The Most Devastating Natural Hazards Environmental Sciences Essay
This chapter reviewed disaster and its devastating effects in a broad context focusing especially on flood risk disaster and thereafter flood risk assessment and its various methodologies; flood estimation techniques for arriving at estimates of flood flows in stream needed to identify flood risk area and methods of delineating floodplains for purpose of overall objective of this project.
2.2 Review of Relevant Literature
Disaster as defined by United Nations International Strategy for Disaster Reduction (UNISDR) in terminology on Disaster Risk Reduction 2009 edition is, a result of the combination of: the exposure to a hazard; the conditions of vulnerability that are present; and insufficient capacity or measures to reduce or cope with the potential negative consequences. It further states that disaster impacts may include loss of life, injury, disease and other negative effects on human physical, mental and social well-being, together with damage to property, destruction of assets, loss of services, social and economic disruption and environmental degradation. Disaster occurs in various forms and magnitude and could be natural or man-made which include: drought; earthquake; volcano; flood; landslide; epidemics; terrorism; tsunamis, typhoons, nuclear/chemical leaks; fire; structural collapse; etc. In Nigeria, major type of disasters are identified to include; floods; drought; fire; oil spill; structural collapse; epidemics and landslide (Unite Nations Office for Outer Space Affairs (UNOOSA, 2002).
Floods are among the most devastating natural hazards in the world, claiming more lives and causing more property damage than any other natural phenomena (Sunday Ishaya et al, 2009). UNOOSA (2002) reported that in Nigeria at least 20 percent of the population is at risk from one form of flooding or another. This includes the whole spectrum from the rich urban residents of Victoria Island, Lagos to poor farmer and fisherman in Benue and Niger trough and the coastal region of Nigeria. Smith (1996) estimated that flood disaster regularly claims over 20,000 lives per year and adversely affects around 75 million people world-wide. This is evident in various flood disaster recorded around the world like in Tanzania where about 20 people died and hundreds left homeless in December 2011, similar occurrences happened in the last quarter of the same year in Sri Lanka, Uganda, Philippine, Australia and Colombia where hundreds of lives and properties were destroyed (Natural Disaster Association blog, 2012). Year 2012 on the other hand, equally witnessed an increment in flood disaster occurrences around the world especially in Africa countries like Sera Leon, Niger and in America like Wisconsin county where properties worth over Two million dollars were reported damaged and in some other Asian countries (Disaster Report, 2012)
The rate of flood disaster in Nigeria is intensifying in various part of the country which resulted in loss of lives and destruction of properties worth billions of naira, including houses, industries and public utilities for instance, Ibadan flood claimed over 120 lives and left thousands displaced in September 2011 and in July 2012, lives were lost and properties worth millions of Naira destroyed; while Lagos flood claimed over about 25 lives, with more than 1000 people displaced in July, 2011 and similar incident repeated in 2012. Also, the Sokoto flood displaced 130,000 people in September 2011; six died with 276 displaced in Kano flood in June 2011 (Tribune, 27 February, 2012). On 25 July, 2012 Jos town, the capital of Plateau State got her own share of the disaster where at least 50 people died, 200 houses destroyed and many people displaced (Tribune, 25 July, 2012) and similar occurrences in August, 2012 in places like Bauchi, Adamawa, Taraba, Cross Rivers and even in Minna, the Niger State Capital where two lives were lost and such incident last occurred about twenty six (26) years ago. Ologunorisa, (2005) ascribed the reason of this wanton destruction to widespread geographical distribution of river floodplains and low-lying coasts, effect of global warming, together with their long standing attractions for human settlement.
Flood means different thing to different people; while it is disaster to some, it serves as a source of blessing to others as it is used for agricultural and economic purposes. Therefore, various definitions have been given to the phenomenon. S. K. Garg (2010) gave the definition of flood as an overflow from some river or from some other body of water. He gave some of the causes as; excessive rainfall, excessive melting of snow or due to some other form of ice obstruction in the form of jams. According to Wikipedia, the free encyclopedia, a flood is viewed as an overflow of water that submerges land, and defined by European Union (EU) Flood Directives as a covering by water of land not normally covered by water. Flooding may result from the volume of water within a body of water, such as river or lake, which overflows or breaks levees, with the result that some of the water escapes its usual boundaries, or may be due to accumulation of rainwater on saturated ground in an aerial flood. Types of flood includes; aerial, riverine, esturine, coastal, catastrophic and human induced (Wikipedia, the free encyclopedia). Abubakar Jimoh (2012) classified causes of flooding in Nigeria into; Natural phenomena which include excessive rain, overflowing of rivers banks, leading to inundation and flash flooding among others and Human causes such as construction of structures on waterways, dumping of refuse in the drainages, disregard of professionalism in building construction and outright negligence on the part of individuals.
