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Egyptian Computer Science Journal Vol. 44 No.3 September 2020 ISSN-1110-2586
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Development of an Advanced Knowledge Domain for Coordinated Flood
Inundation Management in Developing Nations
ChukwuNonso H. Nwokoye1, Obiajulu Ositanwosu2, Ikechukwu Umeh3,
1National Open University of Nigeria Unit, Nigeria Correctional Service, Awka, Nigeria.
2,3Computer Science Department, Nnamdi Azikiwe University, Awka, Nigeria.
chinonsonwokoye@gmail.com,ositanwosuobiajulu@yahoo.com,ikumeh@gmail.com
Abstract
Natural hazards such as floods has become in recent times a recurring phenomenon all
over the world. In Africa, its effects has resulted to immense losses. Flood instances in
Anambra state, Nigeria, has ravaged several communities causing deaths, displacements and
damages to infrastructure. Therefore, this study is aimed at developingthe Anambra State
Environmental Protection Agency Flood Management System (ANSEPA FMS), with an
integrated spatial database and to implement this tool using an object-oriented platform of
Visual Studio. This is to cater for several challenges which include the paucity of
comprehensive data and the lack of instances of computer/communication technologies in the
management and control of flood. Also, there exists the issue of isolation; here ANSEPA
(under the State Ministry of Environment (SME)) hardly shares information to other
flood/disaster-related agencies.On the methodology, firstly, we used data collection methods
like observation, study of procedural manuals and interview of operators at functional
(strategic) points of the institution in order to obtain necessary data and information.
Subsequently, we performed system analyses and design, implementation and testing.The
spatial database and corresponding forms was built based on the recent holistic flood
management knowledge domain proposed by Kaewboonmaa, et al., which employed
experts’opinions in its conception. Aside the benefit of assuming a central position for data
sharing amongst related agencies, ANSEPA FMS can positively impact study area familiarity,
thereby, instigating vulnerability assessment and triggering the necessary post-flood readiness
required for prompt response to flood inundation.
Keywords: Knowledge domain, Information System, Flood Management, Nigeria, Africa
1. Introduction
Floods make up one-third of natural disasters with approximately 37.1% [1], and this is
due to urbanization and immense rise in human population, which allows for the continual
transformation of open places to housing units and workplaces. More so, climate change is
also a major reason for instances of flood. Considering the health consequences, threats,
deaths, tragedies and related losses of floods, officials of nations and affected regions are
becoming increasingly concerned. This is because the cost of damages caused by this
hydrological extreme increases annually. In Africa, statistics has it that 19.59% of 1,699
disasters in 2017 was flood-related and specifically, approximately 28 people died in every
event. In 2017, flood caused distress for 73,906.93 persons, and 7,402.12 others experienced
untold hardship as a result [1]. All these shows that, “natural disasters occurring in African
countries undermine the economic survival of poor communities” [2]. Countries such as
Mozambique, Malawi, Zimbabwe, Botswana, Namibia, have experienced deaths and
displacements in the past. Similarly, in Togo, Ghana, Mauritania, residents were in dire need
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of assistance as flood ravaged communities. X-raying East and Central Africa; people have
been rendered homeless while crops and livestock were grossly damaged as a result of
torrential rain and flood in Uganda, Sudan, Ethiopia, livestock, Rwanda and Kenya. In
Nigeria, flooding has affected its 36 states including the Federal Capital Territory, Abuja. In
the north-east region, it demolished roads and made difficult the landing of airplanes [3]. In
the words of Okpala [3], “the causes of flood are improper city planning with regard to layout
of building and other structures, poor drainage system, over population, government
irresponsibility and climate change. On the other hand,to proffer management solutions,
researchersposit that, “advances in computer and communication technologies have
influenced the movement of the old fashioned hard copy flood maps, graphs and tables to
more sophisticated form; providing much needed real time flood information in more detail,
such as computerization of the flood prediction operations and usage of GIS as a platform for
interaction with the users”[4].Evolutions in computer and communication technologies have
governed the move from the obsolete maps, tables and graphs to more complicated systems
