Study of Digital Surface Data for Soils and Flood Risk Areas Mapping in Sudano-Sahelian Zone (Mayo-Danay Division, Far North Cameroon)

2021 ◽  
Vol 10 (1) ◽  
pp. 3473-3491
Author(s):  
TIKI Denis ◽  
◽  
BITOM Mamdem Lionelle ◽  
IBRAHIM Achille ◽  
SOUNYA Jean Boris ◽  
...  
Keyword(s):  
Spatial Data ◽  
Flood Risk ◽  
Multicriteria Analysis ◽  
Urban Environments ◽  
Careful Study ◽  
Risk Areas ◽  
Vertic Soils ◽  
Flooding Risk ◽  
Hazard Level ◽  
Excellent Tool

In general, living close to a river is advantage, but there is always of flooding risk, that recurrence in recent decades provokes serious material damage and loss of life. Thus, in order to protect environmental health, economic viability and human activity zones of Mayo-Danay, a careful study of components of natural environment, mainly soil, has proved essential. Clearly, use of GIS in management of natural disasters is most relevant method, designed on integration, Multicriteria Analysis (MCA) and spatial data. Thus, Digital Elevation Model is obtained by manual digitization of contour lines, in order to define the large pedological sets on which wells have been opened, profiles described, soil samples taken and analyzed in laboratory. Main results reveal that soils are sandy to clayey, with neutral and basic pH (7 to 8), high CEC and low organic matter. While, quartz is predominant, associated with smectites, illites, feldspars and iron oxyhydroxides. Updated soil map shows five soil units (1) vertisols with hydromorphic characters (26%), (2) tropical ferruginous soils (32%), (3) less evolved hydromorphic soils (15%), (4) halomorphic vertic soils (9%), and (5) hydromorphic vertic soils (18%). It is an excellent tool for work and research, that responds to agronomic and development problems. It is therefore an excellent tool for work and research, which responds to agronomic and development problems. The multi-criteria spatial analysis establishes hazard and vulnerability, crossing of which gives of flood risk areas map, according to hazard level, very high (12%), high (16%), moderate (14%), low (30%) and very low (28%) risks. For this purpose, it emerges that rainfall is relatively low (700 mm/year), but falls very abruptly during short periods, at high intensity with flows exceeding the infiltration capacities. Morphology of low-slope "yayrés" (280 m) (2‰) is bordered by high landscape (500 to 1400 m) that prevent flow of many rivers that converge into plain. Sandy soils dominated by quartz favor fast rising in water table, while very clayey soils governed by 2/1 clayey (smectites) whose behavior induce waterproofing and intense surface runoff that generate flooding. Evidently, land use change leads to transformation of natural spaces into agricultural and urban environments, which makes soils more compact and impermeable, favorable to flooding. Keywords Soil; Flood risks; Mapping; Mayo-Danay Division; Spatial data DOI: https://doi.org/10.23953/cloud.ijarsg.501

scholarly journals A review of modelling methodologies for flood source area (FSA) identification

2021 ◽  
Author(s):  
Amrie Singh ◽  
David Dawson ◽  
Mark Trigg ◽  
Nigel Wright
Keyword(s):  
Flood Risk ◽  
Risk Mitigation ◽  
Ground Cover ◽  
Source Area ◽  
Urban Environments ◽  
Weather Patterns ◽  
Complex Process ◽  
Average Annual Loss ◽  
Flood Source ◽  
Modelling Approaches

AbstractFlooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises.

