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ГЕОЭКОЛОГИЧЕСКАЯ ОЦЕНКА ЭРОЗИИ ОВРАГА НА ТЕРРИТОРИИ УНИВЕРСИТЕТА БЕНИНА С ПРИМЕНЕНИЕМ ГЕОИНФОРМАЦИИ И ИНЖЕНЕРНЫХ МЕТОДОВ
Оконофуа Соломон Эхиц
Университет Бенина, PMB 1154, Нигерия, Штат Эдо, магистр, преподаватель кафедры гео-матики инженерных технологий, тел. (234807)352-26-37, e-mail: ehi_zonoyahoo.com
Изинуон Осадолор Кристофер
Университет Бенина, PMB 1154, Нигерия, Штат Эдо, кандидат технических наук, профессор кафедры гражданского строительства, тел. (234803)503-82-39, e-mail: izinyon2006@yahoo.com
Рафаэль Эхигиатор-Иругхе
Университет Бенина, PMB 1154, Нигерия, Штат Эдо, кандидат технических наук, ст. преподаватель кафедры геоматики инженерных технологий, тел. (234803)368-10-19, e-mail: raphehigiator@yahoo.com
Статья посвящена оценке эрозии оврага на территории университета Бенина (University of Benin) Нигерии, с использованием геоинформации, данных наземной съемки и методов инженерной геологии. Это поможет понять механизм образования оврага и принять соответствующие меры по его контролю. Положение дренажного бассейна определялось с использованием ГННС, электронного тахеометра, а для контроля деградации земли исторические снимки от Google и многовременные космические снимки. Были получены топографические параметры дренажа, такие как угол наклона, высота пятна, контур и другие морфологические параметры оврага. По многовременным космическим снимкам 2003, 2005, 2007, 2010 и 2013 годов выявлено четкое отступление вершины оврага. Образцы почвы были взяты ручным бурением на максимальную глубину 2 м в самой верхней и нижней части дренажного бассейна. В верхней части дренажного бассейна были восстановлены буровые скважины 1, 2 и 3, а буровые скважины 4, 5 и 6 в нижней его части. По результатам топографической съемки выявлено отклонение откоса верхней части бассейна на 0,3-0,5 %, тогда как нижней части от 3 до 7 %, что указывает на высокий показатель эрозии в нижней части дренажного бассейна. Данные наземной съемки были обработаны в формате Excel до импортирования в программное обеспечение Arc GIS 9.3, которое используется для экологического моделирования тенденции деградации.
Ключевые слова: овражная эрозия, водораздел, ГИС, геоинформация GIS, geoinformation, деградация почв.
GEO-ENVIRONMENTAL ASSESSMENT OF GULLY EROSION AT THE UNIVERSITY OF BENIN USING GEOINFORMATION AND ENGINEERING METHODS
Okonofua S. Ehiz
University of Benin, PMB 1154, Nigeria, Edo State, Master of Engineering (M. Eng), Lecturer, Department of Geomatics Technology, tel. (234807)352-26-37, e-mail: ehi_zonoyahoo.com
Izinyon O. Christopher
University of Benin, PMB 1154, Nigeria, Edo State, Ph. D., Professor, Department of Civil Engineering, tel. (234803)503-82-39, e-mail: izinyon2006@yahoo.com
Raphael Ehigiator-Irughe
University of Benin, PMB 1154, Nigeria, Edo State, Ph. D., Senior Lecturer, Department of Geomatics Technology, tel. (234803)368-10-19, e-mail: raphehigiator@yahoo.com
This paper assessed gully erosion at the University of Benin, Nigeria, using geoinformation, ground survey data and geotechnical engineering methods. This will help to understand the mechanism responsible for the gully formation and then develop control/management measures. The catchment was geo referenced using GNSS, total station, Google historical imageries and multi temporal images for monitoring land degradation. Topographical parameters of the catchment such as slope angle, spot height, contour and other morphological parameters of the gully were obtained. Using the multi temporal images, the gully head retreat was ascertained for 2003, 2005, 2007, 2010 and 2013 respectively. Soil samples were obtained to a maximum depth of 2m at both the upper and lower reach of the catchment using hand auger. Boreholes 1, 2 and 3 where recovered from the upper reach of the catchment while Boreholes 4, 5 and 6 were obtained from the lower reach of the catchment. Information obtained during the topographical survey shows that the ground slope at the upper reach of the catchment is between 0,3 and 0,5 % while that of the lower reach is between 3 and 7 %; this accounts for the high rate of erosion at the lower reach of the catchment. Ground survey data were processed in excel format before imported into Arc GIS 9.3 software used for environmental modeling; this was used to produce trend in environmental degradation.
