Analysis of Weather Anomalies to Assess the 2021 Flood Events in Yaounde, Cameroon (Central Africa)

Extreme weather anomalies such as rainfall and its subsequent flood events are governed by complex weather systems and interactions between them. It is important to understand the drivers of such events as it helps prepare for and mitigate or respond to the related impacts. In line with the above statements, quarter-hourly data for the year 2021 recorded in the Yaounde meteorological station were synthesized to come out with daily and dekadal (10-day averaged) anomalies of six climate factors (rainfall, temperature, insolation, relative humidity, dew point and wind speed), in order to assess the occurrences and severity of floods to changing weather patterns in Yaounde. In addition, Precipitation Concentration Index (PCI) was computed to evaluate the distribution and analyse the frequency and intensity of precipitation. Coefficient of variation (CV) was used to estimate the seasonal and annual variation of rainfall patterns, while Mann-Kendall (MK) trend test was performed to detect weather anomalies (12-month period variation) in quarter-hourly rainfall data from January 1st to December 31st 2021. The Standard Precipitation Index (SPI) was also used to quantify the rainfall deficiency of the observed time scale. Results reveal that based on the historical data from 1979 to 2018 in the bimodal rainfall forest zone, maximum and minimum temperature averages recorded in Yaounde in 2021 were mostly above historical average values. Precipitations were rare during dry seasons, with range value of 0 - 13.6 mm for the great dry season and 0 - 21.4 mm for the small dry season. Whereas during small and great rainy seasons, rainfalls were regular with intensity varying between 0 and 50 mm, and between 0 and 90.4 mm, respectively. The MK trend test showed that there was a statistical significant increase in rainfall trend for the month of August at a 5% level of significance, while a significant decreasing trend was observed in July and December. There was a strong irregular rainfall distribution during the months of February, July and December 2021, with a weather being mildly wetted during all the dry seasons and extremely wetted in August. Recorded flooding days within the year of study matched with heavy rainy days including during dry seasons.

Case Study on Identification of Flood Hazard in the Lower Catchment Area of the Attanagalu Oya River Basin

The present work aims to identify flood hazards and risks, particularly to the Attanagalu Oya river basin in Gampaha district, the western province in Sri Lanka. Attanagalu Oya river catchment area periodically faced flood hazards. The flood is categorized by complex like 2008, 2010, 2016, 2017, and it chose 2016 as the primary flood event. Study areas have been selected depending on data availability. Attanagalu Oya river basin is mainly focused as a study area. However, here selected only four Grama Niladhari Divisions are as a sample area. Those are;Kirindivita, Ambanvita, Thammita West, Gonagaha1. Furthermore, many flood hazards can be identified when considering the flood events history. But here selected only two years were 2010 and 2016. These two years were selected with high flood events. For the study, that flood series used 1 feet elevation contours used to identify flood levels and used LiDAR image to identify risk areas in the study site. Due to the blockage of the main waterways that discharge water into the Negombo Lagoon, limited water transportation, low lying land reclamation for development, mainly affect paddy lands and roads, and flood as a major problem identified temporarily and spatially. Eventually, the study could identify flood-prone areas and map the risk zones within the study area.

Flood susceptibility modelling using advanced ensemble machine learning models

Floods are one of nature's most destructive disasters because of the immense damage to land,buildings,and human fatalities.It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods.Therefore,earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters.In this study,we applied and assessed two new hybrid ensemble models,namely Dagging and Random Subspace(RS)coupled with Artificial Neural Network(ANN),Random Forest(RF),and Support Vector Machine(SVM)which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin,the northern region of Bangladesh.The application of these models includes twelve flood influencing factors with 413 current and former flooding points,which were transferred in a GIS environment.The information gain ratio,the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors.For the validation and the comparison of these models,for the ability to predict the statistical appraisal measures such as Freidman,Wilcoxon signed-rank,and t-paired tests and Receiver Operating Characteristic Curve(ROC)were employed.The value of the Area Under the Curve(AUC)of ROC was above 0.80 for all models.For flood susceptibility modelling,the Dagging model performs superior,followed by RF,the ANN,the SVM,and the RS,then the several benchmark models.The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

Flood Hazard Prediction from Soil Properties by Remote Sensing and Genographic Information System:A Case Study of Mae Rim Watershed,Chiang Mai Province,Thailand

Physiography and soil in Mae Rim watershed, Chiang Mai Province, Thailand were investigated by using aerial photographs and satellite image in conjunction with field work, and soil infiltration rate and soil shear resistance were measured in field. Many factors affecting runoff were analyzed using the Integrated Land and Water Information System (ILWIS). As a result, a model determining flood hazard was set up. Three maps including runoff curve number map, runoff coefficient map, and flood inundation map were created. In addition, the time of concentration was predicted.

