The main factors causing flooding in Klaten Regency are slope and land use.

scholarly journals Climate change impact on flood hazard

2014 ◽  
Vol 364 ◽  
pp. 164-170 ◽  
Author(s):  
M. Brilly ◽  
K. Kavčič ◽  
M. Šraj ◽  
S. Rusjan ◽  
A. Vidmar
Keyword(s):  
Climate Changes ◽  
Flood Hazard ◽  
High Impact ◽  
Precipitation Data ◽  
Simple Correlation ◽  
Future Time ◽  
Special Situation ◽  
Change Impact ◽  
Time Periods ◽  
Hbv Model

Abstract. Climate changes have a high impact on river discharges and therefore on floods. There are a few different methods we can use to predict discharge changes in the future. In this paper we used the complex HBV model for the Vipava River and simple correlation between discharge and precipitation data for the Soča River. The discharge prediction is based on the E-OBS precipitation data for three future time periods (2011–2040, 2041–2070 and 2071–2100). Estimated discharges for those three future periods are presented for both rivers. But a special situation occurs at the confluence where the two rivers with rather different catchments unite, and this requires an additional probability analysis.

scholarly journals Is Meteorological Evidence Relevant Enough in Legal Disputes? A Romanian Case Study.

2019 ◽  
Vol 13 (1) ◽  
pp. 115-128
Author(s):  
Ionac Nicoleta ◽  
Tudor Ion ◽  
Grigore Elena ◽  
Constantin Dana ◽  
Uriţescu Bogdan ◽  
...  
Keyword(s):  
Climate Changes ◽  
Weather Extremes ◽  
Severe Thunderstorm ◽  
Distribution Maps ◽  
Force Majeure ◽  
Unbiased Manner ◽  
The Law ◽  
Major Property ◽  
Town Area

Abstract The increasing frequency and intensity of climate and weather extremes due to ongoing climate changes can cause major property and infrastructure damage. Mainly representing unforeseen and unavoidable hazards, some environmental and business laws broadly assimilate them as force majeure situations, excepting parties affected by their impact from prior commitments. The present study, debating on the way law courts should broadly address the force majeure clause when objective and accurate evidence is being provided, describes the terms of a legal dispute between the owners of two neighboring buildings which have seriously been damaged by a severe thunderstorm developing over the Bucharest-Otopeni town area, on the 22nd July 2014. Consistent meteorological evidence (weather reports and forecasts, aerological diagrams, radar and satellite images, air-pressure distribution maps, synoptic messages etc.) have been presented to the law court to document, in an unbiased manner, on the extraordinary, external, unforeseen and unavoidable weather event representing the cause of a civil legal dispute. The extent to which the law court may take all these into consideration under the provisions of the force majeure clause is still to be explored.

Comparison of statistical and analytical hierarchy process methods on flood susceptibility mapping: In a case study of the Lake Tana sub-basin in northwestern Ethiopia

2021 ◽  
Vol 13 (1) ◽  
pp. 1668-1688
Author(s):  
Azemeraw Wubalem ◽  
Gashaw Tesfaw ◽  
Zerihun Dawit ◽  
Belete Getahun ◽  
Tamrat Mekuria ◽  
...  
Keyword(s):  
Land Use Planning ◽  
Analytical Hierarchy Process ◽  
Flood Hazard ◽  
Google Earth ◽  
Information Value ◽  
Lake Tana ◽  
Ahp Model ◽  
Flood Susceptibility ◽  
Susceptibility Modeling ◽  
Hierarchy Process

Abstract The flood is one of the frequently occurring natural hazards within the sub-basin of Lake Tana. The flood hazard within the sub-basin of Lake Tana causes damage to cropland, properties, and a fatality every season. Therefore, flood susceptibility modeling in this area is significant for hazard reduction and management purposes. Thus, the analytical hierarchy process (AHP), bivariate (information value [IV] and frequency ratio [FR]), and multivariate (logistic regression [LR]) statistical methods were applied. Using an intensive field survey, historical document, and Google Earth Imagery, 1,404-flood locations were determined, classified into 70% training datasets and 30% testing flood datasets using a subset within the geographic information system (GIS) environment. The statistical relationship between the probability of flood occurrence and 11 flood-driving factors was performed using the GIS tool. The flood susceptibility maps of the study area were developed by summing all weighted aspects using a raster calculator. It is classified into very low, low, moderate, high, and very high susceptibility classes using the natural breaks method. The accuracy and performance of the models were evaluated using the area under the curve (AUC). As the result indicated, the FR model has better performance (AUC = 99.1%) compared to the AHP model (AUC = 86.9%), LR model (AUC = 81.4%), and IV model (AUC = 78.2%). This research finds out that the applied methods are quite worthy for flood susceptibility modeling within the study area. In flood susceptibility modeling, method selection is not a serious challenge; the care should tend to the input parameter quality. Based on the AUC values, the FR model is comparatively better, followed by the AHP model for regional land use planning, flood hazard mitigation, and prevention purposes.