Urban Environmental Applications of GIScience

2013 ◽  
pp. 602-620 ◽  
Author(s):  
Buket Ayşegul Ozbakir
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Spatial Data ◽  
Information Science ◽  
Geographic Information ◽  
Urban Environments ◽  
Geographical Data ◽  
Technological Advances ◽  
Information Research ◽  
Computer Based

Geographic Information Systems (GIS) are computer-based systems used to store and manipulate geographical data, and perform spatial analysis. These systems serve to reveal the patterns, relationships, and anomalies, or sometimes invisible characteristics of the geographical data in various applications. While the term “GIS” indicates an object or tool, GIScience, the acronym for Geographic Information Science, covers a broader context of methodologies behind spatial data analysis. Among different application areas of GIS, “environmental monitoring and modeling” plays a significant role in the development of the very first GIS in the world-The Canada Geographic Information Systems (CGIS) in the mid-1960s. After almost 40 years of history, significant changes and challenges took place in the geographic information research agenda. This chapter will point out some of the vital tools and methods used in GIScience (including GIS, remote sensing and 3D modeling) to grasp issues of our urban environments. With recent technological advances that facilitate our understanding of the environment; it is more evident that the vision of more “livable” cities is not too far but not easy as well.

scholarly journals Urban Flood Hazard Modeling Using Self-Organizing Map Neural Network

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2370 ◽  
Author(s):  
Rahmati ◽  
Darabi ◽  
Haghighi ◽  
Stefanidis ◽  
Kornejady ◽  
...  
Keyword(s):  
Neural Network ◽  
Flood Risk ◽  
Goodness Of Fit ◽  
Flood Hazard ◽  
Characteristic Curve ◽  
Urban Environments ◽  
Hazard Mapping ◽  
Self Organizing Map ◽  
Urban Flood ◽  
Self Organizing

Floods are the most common natural disaster globally and lead to severe damage, especially in urban environments. This study evaluated the efficiency of a self-organizing map neural network (SOMN) algorithm for urban flood hazard mapping in the case of Amol city, Iran. First, a flood inventory database was prepared using field survey data covering 118 flooded points. A 70:30 data ratio was applied for training and validation purposes. Six factors (elevation, slope percent, distance from river, distance from channel, curve number, and precipitation) were selected as predictor variables. After building the model, the odds ratio skill score (ORSS), efficiency (E), true skill statistic (TSS), and the area under the receiver operating characteristic curve (AUC-ROC) were used as evaluation metrics to scrutinize the goodness-of-fit and predictive performance of the model. The results indicated that the SOMN model performed excellently in modeling flood hazard in both the training (AUC = 0.946, E = 0.849, TSS = 0.716, ORSS = 0.954) and validation (AUC = 0.924, E = 0.857, TSS = 0.714, ORSS = 0.945) steps. The model identified around 23% of the Amol city area as being in high or very high flood risk classes that need to be carefully managed. Overall, the results demonstrate that the SOMN model can be used for flood hazard mapping in urban environments and can provide valuable insights about flood risk management.

scholarly journals Assessing urban recreation ecosystem services through the use of geocache visitation and preference data: a case-study from an urbanised island environment

One Ecosystem ◽  
2018 ◽  
Vol 3 ◽  
pp. e24490 ◽  
Author(s):  
Mario V Balzan ◽  
Iain Debono
Keyword(s):  
Ecosystem Services ◽  
Spatial Data ◽  
Green Infrastructure ◽  
Ecosystem Service ◽  
Urban Areas ◽  
Cultural Landscapes ◽  
Stated Preference ◽  
Urban Environments ◽  
Cultural Ecosystem Service ◽  
Direct And Indirect Benefits