Flood disaster management just as other disasters management can be grouped into (i) The Mitigation phase where efforts are made to prevent hazards from developing into disasters or to reduce the effects of disaster when they occur and include activities like hazard and risk identification, risk assessment, vulnerability and capacity assessment, risk zone mapping etc. (ii) Preparedness phase deals with plans or procedures designed to save lives and to minimize damage when disaster occurs. Activities in this phase includes: planning; ; training; disaster drills, early warming modalities; stockpiling, inventory and maintain disaster supplies and equipment. (iii) Response phase includes actions taken to save lives and prevent further property damage in a disaster situation. It involves putting your preparedness plans into action and also damage assessment and relief management just after the disaster. (iv) Recovery phase deals with actions with actions taken to return to a normal or even safer situation following a disaster. Recovery actions involve rebuilding destroyed property, re-employment, and the repair of the essential infrastructure (FEMA Training Manual) and (Ifatimehin, 2009).
Mitigation has been widely regarded as the cornerstone of disaster management. This assertion was equally buttressed by Abubkar Jimoh (2012) in his write up on averting flood disaster in Nigeria, that mitigation/prevention is a better approach in focusing on disaster risk reduction especially with the paradigm shift from reactionary to a proactive approach. However, Van Western and Hosfstee (2000) noted that mitigation of flood disaster can be successful only when detailed knowledge and vital information is obtained about the expected hazardous event like expected frequency, probability, character and magnitude, areas likely to be affected as well as vulnerability conditions of the people, building, infrastructures and economic activities in a potential dangerous area. But unfortunately, Ifatimehin et al (2009), Ishaya et al (2008) and Ufuah et al (2006) were of the opinion that this detailed knowledge or information is always lacking in most urban centres of the developing world especially Nigeria. In their conclusion, they recommended that a risk assessment be conducted in order to address the challenges.
2.3 Flood Risk Assessment
Ogunorisa (2005) opined that risk is an integral part of life. According to a book on Living with Risk-Reduction Initiative (Geveva-2005), risk is defined as the probability of harmful consequences, or expected losses (deaths, injuries, property, livelihoods, economic activity disruption or environment damaged) resulting from interactions between natural or human induced hazards and vulnerable conditions. Smith (1996) in his analysis on concept of risk explained that Chinese word for risk “weji-ji” combines the characters meaning “opportunity/chance” and “danger” to imply that uncertainty always involved some balance between profit and loss. Understanding risk relates to the ability to define what could happen in the future, given a range of possible alternatives to choose from and since risk cannot be completely eliminated, the only option is to manage it.
Risk assessment is the first step in risk management. Risk assessment is the process of collecting, interpreting and analyzing information on existing risks and their potentials for harmful effects on a given organization or community. Kates and Karprson (1983) defined risk as an appraisal of kinds and degrees of threats posed by a particular hazard and deduced that risk assessment comprises of four distinctive steps as:
i. Hazard Identification
ii. Vulnerability Assessment
iii. Capacity Assessment, and
iv. People’s Perception
In risk analysis, Risk (R) is taken as some product of probability (P) and Loss (L)
That is (i.e.) R = P X L
Flood Risk involves both the statistical probability of an event occurring and the scale of the potential consequences (Smith, 1996). Apparently, all development of lands within the floodplain of a watercourse is at some risk of flooding, however small. The degree of flood risk is calculated from historical data and expressed in terms of the expected frequency like 10 year, 50 year, 100 year flood.
Ologunorisa (2001) connote flood risk mathematically as:
Risk = Hazard X Vulnerability or
Risk = Hazard X Vulnerability
The United Nations Commission for Human Settlements (UNCHS-HABITAT) (1981) defined these terms as:
Hazard: Is the probability that in a given period in a given area, an extreme potentially damaging natural phenomenon occurs that induce air, earth movements, which affect a given zone. The magnitude of the phenomenon, the probability of its occurrence and the extent of its impact can vary and, in some cases, be determined.
Vulnerability: of any physical, structural or socio-economic element to a natural hazard is its probability of being damaged, destroyed or lost. Vulnerability is not state but must be considered as a dynamic process, integrating changes and development that alter and affect the probability of loss and damage of all exposed elements.
