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Page 1: Planning and Warning Tools For Flood Disaster Management ...siteresources.worldbank.org/INTURBANDEVELOPMENT/... · Planning and Warning Tools for Flood Disaster Management in

Planning and Warning Tools for Flood Disaster Management in Lagos Mega City Fifth Urban Research Symposium 2009

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Planning and Warning Tools For Flood Disaster Management in Lagos Mega City

OLUSEGUN ADEAGA Department of Geography, University of Lagos, Yaba , Lagos, Nigeria

e-mail: [email protected] Summary: The need to resolve flood incidence severity within Lagos Mega city, call for a well defined decision planning and warning tool with a detailed preparation and planning network. In this study a flood probability map and landuse/landcover pattern information of part of Lagos NE region, was used to estimate flood risk and probable peak discharge of the different landuse/landcover classes. This information was spatially integrated within the geographical information system (GIS) decision support system framework towards the provision of a detailed flood pre-disaster and lead time geo-information services within the city. Plans towards adopting a GNSS technology options for the creation of early flood warning signal system within the flood disaster management plan was also discussed. Key words: flood disaster, flood risk, flood geo-information service, flood early warning signal I. INTRODUCTION

Cities remain the heart of a fast changing global economy and world economic growth with increasing urbanization growth and activities, most especially in Asia and Africa (UN World Urbanization Prospects report, 2005). Such growth call for better understanding of the functional relationship between urbanization and hydrological systems since urbanization increases the total impervious area (TIA) of regions (Arnold and Gibbons, 1999; Glaeser, 1998). Numerous studies on urbanization effect on hydrological environment noted increasing runoff of about 2 to 6 times from that of undisturbed catchment system while peak flows with recurrence intervals of 2-years has being noted to increase by factors of two, three, and five with 10, 15 and 30 percent impervious development, respectively. It should also be noted that the effects of urbanization are greatest with more frequent storm events but diminish as flood size and recurrence interval increases (Hollis, 1975).

Resultant effect various modifications in the channel morphology and hydrological environment, which increases total impervious area of a region as common in the emerging metropolises and mega cities, include increasing peak flow magnitudes and surface runoff volume with decreases in lag time, base flow and natural groundwater storages and increases incidences of urban and flash floods as common within urban catchments, (Mangarella and Palhegyi, 2002). According to the Munich Re Group (Nirupama & Simonovic, 2004), floods are most frequent and widespread of all natural disasters in the world and noted that within the year 2001, 17 flood events were recorded with more than 2372 fatalities and more than $3.5 billion in economic losses

This study focuses on urbanization and flood incidence within North-Eastern portion of the Lagos Mega city (Figure 1), an upstream section that has not received intensive studies, in terms of expected urbanization rate and peak discharge contribution to downstream section of the Mega city. Such study is important while considering the huge metropolis continuous urbanized built–up area, of about 154,000,00 square kilometers which extent from the Atlantic Ocean

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northwards beyond Otta in Ogun state (Wikipedia, 2009), without adequate consideration for the entire hydrological environment. Hence, the combined effect of heavy rainfall and storm surges and ill-defined planning and her coastal location always result in worrisome flood incidence with severe human, environmental, socio-economic and psychological consequences. Thus, a call for a well defined flood disaster management plan with a detailed warning tool and preparation network within the emergent Lagos Mega City.

F igure 1: Par t of Lagos North- Eastern region II. METHODOLOGY A terrain-based methodology was adopted for the derivation of a flood hazard mapping and risk level analysis within Lagos NE. The region being examined covers about 730 Km2 and the details about data used is given in Table 1. The derivation of the flood map 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. Cubic spline interpolation technique was used for the surface interpolation. Reclassification and cross-tabulation analysis of the DEM dataset with reference to the hypothetical threshold value of 6m water stage was carried out, in order to identify floodable and non-floodable area and estimate floodable as well as newly inundated land at acceptable flood risk level of 20 %, 10 % and 5 % flood probability map. The concept of a smooth transition was adopted, in the generation of the flood probability map for the accommodation of the uncertainty associated with flood map. The technique entails identification of cell value that exceeds or is exceeded by the specified threshold within the flood image. The estimation was carried-out, in order to quantify and reduce predictive flood uncertainty within the Lagos NE region with the aim of attaining a detailed flood mitigation plan.

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Table 1 Data adopted, their sources and characteristics

DATA SOURCE REMARK Topographical maps Federal Surveys Department,

Lagos (i) Scale 1:50,000 (1970) Sheet 279 N.E and 279 S.E

Satellite Imagery LANDSAT 2000 Satellite Imagery Google Earth 2005 Rainfall intensity-duration –frequency Oyebande (1983)

The landuse/landcover pattern for the period 2000 and 2005 for the region was derived

from Landsat and Google earth satellite imageries respectively. In the study, a two (2) level landuse and landcover classification scheme (Table 2), which suits the study objectives and environment as well as the imageries scale, was developed. The image interpretation strategies of direct recognition using experience, skill, auxiliary data and probabilistic judgement to associate image pattern with informational classes was also adopted, with high degree of certainty while estimation of the runoff coefficient of the different urban landuses was also estimated. ‘ Table 2 Landuse/Land cover Classification Scheme

Flood risk analysis was carried out based on the runoff coefficient of the different urban landuses (McCuen, 2005) through the identification and assessment of design probable peak discharge, using the rational formula. The rational formula is used to estimate likely peak flow of a river at designated point based on rainfall depths measurement. Such estimation is based on assumed equal rainfall and runoff return period. The method assumes steady uniform rainfall intensity over the entire catchment and peak flow occurs after the time of concentration.

