Frequent Flash Floods Research Articles

Probabilistic modeling of dam failure scenarios: a case study of Kanlikoy Dam in Cyprus

One of the most perilous natural hazards is flooding resulting from dam failure, which can devastate downstream infrastructure and lead to significant human casualties. In recent years, the frequency of flash floods in the northern part of Nicosia, Cyprus, has increased. This area faces increased risk as it lies downstream of the Kanlikoy Dam, an aging earth-fill dam constructed over 70 years ago. In this study, we aim to assess potential flood hazards stemming from three distinct failure scenarios: piping, 100-year rainfall, and probable maximum precipitation (PMP). To achieve this, HEC-HMS hydrologic model findings were integrated into 2D HEC-RAS hydraulic models to simulate flood hydrographs and generate flood inundation and hazard maps. For each scenario, Monte Carlo simulations using McBreach software produced four hydrographs corresponding to exceedance probabilities of 90%, 50%, 10%, and 1%. The results indicate that all dam breach scenarios pose a significant threat to agricultural and residential areas, leading to the destruction of numerous buildings, roads, and infrastructures. Particularly, Scenario 3, which includes PMP, was identified as the most destructive, resulting in prevailing flood hazard levels of H5 and H6 in the inundated areas. The proportion of inundated areas in these high hazard levels varied between 52.8% and 57.4%, with the number of vulnerable structures increasing from 248 to 321 for exceedance probabilities of 90% and 1%, respectively. Additionally, the number of flooded buildings ranged from 842 to 935, and 26 to 34 km of roads were found to be inundated in this scenario. These findings revealed the need for authorities to develop comprehensive evacuation plans and establish an efficient warning system to mitigate the flood risks associated with dam failure.

Comprehensive investigation of flood-resilient neighborhoods: the case of Adama City, Ethiopia

Adama is the second most populous city in Ethiopia and experiences frequent flash floods that have a detrimental impact on the community’s livelihood. To this effect, this study emphasizes the significance of conducting a comprehensive investigation to identify flood-resilient neighborhoods in Adama City. By considering the existing spatial pattern and morphology that are resilient to urban flooding, the city can enhance its flood management strategies in the future. The findings of this study demonstrate varying levels of spatial connectivity within Adama City. Detailed examination of two neighborhoods identified through space syntax analysis with high and low spatial connectivity revealed important insights into flood resilience. The high-connective neighborhoods exhibited well-interconnected street systems with manageable street spacing, facilitating efficient runoff flow and effective flood management during flooding events. These neighborhoods also had shorter block sizes with frequent intersections, promoting better water drainage and reducing the risk of flooding during heavy rain events. The grid pattern observed in these areas allowed for efficient water runoff through multiple drainage paths, including the street surfaces. On the contrary, neighborhoods with low spatial connectivity exacerbated urban flooding. The lack of connectivity and abundance of dead-end streets posed challenges for flood evacuation during emergencies. Irregular block arrangements disrupted the natural drainage system, aggravating the potential for urban flooding. These findings have implications for other flood-prone areas of neighborhoods in Adama City and similar urban areas in the global south on how human settlements are arranged spatially to mitigate urban flood vulnerability.

Solar Panel Energy With Smart Irrigation System

In today’s climatic conditions such as unprecedented amounts of rain and frequent heat waves, cultivating has become a tedious task. Predicting nature’s next move is not easy but what we can do is minimize its effect on the yield. There are so many regions that receive excessive rainfall, suffer frequent flash floods and scorching heat. To adapt to these conditions, sensor networks can be deployed in the fields and the available resources should be used as efficiently as possible. In order to fulfill this requirement, power storage capable of storing energy efficiently from solar panels and an irrigation controller which monitors the land, be it for farm, gardening or horticulture with little to none intervention in certain aspects. The existing products in the market have proprietary parts, features and they don’t endorse cross-compatibility with other products. Keeping the design open source and easy to work promotes recycling and reparability something essential in the current time of global silicon shortage.
 Farmers or gardeners often don’t know the amount of water and the intervals of irrigation for many exotic and domestic species of plants, they then end up growing crops such as wheat and rice which need flooding of the field, the cultivation of these species can be promoted and be made easy with the project. Telemetry and connected technologies are part of every system these days. The project monitors various parameters and depending on the conditions, will carry out necessary action such as irrigation in only amounts required by the field. This is possible through PWM control of motors coupled with valves.