Flash flood hazard mapping: A pilot case study in Xiapu River Basin, China

Flash flood hazard mapping is a supporting component of non-structural measures for flash flood prevention. Pilot case studies are necessary to develop more practicable methods for the technical support systems of flash flood hazard mapping. In this study, the headwater catchment of the Xiapu River Basin in central China was selected as a pilot study area for flash flood hazard mapping. A conceptual distributed hydrological model was developed for flood calculation based on the framework of the Xinanjiang model, which is widely used in humid and semi-humid regions in China. The developed model employs the geomorphological unit hydrograph method, which is extremely valuable when simulating the overland flow process in ungauged catchments, as compared with the original Xinanjiang model. The model was tested in the pilot study area, and the results agree with the measured data on the whole. After calibration and validation, the model is shown to be a useful tool for flash flood calculation. A practicable method for flash flood hazard mapping using the calculated peak discharge and digital elevation model data was presented, and three levels of flood hazards were classified. The resulting flash flood hazard maps indicate that the method successfully predicts the spatial distribution of flash flood hazards, and it can meet the current requirements in China.

On the Flood Disasters in the Lower Jingjiang Reaches: Grey Prediction Model and Application

In the light of the historical substantial data (covering a 70-year period) collected in the Lower Jingjiang segment and aided by topological grey method, here we attempt to characterize the occurrence and future trend of flood calamities in the study area. Our findings indicate that overall the high-frequent flood disasters with middle to lower damage prevail at present. A series of dramatic flood waves will appear in the years of 2016, 2022, 2030 and 2042, particularly a destructive flood will occur between 2041 and 2045 in the Lower Jingjiang reaches. Typical of sensitive response to flood hazards in close association with its special geographical location, the lower Jingjiang segment hereby can reflect the development trend of floods in the middle Yangtze reaches. According to the results, a good fitness was revealed between the prediction and practical values. This actually hints that the topological grey method is an effective mathematical means of resolving problems containing uncertainty and indetermination, thus providing valuable information for the flood prediction in the middle Yangtze catchment.

Floodplain Mapping and Risks Assessment of the Orashi River Using Re­mote Sensing and GIS in the Niger Delta Region, Nigeria

Residents along the shoreline of the Orashi River have yearly been dis­placed and recorded loss of lives,farmland,and infrastructures.The Gov­ernment’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in devel­oping a 3D floodplain map using ArcGIS software.The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain.Incorporating the 3D slope which reveals that>8 and<8 makes up 1.15%and 98.85%of the study area respectively confirms the area is a floodplain.Aspect indicate west-facing slope are dark blue,3D hillshade indicate yellow is very low area and the high area is pink and also the buffer analysis result reveals wa­terbodies reflecting blue with an estimated area of 1.88 km2,yellow indicate 0.79 km2 of the shoreline,red indicate 0.81 km2 of the minor floodplain and pink contain 0.82 km2 with the length of 32.82 km.The result from google earth image in 2007 indicate absent of settlement,2013 indicate minimal settlement and 2020 indicate major settlement in the study area when cor­related with 3D Floodplain mapping before and during the flood in other to analyze and manage flooding for further purpose and the majority of the area are under seize with flood like in 2020.Therefore,Remote Sensing and GIS techniques are useful for Floodplain mapping,risk analysis for control measures for better flood management.