Key words: gully erosion, watershed, GIS, geoinformation, soil loss.
Flood and erosion have seriously affected man since time immemorial and despite governmental and prodigious effort to prevent and stop them the challenge still remain till today causing damages to property and loss of lives. Initiation of gully is as a result of localized erosion by surface runoff associated by rainfall events of high intensity. Gully erosion is highly noticeable form of soil erosion and can impair soil productivity as well as destroyed highway and water network. Eroded soil from gully bed can cause siltation of streams, culverts, dams and reservoir. Water runoff increases with energy as it spills over gully head and splash back water erodes the subsoil, retreating the gully head up to a slope. This process maybe initiated by several different factors including: cultivation or grazing on sites susceptible to gully erosion, increase in runoff due to increase in land cover change, poor vegetative cover or removal of preferred vegetative cover, improper storm water drainage design, construction or maintenance of waterways in cropping area (Ehiorobo, 2010).
In recent times, almost every part of the region in the world are exposed to degradation and erosion caused by increasing population and over use of limited land resources. Measuring soil erosion may not just be only expensive and time consuming; the results may also be conditioned by single event such as rain storm (Hudson, 1995). Calibration requires soil loss data from the full range of field situation from which the model will be applied. In practice, calibration is often based on data from few runoff plots with or without use of an artificial simulator (FAO, 1993) and data from site in other environment or measured according to the nonstandard technique (Lal, 2001). All of these limit the predictive capacity of soil erosion model (De Bie, 2005). Monitoring procedure based on field measurement and the estimation on the volume of rills and gullies in a time span such as several years are necessary in order to assess erosion at the landscape scale (Poesen, 1996).
The formulation of proper watershed management program for sustainable development requires information on soil erosion and sediment yield (Pandey et al., 2007). However, it is very challenging to model soil erosion because of the complexity of the interactions of factors that influence the erosion process (Wischmeire and Smith, 1978). Substantial effort has been made in developing soil erosion models resulting in a variety of models that range from simple empirically oriented equations such as the Universal Soil Loss Equation, USLE and its Reversed version RUSLE (Renard et al, 1997) to more advanced models such as Water Erosion Prediction Project (WEPP).
When put on efficiency scale, the latter may be more functional and powerful than other empirical models, but those models often need lots of data and are computationally intensive approach in many circumstances particularly with respect to modeling soil erosion in medium and large scale watershed (Wang et al, 2009).
Arising from the above mentioned limitations with respect to soil loss models, researchers dived into other areas of solving environmental challenges within a short space of time using relevant data. In recent times, with the aid of Digital Elevation Models (DEM), research has been addressed to predict the threshold contributing area and other topographic effects, limits of initiation, distribution and location of gullies in different locations (Ghoddusi, 1994). The current development in Remote Sensing techniques provide spatial information that is normally difficult to obtain especially in developing countries (Bakoariniaina et al, 2006; Fistikoglu and Harmancioglu, 2002).
The study area is University of Benin, Ugbowo campus which extends from Benin-Lagos road in the west to the Benin- Auchi road in the Northeast. The campus is divided into two (western and eastern) parts by the large basin of the Ikpoba River which flows in the eastern direction. It lies between latitude 050 44' N to 060 34' N and longitude 050 04' E to 060 45' E. The western sector slopes at between 3-8% (average slope of 4%) into the Ikpoba River which receives sediments from the gully area. On this same sector (western), the slope breaks just behind the Capitol. From this point, runoff due to change in gradient accelerates into the Ikpoba River, (Ehiorobo 2010).
The elevation of the study area ranges from 44m to 88m above mean sea level. The average temperature in this area is approximately 270 C and annual rainfall is between 1,500 mm/yr to 3,000 mm/yr. The wet season spans from March to November with break in the month of August otherwise known as August Break. Maximum rainfall is as high as 549 mm (July/September) with minimum as low as 4.1mm (January/December). The major soil type in the area ranges from clayey soil in the upper reach of the catchment to sandy soil towards the river bank. The land use types mainly include grassland, shrubs and bare soil. Humidity is about 85% most of the time and the area lies in the tropical rain forest zone.
