LAND USE/LAND COVER CHANGE EARLY WARNING SYSTEM AND CLIMATE CHANGE IN THE QUA IBOE RIVER BASIN, NIGERIA

1
LAND USE/LAND COVER CHANGE EARLY WARNING SYSTEM
AND CLIMATE CHANGE IN THE QUA IBOE RIVER BASIN,
NIGERIA

• EKPENYONG, Robert Etim
• Department Of Geography and Regional Planning
• University Of Uyo
• Uyo, AKS
• Nigeria

2
Introduction

• Studies have shown that information on land use/
  land cover is required for rational and
  sustainable allocation of land resources for
  development YANG and LO, 2003 EL-RAEY et.al.,
  2000 BRONSVELD et. al., 1994.
• In the Qua Iboe River Basin, Nigeria, growing
  population densities, urbanization and poverty is
  leading to widespread changes in land use and
  land cover. The situation is so serious that food
  security, socio-economic development and the
  climate/microclimate of many areas are being
  threatened.
• To effectively address these problems and ensure
  that future generations can enjoy the benefits of
  the earths resources, there is need for an early
  warning system for land cover change analysis and
  mapping.

3
LOCATION OF STUDY AREA

• The Qua Iboe River basin is located within Akwa
  Ibom State which is situated in South Eastern
  Nigeria.
• It lies between latitude 430 and 530N and
  long 730 and 815E (Fig.1)
• The catchment area of the basin lies between the
  Imo and Cross Rivers and covers about 3266sq.km.

4
Theoretical Considerations

• Generally, urban areas are made up of buildings
  and pavements which changes the natural landscape
  into townscape. The surface materials are mostly
  hard. This implies that, the thermal conductivity
  and heat capacity are greater than when the
  surface was mostly composed of vegetation.
• Studies have shown that, the modification of the
  environment through the creation of cities
  represents a more extreme form of microclimate
  alteration Ojo 1977.
• Transpiration from vegetation causes higher
  humidity. However, changes in vegetation cover
  from trees to grass usually decreases evaporation
  and transpiration losses and reduces the amount
  of rain and snow intercepted by foliage.
  Furthermore, temperature and wind speeds are
  lower within forested areas than in the open.
  Cities tend to have higher temperatures than the
  surrounding suburbs and they produce more haze
  and smoke MILLER et. al, 1970 OJO, 1977.
• The foregoing underscores the importance of land
  use/land cover in climate change.

5
Materials and Methods

• Data Acquisition, Database creation and Data
  Analysis
• Maps of the area, mainly those showing relief and
  drainage, soils, vegetation, rainfall and
  temperature distribution, land capability/suitabil
  ity, land resource development areas etc.,
  published in 1982 by Cross River basin
  Development Authority at a scale of 1250,000
  were scanned, geo-referenced and digitized to
  create the early warning system baseline dataset.
  
• Supervised classification was carried out to
  produce Land use/Land cover maps for the
  different time periods year 1984 and 2003.
  These are periods before the area was constituted
  into a State and the period 16years after State
  creation. Random test fields were located in the
  original image and in the field to perform
  accuracy assessment. An overall accuracy of
  82.11 was estimated. For change detection, the
  areas of the cover types were derived from the
  histogram of the respective classified imagery.
  YANG et al, 2002 SINGH, 1999 JENSEN, 1995
  LILLESAND et al, 1994. The image processing
  software used was ILWIS 3.3.

6
The Early Warning System

• According to EWC 111 2006, a complete and
  effective Early Warning System comprises a chain
  of four elements
• Risk knowledge-prior knowledge of the likely risk
  scenarios communities are faced with
• Monitoring and warning services-monitoring
  capabilities for these risks and rapid and
  reliable decision mechanisms for early warning
• Communication-dissemination of understandable
  warnings to those at risk
• Response capability-knowledge and preparedness
  capacity to act by all partners of the
  information chain.

7
The Land Cover Change Early Warning System

• The land use/land cover change early warning
  system comprised a personal computer system with
  intel Pentium 4 processor 3GHz, 200GB HDD, 1024GB
  RAM and 21 color monitor, a variety of GIS and
  image processing software ILWIS 3.3, ArcGIS 9,
  GPS Utility 4.2, Global mapper, LCCS 2.4.5,
  SURFER 32, JT Maps etc and database. It is
  located in the Department of Geography and
  Regional Planning, University of Uyo, AKS-Nigeria
  where it is used for capacity building. To
  enhance its capabilities, the system is
  frequently updated as new theory, models and/or
  data become available. Also advantage is often
  taken of the free GIS/Image processing software
  and landsat data available in the internet.
• The early warning system is capable of providing
  information on the likely risk scenario that
  communities may face but the challenge now is to
  build partnerships that can support its
  monitoring, communication and response
  capabilities.