scholarly journals Delimitation of flood areas based on a calibrated a DEM and geoprocessing: case study on the Uruguay River, Itaqui, southern Brazil

2019 ◽  
Vol 19 (1) ◽  
pp. 237-250 ◽  
Author(s):  
Paulo Victor N. Araújo ◽  
Venerando E. Amaro ◽  
Robert M. Silva ◽  
Alexandre B. Lopes
Keyword(s):  
Statistical Analysis ◽  
Flood Hazard ◽  
Satellite Image ◽  
Water Levels ◽  
Calibration Model ◽  
Southern Brazil ◽  
Temporal Series ◽  
Vertical Accuracy ◽  
High Flood ◽  
Uruguay River

Abstract. Flooding is a natural disaster which affects thousands of riverside, coastal, and urban communities causing severe damage. River flood mapping is the process of determining inundation extents and depth by comparing historical river water levels with ground surface elevation references. This paper aims to map flood hazard areas under the influence of the Uruguay River, Itaqui (southern Brazil), using a calibration digital elevation model (DEM), historic river level data and geoprocessing techniques. The temporal series of maximum annual level records of the Uruguay River, for the years 1942 to 2017, were linked to the Brazilian Geodetic System using geometric leveling and submitted for descriptive statistical analysis and probability. The DEM was calibrated with ground control points (GCPs) of high vertical accuracy based on post-processed high-precision Global Navigation Satellite System surveys. Using the temporal series statistical analysis results, the spatialization of flood hazard classes on the calibrated DEM was assessed and validated. Finally, the modeling of the simulated flood level was visually compared against the flood area on the satellite image, which were both registered on the same date. The free DEM calibration model indicated high correspondence with GCPs (R2=0.81; p<0.001). The calibrated DEM showed a 68.15 % improvement in vertical accuracy (RMSE = 1.00 m). Five classes of flood hazards were determined: extremely high flood hazard, high flood hazard, moderate flood hazard, low flood hazard, and non-floodable. The flood episodes, with a return time of 100 years, were modeled with a 57.24 m altimetric level. Altimetric levels above 51.66 m have a high potential of causing damage, mainly affecting properties and public facilities in the city's northern and western peripheries. Assessment of the areas that can potentially be flooded can help to reduce the negative impact of flood events by supporting the process of land use planning in areas exposed to flood hazard.

scholarly journals GIS-Based Geomorphological Map of the Calore River Floodplain Near Benevento (Southern Italy) Overflooded by the 15th October 2015 Event

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 148 ◽  
Author(s):  
Paolo Magliulo ◽  
Alessio Valente
Keyword(s):  
Flood Hazard ◽  
Anthropogenic Activities ◽  
Negative Effects ◽  
River Floodplain ◽  
River Terraces ◽  
Channel Adjustments ◽  
Geomorphological Map ◽  
Loose Sediments ◽  
Abandoned Channels ◽  
The 19Th Century

On 15 October 2015, the floodplain of the Calore River underwent a destructive flood, with a stream stage increase up to 10 m. In this paper, we describe the GIS-based, object-oriented geomorphological map of the overflooded sectors of the Calore River floodplain near Benevento. The map graphically represents the field-checked results of a detailed geomorphological study carried out by means of GIS analysis of historical and topographic maps and orthophotos. Particular attention was devoted to the analysis of the channel adjustments experienced by the Calore River since the end of the 19th century, which shaped most of the landforms in the floodplain. The results showed that the investigated floodplain is characterized by abandoned channels, anthropogenic landforms, and five orders of recent river terraces separated by gently-sloping inactive fluvial scarps, less than 2 m high. On the oldest and/or more distal sectors of the floodplain, landforms are badly preserved, probably due to the more prolonged reshaping by natural erosional processes and anthropogenic activities, and to the high erodibility of the loose sediments in which they are shaped. The proposed map could be a key tool for a correct flood hazard assessment in the Benevento area, permitting thematic maps that avoid or reduce the negative effects of events similar to the 15 October 2015 flood.