that present timely and elaborate flood data and information. But essentially, there is the need
to address a fundamental requirement for the introduction of other complex computer and
communication technologies i.e. building a system that allows comprehensive and updated
knowledge acquisition.Review of information systems studies on disasters showed that
African nations are yet to vigorously apply instances of computer/communication
technologies in the management and control of flood. Although, they perform post-flood
management activities such as providing and catering for displaced persons, the dead etc.,
they are yet to introduce information systems (IS) for any of the phases of flood
inundation.During investigation, we noticed several issues with flood management and
control in Anambra state, Nigeria. As Okpala [3] puts it, “Anambra state is always affected by
flood because it is situated at the lowest point of the River Niger, submerging in water local
government areas such as Anambra West, Anyamelum, Anambra East and Ogbaru”. Firstly,
we observed from the few data available at the Anambra State Environmental Protection
Agency (ANSEPA) (under the State Ministry of Environment) that the flood-prone areas in
the state include Onitsha, Obosi, Nkpor, Iyowa Odaekpe, Ogidi (Afor Igwe), Awka (Iyiagu,
Arthue Eze lane, Ziks Avenue) etc. However, we discovered that the agency do not use any
kind of IS for collecting, organizing, analyzing and presenting flood-related data and
information. The little information they possess are written on papers/notes and the
information was found to be grossly inadequate and insufficient for effective and efficient
management and control of flood in the state.
Interview of the personnel of the agency showed that there are other agencies under the
State Ministry of Environment that are involved in different phases of flood inundation. They
include Nigerian Erosion and Watershade Management Project (NEWMAP), State
Emergency Management Agency (SEMA) and the Nigerian Inland Waterways Agency
(NIMA). However, we discovered that these agencies work in isolation and like ANSEPA,
they all possess few data and information for the effective management of flood (and every
other disaster type) in the state. This isolated approach of flood control tends to make
knowledge sharing difficult for these agencies. The management of ANSEPA alluded to the
inclusion of other experts that will help Anambra state in handling flood issues, for example,
by monitoring, controlling the water condition as well as the removal of waste blocking
gutters and drainages. Actually, the knowledge owned by these experts and agencies are
inadequate. Furthermore, the few existent flood-related information are yet to be captured,
categorized and incorporated into an IS for purposes of proactive decision making.
Interestingly, this situation matches the challenges faced by Chi River Basin (CRB), Thailand
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which necessitated research efforts expended by Kaewboonmaa, et al. [4], only that the
African (Nigeria) case is even worse i.e. there are no data. These authors used document
analysis, qualitative methods as well as the interview of professionals in Geographic
Information Systems (GIS), Environmental engineering and Water resources engineering, so
as to develop a comprehensive knowledge domain for flood management.
In view of these issues, our study, therefore, aims at developing an IS platform, which
is a pragmatic extension of the proposal in Kaewboonmaa, et al. [4]. Thiswould enable data
capturing and other capabilities that facilitates proper management of flood in the state.
Specifically, this system would be implemented using an object-oriented platform such as the
Visual Studio. In addition, our study goes further to presents a method in which ANSEPA,
with the developed tool assumes a central position that makes it possible for other related
agencies to share information i.e. a statewide data sharing and integrated approach to flood
management as described in Figure 1. From the diagram, “OTHERS” implies other well
spirited individuals, churches, state-based arm of the Nigerian Armed Forces (i.e. Army and
Navy formations), the Nigeria Police Force, non-governmental institutions (NGO) that partner
with Anambra state during post-disaster times.
2. Related Works
In this review, we hope to learn insights that will impact positively the design and
implementation of Flood Management System (FMS). Note that decisions support systems
(DSS) and geographic information systems (GIS) enjoyed the most usage in the automation of
flood management and administration. While conducting a literature search, which resulted in
the review below, we couldn’t find a study bearing the aversion of flood in Africa in mind,
and this singular reason underlies the essentiality of work herein.