Recreation is an important cultural ecosystem service and is one way in which communities experience the direct and indirect benefits arising from the experiential use of their environment. The recent rise in popularity of Global Positioning System (GPS) game applications, which combine information technology with an activity that increases mobility and encourages outdoor enjoyment, provides ecosystem service practitioners with an opportunity to make use of this georeferenced data to assess recreational ecosystem services. Geocaching is one such worldwide outdoor game. It has fixed points of incursion where people can hide and look for caches. This study explores the possibility of using geocaching data as a proxy for recreational ecosystems services in the Maltese Islands. A quantitative analysis of the georeferenced caches was used together with their visit rates and number of favourite points. This was supplemented by two questionnaires that investigated the preferences and experiences of both geocache placers (n=39) and hunters (n=21). Results show that the highest number of caches were placed and searched for in urban areas and that geocaching is strongly associated with the presence and accessibility of urban green infrastructure. The number of geocachers who stated preference for experiences in nature did not translate into high visit rates to sites of high conservation value (protected areas) but landscape value was significantly associated with recreational ecosystem services flow. The results presented here provide evidence that geocaching spatial data can act as an indicator for assessing and mapping recreational ecosystem services in urban environments and in cultural landscapes.

scholarly journals Vulnerability Assessment of Urban Floods in Lahore, Pakistan using GIS based integrated Analytical Hierarchy Approach

2021 ◽  
Vol 58 (1) ◽  
pp. 85-96
Author(s):  
Sahar Zia ◽  
Safdar A. Shirazi ◽  
Muhammad Nasar-u-Minallah
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Urban Areas ◽  
Physical Factors ◽  
Urban Flooding ◽  
Residential Areas ◽  
Urban Flood ◽  
Risk Areas ◽  
Practical Tool ◽  
Flood Risk Mapping

Urban flooding is getting attention due to its adverse impact on urban lives in mega cities of the developing world particularly Pakistan. This study aims at finding a suitable methodology for mapping urban flooded areas to estimate urban flooding vulnerability risks in the cities of developing countries particularly Lahore, Pakistan. To detect the urban flooded vulnerability and risk areas due to natural disaster, GIS-based integrated Analytical Hierarchy Process (AHP) is applied for the case of Lahore, which is the second most populous city and capital of the Punjab, Pakistan. For the present research, the flood risk mapping is prepared by considering these significant physical factors like elevation, slope, and distribution of rainfall, land use, density of the drainage network, and soil type. Results show that the land use factor is the most significant to detect vulnerable areas near roads and commercial areas. For instance, this method of detection is 88%, 80% and 70% accurate for roads, commercial and residential areas. The methodology implemented in the present research can provide a practical tool and techniques to relevant policy and decision-makers authorities to prioritize and actions to mitigate flood risk and vulnerabilities and identify certain vulnerable urban areas, while formulating a methodology for future urban flood risk and vulnerability mitigation through an objectively simple and organizationally secure approach. 

scholarly journals Flood risk assessment in selected communes of the Łódź region

2017 ◽  
pp. 21-41
Author(s):  
Marta Borowska-Stefańska
Keyword(s):  
Flood Risk ◽  
Land Development ◽  
Risk Level ◽  
Individual Risk ◽  
Negative Consequences ◽  
Risk Levels ◽  
Risk Areas ◽  
High Flood ◽  
Very High ◽  
Risk Categories

The aim of the article is to assess the present level of land development of flood risk areas in selected communes of the Łódź province in the context of potential negative consequences for people, the natural environment, cultural heritage and economic operations. The research includes urban as well as urban and rural communes (9 communes in total) of the Łódź province which display high and very high flood risk levels according to the methodology used in Flood protection operating plan for the Łódź province from 2013 ( Plan operacyjny… 2013). Uniejów and Warta have the highest synthetic flood risk levels due to the surface occupied by buildings and areas assigned to individual risk categories. In turn, Łowicz and Tomaszów Mazowiecki (town) display the highest general flood risk level due to diversification of buildings and areas of individual risk categories.

scholarly journals Environmental Inequalities in Flood Exposure: A Matter of Scale

2021 ◽  
Vol 3 ◽  
Author(s):  
Clémence Poussard ◽  
Benjamin Dewals ◽  
Pierre Archambeau ◽  
Jacques Teller
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Economic Status ◽  
Flood Hazards ◽  
Socio Economic Status ◽  
Flood Exposure ◽  
Class 1 ◽  
Riverine Floods ◽  
Peripheral Areas ◽  
Hazard Level