Capacity: Ability to cope or withstand an unfavourable condition. It is a means by which people, organization, community or society use resources and abilities to face adverse consequences that could lead to a disaster.
Flood risk assessment is the systematic approach to identifying how flooding impacts the environment. It therefore, serves as the basis for mitigation strategies and action in hazard mitigation planning.
Ologunorisa and Abawua (2005) reviewed various techniques used for flood risk assessment and deduced the following as some of the major techniques:
i. Meteorological Parameters
ii. Hydrological Parameters
iii. Socio-economic Factors
iv. Combination of hydro-meteorological and socio-economic factor
v. Geographic Information System (GIS)
2.3.1. Meteorological Parameters
Flood has been defined in various ways and rainfall which can reflect many aspect of flood is virtually used in all these definitions. Meteorological flood is defined as situation over a region where rainfall is mostly higher than the climatological mean value because the natural vegetation and economic activities of the region have been adjusted to the long-term average rainfall of that region (Partha Sarathy, et all, 1987). Therefore, the conditions which lead to flood occur when rainfall amount over a particular region is more than a certain amount normal for that region (Friedman, 1957, WMO, 1975).
Laughlin and Kalma (1990) developed a methodology for frost risk mapping based on regional weather data and local terrain analysis. Minimum air temperatures were measured during three winters with a network of stations in open, undulating terrain. It was observed that the change in minimum air temperature with elevation could be predicted from mean night time wind speed, total nighttime net radiation loss and a hill-top reference minimum temperature. Finally the study describes the model and illustrates the regional weather and terrain effect with the three-dimensional block diagrams.
Single et al (1990) after considering the total seasonal rainfall of June through September as well as its time developed an index that has been evolved for identifying a year as hydrological flood/drought in different parts of India. In general frequency of both hydrological flood and drought years are more in low rainfall areas as compared to high rainfall areas.
Olaniran (1983) examined flood generating mechanism at Ilorin, Kwara state. He noted that in the decade 1971 – 1980, the town experienced rains greater than 25.4mm/day which induce floods when they occur in a month for about three or more times during the period of moisture surplus at Ilorin. The study shows further that the construction of Asa dam has not prevented the occurrence of flood at Ilorin which is situated downstream of the dam on the account of the network characteristics and channel slopes of the tributary stream and the increasing rate of urban development downstream.
2.3.2. Hydrological Parameters
Trinic (1997) did a hydrological analysis of high flows and floods of the Sava River near Zargred (Croatia) in the period from 1926 to 1992. Particular attention was paid to the causes of flood waves volumes from direct inflows above reference discharged and of constant duration were analyzed. The results of hydrological analysis of the flood wave hydrographic can be used to improve manipulation with waters using weirs, flood diversion canals and retentions.
Nobilis and Lorenz (1997) analyzed flood trends in Australia. The study deals with the analysis of previous floods, the assessment of damage, and the evaluation of possible changes in the flood behaviour due to natural or artificial influences. The result of the analysis show areas with predominantly linear trend and areas predominant positive significant (P=0.05) linear trend.
Bogdani and Selenica (1997) analyzed catastrophic floods and their risk in the rivers of Albania. The study described the main characteristics of floods in Albania rivers including information on the highest flood observed during the last 150 years.
Richard et al (1997) describes a two-dimensional mathematical model and the determination of inundation risk maps for two rivers in the Rosario region Argentina. The mapping was made over both Saladillo and Luduena rivers, for floods of return periods of 50, 100, 500 years. The studied zones embraced an area of 700ha, with population of 500,000 inhabitants. Based on the results, state and local government are planning non-structural rules with the associated legislation.
2.3.3. Socio-Economic Factor
Oriola (1994) observed that various socio-cultural activities have promoted flooding in many of the Nigerian urban environments. He explained that these activities are characterized by stream or river channel encroachment and abuse, increase paved surface and poor solid waste disposal techniques due to high level of illiteracy, a low degree of community awareness, poor environmental education, ineffective town planning laws and poor environmental management. He argued that government at various levels needs to address these issues. He however, concluded that flood risk in the Ondo urban environment was a function of the following factors; land-use pattern, refuse disposal habits, the nature of the surrounding buildings, distance of buildings from the course of stream, rainfall amount and duration, the relief or the terrain, slope, gradient, and other stream basin parameters.