Rational formula (Shaw, 1993) can be empirically expressed in metric units as; Qp (m3s-1) = 0.278 * CI A ……………………………………… (1)

Where Qp is peak discharge, C is runoff coefficient, I is the rainfall intensity in time T (mmh-1 and A is the catchment area (Km2)

This information was spatially integrated within the geographical information system (GIS) decision support system framework towards the provision of a detailed flood pre-disaster and lead time geo-information services within the city. III. RESULTS The flood pre-disaster and lead time geo-information services within Lagos NE region as depicted in digital elevation model (Figure 2) of the region shows an extensive floodplain of about 472 km2. The Flood hazard mapping (Figure 3) and risk level analysis depict that within the North-western portion of the study area, about 292 km2 of the total area is prone to flooding. Of the floodable area about 230 km2 is highly prone to floods (Floodable area) while an area

Class Level 1 Class Level 11 Element of Image Interpretation Built-up Area Densely Tone, Shape, Texture

Medium Tone, Shape, Texture low Tone, Shape, Texture

Wetland Swamp Tone, Shape, Texture, Association Vegetal Cover Forest Tone, Shape, Texture, Association

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covering about 62 km2 consists of newly inundated regions. Various scenarios building on acceptable risk levels design of floodable area extent as generated from the flood probability map shows that floodable areas under 20 %, 10 % and 5 % risk levels have increased to about 308 km2, 315 km2 and 320 km2, this shows an increase of about 6, 8 and 10 % respectively above the initial flood prone region

Figure 2: Digital elevation model of Part of Lagos NE

Figure 3: Flood Prone region within Part of Lagos NE

The break down of the land use and landcover spatial distribution based on the adopted

classification scheme as depicted in figures 4 and 5 shows that built-up area constitute about 456

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km2 and 518km2. This represent about 63% and 71% of the total areal covered for the period and of the built-up area while the densely built up area constitute 51% and 67% of the built-up area for period 2000 and 2005 respectively.

The magnitude of changes between built-up area for the study periods as shown in table 3, depicts that densely built-up area gains 49% between the study period which represents on average, annual increase of 9.8% while medium and low built-up area losses by 23% and 25 % within the study period. Such loses are evident, since quite number of medium are now densely built-up area, while a lot of low built-up area are now medium built-up area with a few emerging low densely.

Figure 4: Landuse/Landcover Pattern of Part of Lagos NE (Source: Landsat Imagery, 2000) The overlay of the landuse/landcover map on the digital elevation model (Figure 2),

depicts that built-up area within the Ogun River floodplain constitutes about 358 km2 and 393 km2, with many isolated settlements. Also, the overlay of the landuse/landcover map on the flood probability map (Figure 3) shows that within the floodable region, built–up area constitutes 151km2 and 187 km2 for the period 2000 and 2005 respectively. Also, built-up area distribution within the total areal coverage, flood plain and floodable region as shown in Figures 6 (a & b) increases by 14%, 10% and 25%, respectively. This has a lot of implication with the floodable region actually extending beyond the identified floodable region on the flood probability map, since urbanization increases the total impervious area while channel lining easily transfer flooding problem from the upstream to downstream reach. The impervious surface combined with increased hydraulic conveyance and poor urban landuse planning has being identified to

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raise flood peak artificially by 3 to 8 times than their pre-urban (Oyebande, 1990 ) with a lot of hydrological design problems.

Figure 5: Landuse/Landcover Pattern of Part of Lagos NE (Google Earth, 2005)

Table 3: Areal Coverage of Landuse/Landcover Pattern in Lagos NE

The peak discharge estimation (Table 4) as derived using rational formula shows that for

a 1yr-10 min rainfall within the densely built-up area peak discharge increases by about 48% within the study period, although peak discharge has decreased within the medium and low built-up area by about 29 and 48% respectively, this is due to losses to densely built-up area.