Figure 1: Location plan of the study area
Reconnaissance survey was undertaken to have a good knowledge of the study area while spatial and topographic survey was carried out using Total station instrument (for gully bed mapping) and GNSS receiver, the coordinate obtained were converted to Nigerian Transverse Mercator (NTM) by using INCA software. Morphological parameters of the gully such as depth, top and bottom width, area of coverage and total length of gully were determined at the site using measuring instruments and spatial data. From the field measurement data, the cross sectional area was computed using:
A = d (b+s.d) (1)
Where d - depth of Gully
b - Average width of Gully s - Side slope of Gully A - Cross sectional area
Volume of soil loss was also computed using Simpson rule given by Ehiorobo (2011) as shown below:
A +4Am + A ■ 1 2
(2)
Where VL - volume of soil loss between the sections Ai - cross sectional area of first section A2 - cross sectional area of second section
Am - cross sectional area of section midway between the first and second section
The projects coordinates from the total station were down loaded into arc GIS environment as an excel spread sheet for further processing. Elevation data which was used to produce the topographic catchment map. Apart from the fact that Geographic Information System (GIS) was used for contour and slope generation it was also used to capture the extent of damage to infrastructure, water shed characteristics and flood inundated areas within the catchment. During the reconnaissance and detailed topographical survey of the area, it was observed that the average point density
in some parts such as the gully head and edge were more intense than others. Arising from the above, slope angle were computed at different sections of the gully so as to ascertain or differentiate erosion intense area (due to increase in slope) from relatively flat terrain. Total station also captured break in slope and other important topographic features of the catchment area. The cross section of the gully was recorded at a spacing of 20m interval from the longitudinal direction.
The rate of gully head retreat over a period of five years (5) was ascertained using multi temporal satellite images for the period. Apart from 2013 head retreat which was acquired using GPS receiver other were acquired from Google earth historic images. Control points were set on each image and this control points were used to carry out geo referencing of the images. The gully was then digitized for each year; using overlay operation the various years were overlaid and the annual retreat was measured. This will be used to compute the head retreat in other years.
Hand Auger was used to obtain soil samples from within the gully area and on encroaching layer of the gully to a maximum depth of 2m. The samples were taken to the Geotechnical Engineering laboratory for analysis/classification and other tests which included particle size distribution, Natural moisture content, specific gravity; Atterberg limits test, compaction and permeability. The tests were carried out in accordance with BS 1377:85. In order to ensure proper classification of soil within the catchment, the study area was divided into two. Samples from boreholes 1, 2 and 3 were obtained from the upper reach of the catchment (towards Ekosodin) while samples from borehole 4, 5 and 6 were recovered from the lower reach (close to the river).
Information obtained during the topographical survey of the study area includes the morphological data of the gully (length, breath, depth and volume of soil loss. Also, the ground survey data was used to produce the catchment basin of the area showing the direction of flow of the Ikpoba River. Using multi temporal satellite imagery, the head retreat of the gully was monitored and recorded for a period of four years. Acquisition of this imagery was then carried out from Google historic images while that of 2013 was carried out using GNSS. Table 1 shows the head retreat acquired from Google historical images while Fig. 2 shows the head retreat of the gully. Information gathered during the ground survey was also used for slope computations across each break in the catchment.
Table 1: Gully head retreat
Year Head retreat (m)
2005 -2006 90.8m
2006 - 2007 82.8
2007 - 2010 205.4
2010 - 2013 29.69
Figure 2: Gully head retreat for 2003, 2005, 2007, 2010 and 2013
The tests carried out in accordance with BS 1377:85 are: specific gravity, particles size distribution (sieve analysis), Atterberg/consistency test, compaction test, triaxial test and permeability test. Samples from boreholes 1, 2 and 3 (Ekosodin i.e. upper reach of the catchment) were analyzed separately from those recovered from the lower end (close to the sediment deposit). This was done so as to ensure proper soil classification and identify the zone of soil transition within the catchment. The results of the geotechnical investigation on the Hand Auger samples recovered from different location within the catchment are presented in Table 2.
There are symbols in the table which mean: NP - not-plastic, LL - liquid limit, PL - plastic limit, PI - plastic index, OMC - maximum moisture content, MDD -maximum dry density, C - cohesion while 0 - angle of internal friction.
The data collected from the Nigerian Meteorological Agency, NIMET were used to plot the charts in Fig. 3 using linear trend and scattered plot format. The chart shows the yearly variation of the rainfall while the trend line represents the linear relationships between the parameters involved.