2.3.4. Combination of Hydro-meteorological and Socio-Economic Factors
Hogue et al (1997) undertook an assessment of the risks involved with the cyclones and storms surges in Chilagong, the second largest city in Bangladesh. The study finds the extent of storm surge flooding and the related risk in the metropolitan area. To identify the risk, the probability of occurrence has been predicted and were expressed as a hazard index. The city area was divided into five categories of land-use: industrial areas, commercial areas, planned housing areas, unplanned areas and mixed areas. For each area have been considered and were expresses as importance index. Using the hazard index and important index the risk for each area was calculated. On the final analysis the while city was classified into four categories: the low risk area, the risk area, the high risk area, and then the severe risk area.
Ologunorisa (2004) carried out an assessment flood risk in the Niger Delta, Nigeria using a combination of a hydrological techniques based on some measurable physical characteristics of flooding, and socio-economic techniques based on vulnerability factors. Some of the physical characteristics of flooding selected include depth of flooding, duration of flood (hours/weeks), perceived frequency of flood occurrence, and relief or elevation while vulnerability factors selected include proximity to hazard source, land use or dominant economic activity and adequacy of flood alleviation schemes and perceived extent of flood damage. In the analysis, three flood risk zones emerge as; severe flood risk zones, moderate flood risk zones and low flood risk zones.
2.3.5. Geographical Information System (GIS)
Okoduwa (1999) applied Geographical Information System in the prediction of urban flooding in Benin City, Nigeria. This was achieved by creating a digital database of selected variables such as land use, land cover and soil strength. The software used was Arcview 3.1 and the overlay techniques in GIS were used for analysis. The result of the analysis showed high flood prone areas, medium flood prone areas and low flood prone areas. He reported further that in Thailand, flood forecast were prepared for the Huei nam Chun catchment of Pa Sak watershed, Phetchabun Province, using a hydraulic model and a GIS. The objective was to test what extent the integration of a hydraulic model and a GIS can contribute to the quantitative assessment of effects of the upstream land use changes on downstream flood pattern. The HEC-1 hydraulic model and ILWIS (GIS) were used. The results of the simulation were able to show the effect of the land use changes on flood levels downstream.
Also in Lagos, Nigeria, Olusegun Adeaga (2009) undertook a study on planning and warning tools for flood disaster management in Lagos mega city using a flood probability and land cover pattern information. He adopted a terrain-based methodology for derivation of a flood hazard mapping and risk level analysis within Lagos North East. The technique used involves the digitizing of the ISO-elevation (contours) from the topographic maps in order to generate a digital elevation model (DEM) at 15 meters resolution for the region. The result of his analysis shows extensive floodplain and finally was able to classify them according to level of flood risk severity.
2.4 Flood Discharge Estimation Techniques
Various methods have been used for estimating flood discharges. Some of them based on the characteristic of the drainage basin, and others on the theory of probability applied to the previous known flood data, while others are based on a study of rainfall and runoff data (S. K. Garg, 2010). Several of these methods are often employed together, and a value of the design flood is chosen, so as to suit and individual problem.
A flood is said to occur when there is an unusual increase of water level of river due to runoff from precipitation or other source in quantities too large to be confined in the normal water surface elevations of the stream or river. This may result from combination of factors like; drainage basin characteristics which include: shape, size, slope, land use, geology, soil type, surface infiltration and storage, Stream channel characteristics including: geometry and configuration, natural and artificial controls, channel modification, aggradation and degradation) and floodplain characteristics and meteorological factors such as precipitation amount, type and time rate.
The maximum flood that any structure can safely pass is called a design flood (S. Mustafa et al, 1997). It may be arrived at by considering the construction cost of the structure to provide flood control, flood control benefits and floodplain delineation. General terms commonly employed to designate design floods for major structure are given as: Probable Maximum Flood (PMF), The Standard Project Flood (SPF) and the Frequency-Based Flood, that is floods ranging in magnitude between standard project flood and maximum probable flood.
Federal Emergency Management Agency (FEMA) and Emergency Management Institute (EMI) Training Manual (2008) explained that there is plethora of methods from which a hydrologist or researcher can choose from for a specific task and gave the commonly apply techniques as:
i. Regional Methods
ii. Rational Methods
iii. Empirical Equation
iv. Transfer Methods
v. Watershed Modeling, and
vi. Flood Frequency Analysis or Statistical Analysis of Stream-flow records
2.4.1. Regional Methods
This method involves correlation of a dependent variable (e.g., x-year recurrence interval discharge) with one or more causative or physically related, and readily determined watershed and stream system factors for a defined geographic area. This category of hydrologic methods is specified as being regional because any given method is applicable only within the region that provided the stream flow and watershed data used to develop the method.