Implementation of Remote Sensing and GIS Techniques to Study the Flash Flood Risk at NEOM Mega-City, Saudi Arabia

Southern Red Sea flooding is common. Assessing flood-prone development risks helps decrease life and property threats. It tries to improve flood awareness and advocate property owner steps to lessen risk. DEMs and topography data were analyzed by RS and GIS. Fifth-through seventh-order rivers were studied. Morphometric analysis assessed the area’s flash flood danger. NEOM has 14 catchments. We determined each catchment’s area, perimeter, maximum length, total stream length, minimum and maximum elevations. It also uses remote sensing. It classifies Landsat 8 photos for land use and cover maps. Image categorization involves high-quality Landsat satellite images and secondary data, plus user experience and knowledge. This study used the wetness index, elevation, slope, stream power index, topographic roughness index, normalized difference vegetation index, sediment transport index, stream order, flow accumulation, and geological formation. Analytic hierarchy considered all earlier criteria (AHP). The geometric consistency index GCI (0.15) and the consistency ratio CR (4.3%) are calculated. The study showed five degrees of flooding risk for Wadi Zawhi and four for Wadi Surr, from very high to very low. 9.16% of Wadi Surr is vulnerable to very high flooding, 50% to high flooding, 40% to low flooding, and 0.3% to very low flooding. Wadi Zawhi’s flood risk is 0.23% high, moderate, low, or extremely low. They’re in Wadi Surr and Wadi Zawhi. Flood mapping helps prepare for emergencies. Flood-prone areas should prioritize resilience.

Flood Hazard Mapping of Lower Indus Basin Using Multi-Criteria Analysis

Flooding has been one of the recurring occurred natural disasters that induce detrimental impacts on humans, property and environment. Frequent floods is a severe issue and a complex natural phenomenon in Pakistan with respect to population affected, environmental degradations, and socio-economic and property damages. The Super Flood, which hit Sindh in 2010, has turned out to be a wakeup call and has underlined the overwhelming challenge of natural calamities, as 2010 flood and the preceding flood in 2011 caused a huge loss to life, property and land use. These floods resulted in disruption of power, telecommunication, and water utilities in many districts of Pakistan, including 22 districts of Sindh. These floods call for risk assessment and hazard mapping of Lower Indus Basin flowing in the Sindh Province as such areas were also inundated in 2010 flood, which were not flooded in the past in this manner. This primary focus of this paper is the use of Multi-criteria Evaluation (MCE) methods in integration with the Geographical Information System (GIS) for the analysis of areas prone to flood. This research demonstrated how GIS tools can be used to produce map of flood vulnerable areas using MCE techniques. Slope, Aspect, Curvature, Soil, and Distance from Drainage, Land use, Precipitation, Flow Direction, and Flow Accumulation are taken as the causative factors for flooding in Lower Indus Basin. Analytical Hierarchy Process-AHP was used for the calculation of weights of all these factors. Finally, a flood hazard Map of Lower Indus Basin was generated which delineates the flood prone areas in the Sindh province along Indus River Basin that could be inundated by potential flooding in future. It is aimed that flood hazard mapping and risk assessment using open source geographic information system can serve as a handy tool for the development of land-use strategies so as to decrease the impact from flooding.

Upgrade to Nuclear Power Plant Krsko Internal Flooding Probabilistic Safety Analysis

The original internal flooding probabilistic safety analysis （PSA） study of Krsko Nuclear Power Plant （two-loop Pressurized Water Reactor （PWR） plant of Westinghouse design） was performed in mid nineties and limited to reactor core damage risk （Level 1 PSA）. In 2003, it was, together with other safety and hazard analyses, subject to the Periodic Safety Review （PSR）. In the PSR, it was stated that methodological PSA approaches and guidelines have evoluted during the past decade and several observations were provided, concerning the area screening process, residual risk and treatment of plant damage states and risk from radioactivity releases （i.e., Level 2 PSA）. In order to address the PSR observations, upgrade ofKrsko NPP internal flooding PSA was undertaken. The area screening process was revisited in order to cover the areas without automatic reactor trip equipment. The model was extended to Level 2. Residual risk was estimated at both Level 1 and Level 2, in terms of core damage frequency （CDF） and large early release frequency （LERF）, respectively.

Assessing Multidimensional Vulnerability of Rural Areas to Flooding:An Index‑Based Approach

Vulnerability assessment is essential for understanding and launching effective flood risk reduction strategies.This study aimed to examine the vulnerability of flood-prone rural communities in southern Punjab,Pakistan to external shocks.The concept of vulnerability encompasses a range of dimensions,including physical,social,institutional,environmental,economic,and attitudinal.Using a composite index method,indices were developed for each dimension and combined to create a multidimensional measure of vulnerability.A sample of 365 communities was selected using the Yamane sampling technique,and data were collected through a questionnaire containing 65 indicators across all dimensions.Descriptive statistics and ANOVA tests were used to analyze the data.The results show that communities near the Chenab River had higher attitudinal and institutional vulnerability compared to other communities.High attitudinal vulnerabilities were as sociated with poorly perceived flood risks and low preparedness measures,whereas institutional vulnerabilities were driven by conventional flood protection strategies,lack of institutional trust,and lack of flood risk awareness.This research provides insights into the various components of vulnerability in flood-prone rural communities in Pakistan and demonstrates a useful methodology that can be applied to other disasters at different spatial scales.