Studies on inequalities in exposure to flood risk have explored whether population of a lower socio-economic status are more exposed to flood hazard. While evidence exist for coastal flooding, little is known on inequalities for riverine floods. This paper addresses two issues: (1) is the weakest population, in socio-economic terms, more exposed to flood hazard, considering different levels of exposure to hazard? (2) Is the exposure to flood risk homogeneous across the territory, considering different scales of analysis? An analysis of the exposure of inhabitants of Liège province to flood risk was conducted at different scales (province, districts, and municipalities), considering three levels of exposure to flood hazard (level 1- low hazard, level 3- high hazard), and five socio-economic classes (class 1-poorest, class 5-wealthiest households). Our analysis confirms that weaker populations (classes 2 and 3) are usually more exposed to flood hazards than the wealthiest (classes 4 and 5). Still it should be stressed that the most precarious households (class 1) are less exposed than low to medium-range ones (classes 2 and 3). Further on the relation between socio-economic status and exposure to flood hazard varies along the spatial scale considered. At the district level, it appears that classes 4 and 5 are most exposed to flood risk in some peripheral areas. In municipalities located around the center of the city, differences of exposure to risk are not significant.

scholarly journals Assessment of Flood Risk Map under Climate Change RCP8.5 Scenarios in Taiwan

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 207
Author(s):  
Yun-Ju Chen ◽  
Hsuan-Ju Lin ◽  
Jun-Jih Liou ◽  
Chao-Tzuen Cheng ◽  
Yung-Ming Chen
Keyword(s):  
Climate Change ◽  
High Risk ◽  
Flood Risk ◽  
Spatial Scales ◽  
Disaster Risk ◽  
Decision Makers ◽  
Risk Map ◽  
Climate Data ◽  
Risk Areas ◽  
Flood Risk Map

Climate change has exerted a significant global impact in recent years, and extreme weather-related hazards and incidents have become the new normal. For Taiwan in particular, the corresponding increase in disaster risk threatens not only the environment but also the lives, safety, and property of people. This highlights the need to develop a methodology for mapping disaster risk under climate change and delineating those regions that are potentially high-risk areas requiring adaptation to a changing climate in the future. This study provides a framework of flood risk map assessment under the RCP8.5 scenario by using different spatial scales to integrate the projection climate data of high resolution, inundation potential maps, and indicator-based approach at the end of the 21st century in Taiwan. The reference period was 1979–2003, and the future projection period was 2075–2099. High-resolution climate data developed by dynamic downscaling of the MRI-JMA-AGCM model was used to assess extreme rainfall events. The flood risk maps were constructed using two different spatial scales: the township level and the 5 km × 5 km grid. As to hazard-vulnerability(H-V) maps, users can overlay maps of their choice—such as those for land use distribution, district planning, agricultural crop distribution, or industrial distribution. Mapping flood risk under climate change can support better informed decision-making and policy-making processes in planning and preparing to intervene and control flood risks. The elderly population distribution is applied as an exposure indicator in order to guide advance preparation of evacuation plans for high-risk areas. This study found that higher risk areas are distributed mainly in northern and southern parts of Taiwan and the hazard indicators significantly increase in the northern, north-eastern, and southern regions under the RCP8.5 scenario. Moreover, the near-riparian and coastal townships of central and southern Taiwan have higher vulnerability levels. Approximately 14% of townships have a higher risk level of flooding disaster and another 3% of townships will become higher risk. For higher-risk townships, adaptation measures or strategies are suggested to prioritize improving flood preparation and protecting people and property. Such a flood risk map can be a communication tool to effectively inform decision- makers, citizens, and stakeholders about the variability of flood risk under climate change. Such maps enable decision-makers and national spatial planners to compare the relative flood risk of individual townships countrywide in order to determine and prioritize risk adaptation areas for planning spatial development policies.

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