From the data obtained during the topographical and field survey, the slope angle for each section was computed at each slope break. The value of the slope angle for the upper reach of the catchment (Ekoshodin area) ranges from 0.003% to 0.005% while the value for the downstream (towards the Ikpoba River) ranges from 2.2% to 7%. Table 1 shows that between 2005 and 2013 the gully head retreat ranged from 29.69m (2013) to 205.4m (2007 - 2010; annual average retreat of 51.4m). Within this period, the gully head had retreated 400m. A careful observation of Fig. 2 shows that despite heavy rainfall recorded in 2013, the gully head retreat was almost 30m; the smallest recorded since the initiation of the gully in year 2000. One of the factors responsible for the retarded retreat was the sharp reduction in the slope angle. Towards
the upper reach of the catchment (Ekoshodin), the terrain is relatively flat and as such runoff erosive index is low but increases in velocity as it approaches the lower part of the catchment especially at the point where it experiences a break in slope (runoff erosive index also increases at this section). At this section, runoff has left more devastating effects than the upper reach.
Table 2: Geotechnical test results for the University of Benin erosion site
S/N. LOC. Specific gravity (GS) Sieve analysis Atterberg limit Compaction Triaxial Permeability
Test Test (cm/sec)
% Passing % Passing LL PL PI MDD (g/cm3) OMC (%) C(KN/ m2) 00
Sieve 1.18 mm Sieve 0.075 mm
1 BH 1 1.006 x 10-7
0.5m 2.58 85.89 46.84 57.82 34.79 23.03 12.8 1.74 27.76 20
1m 2.6 82.7 57.93 66.1 41.04 25.06 10 1.75 18.45 23
2m 2.67 92.32 55.25 62.8 39.87 22.93 10 1.83 21.64 19
2 BH 2 1.553 x 10-7
0.5m 2.58 96.9 45.93 58.91 32.44 26.47 11.9 1.73 22.74 12
1m 2.53 80.51 55.62 56.43 29.48 26.95 12.01 1.7 25.3 11
2m 2.61 95.18 34.16 59.01 32.53 26.48 9.5 1.18 18.1 12
3 BH 3 1.782 x 10-8
0.5m 2.52 96.9 65.93 63.35 44.21 19.14 12.5 1.8 19.73 9.8
1m 2.6 96.42 58.92 56.11 39.72 16.39 13.3 1.75 18.62 13
2m 2.59 96.45 49.91 55.43 38.82 16.61 13.2 1.73 21.29 18
4 BH 4 1.104x 10-3
0.5m 2.38 89.23 12.97 N.P - - 11.03 1.68 6.9 5.4
1m 2.41 97.45 10.77 - - - 9.35 1.62 7.11 7.8
2m 2.39 80.15 17.57 - - - 10.65 1.55 6.55 6.1
5 BH 5 1.464x10-3
0.5m 2.33 89.11 11.94 - - - 13.22 1.48 6.43 6.5
1m 2.28 93.47 17.62 - - - 10.14 1.71 8.18 7.1
2m 2.4 91.73 15.45 - - - 13.22 1.74 8.51 6.6 1.433x10-3
6 BH 6
0.5m 2.42 89.01 9.73 - - - 11.57 1.44 7.72 5.2
1m 2.31 90.34 11.37 - - - 9.63 1.56 10.73 5.7
2m 2.57 94.73 16.84 - - - 10.58 1.8 11.48 7.1
Figure 3: Yearly variation of rainfall (1960 - 2010)
The geotechnical result (from the upper and lower part of the catchment) presented in Table 2 showed that the specific gravity for Bore Hole 1, 2 and 3 ranged 2.52 to 2.67 while the percentage passing through sieve number 0.075mm is between 34.16 and 65.93, this indicates that the soil in this part of the catchment is clayey soil with high water retaining ability as reflected by the soil moisture content (1.18% -1.8%) and also high plasticity index (16.61% - 26.95%). The permeability test results show that the soil is impervious and hard when dried but swells when under wet condition. When the topography is not tilted or faulted such soil hardly erode; this was why the rate of retreat slowed during the wet season of 2013 despite the heavy rainfall. For Bore holes 4. 5 and 6, the specific gravity ranged from 2.28 to 2.42 while the percentage passing sieve 0.075mm is between 10.77% and 17.62%. This implies that this part of the catchment is predominantly sandy soil. This was confirmed by the non-plastic nature of the samples and permeable tendency of the soil. The erodibility index of the sample at this part of the catchment was also very low (2.6), a factor which predisposes the soil to high erosion as gully retreated by almost 300m in four (4) years (2007, 2011). From the foregoing, the following conclusion can be ascertained:
- Geoinformation, multi temporal images and ground/field survey data can be used to monitor the rate of head retreat in gully and other environmental changes with respect to change in climate.