Parker and Fordham [6] presented results from the EUROflood research project which
assessed the degree of advancement in flood prediction, notifications and response structures
within the European Union in relation to foods in Netherlands, the United Kingdom,
Germany, France and Portugal. In order to serve the needs of decision-makers and
stakeholders in the Red River Basin, Simonovic [7] developed and implemented a Red River
Basin Decision Support System(REDES), wherein the purpose is to move past improving
readiness, strategizing, reactions and recovery to flood forecast, inspection, response at
emergency times as well as residents involvement in control, management and administration
of flood. The study by Todini [8] shed light on the development of a wholesome tool for flood
strategizing and management, so as to exploit the merits of the ubiquitous high level
computing platforms. With this system, it was possible to identify risk areas, estimate
potential damages and predict hydrological extremes by relying on a real-time understanding
of the current meteorological scenario as well as the extant forecasts at diverse spatio-
temporal scales.
Sanders and Tabuchi [9] evaluated the advantages of creating a DSS for flood-related
risk assessment alongside its applications, with emphasis on the insurance industry.
Furthermore, the study elaborates on the “Intederometric Synthetic Aperture Radar
(IFSAR)map products data in the building of a huge flood risk assessment system for the
River Thames in the United Kingdom”.Shim, et al. [10] built a prototype spatial DSS for
wholesome, timely river basin flood management for a system that possessed numerous
reservoirs and purposes. In the words of the authors, “this DSS incorporates, a database
system, a real-time meteorological and hydrological data monitoring system, a model-base
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subsystem for system simulation and optimization, and a graphical dialog interface allowing
effective use by system operators”. After studying diverse system development approaches
for the object-oriented idea, Mwakapuja [11] built a GIS that caters for local level flood
management; this is due to recurring nature of environmental hazards. The gruesome deaths
and huge destruction of physical infrastructure and social/economic activities in the Red River
basin caused by flood disasters inspired Booij [12] to develop a DSS for identifying and
selecting a better mixture of flood management and ecosystem development initiatives. As
part of a joint IST project between the EU and the People’s Republic of China, Prastacos, et
al. [13] designed and implemented a DSS called ANFAS, which is an online platform,
possessing a distributed internal structure that allows the management level executives to
estimate future flood effects by varying system parameters of river floods.
Ahmad and Simonovic [14] developed a smart DSS which incorporated knowledge
possessed by humans so as to provide virtual assistance for decision makers who daily
strategize to solve both engineering and non-engineering associated to flood control at
different phases. To alleviate the limitation of only making availablehard copy inundation
maps in a specific GIS application format, Muncaster, et al. [15] developed a web-based GIS
interface to enable online access and interpretation of maps. In the light of the statistics that
named Gold Coast as Australia’s most susceptible location for flood inundation,Mirfenderesk
[4] built a flood emergency DSS amongst a decade-long flood and drainage plan to address
the issue of an increase in residual flood risk. Complexities in the urban environment and the
lack of high-resolution topographic and hydrologic data compromise the development and
implementation of models of non-riverine flooding in urban areas spurred Chen, et al. [16] to
perform a case study analysis of an urban university campus to develop and test a GIS-based
urban flood inundation model (GUFIM). The essentiality of an exhaustive knowledge of flood
risk in different spatial locations and the development of a flood mitigation scheme for a
watershed motivated Karmakar, et al. [17] to perform a flood risk-vulnerability analysis using
a GIS, with emphasis on the four categories of vulnerability to flood (i.e. physical, the
economic, infrastructural and social).
Honghai and Altinakar [18] developed a DSS for integrated flood management within
the framework of ArcGIS based on realistic two dimensional flood simulations. This system
has the ability to interact with and use classified Remote Sensing (RS) image layers and other
GIS feature layers like zoning layer, survey database and census block boundaries for flood
damage calculations and loss of life estimations. Ibañez, et al. [19] designed and implemented
a DSS that is based on an open-shell platform for integrating various data sources and
different simulation models. In order to display the benefits of applying information
technology in monitoring and enhancing flood response management, Hysenaj [20] developed
a GIS that allows the presentation of a complete statistic synopsis of flood occurrences in the
region. Laine,et al. [21] described the development of a new flood management DSS which
significantly enhances the ability of flood practitioners to; “identify adaptation and mitigation
solutions to flood inundation, facilitate objective community flood risk management
consultation and justify floodplain management decisions in a transparent and structured
manner to all stakeholders”.Demir and Krajewski [22] developed the community-centric Iowa
Flood Information System (IFIS) – “a web-based platform application to provide access to
flood inundation maps, real-time flood conditions, flood forecasts both short-term and
seasonal, flood-related data, information and interactive visualizations for communities in
Iowa”. Due to numerous reoccurrences of flood in the Portuguese river Lima basin, Vieira, et
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al. [23] built a DSS called FEWS-LIMA, which incorporates a hydrological database and
model for flood forecasting and was implemented by employing the Delft-FEWS software.