8
Manipulation and Analysis of Data for Early
Warning Purpose

• Fig. 2 and Fig 3 are land use/land cover maps of
  lower Qua Iboe River Basin for 1984 and 2003.
  They were produced using landsat TM. A summary of
  the changes in land use/land cover is given in
  table 1.

9
Table 1 Qua Iboe Basin Land Cover Type Coverage
Area
LAND COVER TYPE AREA IN 1984ha AREA IN 2003ha
Bare soil 2,504.133 38.817
Beach sand 35.946 127.539
Fallow land/grassland 26,939.05 32,074.48
Mosaic farmland/oilpalm forest 8,464.60 18,662.29
Freshwater swamp forest 9,922.95 7,545.29
Mangrove forest 3,739.45 3,644.91
Rivers/Natural water bodies 8,192.99 10,721.20
Urban/Industrial/built-up 895.995 1028.115

Source Histograms of classified imageries for
1984 and 2003
A critical examination of the images reveals the
facts that, much of the farmland and fallow land
were encroached upon by urban centers. This has
serious implications on sustainable
agriculture/food security, climate etc.
10
Impact of Urbanization

• Urbanization refers to the process in which an
  increasing proportion of an entire population
  lives in urban and suburban areas. Historically,
  this has been closely connected with
  industrialization and the discovery of petroleum
  in Nigeria. New job opportunities in urban areas
  spurred the mass movement of surplus population
  away from the rural communities Yang and Lo,
  2003 El-Raey et.al., 2000.
• In Akwa Ibom state where the Qua Iboe river basin
  is located there were only 10 urban centres as
  at 1987 when the state was created. Of this
  number, five were within the river basin. With
  the creation of new Local Government Areas, the
  number of urban centres in the State increased to
  31. Of this number, 16 are within the catchment
  of the Qua Iboe River basin.
• The population of people attracted to these urban
  centres continues to increase because of the
  important industries and socio economic activity
  centres located within and or close to them. For
  instance, Uyo is a capital city and the sit of
  Government of Akwa Ibom State. It grew in size as
  a result of urbanization from 125.595ha in 1984
  to 242.262ha in 2003table 2.
• Two other areas within the basin Eket and Mkpanak
  also expanded in size. Eket expanded from 23ha to
  27ha while Mkpanak expanded from 7ha to 33ha
  table 2.

11
Table 2. Urban/Industrial/Built-Up Area Land
Cover type coverage Areas
PLACE NAME AREA IN 1984ha AREA IN 2003ha
Uyo 125.595 242.262
Eket 23.472 27.567
Mkpanak 6.912 32.697
A critical visual interpretation of the 1984
images of Uyo, Eket and Mkpanak reveals the fact
that, the settlements were surrounded by
agricultural land i.e. mosaic farmland/oil palm
forest and bush fallowing/grassland land cover
types. This implies that, the growth of the
urban areas in 2003 have encroached on valuable
agricultural land. This is a serious threat to
agriculture/food security in the area under study.
12
Images Showing Land Cover Change in Uyo Capital
City
13
Climate Change

• There is no doubt that a city modifies its own
  climate. It is however difficult to separate the
  influence of the city from that of other factors
  such as relief, drainage, or water bodies within
  or near the city, which independently affect
  climate OJO 1977 MILLER et.al 1970.
• However, of all the climatic elements, the only
  one that changes quite often within the area is
  rainfall.