Flood sensitivity assessment of super cities

In the context of global urbanization, more and more people are attracted to these cities with superior geographical conditions and strategic positions, resulting in the emergence of world super cities. However, with the increasing of urban development, the underlying surface of the city has changed, the soil originally covered with vegetation has been substituted by hardened pavement such as asphalt and cement roads. Therefore, the infiltration capacity of urban rainwater is greatly limited, and waterlogging is becoming more and more serious. In addition, the suburbs of the main urban areas of super cities are usually villages and mountains, and frequent flash floods seriously threaten the life and property safety of people in there. Flood sensitivity assessment is an effective method to predict and mitigate flood disasters. Accordingly, this study aimed at identifying the areas vulnerable to flood by using Geographic Information System (GIS) and Remote Sensing (RS) and apply Logistic Regression (LR) model to create a flood sensitivity map of Beijing. 260 flood points in history and 12 predictors [elevation, slope, aspect, distance to rivers, Topographic Wetness Index (TWI), Stream Power Index (SPI), Sediment Transport Index (STI), curvature, plan curvature, Land Use/Land Cover (LULC), soil, and rainfall] were used in this study. Even more noteworthy is that most of the previous studies discussed flash flood and waterlogging separately. However, flash flood points and waterlogging points were included together in this study. We evaluated the sensitivity of flash flood and waterlogging as a whole and obtained different results from previous studies. In addition, most of the previous studies focused on a certain river basin or small towns as the study area. Beijing is the world's ninth largest super cities, which was unusual in previous studies and has important reference significance for the flood sensitivity analysis of other super cities. The flood inventory data were randomly subdivided into training (70%) and test (30%) sets for model construction and testing using the Area Under Curve (AUC), respectively. The results turn out that: (1) elevation, slope, rainfall, LULC, soil and TWI were highly important among these elements, and were the most influential variables in the assessment of flood sensitivity. (2) The AUC of the test dataset revealed a prediction rate of 81.0%. The AUC was greater than 0.8, indicating that the model assessment accuracy was high. (3) The proportion of high risk and extremely high risk areas was 27.44%, including 69.26% of the flood events in this study, indicating that the flood distribution in these areas was relatively dense and the susceptibility was high. Super cities have a high population density, and once flood disasters occur, the losses brought by them are immeasurable. Thus, flood sensitivity map can provide meaningful information for policy makers to enact appropriate policies to reduce future damage.

Physiological and molecular insight of microbial biostimulants for sustainable agriculture.

Increased food production to cater the need of growing population is one of the major global challenges. Currently, agro-productivity is under threat due to shrinking arable land, increased anthropogenic activities and changes in the climate leading to frequent flash floods, prolonged droughts and sudden fluctuation of temperature. Further, warm climatic conditions increase disease and pest incidences, ultimately reducing crop yield. Hence, collaborated global efforts are required to adopt environmentally safe and sustainable agro practices to boost crop growth and productivity. Biostimulants appear as a promising means to improve growth of plants even under stressful conditions. Among various categories of biostimulants, microbial biostimulants are composed of microorganisms such as plant growth-promoting rhizobacteria (PGPR) and/or microbes which stimulate nutrient uptake, produce secondary metabolites, siderophores, hormones and organic acids, participate in nitrogen fixation, imparts stress tolerance, enhance crop quality and yield when applied to the plants. Though numerous studies convincingly elucidate the positive effects of PGPR-based biostimulants on plants, yet information is meagre regarding the mechanism of action and the key signaling pathways (plant hormone modulations, expression of pathogenesis-related proteins, antioxidants, osmolytes etc.) triggered by these biostimulants in plants. Hence, the present review focuses on the molecular pathways activated by PGPR based biostimulants in plants facing abiotic and biotic challenges. The review also analyses the common mechanisms modulated by these biostimulants in plants to combat abiotic and biotic stresses. Further, the review highlights the traits that have been modified through transgenic approach leading to physiological responses akin to the application of PGPR in the target plants.