To curb the imminent occurrences of long term risk (due to climate change and
population growth) and to facilitate the development of long-term flood mitigation plans,
Maier, et al. [24] developed a framework for a DSS framework consisting of an integrated
model consisting of dynamic, spatially distributed land-use and flood inundation models. Due
to the floods that struck Johor state in 2006 and 2007 and the East Coastal in 2014, flood
management using IT has been greatly triggered in Malaysia. Bukari, et al. [25] showed how
a GIS can be used to identify potential areas of flooding. Mirfenderesk, et al. [26] challenged
the following paradigm; “that undertaking complex flood simulation models has been
considered as infeasible in the short time available during a flood emergency and this has
warranted the use of surrogate or simplified flood modelling systems in the DSS of flood
emergency management”. The desire for this paradigm shift is underpinned by the recent
advent of Graphic Processing Unit (GPU) flood modelling systems and sophisticated web-
based GIS systems that can better present the results of these models. Muste and Firoozfar
[27] identified several reasons that calls for the formation of a strategic global partnership for
framing and subsequently assisting in the development of a generalized flood DSS
(FLOODSS) that can overcome the current associated drawbacks. Xu, et al. [28] identified
several issues with the existent Enterprise Information Systems (EISs) designed for urbanized
flood control. Therefore, they proposed a cloud-based asset management platform to cater for
some of the highlighted challenges which include; “ineffective management of physical assets
which has greatly impeded their deployment, the sharing of assets and services between
agencies, and ensuring real-time and flexible decision supports.
Our literature search availed few studies related to flood management and control that
did not necessarily involve the use of an IS such as FIS, DSS, GIS and EIS. These were
discussed here. Ghozalia, et al. [29] attempts to make a case for climate change as having
significant direct and indirect impact on flood risks by exploring flood management
procedures in in Ayutthaya, Thailand and Samarinda, Indonesia using both primary and
secondary data, while qualitative methods were used for analysis. Findings of the study
depicts that the flood risk on both cities has same characteristics and indicates that the role of
government of Ayutthaya also stronger than Samarinda. Since Huaihe River Basin is a
transitional river which has been frequently hit by big floods and has suffered from flood
disasters; it motivated Wang, et al. [30] to summarize flood management and disasters of the
River basin, and then summarizes achievements in flood control and management. The fact
that climate change is expected to cause rise in both the magnitude and frequency of extreme
precipitation instances, which culminatesto hugely intense and frequent river flooding
inspired Shrestha and Lohpaisankrit [31] to assess the flood hazard potential under climate
change scenarios in Yang River Basin of Thailand.
In summary, the reviewed works involved DSSs [4, 9, 10, 12-14, 18, 19, 21, 23, 24, 26-
27], GISs [11, 15-17, 20, 25] and an EIS [28]. Unlike these studies, our work herein proves
more holistic and comprehensive i.e. it includes not only scientific data which are necessary
for flood forecast, response and recovery, it also allows for a more detailed approach to
making decisions related to water management using geo-informatics (ground water, bank
line, river basin network etc.) and historical data such as climate, population, irrigation
demands, irrigation efficiency as well as soil/water conservation and moisture.
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3. Methodology
Major methodologies for developing an IS include the Structured System Analysis and
Design Methodology (SSADM), Systems-Development Life Cycle (SDLC), Rapid
application development (RAD) and Agile approaches. A thorough look at these
methodologies [32]shows they all include requirement gathering, system analysis, design, and
implementation. Therefore, we would concentrate and present herein the requisite activities
performed for these phases of IS development.