scholarly journals Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms

2020 ◽  
Vol 12 (21) ◽  
pp. 3568
Author(s):  
Shahab S. Band ◽  
Saeid Janizadeh ◽  
Subodh Chandra Pal ◽  
Asish Saha ◽  
Rabin Chakrabortty ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Flash Flood ◽  
Flood Hazard ◽  
Machine Learning Algorithms ◽  
Mitigation Strategies ◽  
Boosted Regression Tree ◽  
Flash Flooding ◽  
Flood Susceptibility ◽  
Susceptibility Modeling

Flash flooding is considered one of the most dynamic natural disasters for which measures need to be taken to minimize economic damages, adverse effects, and consequences by mapping flood susceptibility. Identifying areas prone to flash flooding is a crucial step in flash flood hazard management. In the present study, the Kalvan watershed in Markazi Province, Iran, was chosen to evaluate the flash flood susceptibility modeling. Thus, to detect flash flood-prone zones in this study area, five machine learning (ML) algorithms were tested. These included boosted regression tree (BRT), random forest (RF), parallel random forest (PRF), regularized random forest (RRF), and extremely randomized trees (ERT). Fifteen climatic and geo-environmental variables were used as inputs of the flash flood susceptibility models. The results showed that ERT was the most optimal model with an area under curve (AUC) value of 0.82. The rest of the models’ AUC values, i.e., RRF, PRF, RF, and BRT, were 0.80, 0.79, 0.78, and 0.75, respectively. In the ERT model, the areal coverage for very high to moderate flash flood susceptible area was 582.56 km2 (28.33%), and the rest of the portion was associated with very low to low susceptibility zones. It is concluded that topographical and hydrological parameters, e.g., altitude, slope, rainfall, and the river’s distance, were the most effective parameters. The results of this study will play a vital role in the planning and implementation of flood mitigation strategies in the region.

scholarly journals Social vulnerability of rural households to flood hazards in western mountainous regions of Henan province, China

2016 ◽  
Vol 16 (5) ◽  
pp. 1123-1134 ◽  
Author(s):  
Delin Liu ◽  
Yue Li
Keyword(s):  
Social Vulnerability ◽  
Local Governments ◽  
Flood Hazard ◽  
Rural Households ◽  
Henan Province ◽  
Mitigation Strategies ◽  
Flood Hazards ◽  
Social Vulnerability Index ◽  
Scoring Method ◽  
Mountainous Regions

Abstract. Evaluating social vulnerability is a crucial issue in risk and disaster management. In this study, a household social vulnerability index (HSVI) to flood hazards was developed and used to assess the social vulnerability of rural households in western mountainous regions of Henan province, China. Eight key indicators were identified using existing literature and discussions with experts from multiple disciplines and local farmers, and their weights were determined using principle component analysis (PCA) and an expert scoring method. The results showed that (1) the ratio of perennial work in other places, hazard-related training and illiteracy ratio (15+) were the most dominant factors of social vulnerability. (2) The numbers of high, moderate and low vulnerability households were 14, 64 and 16, respectively, which accounted for 14.9, 68.1 and 17.0 % of the total interviewed rural households, respectively. (3) The correlation coefficient between household social vulnerability scores and casualties in a storm flood in July 2010 was significant at 0.05 significance level (r  =  0.748), which indicated that the selected indicators and their weights were valid. (4) Some mitigation strategies to reduce household social vulnerability to flood hazards were proposed, which included (1) improving the local residents' income and their disaster-related knowledge and evacuation skills, (2) developing emergency plans and carrying out emergency drills and training, (3) enhancing the accuracy of disaster monitoring and warning systems and (4) establishing a specific emergency management department and comprehensive rescue systems. These results can provide useful information for rural households and local governments to prepare, mitigate and respond to flood hazards, and the corresponding strategies can help local households to reduce their social vulnerability and improve their ability to resist flood hazard.

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