An Extended Neutrosophic Stepwise Weight Assessment Ratio Analysis Technique Based on GIS for Analysing Flash Floods

Flash floods are a sudden natural hazard caused by successive heavy rains in a short period of time. The world suffers from heavy and frequent rains due to climate change. So, the risk assessment of flash floods is considered increasingly important and urgent. Egypt is considered one of the countries exposed to sudden floods resulting from heavy rains, especially in Upper Egypt. Multi-criteria techniques are widely used to study and analyze the causes and effects of natural hazards. In contrast to the traditional multi-criteria techniques used in the process of estimating flood problems, we applied neutrosophic logic in this study that has a great ability for simulating and reflecting uncertain human’s thoughts in real world problems. Our study area sits in Southeast Sohag, and it is one of the most flash floods prone regions of Egypt's Eastern Desert. This area of Sohag has suffered from frequent flash floods, with some flood events resulting in human casualties in the last decades. This study focuses on using a neutrosophic stepwise weight assessment ration analysis (N-SWARA) technique with remotely sensed data and geographical information system (GIS) for producing a flash floods hazard map. The N-SWARA technique is applied to determine the weights of various factors that related to flash flooding, including elevation, slope, topographic wetness index, distance from the stream, flow accumulation, aspect, and flow direction. The obtained weight of selected criteria used then to produce the flood hazard map (FHM) using a raster calculator tool in geographic information system. The weight of each factor calculated by using the N-SWARA multi criteria analysis method and obtained the following results: 0.39 for slope, 0.21 for elevation, 0.12 for distance, 0.08 for flow direction, 0.05 for flow accumulation, 0.09 for TWI and 0.03 for aspect.

An effective Decision making model through Fusion Optimization and risk associated with flash flood hazards: A case study Asyut, Egypt

One of the most dangerous natural disasters, which causes massive damage all over the world, is flash floods. Therefore, the assessment of flash floods disasters is considered increasingly urgent and important. The widely used techniques for studying and analyzing the causes and impact of natural hazards are multi-criteria techniques. Several researchers used traditional multi-criteria decision-making techniques in the estimation process of flash floods problems as the analytical hierarchy process, decision making trial and evaluation laboratory and analytic network process. The main disadvantage of these traditional models is the incapability of simulating and reflecting uncertain human thoughts. Since neutrosophic logic has a great ability for simulating human’s thoughts and increase the flexibility of expert's preferences in real world problems, we applied it in this study. There are different locations in Egypt that are at a serious risk of flooding, especially in Upper Egypt. Asyut has suffered from frequent flash floods, with some flood events that lead to mortality, damages, and economic losses in the last decades. The intensity of floods in Egypt varies from year to year, according to several climatic and hydrological variables. This study focuses on using a Neutrosophic Decision making trial and evaluation laboratory (N-DEMATEL) technique with remotely sensed data and geographical information system (GIS) for producing a flash floods hazard map. The N-DEMATEL technique is applied to determine the weights of various factors that related to flash flooding, including elevation, slope, topographic wetness index, distance from the stream, flow accumulation, aspect, flow direction, soil, land cover, watershed, curvature, drainage density , total population , population density and precipitation. The obtained weight of selected criteria used then to produce the flood hazard map (FHM) using a raster calculator tool in geographic information system.

Characteristics of July 2019 Cherna Mesta River flash flood

One of the biggest rivers in the southern part of the Balkan peninsula – the Mesta River is wellknown for frequent flash floods, especially in the upper river course. As a result of severe storms and related heavy rain in mid-July 2019, the Cherna Mesta River flooded, and this resulted in heavy damage to the road infrastructure and water-supply systems. All data indicate that this was not a usual water flood, instead at peak flow, the river carried a huge amount of gravel. Our mapping of erosional and depositional features related to the 2019 event, as well as geomorphological analysis, allows for distinguishing distinct sectors along the river valley. Most hazards are defined in the lower reaches of the Cherna Mesta River, where the processes of channel aggradation and lateral erosion are pronounced. The field analysis of the flood-related deposits indicates the operation of debris flood and hyperconcentrated and water flood processes.

Perspective Impact on Water Environment and Hydrological Regime Owing to Climate Change: A Review

This study summarizes reviews on climate change’s impact on the water environment and hydrological regime. The results indicate a strong relationship between the climatological parameters and hydrological patterns. This relationship can be determined in two steps: (1) define the variations in climatological factors, particularly temperature and precipitation, and (2) measure the variations in runoff and inflows to streams and river systems using different statistical and global climate modeling approaches. It is evident that the increasing global temperatures have significant positive effects on runoff variations and evapotranspiration. Similarly, the increase in temperature has speeded up the melting of glaciers and ice on hilly terrains. This is causing frequent flash floods and a gradual rise in the sea level. These factors have altered the timing of stream flow into rivers. Furthermore, the accumulation of greenhouse gases, variations in precipitation and runoff, and sea-level rise have significantly affected freshwater quality. These effects are likely to continue if timely mitigation and adaptation measures are not adopted.