2.4.2. Rational Methods
The most widely used uncalibrated equation is the Rational Method. Mathematically, the rational method relates the peak discharge (q, m3/sec) to the drainage area (A, ha), the rainfall intensity (i, mm/hr), and the runoff coefficient (C).
q = 0.0028CiA
Where q = design peak runoff rate in m3/s
C = the runoff coefficient
i = rainfall intensity in mm/h for the design return period and for a duration equal to the “time of concentration” of the watershed (Chow, 1988).
2.4.3. Empirical Equation
Chow (1988), describe this method as a multitude of peak flow formulae relating the discharge area and other basin characteristics and gave the formulae as:
Qp = CAm
where m and C are regarded as constant, A = Drainage area, Qp = peak discharge associated with a given return period.
2.4.4. Transfer Methods
In employment of the transfer method for determining peak discharge, a flood flow of specified recurrence interval for a stream of a given size and runoff characteristics is used to estimate a flood flow of the same recurrence interval for a larger or smaller portion of the watershed having similar runoff characteristics. Such transfers are made on the basis of drainage area ratios raised to an exponential power. Underlying the transfer method is the assumption that the area to which it is being applied has runoff characteristics similar to the area for which a flow of specified recurrence interval is known. The only significant difference between the two watersheds, or two points in a given watershed, should be the size of the drainage areas (FEMA/EMI Training Manual, 2008).
2.4.5. Watershed Modeling
Smith (1999) pointed out that this method can be carried out to arrive at peak flood flows for a stream where time and expenses can be justified. He stated that the method is inherently the most accurate of the hydrological approaches because of the level of detail of the analyses. This technique of predicting the run-off, which is the catchments response to a given rainfall input, is called deterministic watershed simulation. In this the mathematical relationships describing the interdependence of various parameters in the system are first prepared and this is called the model. The model is then calibrated i.e. the numerical values of various coefficients determined, by simulating the known rainfall-run-off records. The accuracy of the model is further checked by reproducing the results of another string of rainfall data for which run-off values are known. This phase is known as validation, or verification of the model. After this, the model is ready for use. Crawford and Linsley (1951) pioneered this technique-by proposing a watershed simulation model known as the Stanford Watershed Model (SWM). This underwent Successive modifications and the Stanford Watershed Model-IV (SWM-IV) suitable for use on a wide variety of conditions was proposed in 1966 (Crawford and Linsley, 1959). The flow chart of SWM-IV is shown in Figure 18.104.22.168; the main inputs are hourly precipitation and daily evapotranspiration in addition to physical description of the catchments. Jimoh and Sule (1992) in their analysis of the Gurara River basin used nine parameters model of which they found that the channel storage constant was the most sensitive. The model performance is 0.88. This model was however adapted by Musa Patiko (2010) in his study of assessment of catchment yield of River Chanchaga where he used the model to generate annual run-off for period of 1960 – 2000 and validate the simulated result with available five year observed discharge value obtained from Niger State Water Board which gave fitness of 0.92.
Lower zone or ground water storage
Precipitation, potential evapotranspiration, temperature, radiation
Active or deep ground water storage
Lower zone or ground water storage
Deep or inactive groundwater storage
Lower zone storgae
upper zone storgae
Figure. 22.214.171.124: Flow Chart of SWM – IV
Source: Musa Patiko, 2010
2.4.6 Flood Frequency Analysis/ Statistical Analysis of Stream-flow Records
S. K. Garg (2010) explained that these methods are often used for the prediction of future floods which are made on the basis of available records of stream flow. He further states that the methods can be safely used to determine the maximum flood that is expected on a river with a given frequency. Flood frequency analyses are used to predict design floods for sites along a river. The technique involves using observed annual peak flow/discharge data to calculate statistical information. These statistical data are then used to construct frequency distributions which may be graphs or tables that tells the likelihood of various discharges as a function of recurrence interval or exceedence probability.