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Figure 6: Built-up area within the floodable region (A) and flood plain (B) within Lagos NE Table 4: Peak Discharge � h �� � � � � � � �Densely 2000 2005

Return Period

Peak Discharge (m3s-1)

Runoff (mm) Volume(m3m)

Peak Discharge (m3s-1)

Runoff (mm) Volume(m3m)

1yr-10 min 4264.687 732.9219 134491162.9 6289.462 757.9078 198344482.1 2yr-15 min 4938.058 848.6464 155726609.7 7282.535 877.5775 229662032 2yr-30 min 3591.315 617.1974 113255716.1 5296.389 638.2382 167026932.3 5yr-10 min 7631.545 1311.544 240668396.8 11254.83 1356.256 354932231.2 5yr-15 min 6284.802 1080.095 198197503.3 9268.681 1116.917 292297131.6 10yr-10 min 7182.63 1234.395 226511432.3 10592.78 1276.476 334053864.7 Medium 1yr-10 min 2905.76 624.6493 91636055.24 2042.18 682.9499 64402177.76 2yr-15 min 3364.565 723.2782 106104906.1 2364.629 790.7841 74570942.67 2yr-30 min 2446.956 526.0205 77167204.42 1719.73 575.1157 54233412.85 5yr-10 min 5199.782 1117.794 163980309.4 3654.427 1222.121 115246002.3 5yr-15 min 4282.173 920.5358 135042607.7 3009.528 1006.453 94908472.49 10yr-10 min 4893.912 1052.041 154334408.8 3439.46 1150.231 108466825.7 Low 1yr-10 min 478.9454 541.3627 15104020.56 247.5938 624.6493 6575256 2yr-15 min 554.5683 626.8411 17488865.91 286.6875 723.2782 13972419 2yr-30 min 403.3224 455.8844 12719175.21 208.5 526.0205 11506698 5yr-10 min 857.0601 968.7544 27028247.31 443.0625 1117.794 13150512 5yr-15 min 705.8142 797.7977 22258556.61 364.875 920.5358 11506698 10yr-10 min 806.6448 911.7688 25438350.41 417 1052.041 13972419

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IV. CONCLUSION AND RECOMMENDATION Varied degree of urbanization growth is being witness within the North-Eastern region of the Lagos Mega city which constitutes part of lower Ogun River systems, with about 54 % of the total built-up areas, being located within the flood plains. The total impervious area (TIA) as conduits for excess stormwater within the regions is therefore at increase, thereby decreasing the lag time between the peak rainfall and peak discharge, with increasing cases of urban and flash flooding. Besides the impervious surfaces, inadequate drainage and channelization system as well as non adhesiveness to the regulated planning scheme, further enhances flood incidences within the region.

An appropria te flood mit iga t ion plan , which should involve creat ion of na tura l greenway cor r idors a long r iverbanks, restora t ion of r ipar ian zones, in order to a llow na tura l flooding a long r ivers course and use of flood-probability r isk mapping for different flood recurrence Intervals, as index towards reducing urban sprawl in flood-prone a reas and flood pla in zoning, should therefore be encouraged. St r ingent flood cont rol measures a re a lso necessary in the densely urbanized a reas, in order to minimize flood damage.

Furthermore, the need to monitor the various urban expansion and flood incidences within Lagos Mega city, call for a flood early warning signal system with the capability to deliver reliable, timely and effective flood information at an appropriate response time. It is suggested that the system option must involve integration of Global Navigation Satellite System (GNSS) technology into Geographical Information System (GIS) framework towards appropriate flood modeling, simulation and forecasting. This will ease service information provision on real time flood risk analysis, flood extent, acceptable risk level modelling and mapping and potential damages and alerts V. REFERENCES Arnold, C. L, Jr. and C. J. Gibbons (1996): Impervious surface coverage: The emergence of a key environmental indicator. Journal of the American Planning Association 62 (2): 243-258. Glaeser, E (1998): Are Cities Dying? The Journal of Economic Perspectives, Vol. 12, No. 2 (Spring, 1998), pp. 139-160 Hollins, G (1975): The Effect of Urbanization on Floods of Different Recurrence Intervals. Water Resources Research 11 (3): 431 - 435 Mangarella, P. and G. Palhegyi (2002): Santa Clara Valley Urban Runoff Pollution Prevention Program: Hydromodification Management Plan Literature Review. GeoSyntec Consultants, Walnut Creek, CA. McCuen, R. (2005): Hydrologic Analysis and Design, Pearson Education Inc. Prentice Hall, Upper Saddle River, new Jersey 07455, Pp 380. Nirupama, N. and S. P. Simonovic, (2004): Is Urbanization Increasing Flood Risk ? An Ontario Assessment, Ecclectica www.ecclectica.ca/issues/2004/1/nirupama.asp Oyebande, L. (1983): ‘Rainfall Intensity-Duration-Frequency Curves and Maps for Nigeria’ Occasional Paper No. 2, Department of Geography, University of Lagos, Akoka, Lagos. Oyebande, L. (1990) Aspects of urban hydrology and the challenges for African urban environment. African Urban Quarterly 5,(1/2), 39–63. Shaw, E. M. (1993): ‘Hydrology in practice’ 2nd Ed. Chapman and Hall UN World Urbanization Prospects report (2005), World Urbanization Prospects: The 2005 Revision, Pop. Division, Department of Economic and Social Affairs, UN, http://www.un.org/esa/population/publications/WUP2005/2005wup.htm Wikipedia (2009): http://en.wikipedia.org/wiki/Lagos