ASSESSING LAND USE AND LAND COVER CHANGE IMPACT ON FLASH FLOODS IN KASARANI CONSTITUENCY, KENYA

Kasarani Constituency in Nairobi County, Kenya is one of the areas that experienced frequent flash floods over the last decade. Anthropogenic activities such as the construction of roads, buildings, and industrialization are identified as key drivers of change in LULC. The aim of this study was to assess the impact of LULC change on flooding in the Kasarani constituency by comparing Spectral indices from Landsat images captured before, during, and after floods between 2013 and 2020. The value of NDVI and MSAVI indices declined during flood days indicating that the vegetation was covered with water while the NDMI value increased during flood days indicating a water-logged surface. The Digital Elevation Model of the study area was created to identify the low-lying areas and river channels that were identified as high flood risk areas. In order to reduce vulnerability to frequent floods, there is a need to identify safe areas for evacuation as well as raised areas for settlement.

Performance evaluation of a high‐resolution regional model over West Africa for operational use: A case study of August 2017

AbstractThe frequency of flash floods resulting from heavy rainfall over West Africa has increased in recent years with serious socio‐economic consequences. Therefore, the need to utilize numerical weather prediction models to forecast heavy rainfall events reliably is also rising at many operational meteorological centres in West Africa. This paper evaluates the performance of the Consortium for Small‐scale Modelling (COSMO) model of the German Meteorological Services (DWD) in predicting rainfall over West Africa for high‐impact rainfall events that occurred between 19 and 26 August 2017. The paper aims to investigate the synoptic forcings modulating daily rainfall variability during that period. Results show that COSMO simulates adequately the spatio‐temporal variability of rainfall distribution over West Africa, though with inherent biases. COSMO displays a decreasing skill in producing spatial rainfall distribution as rainfall amounts tend to 30 mm and above. Additionally, areas of heavy rainfall, mostly about 100–300 km southwest of the core of the Africa Easterly Jet (AEJ), often coincide with areas of decreasing mean sea level pressure of at least 0.6 hPa and areas of increasing convective available potential energy of at least 500 J/kg. Although not in all cases, the trough of the Africa Easterly Wave (AEW) is always located to the east of these areas. We show that not every storm, especially east of the prime meridian, is associated with an AEW trough. COSMO is able to reproduce the atmospheric dynamics modulating the daily rainfall variability, in addition to capturing the daily propagation of the AEW trough, and the core of the AEJ. However, the reproducibility skill of the model in predicting atmospheric dynamics may not transform into the predictive skill of the model in producing rainfall. Nevertheless, operational forecasters may be able to determine likely areas of heavy rainfall by estimating the position of the AEJ core based on the position of areas of the least falling pressure from COSMO. Finally, the incorporation of the fractions skill score metric based on the neighbourhood approach could also assist operational forecasters to decide at which scale a severe weather alert can be issued.

Hybrid ensemble modeling for flash flood potential assessment and susceptibility analysis of a Himalayan river catchment

The occurrence of frequent flash floods in the Indian Himalayan state of Uttarakhand causes massive destruction and damage to life and property every year. In this study, five bivariate statistical models, namely Frequency Ratio, Fuzzy Membership Value, Weights of Evidence (WOE), Statistical Index (SI), and Information Value (IV), were individually integrated with the Index of Entropy (IOE). These models were employed to calculate the flash flood potential index and identify susceptible zones in the Mandakini River Basin. 39 flash flood locations, 39 non-flash flood locations, and 15 flash flood conditioning factors were utilized for training and testing the models with 70% and 30% of the dataset, respectively. The model performances were examined using receiver operating characteristics curves. This best prediction rate performance was featured by SI-IOE and IV-IOE with an AUC = 0.896 followed by WOE-IOE (AUC = 0.889). The results revealed that the areas with high and very high susceptibility cover approximately 40% of the study area.

A systematic review of the emergency planning for flash floods response in the Kingdom of Saudi Arabia

Every year, flash floods hit many cities in the Kingdom of Saudi Arabia (Saudi Arabia) leading to many injuries and deaths as well as a huge amount of damage to infrastructure. Risks of frequent flash floods have been linked to a lack of emergency planning. This paper presents a systematic review of emergency planning for flash floods response currently in place in Saudi Arabia. Collected information was analysed based on the suitability of content and data for emergency planning in flash floods response. Aspects of the dominant approach of emergency planning and the community-based approach are examined and considered against applications in Saudi Arabia. A case study is used about flash floods in Jeddah in 2009 and 2011 to consider these approaches. This may be the first systematic review of emergency planning for flash floods response in Saudi Arabia and shortcomings listed may lead to improvements in policy, planning and training, particularly given the scientific consensus of an increase in the frequency and magnitude of flash floods in Saudi Arabia.