14
Table 3 Rainfall Pattern in Uyo Capital City
Years Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Total (mm) Ave mm)
1984 0 0 147.8 100.6 217.6 400.2 244.2 170.2 225 223.7 149.4 0 1878.1 156.5
1985 63.5 0 157.5 191.2 281.7 213.6 274 392.7 226.4 239.8 84.6 7.6 2132.6 177.7
1986 1.05 63 207.9 99.8 198.8 154.4 313.6 107.8 399.3 296.3 63.2 0 2132.6 177.7
1987 0 42.9 225 165 419 205.8 188.6 300.9 329.4 289.7 26.6 58.5 2251.7 187.6
1988 5.5 3 143.9 228.5 198.4 233.4 310.9 251.3 475.1 213.6 18.3 33.1 1915.1 159.6
1989 0 0 39.1 200.7 261.6 223.8 553.2 331.6 453.7 442.8 82.2 0 2631.7 219.3
1990 22.6 1.5 27 158.7 308.6 113.1 456.2 417.9 152.3 204.5 124.3 41.1 2032.8 169.4
1991 0 29.5 41.2 395.3 207.9 319.6 383.8 405.2 78.2 239.9 69.4 76.7 2243.7 186.9
1992 7.5 0 113.3 115.9 248.5 307.6 470.8 383.1 322.8 116.9 165.7 4.7 2276.8 189.7
1993 2 0 121.8 130.4 141.4 339.9 352.5 468.4 324 252.1 97 0 2229.6 185.8
1994 7.2 6.2 153.3 167.6 300.5 315.4 456.6 380.9 463.6 294.8 122.6 0 2668.7 222.4
1995 4.4 26.1 168.9 82.4 316.8 221.4 428.6 313.7 234.7 339.5 122.9 5 2264.4 188.7
1996 34.8 112.4 124 240.9 398.2 295.2 275.5 407.9 409.6 220.4 1.8 0 2117.6 176.5
1997 17.5 0 113.4 120.8 195.2 237.5 345.4 326.6 151.7 314.7 81.2 17.3 1957 163
1998 26.5 1.8 81.5 131.9 144 303.2 302.7 253 300.4 178.6 241.7 68.5 2033.8 169.5
1999 60.4 85 224.2 275 177.2 154.9 211.1 327 468.6 420.9 95.1 9.1 2509.5 209.1
2000 31.5 0 106.5 125.3 320.4 146.2 254 262.7 281 172.5 95.1 45.6 1840.7 153.4
2001 0 8.6 229.9 219.3 339.7 503.2 219 182.6 270.6 225.6 118.3 0.4 2317.2 193.1
2002 0 10.8 135.1 261.4 312.4 255.8 205 347 320 414.9 30.1 9 2341.5 195.1
2003 20 43 104 223.5 235.6 181.6 202.4 218.6 340.6 207.8 116.7 1 1894.8 157.5
2004 2.1 57 24.2 165.8 218.1 363.8 357.1 288.9 362.3 280.9 79.4 22 2221.6 185
2005 22.4 97 156 284.8 186.7 325.6 637.7 325.1 279 505.5 207.1 3.6 3030.5 252.5
2006 3.7 60.8 277.8 296.8 370.8 592.7 419.3 360.5 566.8 374.9 49.6 0 3373.7 281.1
SOURCE Department of Meteorological services,
station Number 050705B, University of Uyo.
Uyo,AKS, Nigeria
SOURCE Department of Meteorological services,
station Number 050705B, University of Uyo.
Uyo,AKS, Nigeria
15
Climate Change

• Table 3 shows the yearly variations of rainfall
  between 1984 and 2006 for Uyo Capital city.
• Relatively high rainfall of more than 2500mm
  occurred in 1989, 1994, 1999, 1005 and 2006
  whereas, unusually low rainfall of less than
  1900mm was recorded in 1984, 2000 and 2003.
• Compared with the mean annual rainfall of 189.4mm
  for Uyo, the years 1989, 1994, 1994, 1999, 2001,
  2002, 2005 and 2006 were years with rainfall
  above the average.

16
Climate Change

• As can be observed from table 3, more than 80 of
  the annual rainfall occurs between March and
  October of each year, while less than 20 of the
  rain falls between November and February.
• However, a lot of variations occur from year to
  year in the monthly distribution of rainfall. For
  example, the highest rainfall in 1984 and 2006
  occurred in June whereas in 1985, 1987, and 2002,
  it occurred in August, May and October
  respectively.

17
Conclusion

• This study confirms reports of destruction of
  vegetation cover in the Qua Iboe River Basin.
  Since studies have shown that losing vegetation
  cover in any area can affect climate, there is
  need for the land use/land cover Change early
  warning system.
• The results of this study shows that, with the
  land use/land cover change early warning system,
  it is possible to among other things, monitor and
  manage urban growth to ensure food security and
  a stable climate regime in any area.