Requirement Gathering Phase: The developed application has some needs that must be
fulfilled for it to function efficiently. FMS is an electronic platform needed by staff of
ANSEPA and other related agencies of the SME for the proper management of flood and
other disasters in the State. The system mirrors an efficient and secure manner of handling
flood-related issues. Since most of our conceptions are for a non-existent system, ANSEPA
would have to think of employing information technology (IT) personnel or retrain its staff in
system security and administration; and with these skills they can secure there IT
infrastructure and manage the electronic system respectively. These trained staffalongside
other ANSEPA staff ensure that all necessary data and information are collected, documented
and used for appropriate decision making in all the phases of flood management. Aside
documentation, the developed system must achieve the needs of authorization and
authentication according to the regulations of the agency. At this phase, we were able to elicit
several challenges facing the agency. As a result of in-depth analysis and investigation of the
present system, its policies, practices and procedures, many weaknesses were identified. In
order to have an efficient service delivery, the following weaknesses are worthy of note. First,
books are used to store data, which implies manual data entry and recovery procedures as well
as slower update and retrieval of information. Consequently, operations are prone to errors.
Additionally, there is the challenge of unavailability of information for faster decision making
and less effective method of sorting and searching for required information. The managerial
approach is adjudged tough and consumes a lot of time and labor. All these are issues still add
to the isolated nature of the overall flood administration. However, the proposed design of an
IS would eliminate the above weaknesses as well as enhance the smooth running of Anambra
State Environmental Protection Agency (ANSEPA).
System Analyses: for the developed system we channeled analytical thoughts towards
prospective graphics and functions of the ANSEPA FMS. On the graphics, we noted color
schemes, logos and as well as other images to be employed. Subsequently, the colors used
included white, ash, pink, yellow alongside the map of Anambra state, Nigeria (on the home
page) while the renowned unified modeling language (UML) was used to express the
necessary functions of the system. The gallery also holds photographs of several damages
caused by the flood over time. On the navigation of the system, Figure 2 shows the main
menu of the knowledge system i.e. a graphical description of the road throughout the FMS.
UML diagram were employed in order to shed light on the requirements of ANSEPA in flood
management, which include addressing both pre-flood and post-flood activities, implementing
government land use policies and increasing the learning experience of the their staff on
predictions for proactive management. Figure 3is a UML case diagramthat incorporates roles
and functions in the proposed ANSEPA FMS. In the light of the organizational structure of
ANSEPA, the case diagrams depicts activities that may be performed by officials i.e.
Secretary (lower level management), Engineer 1, Engineer 2, Field Inspector(middle level
management), and Chairman/Director and General Manager (top level management)as well as
other stakeholders that help in flood recovery. On the database specifications, we used
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MySQL for the creation of tables that will eventually hold scientific data, historical data,
geoinformatics data, pre-flood social and economic data, post flood scientific data, flood
response and the flood recovery data. Figure 4 shows a topmost section of theANSEPA
FMSflowchart.
Figure 1. Data sharing approach Figure 2. Main Menu of FMS
Figure 3. Use case diagram for FMSFigure 4. Flowchart of the Proposed FMS
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Design: With the requirements gathered from the analysis performed above, the
graphical user interface (GUI) layout of the FMS is created. More so, we ensured that these
interfaces possessed the vital elements, and this is was achieved by involving the actual users
of the system, which are the ANSEPA officials themselves. The aim of an active user
involvement in our design is to increase the usability of the final application. Note that the
minimum hardware requirements needed to run the developed application are processor –
Intel 80586 and above, hard disk capacity of 4 Gigabyte and above, with an enhanced window
keyboard, DVD/CD ROM, a printer and a computer that has both webcam and Bluetooth. On
the software requirements, there is need for the installation of the operating system (Windows
or Linux) as well as the Visual Studio with the .Net framework.