GIS based Approach for Planning the Evacuation Process During Flash Floods: Case Study for Gampaha Divisional Secretariat Division, Sri Lanka

Gampaha district is one of the areas that suffer from frequent flash floods in Sri Lanka. Since flash floods occur unexpectedly, and with minimal warning, preparedness is essential to minimize losses during such a disaster. Planning the evacuation during a flood is a complex process; therefore, it needs focused consideration on several factors. The main objective of this paper is to propose a Geographical Information Systems (GIS) based approach to plan the evacuation process during a situation where there is a flash flood in the Gampaha Divisional Secretariat Division (DSD), with the intent to reduce negative consequences. The study has considered seven criteria: elevation, accessibility, land-use, availability of buildings, presence of water features, rainfall, and population density, in selecting locations for evacuation centers. These data were analyzed with the tools and models available in the GIS software package. As a first step, the flood inundation map was created using elevation and rainfall data. Evacuation centers were then identified outside of the inundated area. Finally, after field verification, 7 potential locations (Bandaranayake Vidyalaya, Bandarawatta Parakrama Vidyalaya, Sri Sumangalaramaya, Madegama Sri Sunandaaramaya, Sri Wajiraghanaramaya, St. Jude Church Idigolla, and Holy Cross College) were selected by considering the capacities such as elevation (above 15m from the Mean Sea Level), accessibility (within 200m from main roads), ownership (public only), and the number of people accommodated. The results of this study will be very helpful for the government, non-government organizations, and the victims to take immediate actions during a flash flood event in the study area.

Mapping of Flood Zones in Urban Areas through a Hydro-climatic Approach: the Case of the City of Abha

Flooding is a natural phenomenon of the hydrological cycle, but it has become an urban concern in many cities around the world. Due to human intervention on the functioning of hydrosystems through infrastructure, the channelling of watercourses, the redirection of the flow and the inevitable extension of the urban landscape, floods have become a growing urban hazard. Several cities are currently facing very frequent flash floods. These floods are of various types and several factors are at the origin of their manifestation, which leaves its understanding and prevention for local stakeholders a long-term process that requires a colossal amount of work among several multidisciplinary researchers. Without denying the scientific consensus on the role of climate change, currently floods are largely caused by the senseless and irresponsible behaviour of humans. Among the cities in Saudi Arabia facing the risk of flooding is the city of Abha located in the southwest of the country, the focus of this research. It is subject to recurrent and devastating floods caused by several factors. Controversial topography, dissected orography, aggressive rainfall, accelerated and unregulated urban growth, and irresponsible human intervention are all factors that aggravate this problem. The resolution of this problem, or at least the minimization of its consequences, requires a rigorous and carefully studied approach. The appropriate knowledge by local stakeholders must be reinforced by a methodological and cartographic assessment of this phenomenon in order to mitigate its consequences. The main objective of this work is to make cartographic and methodological contributions to acquire additional knowledge on the flood hazard in the city of Abha through a statistical processing of rainfall data for the period 1978-2018, a mapping of the factors intervening on the runoff and its various behaviors and finally a synthetic analysis.

A mechanism-based assessment framework for masonry arch bridges under scour-induced support rotation

Increase in the frequency of flash floods owed to climate change, excessive sand mining, and urbanisation of watersheds has accelerated the need to quantify the structural effect of scour-induced structural damages in masonry arch bridges. The structural effects of scour-induced rotation are unaddressed in literature. In this context, a mechanism-based framework based on limit state principles is developed for masonry arch bridges subjected to scour-induced rotation. Critical collapse mechanisms caused by scour-induced rotation are identified, and analysis framework is developed using rigid-body kinematics. The spectrum of bridges under consideration is classified into subsets, and an assessment scheme is developed using fragility curves as a function of scouring location as well as bridge typology.

Variations in Flash Flood–Producing Storm Characteristics Associated with Changes in Vertical Velocity in a Future Climate in the Mississippi River Basin

AbstractThe Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood–producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood–producing storms in the MRB. Specifically, the variations in flash flood–producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood–producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo–global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood–producing storms in the MRB. While rainfall increases in all flash flood–producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood–producing storms in order to create more resilient communities.