- Faulted or tilted land with intermediate slope break aid the velocity of runoff and when such catchment lacks adequate soil protection, the rate of erosion in such areas is usually intense.
- When GIS is fully utilized in addition to geotechnical and meteorological data, various factors contributing to the degradation of land can be ascertained and adequate control measures recommended.
REFERENCES
1. Bakoariniaina, L.N., Kusky, T., Raharimahefa, T., 2006. "Disappearing Lake Alaotra: Monitoring Catastrophic Erosion, Waterway Sitting and Land Degradation Hazards in Madagascar Using Landsat Imagery. Journal of African Earth Sciences, 44(2): pp. 241 - 252.
2. De Bie, C.A.J.M., 2005: Assessment of Soil Erosion Indicators for maize based agro-ecosystems in Kenya. Catana 59, pp. 231 -251.
3. Ehiorobo, J. O. (2010); "Flood and Erosion Control in Edo State" Inception report submitted to NDDC on flood and erosion control in Niger Delta States.
4. FAO, 1993 "Field Measurement of Soil Erosion and Runoff. FAO Soils Bulletin, vol. 68. FAO, Rome, p. 139.
5. Fistikoglu, O., Harmancioglu, N.B., 2002. Integration of GIS with USLE in Assessment of Soil Erosion. Water Resources Management, 16(6): pp. 447 -467
6. Ghoddusi, J., 1994, "Growth and Development of Gullies Research Report, Institute of Researchers of Forest and Rangelands, 28p.
7. Hudson, N., 1995 "Runoff, Erosion and Sedimentation: Prediction and measurement. In: FAO (Ed.), Land and Water Integration and River Basin Management", FAO Land and Water Bulletin, Vol. 1, p. 85.
8. Lal, R., 2001 "Soil degradation by Erosion. Land Degradation Journal; Vol. 12, pp. 519 - 539.
9. Nisar, T. R., Ahamed, K., Rao, G., et al., 2000. Fuzzy Class Membership Approach to Soil Erosion Modeling. Agricultural System Journal, Vol. 63, pp. 97 -110.
10. Pandey, A., Chowdary, V.M., Mal, B. C., 2007: Identification of Critical Erosion Prone Areas in Small Agricultural Watershed Using USLE, GIS and Remote Sensing. Water Resource Management, 21(14): pp. 729 - 746.
11. Poesen, J., Boardman, J., Wailcox, B., Valentin, C., 1996: Water Erosion Monitoring and Experimentation for Global Change Studies. Journal of Soil and Water Conservation 51, pp. 386 -390.
12. Renard, K.G., Foster, G.R., et al., 1994: The Revised Universal Soil Loss Equation. In: Lal, R., ed., Soil Erosion Research Methods. St. Lucie Press, Delray Beach, FL. Pp. 105 - 124.
13. Rodda, H. J. E., Demuth, S., Shankar, U., 1999. The Application of GIS Based Decision Support System to Predict Nitrate Leaching to Groundwater in Southern Germany. Hydro Science Journal 44(2): pp. 221 - 236.
14. Wang, G.X., Gertner, G, Fang, S.F., et al. 2003. Mapping Multiple Variables for Predicting Soil Loss by Geo Statistical Methods with TM Images and a Slope Map. Photogram Engineering and Remote Sensing Journal, Vol. 69(8): pp. 889 - 898.
15. Wang, G.Q., Hapuarachchi, H., Ishidaira, H., 2009: Estimation of Soil Erosion and Sediment Yieldduring Individual Rainstorms at Catchment Scale. Water Resource Management, 23(8): pp. 3649 - 3667.
16. Wischmeier, J.H., Smith, D.D., 1978: Predicting Rainfall Erosion Losses: A Guide to Convention Planning, Agricultural Handbook 537. U.S. Department of Agricultural Sci. and Education Administration, Washington DC.
© O. S. Ehiz, I. O. Christopher, R. Ehigiator-Irughe, 2015