O. C. Izinyon et al (2011) observed that Flood Frequency Analysis (FFA) commonly focus on the estimation of return periods associated with annual maximum flood peaks of various magnitudes. He remarked that, if based on an assumed distribution, it is possible to make a probability statement of future flows of various magnitudes. FFA is generally regarded as a viable method of flood flow estimation in most situation and provides reliable prediction in regions of relatively uniform climatic condition from year to years and it is now an established method of determining critical design discharges for small to moderate hydraulic structures and to delineate flood plains and determine the effect of encroachments on the flood plain (Haktan, 1992).
The objective of frequency analysis is to relate the magnitude of events to their frequency of occurrence through probability distribution. It is assumed the events (data) are independent and come from identical distribution (Chow, 1988).
Return Period (T) of an event X ≥ xτ of a given magnitude as given by Ven, Te Chow., et al (1988) is the average recurrence interval between events equalling or exceeding a specified magnitude. i.e.
Extreme event occurs if:
Recurrence Interval is the time between occurrences of an events equaling or exceeding a specified magnitude.
However, If p is the probability of occurrence of an extreme event, then
E (τ) = T = 1/P or
P (X ≥ xτ) = 1/T, similarly
If p is probability of success, then (1 – p ) is the probability of failure, therefore probability that (X ≥ xτ) once in a year as given by Chow (1988) as:
Probability Plotting on Empirical Relations
The main purpose of probability frequency analysis is to obtain a relation between the magnitude of a flood or a storm and its probability of exceedence. This analysis may be made by empirical or analytical methods.
The simplest empirical technique as proposed by S. K. Garg (2010) is to arrange the given annual peak flood data in the descending order and to assign the ranking number (m) to each flood. The flood with the highest magnitude will be placed at the top with its ranking as 1 and the least flood data will be placed at the last place (Nth place), and its ranking will be N.
The probability of an event equaling or exceeding is then computed by the empirical California formula as:
and the recurrence interval (T) = =
It further explained that after the values of recurrence interval (T0 for different floods are calculated, a graph can be plotted between frequencies and flood discharges; which can be extended if desired, as to extrapolate the values of flood magnitude corresponding to any high value of frequency. The flood discharge for any other frequency can also be determined from the plotted graph.
Theoretical Probability Distribution Methods
The simple empirical procedure explained above can give good results for small extrapolations only; and as the extrapolation increases, the error also increases. However, for obtaining better result for larger extrapolations, theoretical probability distributions have to be used.
Theoretical probability distributions can take on many forms according to the equations used to carry out the statistical analyses. The commonly used functions are classified into these families:
Generalized extreme value family
Exponential/Pearson type family
Pearson type III
Log-Pearson type III
4.5 Methods of Delineating Flood-Prone Areas/ Floodplain Mapping
The essence of flood risk assessment is to create flood risk awareness and to effectively manage the floodplain for various purposes, therefore a determination of the areas subject to floodwater inundation for expected recurrence interval of interest is necessary, however many writers and researchers have enumerated various methods of delineating flood-prone areas, but FEMA/EMI Training Manual (2008) explained that flood hazard areas can be delineated based on two different analysis approaches as: detailed and limited methods. It suggested that detailed study approach should be used when accurate floodplain information including floodplain limits, water surface elevations and profiles, flood depths and velocities and floodway limits are needed for the drainage-way being studied, while the limited study method may be used when detailed floodplain information is not necessary. The two methods entail hydrologic, geometric/topographic mapping and hydraulic analysis. The manual proposed that peak flow rates should be computed using statistical analysis, rainfall-runoff models or regional regression methods.
This involve the use of statistical analysis to determine probability of occurrence or likelihood of flood, recurrence interval, return period, discharges corresponding to each return period and other related hydrological data needed to identify flood hazard areas and flood risk within those areas.
Geometric Modeling/Topographic Mapping
This involves the modeling of geometric configuration of the river which includes riverine cross-section data for hydraulic modeling purposes and could be obtained through the following methods:
Photogrammetric methods at the time of map compilation.
From Digital Terrain Model (DTM), Digital Elevation Model (DEM), or Triangular Irregular Network (TIN).
Remote Sensing Application
From map contours and spot elevations
Through field surveys
It involves determination of flow conditions like steady flow analysis, unsteady flow analysis or combined (steady/unsteady) flow analysis as well as flood/water surface profile which may be calculated using Bernoulli energy equation with energy losses due to friction evaluated with the manning equation. Many computer programs are available for computation of backwater curves. The most general and widely used programs are US Army Corps of Engineers’ HEC-2 and HEC-RAS. Both HEC-2 and HEC-RAS programs can be used to model one-dimensional subcritical and supercritical flow condition.
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