Assessment of Climate-Driven Flood Risk and Adaptation Supporting the Conservation Management Plan of a Heritage Site. The National Art Schools of Cuba

This work illustrates the contribution of flood risk assessment and adaptation to set up a conservation management plan for a masterpiece of 20th-century architecture. Case study is the iconic complex, internationally known as the National Art Schools of Cuba. It consists of five buildings built in the early 1960s within a park of Habana next to the Caribbean Sea. The path of the river (Rio Quibù) crossing the estate was modified to fit the landscape design. The complex has then been exposed to the risk of flooding. The School of Ballet, located in a narrow meander of the river, slightly upstream of a bridge and partially obstructing the flow, is particularly subject to frequent flash floods from the Rio Quibù, and it needs urgent restoration. Keeping ISA Modern is a project aimed at preserving the Schools complex. Based upon in situ surveys on the Rio Quibù and local area measurements during 2019, numerical modelling, and previous work by the Cuban National Institute of Hydraulic Resources, we pursued a flood risk analysis for the area, and a preliminary analysis of available risk reduction strategies. Using HEC-RAS 2D software for hydraulic modelling, we evaluated the flooded area and the hydraulic conditions (flow depth, velocity) for floods with given return periods. Our results show that SB is a building most subject to flooding, with high levels of risk. Defense strategies as designed by Cuban authorities may include a (new) wall around the School of Ballet and widening of the river channel, with high impact and cost, although not definitive. Temporary, light, permanent, and low cost/impact flood proofing structures may be used with similar effectiveness. We demonstrate that relatively little expensive hydraulic investigation may aid flood modelling and risk assessment in support of conservation projects for historically valuable sites. This may support brainstorming and the selection of (low to high cost) adaptation and risk reduction measures in the coastal areas of Cuba in response to ever increasing extreme storms and sea level rise controlling flood dynamics under transient climate change.

Investigation of soil permeability and suitable vegetation for rain gardens in Kecskemet

Nowadays, the implementation of integrated stormwater management is an important element of urban climate adaptation. Rain gardens are part of this system, which effectively handles large amounts of sudden precipitation. In this way, they are suitable for preventing the increasing frequency of flash floods. For rain gardens, it is important to collect information about the soil and the vegetation.We examined the permeability of the typical soil types in Kecskemét – humus sandy soil, solonetz meadow soil – and Bácsvíz compost, in order to decide what proportion of soils and compost can be considered ideal for rain gardens. In addition, experiments were performed with three broad-tolerant plants (Inula Britannica, Aster tripolium subsp. pannonicus and Limonium gmelinii) planted in the studied soil types and compost, as well as in a mixture of these. Based on our results, it can be concluded that the solonetz meadow soil practically means a waterproof layer, while a mixture of half of this soil type and compost already has adequate water permeability and water storage properties, which provide the necessary living conditions for plants.

A novel hybrid quantum-PSO and credal decision tree ensemble for tropical cyclone induced flash flood susceptibility mapping with geospatial data

Flash flood is considered as one of the most destructive natural hazards worldwide, especially in tropical countries, where tropical cyclones with torrential rains are recurrent problems yearly. Therefore, an accurate prediction of susceptible areas to flash floods is crucial for developing measures to prevent, avoid, and minimize damages associated with flash floods. The aim of this research is to propose a new state-of-the-art model based on hybridizing Quantum Particle Swarm Optimization (QPSO) and the Credal Decision Tree (CDT) ensemble, namely the QPSO-CDTreeEns model, for spatial prediction of the flash flood. The concept of the proposed model is to build a forest tree of the CDT established through the Random Subspace ensemble. Therein, QPSO is integrated to optimize the three parameters, the subspace size, number of trees, and the maximum depth of trees. A district suffered from a high frequency of flash floods in the north-western mountainous area of Vietnam was selected as a case study. In this regard, a geospatial database that includes a total of 1698 flash flood and inundation polygons derived from Sentinel-1 C-band SAR images and ten input indicators were used to construct and to verify the proposed model. The result shows that the QPSO-CDT-Ens model performed well (Overall accuracy = 90.4, Kappa coefficient = 0.807) and outperformed the five machine learning algorithms in flash flood susceptibility mapping. Among the ten factors, the land-use/land-cover (LULC), the slope, the curvature, and the TWI are the most important indicators. We conclude that the proposed model is a promising tool for flash flood susceptibility mapping in the tropics and may assist decision-makers in sustainable land-use planning in the national disaster mitigation strategies.