Implementation and Testing : As was stated above, the database tables was created
using MySQL while actual coding was done with Visual Studio. This integrated dvelopment
environemnt (IDE) was used due some of its beenefits which include assited/accurate coding,
quick debugging, rigourous testing and team colloboration. At first, we implemented smaller
modules, and thereafter, these modules were brought together to meet several designated
specifications. We commenced the testing phase, as soon as the implementation of all the
necessary moduiles were complete. This is to identify errors of any kind that may hinder the
smooth running of the application. Some of the forms are presented below.The results of the
study are GUIs, which are described as figures 5 – 11. Figure 5shows the login page for the
flood activities (or different modules) involved in the ANSEPA FMS. They include Pre-flood,
Post-flood Activities, Government Policy and Land Use, Guided Learning Experience and the
Events/Images Gallery. The user chooses a particular flood activity and inserts the right
username and password in order to gain access into the system. Figure 6 consists of renowned
and emerging flood areas in the State. It also allows the inclusion of more flood prone areas to
the two categories mentioned. On that same screen are buttons for acquiring several flood-
related knowledge such as scientific data, geo-informatics data and the social/economic losses
incurred. Figure 7 allows input for scientific data such as flood area, date, frequency, severity
level, images, observation, water level, ground water level, rainfall, water quality, flood
hazard and dam break hazard. Figure 8 depicts the historical and geoinformatics data i.e. we
allowed the collection of two different types of data using one input/output form. Data that
consistitute historical information inlcude climate, cropping pattern, deficiencies, ground
water, irrigation demand, land used, potential evans-transportation, population, reservoir, soil
moisture, irrigation efficiencies, stream flow and water used. While the data that consistute
the geoinformatics information include; bank line, contour, dam location, digital elevation,
flow part, hydro edge, hydro junction, LU manning, river basin network, contour and profile,
spot GPS, height and river etc.Figure 9 and 10 allows the documentation of social/economic
losses for both the pre and post flood phases.
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Figure 5. Welcome Screen for the Proposed FMS Figure 6. Top Form for Pre-flood Activities
Figure 7. Scientific data screen Figure 8. Historical/GeoInformatics form
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Figure 9. Pre-flood Social/Economic Losses Form Figure 10: Post-flood Social and Economic Losses
Note that the losses in Figure 9 and Figure 10 include tangible direct, tangible indirect
and tangible human and other damages for primary, secondary and tertiary categories of
losses due to disaster. These forms allow the user check the applicable losses. Primary losses
can be in form of damages to buildings (and other infrastructure), crops, animals, death,
heritage and archeological sites. Secondary losses can be fire damages, crop yield reduction,
water contamination, work disruption as well as increased stress, physical and psychological
trauma, and ill-health. While tertiary losses include property deformation/decay, loss of
imports/exports, reduced GDP, homelessness, loss of livelihoods and total loss of possessions.
Figure 11depicts the post-flood form which allows the electronic documentation of both flood
response and its recovery. Specifically, it allows inputs for rainfall, channels, evacuation
team, risk forecast, weather forecast, tide predictions, peak river height, predicted river height,
river levels and temperature. Whereas for flood recovery it collects information on evacuation
center name and locations, donations, water level, committee name and committee decisions.
Finally, Figure 12 shows the events and gallery form, wherein photographs and training
events meant to enlighten the members of ANSEPA staff are displayed.
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Figure 11. Post-flood Form Figure 12. Events and gallery form
4. Conclusion and Future Work
The study proposed the design and implementation of the ANSEPA FMS, which allows
for better coordinated flood administration. FMSwould play a major role in collecting,
organizing, analyzing and presenting data for all flood phases allowing proactive
management. More so,the system would enable documentation and sharing of knowledge
meant for responsible flood-related organizations and researchers who are the experts in
monitoring and controlling the parameters that influence flood. With this system, the
knowledge owned by professionals can be easily captured, categorized and integrated better
for decision making. Note that since we built the system for the state level, FMS can be used
to formulate investment projects and specific investment mitigation plans. With extensions
suggested in this study, the FMS can also beused at the national level for study area
familiarity to planners who need references for the whole disaster scenario and at the regional
level for analyzing resources and identifying viable projects. In the light of the comprehensive
data collected, the system can be used to initiate flood and area vulnerability evaluation as
well as the activation of the readiness required for post-flood phases where authorities seek to
respond, recover and reconstruct all form of damages/losses. Since our study advocates the
inclusion of ‘flood inspectors’, alongside the developed flood management system, our work
herein would provide a monitoring capability that may add to the mitigation strategies
formulated by Anambra state. In the future, when ANSEPA staff and all stakeholders must
have appreciated the impact of the developed FMS, we would explore the possibilities of
mobile version of the tool, wherein the masses are allowed to contribute to flood management
and control.
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