Human-environmental interaction with extreme hydrological events and climate change scenarios as background

Climate change significantly impacts the lives of all people.Global change is composed of multiple factors that affect the population differently,having a very significant impact in the Mediterranean area.Human beings,through their actions,try to mitigate this impact and thus generate a more resilient society.Extreme hydro-logical events are affected by this climate change,with torrential rainfall events and severe droughts becoming frequent.Understanding these trends will allow us to better adapt to future conditions.This study aims to analyse catastrophic floods and severe droughts from paleo studies to studies that focus on future projections.For this purpose,a search for information has been carried out through other studies over the last five years to have a current perspective of this situation.Studies point to changes in the dynamics of floods and droughts,not only worsening the extremes but also affecting the average values of the records of each.In addition,the studies point out that anthropic action is accelerating the changes,with human beings and their capacity to adapt being infe-rior to the velocity of this global change.It is necessary to generate a paradigm shift in terms of global production by trying to adapt to future extreme flood and drought hazards.

Building-Back-Better in Post-Disaster Recovery: Lessons Learnt from Cyclone Idai-Induced Floods in Zimbabwe

This study evaluated the build-back-better considerations in post-disaster recovery,following the devastation of Chipinge and Chimanimani communities by Cyclone Idai-induced floods in 2019.Conducted in 2020,the study assessed the impact of Cyclone Idai-induced floods on communities in Chipinge and Chimanimani Districts of Zimbabwe;evaluated the build-back-better considerations;and analyzed the lessons learned.Based on a qualitative approach and case study design,the study depended on focus group discussions,interviews,and researcher observations to gather data from 85 participants.The findings indicate that Cyclone Idai-induced floods seriously impacted human lives,infrastructure,and livelihoods of communities that had been living with flood risk and vulnerability.Build-back-better considerations were absent in much of the post-disaster recovery effort to address the cyclone disaster impact.There are important early lessons for both practitioners and community members to learn from the Cyclone Idai event.These lessons still can inform policy and disaster risk reduction practice in the medium and long term.Build-back-better should be a mandatory objective in the recovery from any disaster impact.Continuous training is also recommended to improve the disaster knowledge of stakeholders and increase local ability to cope with future disaster events.

Hydrodynamic modelling of flow impact on structures under extreme flow conditions

Apart from the direct threat to human lives, the flood waves as a result of the rapid catchment response to intense rainfall, breaches of flood defences, tsunamis or storm surges may induce huge impact forces on structures, causing structural damage or even failures. Most existing design codes do not properly account for these impact forces due to the limited understanding of the underlying physical processes and the lack of reliable empirical formulae or numerical approaches to quantifying them. This paper presents laboratory experiments to better understand the interaction between the extreme flow hydrodynamics and the hydraulic structures and uses the measured data to validate a numerical model. The model solves the two-dimensional shallow water equations using a finite volume Godunov-type scheme for the reliable simulation of complex flow hydrodynamics. New model components are developed for estimating the hydrostatic and hydrodynamic pressure to quantify the flow impact on structures. The model is applied to reproduce two selected experiment tests with different settings and satisfactory numerical results are obtained, which confirms its predictive capability. The model will therefore provide a potential tool for wider and more flexible field-scale applications.

Taking Children’s Voices in Disaster Risk Reduction a Step Forward

Disaster risk reduction(DRR) continues to gain momentum globally and locally, but there is a notable void in the DRR literature on the role of children in communitylevel disaster risk management in Zimbabwe. Children are among the most vulnerable groups when disasters occur,yet their voices in disaster risk reduction are rarely heard.Using a qualitative methodology, this article examines the extent to which children are involved in disaster risk reduction in Muzarabani District, Zimbabwe. Despite evidence of the potential positive impact that children can have on DRR, their involvement in risk reduction planning in Zimbabwe is negligible. To achieve greater resilience to disasters requires that children’s voices are heard and recognized as central to improved disaster risk reduction.